Low-Dose CT Image Denoising using Image Decomposition and Sparse Representation

X-ray computed tomography (CT) is now a widely used imaging modality for numerous medical purposes. The risk of high X-ray radiation may induce genetic, cancerous and other diseases, demanding the development of new image processing methods that are able to enhance the quality of low-dose CT images. However, lowering the radiation dose increases the noise in acquired images and hence affects important diagnostic information. This paper contributes an efficient denoising method for low-dose CT images. A noisy image is decomposed into three component images of low, medium and high frequency bands; noise is mainly presented in the medium and high component images. Then, by exploiting the fact that a small image patch of the noisy image can be approximated by a linear combination of several elements in a given dictionary of noise-free image patches generated from noise-free images taken at nearly the same position with the noisy image, noise in these medium and high component images are effectively eliminated.Specifically, we give new solutions for image decomposition to easily control the filter parameters, for dictionary construction to improve the effectiveness and reduce the running-time. Instead of using a large dataset of patches, only a structured small part of patches extracted from the raw data is used to form a dictionary, to be used in sparse coding. In addition, we illustrate the effectiveness of the proposed method in preserving image details which are subtle but clinically important. Experimental results conducted on both synthetic and real noise data demonstrate that the proposed method is competitive with the state-of-the-art methods

3D Reconstruction using Kinect Sensor and Parallel Processing on 3D Graphics Processing Unit

One of depth cameras such as the Microsoft Kinect is much cheaper than conventional 3D scanning devices, thus it can be acquired for everyday users easily. However, the depth data captured by Kinect over a certain distance is of low quality. In this work, we implement a set of algorithms allowing users to capture 3D surfaces by using the handheld Kinect. As a classic alignment algorithm such as the Iterative Closest Point (ICP) does not show efficacy in aligning point clouds that have limited overlapped regions, another coarse alignment using the Sample Consensus Initial Alignment (SAC-IA) is incorporated in to the registration process in order to ameliorate 3D point clouds’ fitness. Two robust reconstruction methods namely the Alpha Shapes and the Grid Projection are also implemented to reconstruct 3D surface from registered point clouds. The experimental results have shown the efficiency and applicability of of our blueprint. The constructed system obtains acceptable results in a few minutes with a low price device, thus it may practically be an useful approach for avatar generations or online shoppings

Central Asia and the globalisation of the contemporary legal consciousness

What is the logic which governs the processes of legal globalization? How does the transnational proliferation of legal forms operate in the contemporary geo-juridical space? What are the main defining characteristics of the currently dominant mode of transnational legal consciousness and how can the concept of legal consciousness help us understand better the historical ebb and flow of the Western-led projects of good governance promotion in regions like Central Asia after the fall of the Soviet Union? Using Duncan Kennedy’s seminal essay Three Globalizations of Law and Legal Thought as its starting platform, this essay seeks to explore these and a series of other related questions, while also drawing on the work of the Greek Marxist lawyer-philosopher Nicos Poulantzas to help elucidate some latent analytical stress-points in Kennedy’s broader theoretical framework. Reacting against the neo-Orientalist tone adopted across much of the contemporary field of Central Asian studies, it develops an alternative account of the internal history of the legal-globalizational encounter between the Western-based reform entrepreneurs and the national legal-political elites in Central Asia in the post-1991 period, complementing it with a detailed description of the general institutional and discursive structures within which this encounter took place

Molecular Characterization of HIV-1 CRF01_AE in Mekong Delta, Vietnam, and Impact of T-Cell Epitope Mutations on HLA Recognition (ANRS 12159)

To date, 11 HIV-1 subtypes and 48 circulating recombinant forms have been described worldwide. The underlying reason why their distribution is so heterogeneous is not clear. Host genetic factors could partly explain this distribution. The aim of this study was to describe HIV-1 strains circulating in an unexplored area of Mekong Delta, Vietnam, and to assess the impact of optimal epitope mutations on HLA binding.We recruited 125 chronically antiretroviral-naive HIV-1-infected subjects from five cities in the Mekong Delta. We performed high-resolution DNA typing of HLA class I alleles, sequencing of Gag and RT-Prot genes and phylogenetic analysis of the strains. Epitope mutations were analyzed in patients bearing the HLA allele restricting the studied epitope. Optimal wild-type epitopes from the Los Alamos database were used as reference. T-cell epitope recognition was predicted using the immune epitope database tool according to three different scores involved in antigen processing (TAP and proteasome scores) and HLA binding (MHC score). with a Vietnamese specificity held by two different haplotypes. The percentage of homology between Mekong and B consensus HIV-1 sequences was above 85%. Divergent epitopes had TAP and proteasome scores comparable with wild-type epitopes. MHC scores were significantly lower in divergent epitopes with a mean of 2.4 (±0.9) versus 2 (±0.7) in non-divergent ones (p<0.0001).Our study confirms the wide predominance of CRF01_AE in the Mekong Delta where patients harbor a specific HLA pattern. Moreover, it demonstrates the lower MHC binding affinity among divergent epitopes. This weak immune pressure combined with a narrow genetic diversity favors immune escape and could explain why CRF01_AE is still predominant in Vietnam, particularly in the Mekong area

Towards an end-to-end analysis and prediction system for weather, climate, and marine applications in the Red Sea

Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 102(1), (2021): E99-E122, https://doi.org/10.1175/BAMS-D-19-0005.1.The Red Sea, home to the second-longest coral reef system in the world, is a vital resource for the Kingdom of Saudi Arabia. The Red Sea provides 90% of the Kingdom’s potable water by desalinization, supporting tourism, shipping, aquaculture, and fishing industries, which together contribute about 10%–20% of the country’s GDP. All these activities, and those elsewhere in the Red Sea region, critically depend on oceanic and atmospheric conditions. At a time of mega-development projects along the Red Sea coast, and global warming, authorities are working on optimizing the harnessing of environmental resources, including renewable energy and rainwater harvesting. All these require high-resolution weather and climate information. Toward this end, we have undertaken a multipronged research and development activity in which we are developing an integrated data-driven regional coupled modeling system. The telescopically nested components include 5-km- to 600-m-resolution atmospheric models to address weather and climate challenges, 4-km- to 50-m-resolution ocean models with regional and coastal configurations to simulate and predict the general and mesoscale circulation, 4-km- to 100-m-resolution ecosystem models to simulate the biogeochemistry, and 1-km- to 50-m-resolution wave models. In addition, a complementary probabilistic transport modeling system predicts dispersion of contaminant plumes, oil spill, and marine ecosystem connectivity. Advanced ensemble data assimilation capabilities have also been implemented for accurate forecasting. Resulting achievements include significant advancement in our understanding of the regional circulation and its connection to the global climate, development, and validation of long-term Red Sea regional atmospheric–oceanic–wave reanalyses and forecasting capacities. These products are being extensively used by academia, government, and industry in various weather and marine studies and operations, environmental policies, renewable energy applications, impact assessment, flood forecasting, and more.The development of the Red Sea modeling system is being supported by the Virtual Red Sea Initiative and the Competitive Research Grants (CRG) program from the Office of Sponsored Research at KAUST, Saudi Aramco Company through the Saudi ARAMCO Marine Environmental Center at KAUST, and by funds from KAEC, NEOM, and RSP through Beacon Development Company at KAUST

Carbonic Anhydrase 9 Expression Increases with Vascular Endothelial Growth Factor-Targeted Therapy and Is Predictive of Outcome in Metastatic Clear Cell Renal Cancer

AbstractBackgroundThere is a lack of biomarkers to predict outcome with targeted therapy in metastatic clear cell renal cancer (mccRCC). This may be because dynamic molecular changes occur with therapy.ObjectiveTo explore if dynamic, targeted-therapy-driven molecular changes correlate with mccRCC outcome.Design, setting, and participantsMultiple frozen samples from primary tumours were taken from sunitinib-naïve (n=22) and sunitinib-treated mccRCC patients (n=23) for protein analysis. A cohort (n=86) of paired, untreated and sunitinib/pazopanib-treated mccRCC samples was used for validation. Array comparative genomic hybridisation (CGH) analysis and RNA interference (RNAi) was used to support the findings.InterventionThree cycles of sunitinib 50mg (4 wk on, 2 wk off).Outcome measurements and statistical analysisReverse phase protein arrays (training set) and immunofluorescence automated quantitative analysis (validation set) assessed protein expression.Results and limitationsDifferential expression between sunitinib-naïve and treated samples was seen in 30 of 55 proteins (p<0.05 for each). The proteins B-cell CLL/lymphoma 2 (BCL2), mutL homolog 1 (MLH1), carbonic anhydrase 9 (CA9), and mechanistic target of rapamycin (mTOR) (serine/threonine kinase) had both increased intratumoural variance and significant differential expression with therapy. The validation cohort confirmed increased CA9 expression with therapy. Multivariate analysis showed high CA9 expression after treatment was associated with longer survival (hazard ratio: 0.48; 95% confidence interval, 0.26–0.87; p=0.02). Array CGH profiles revealed sunitinib was associated with significant CA9 region loss. RNAi CA9 silencing in two cell lines inhibited the antiproliferative effects of sunitinib. Shortcomings of the study include selection of a specific protein for analysis, and the specific time points at which the treated tissue was analysed.ConclusionsCA9 levels increase with targeted therapy in mccRCC. Lower CA9 levels are associated with a poor prognosis and possible resistance, as indicated by the validation cohort.Patient summaryDrug treatment of advanced kidney cancer alters molecular markers of treatment resistance. Measuring carbonic anhydrase 9 levels may be helpful in determining which patients benefit from therapy

Development of the Preferred Components for Co-Design in Research Guideline and Checklist: Protocol for a Scoping Review and a Modified Delphi Process

Background: There is increasing evidence that co-design can lead to more engaging, acceptable, relevant, feasible, and even effective interventions. However, no guidance is provided on the specific designs and associated methods or methodologies involved in the process. We propose the development of the Preferred Components for Co-design in Research (PRECISE) guideline to enhance the consistency, transparency, and quality of reporting co-design studies used to develop complex health interventions. Objective: The aim is to develop the first iteration of the PRECISE guideline. The purpose of the PRECISE guideline is to improve the consistency, transparency, and quality of reporting on studies that use co-design to develop complex health interventions. Methods: The aim will be achieved by addressing the following objectives: to review and synthesize the literature on the models, theories, and frameworks used in the co-design of complex health interventions to identify their common elements (components, values or principles, associated methods and methodologies, and outcomes); and by using the results of the scoping review, prioritize the co-design components, values or principles, associated methods and methodologies, and outcomes to be included in the PRECISE guideline. Results: The project has been funded by the Canadian Institutes of Health Research. Conclusions: The collective results of this project will lead to a ready-to-implement PRECISE guideline that outlines a minimum set of items to include when reporting the co-design of complex health interventions. The PRECISE guideline will improve the consistency, transparency, and quality of reports of studies. Additionally, it will include guidance on how to enact or enable the values or principles of co-design for meaningful and collaborative solutions (interventions). PRECISE might also be used by peer reviewers and editors to improve the review of manuscripts involving co-design. Ultimately, the PRECISE guideline will facilitate more efficient use of new results about complex health intervention development and bring better returns on research investments

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Vision, challenges and opportunities for a Plant Cell Atlas

With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them.</jats:p