1,048 research outputs found

    UMSL Bulletin 2023-2024

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    The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp

    UMSL Bulletin 2022-2023

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    The 2022-2023 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1087/thumbnail.jp

    2023-2024 Catalog

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    The 2023-2024 Governors State University Undergraduate and Graduate Catalog is a comprehensive listing of current information regarding:Degree RequirementsCourse OfferingsUndergraduate and Graduate Rules and Regulation

    Digital agriculture: research, development and innovation in production chains.

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    Digital transformation in the field towards sustainable and smart agriculture. Digital agriculture: definitions and technologies. Agroenvironmental modeling and the digital transformation of agriculture. Geotechnologies in digital agriculture. Scientific computing in agriculture. Computer vision applied to agriculture. Technologies developed in precision agriculture. Information engineering: contributions to digital agriculture. DIPN: a dictionary of the internal proteins nanoenvironments and their potential for transformation into agricultural assets. Applications of bioinformatics in agriculture. Genomics applied to climate change: biotechnology for digital agriculture. Innovation ecosystem in agriculture: Embrapa?s evolution and contributions. The law related to the digitization of agriculture. Innovating communication in the age of digital agriculture. Driving forces for Brazilian agriculture in the next decade: implications for digital agriculture. Challenges, trends and opportunities in digital agriculture in Brazil

    Measuring the impact of COVID-19 on hospital care pathways

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    Care pathways in hospitals around the world reported significant disruption during the recent COVID-19 pandemic but measuring the actual impact is more problematic. Process mining can be useful for hospital management to measure the conformance of real-life care to what might be considered normal operations. In this study, we aim to demonstrate that process mining can be used to investigate process changes associated with complex disruptive events. We studied perturbations to accident and emergency (A &E) and maternity pathways in a UK public hospital during the COVID-19 pandemic. Co-incidentally the hospital had implemented a Command Centre approach for patient-flow management affording an opportunity to study both the planned improvement and the disruption due to the pandemic. Our study proposes and demonstrates a method for measuring and investigating the impact of such planned and unplanned disruptions affecting hospital care pathways. We found that during the pandemic, both A &E and maternity pathways had measurable reductions in the mean length of stay and a measurable drop in the percentage of pathways conforming to normative models. There were no distinctive patterns of monthly mean values of length of stay nor conformance throughout the phases of the installation of the hospital’s new Command Centre approach. Due to a deficit in the available A &E data, the findings for A &E pathways could not be interpreted

    Cryo-Electron Microscopy to Investigate Molecular Dynamics and Conformational Changes in Protein Complexes

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    Stress can be considered as one of the most fundamental aspects in life, and all living organisms are constantly exposed to a variety of different stress situations. Thus, efficient stress sensing and reaction mechanisms are crucial for their survival. Stress response mechanisms are as diverse as the causative stimuli and oftentimes cross-linked forming a versatile reaction network, to ensure the cells’ survival under critical situations. Notably, stress response mechanisms play a major role in pathogenicity, virulence and disease. Pathogenic Bacteria are permanently facing environmental pressure originating from the host’s defense systems or drug treatments, while mutations in eukaryotic stress response systems have been shown to cause a large number of severe human diseases such as diabetes, cancer or Parkinson’s and Alzheimer’s disease. A profound molecular knowledge on the respective mechanisms is thus the inevitable prerequisite towards a global understanding of this fundamental aspect of life, paving the way for the development of new drugs or therapeutic approaches. Within this thesis, various aspects of stress response mechanisms in three different systems were investigated using state-of-the-art electron microscopy techniques. First, I set out to solve the structure of the Vibrio vulnificus stressosome complex, a key player in the bacterial environmental stress response. Currently, there is no structural data available for any gram-negative stressosome. A medium-resolution cryo-electron microscopy (cryo-EM) structure of the minimal complex could be obtained, which features an exceptional symmetry break originating from its unique, regulatory stoichiometry. Based on the structural data, it was possible to propose an activation mechanism and to pinpoint a number of significant differences in comparison to gram-positive stressosome complexes. Undoubtedly, the structure contributes a major piece of information necessary to understand stress sensing and signal transduction in this human pathogen. This study was complemented by a number of physiological and phylogenetic experiments contributed by our co-workers, and published recently (VIII. PUBLICATION 1). The second project focused on the gram-positive soil bacterium Corynebacterium glutamicum, a prime model organism for investigations of the bacterial osmostress response. Sensing of hyper-osmotic stress and regulation of the respective stress response in C. glutamicum are simultaneously performed by BetP, a conformationally asymmetric-trimeric secondary active transporter able to import the compatible solute betaine. Two stimuli are identified to initiate the full osmostress response in BetP, namely an elevated cytoplasmic K+ concentration and a loosely defined ‘membrane stimulus’. Despite the availability of functional data on BetP regulation, structural information especially of the down-regulated state and the subsequent transition events are absent. Using single particle cryo-EM analysis, I was able to provide high-resolution structures of the down-regulated and a transition state, which elucidated a number of important structural features not described so far. It could be shown that down-regulated BetP adopts a symmetric arrangement stabilized by antight cytoplasmic interaction network of the sensory domain, further strengthened by Cardiolipin molecules located at regulatory lipid binding sites. These constraints are released upon stress sensing, as demonstrated by fourier transform infrared (FTIR) spectroscopy and molecular dynamics simulation (MD) data contributed by our co-workers, resulting in the well-established, asymmetric-trimeric structures previously known. The wealth of new data on the down-regulated state allowed to propose a detailed regulation mechanism and to further sharpen the previously vague picture of the membrane stimulus. The data are summarized and presented in IX. PREPRINT 1. A third topic of this thesis was the three dimensional investigation via dual-axis scanning transmission electron microscopy (STEM) tomography of crystalloid-ER structures we identified before in human embryonic kidney (HEK) cells upon over-expression of polycystin-2 (PC-2). In this study presented in X. MANUSCRIPT 1, I was further able to proof the presence of ER whorls, and to obtain high-resolution three-dimensional (3D) reconstructions of the two different ER morphotypes. These data provided unmatched insights into the cellular ER interaction partners and clearly demonstrated the dynamic nature of the organelle even under stress situations. A detailed discussion of the identified morphological features in their respective cellular context finally allowed for the description of the organellar membrane architecture at a high level of detail. Lastly, the discussion addresses the electron microscopy techniques and instruments used and contains an outlook on further perspectives for the projects. Overall, this thesis yielded intriguing mechanistic insights into the versatile bacterial and eukaryotic stress response mechanisms, reflecting their manifold nature ultimately converging to a common outcome

    Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to Interpretability

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    The integration of Artificial Intelligence (AI) into the field of drug discovery has been a growing area of interdisciplinary scientific research. However, conventional AI models are heavily limited in handling complex biomedical structures (such as 2D or 3D protein and molecule structures) and providing interpretations for outputs, which hinders their practical application. As of late, Graph Machine Learning (GML) has gained considerable attention for its exceptional ability to model graph-structured biomedical data and investigate their properties and functional relationships. Despite extensive efforts, GML methods still suffer from several deficiencies, such as the limited ability to handle supervision sparsity and provide interpretability in learning and inference processes, and their ineffectiveness in utilising relevant domain knowledge. In response, recent studies have proposed integrating external biomedical knowledge into the GML pipeline to realise more precise and interpretable drug discovery with limited training instances. However, a systematic definition for this burgeoning research direction is yet to be established. This survey presents a comprehensive overview of long-standing drug discovery principles, provides the foundational concepts and cutting-edge techniques for graph-structured data and knowledge databases, and formally summarises Knowledge-augmented Graph Machine Learning (KaGML) for drug discovery. A thorough review of related KaGML works, collected following a carefully designed search methodology, are organised into four categories following a novel-defined taxonomy. To facilitate research in this promptly emerging field, we also share collected practical resources that are valuable for intelligent drug discovery and provide an in-depth discussion of the potential avenues for future advancements
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