111 research outputs found

    Remote Sensing of Precipitation: Part II

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    Precipitation is a well-recognized pillar in the global water and energy balances. The accurate and timely understanding of its characteristics at the global, regional and local scales is indispensable for a clearer insight on the mechanisms underlying the Earth’s atmosphere-ocean complex system. Precipitation is one of the elements that is documented to be greatly affected by climate change. In its various forms, precipitation comprises the primary source of freshwater, which is vital for the sustainability of almost all human activities. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne. This volume hosts original research contributions on several aspects of remote sensing of precipitation, including applications which embrace the use of remote sensing in tackling issues such as precipitation estimation, seasonal characteristics of precipitation and frequency analysis, assessment of satellite precipitation products, storm prediction, rain microphysics and microstructure, and the comparison of satellite and numerical weather prediction precipitation products

    Integrative omics approaches for new target identification and therapeutics development

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    The growing research and commercial pressures for novel therapeutics development accentuate why better strategies are needed for drug discovery. The costly nature of developing a pharmaceutical compound as well as the shrinking pool of ‘easy’ targets are some of the key reasons why there is a research paradigm shift towards integrative and systems biology driven approaches. Moreover, multifactorial aspects of many diseases require more innovative clinical strategies rather than just focusing on a single target. Cardiovascular diseases as well as associated immune components exemplify this complexity well. This thesis aimed to introduce a gradual and highly integrative analytical framework by incorporating a full range of studies from disease target selection to high-throughput virtual screening so that a cost-effective and efficient stratification of targets and associated compounds could be achieved. Heart failure served as a case study for complex diseases where the first in-depth omics study on cardiomyopathies helped to elucidate new therapeutic avenues. This research tied in with a development of a novel scoring function and integrated machine learning approach for multiple therapeutic target classification and exploration. Finally, all pieces of the introduced research were used to create a highly integrative in silico screening workflow. Some of the key results included the first reported molecular dynamics analyses for a complex immunotherapeutic target, c-Rel, as well as 15 new therapeutic compounds that could potentially modulate this transcription factor subunit. Thus, this dissertation provided several important improvements for target identification, validation, and drug discovery that could significantly advance current development strategies and accelerate new therapeutics production

    Aneuploidy in Health and Disease

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    Aneuploidy means any karyotype that is not euploid, anything that stands outside the norm. Two particular characteristics make the research of aneuploidy challenging. First, it is often hard to distinguish what is a cause and what is a consequence. Secondly, aneuploidy is often associated with a persistent defect in maintenance of genome stability. Thus, working with aneuploid, unstable cells means analyzing an ever changing creature and capturing the features that persist. In the book Aneuploidy in Health and Disease we summarize the recent advances in understanding the causes and consequences of aneuploidy and its link to human pathologies

    Multiplexed affinity peptidomic assays: multiplexing and applications for testing protein biomarkers

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    Biomarkers are increasingly used in a wide range of areas such as sports and clinical diagnostics, biometric applications, forensic analysis and population screening. Testing for such biomarkers requires substantial resources and has traditionally involved centralised laboratory testing. From cancer diagnosis to COVID testing, there is an increasing demand for protein based assays that are portable, easy to use and ideally multiplexed, so that more than one biomarker can be tested at the same time, thus increasing the throughput and reducing time of the analysis and potentially the costs. Events in recent years, not least the ongoing investigations into claims of widespread state-sponsored doping schemes in sport and the COVID-19 pandemic of 2020 highlight the ever-growing requirement and importance of such tests across multiple frontiers. The project evaluated the feasibility of new antipeptide affinity reagents and suitable technologies for application to multiplexed affinity assays geared towards quantitatively analysing a range of analytes. In the first part of this project, key protein biomarkers available from blood serum and covering a range of conditions including cancer, inflammation, and various behavioural traits were chosen from the literature. Peptide antigens for the development of antipeptide polyclonal antibodies for each protein were selected following in silico proteolysis and ranking of the peptides using an algorithm devised as part of this research. A microarray format was used to achieve spatial multiplexing and increase throughput of the assays. The arrays were evaluated experimentally and were tested for their usability for studying up/down regulation of the target biomarkers in human sera samples. Another protein assay format tested for compatibility with affinity peptidomics approach was a gold nanoparticle based lateral flow test. An affinity-based lateral flow test device was built and used for the detection of the benzodiazepine Valium. Here spectral multiplexing of detection was considered. The principle was tested using quantum dot nanoparticles instead of traditionally used gold nanoparticles. The spectral deconvolution was achieved for mixtures containing up to six differently sized quantum dots. In the final part of this project, a search for novel peptide affinity reagents against insulin growth-like factor 1 (IGF-1) was conducted using phage display. Four peptides were identified after screening a phage display library, and the binding of these peptides to IGF-1 was compared to that of traditional antibody

    YOUMARES 8 – Oceans Across Boundaries: Learning from each other

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    This open access book presents the proceedings volume of the YOUMARES 8 conference, which took place in Kiel, Germany, in September 2017, supported by the German Association for Marine Sciences (DGM). The YOUMARES conference series is entirely bottom-up organized by and for YOUng MARine RESearchers. Qualified early career scientists moderated the scientific sessions during the conference and provided literature reviews on aspects of their research field. These reviews and the presenters’ conference abstracts are compiled here. Thus, this book discusses highly topical fields of marine research and aims to act as a source of knowledge and inspiration for further reading and research

    An Efficient Fully Automated Method for Gridding Microarray Images

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    Abstract DNA microarray is a powerful tool and is widely used in genetics to monitor expression levels of thousands of genes in parallel. The gene expression process consists of three stages: gridding, segmentation and quantification. Gridding deals with finding areas in the microarray image which contain one spot using grid lines. This step can be done manually or automatically. In this paper, we propose an efficient and simple automatic gridding method for microarray image analysis. This method was implemented using MATLAB software and found very effective for gridding arrays with low intensity, poor quality spotsand tested by a number of microarray images. Results show that this method gives high accuracy of 76.9% improved to 98.6% when a preprocessing step is considered, rendering the method a promising technique for an efficient and automatic gridding the noisy microarray images

    Microarray spot partitioning by autonoumsly organising maps thorugh contour model

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    In cDNA microarray image analysis, classification of pixels as forefront area and the area covered by background is very challenging. In microarray experimentation, identifying forefront area of desired spots is nothing but computation of forefront pixels concentration, area covered by spot and shape of the spots. In this piece of writing, an innovative way for spot partitioning of microarray images using autonomously organizing maps (AOM) method through C-V model has been proposed. Concept of neural networks has been incorpated to train and to test microarray spots.In a trained AOM the comprehensive information arising from the prototypes of created neurons are clearly integrated to decide whether to get smaller or get bigger of contour. During the process of optimization, this is done in an iterative manner. Next using C-V model, inside curve area of trained spot is compared with test spot finally curve fitting is done.The presented model can handle spots with variations in terms of shape and quality of the spots and meanwhile it is robust to the noise. From the review of experimental work, presented approach is accurate over the approaches like C-means by fuzzy, Morphology sectionalization

    Finding Binding Sites in ChIP-Seq Data via a Linear-time Multi-level Thresholding Algorithm

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    Chromatin immunoprecipitation (ChIP-Seq) has emerged as a superior alternative to microarray technology as it provides higher resolution, less noise, greater coverage and wider dynamic range. While ChIP-Seq enables probing of DNA-protein interaction over the entire genome, it requires the use of sophisticated tools to recognize hidden patterns and extract meaningful data. Over the years, various attempts have resulted in several algorithms making use of different heuristics to accurately determine individual peaks corresponding to unique DNA-protein binding sites. However, finding all the binding sites with high accuracy in a reasonable time is still a challenge. In this work, we propose the use of Multi-level thresholding algorithm, which we call LinMLTBS, used to identify the enriched regions on ChIP-Seq data. Although various suboptimal heuristics have been proposed for multi-level thresholding, we emphasize on the use of an algorithm capable of obtaining an optimal solution, while maintaining linear-time complexity. Testing various algorithm on various ENCODE project datasets shows that our approach attains higher accuracy relative to previously proposed peak finders while retaining a reasonable processing speed

    Microfluidics and Nanofluidics Handbook

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    The Microfluidics and Nanofluidics Handbook: Two-Volume Set comprehensively captures the cross-disciplinary breadth of the fields of micro- and nanofluidics, which encompass the biological sciences, chemistry, physics and engineering applications. To fill the knowledge gap between engineering and the basic sciences, the editors pulled together key individuals, well known in their respective areas, to author chapters that help graduate students, scientists, and practicing engineers understand the overall area of microfluidics and nanofluidics. Topics covered include Finite Volume Method for Numerical Simulation Lattice Boltzmann Method and Its Applications in Microfluidics Microparticle and Nanoparticle Manipulation Methane Solubility Enhancement in Water Confined to Nanoscale Pores Volume Two: Fabrication, Implementation, and Applications focuses on topics related to experimental and numerical methods. It also covers fabrication and applications in a variety of areas, from aerospace to biological systems. Reflecting the inherent nature of microfluidics and nanofluidics, the book includes as much interdisciplinary knowledge as possible. It provides the fundamental science background for newcomers and advanced techniques and concepts for experienced researchers and professionals

    Genetic and Molecular Investigation of the Schnitzler Syndrome

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    The Schnitzler Syndrome (SchS) is a rare, autoinflammatory condition with an unknown pathological mechanism, but treatment with IL-1 inhibition provides remarkable efficacy. Exhibiting two main defining features: (1) an urticarial rash and (2) an IgM gammopathy, this IL-1 mediated disease phenotypically bears stark resemblance to NLRP3-associated inflammatory disease. The latter monogenic entity is known to show gain-of-function and pathological mutations in the NACHT, LRR and PYD domains-containing protein 3 (NLRP3) inflammasome. Furthermore, 20% of SchS patients go on to develop overt lymphoproliferative diseases, namely Waldenström's Macroglobulinaemia (WM). This condition presents with a specific mutation in the Myeloid Differentiation Primary Response (MYD88) gene in over 90% of patients. Against the backdrop of these imperative findings, the work presented in this thesis therefore examines the role of these immunological constituents in SchS, via the assessment of mutations in NLRP3 and MYD88 alongside a panel of genes frequently mutated in haematological malignancies. Identification of a causative gene would not only improve molecular diagnosis, but allows for potential unearthing of genotype-phenotype correlations. Since the identification of this condition in 1972, the features and consequences of the IgM gammopathy has remained elusive. In a bid to delineate the latter, examination of the heavy chain of the immunoglobulin repertoire would therefore indicate aspects of the adaptive immune response integral to formation of the monoclonal component. A biased repertoire would therefore indicate the existence of a clonal B-cell population. Additionally, isolation of SchS-IgM and interrogation of a protein array comprising of over 15,700 human proteins further indicates whether this element causes pathological effects. Exploration of the genetic and molecular components did not expose a common mechanism through which SchS manifests, ruling out the notion that NLRP3, MYD88 and other associated genes are universally causative of this enigmatic disease. Assessment of the IgH repertoire indicated that SchS patients show evidence of expanded B-cell populations, and together with protein array analysis demonstrating the preference of IgM binding to nuclear antigens, this study supports the theory that SchS is a clonal disorder. The breadth and depth of these findings broadens the currently limited scientific knowledge pertaining to SchS, forming the basis upon which further investigations can commence
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