5,284 research outputs found

    The ins and outs of open-angle Glaucoma:drugs, diet, and defecation

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    Glaucoma is the leading cause of irreversible blindness and second leading cause of blindness. The primary aim of this thesis is to provide insight into the role of systemic effectsin the pathophysiology of OAG.<br/

    Application of Computer Vision and Mobile Systems in Education: A Systematic Review

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    The computer vision industry has experienced a significant surge in growth, resulting in numerous promising breakthroughs in computer intelligence. The present review paper outlines the advantages and potential future implications of utilizing this technology in education. A total of 84 research publications have been thoroughly scrutinized and analyzed. The study revealed that computer vision technology integrated with a mobile application is exceptionally useful in monitoring students’ perceptions and mitigating academic dishonesty. Additionally, it facilitates the digitization of handwritten scripts for plagiarism detection and automates attendance tracking to optimize valuable classroom time. Furthermore, several potential applications of computer vision technology for educational institutions have been proposed to enhance students’ learning processes in various faculties, such as engineering, medical science, and others. Moreover, the technology can also aid in creating a safer campus environment by automatically detecting abnormal activities such as ragging, bullying, and harassment

    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

    CANCER TREATMENT BY TARGETING HDAC4 TRANSLOCATION INDUCED BY MICROSECOND PULSED ELECTRIC FIELD EXPOSURE: MECHANISTIC INSIGHTS THROUGH KINASES AND PHOSPHATASES

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    Epigenetic modifications, arising from sub-cellular shifts in histone deacetylase (HDAC) activity and localization, present promising strategies for diverse cancer treatments. HDACs, enzymes responsible for post-translational histone modifications, induce these epigenetic changes by removing acetyl groups from ε-N-acetyl-lysine residues on histones, thereby suppressing gene transcription. Within the HDAC group, class IIa HDACs are notable for their responsiveness to extracellular signals, bridging the gap between external stimuli, plasma membrane, and genome through nuclear-cytoplasmic translocation. This localization offers two significant mechanisms for cancer treatment: nuclear accumulation of HDACs represses oncogenic transcription factors, such as myocyte-specific enhancer factor 2C (MEF2C), triggering various cell death pathways. Conversely, cytoplasmic HDAC accumulation acts similarly to HDAC inhibitors by silencing genes. My dissertation introduces an innovative approach for glioblastoma and breast cancer treatment by investigating the application of microsecond pulsed electric fields. It particularly focuses on HDAC4, a class IIa HDAC overexpressed in these cancers. Beyond demonstrating HDAC4 translocation, my research delves into the intricate roles of kinases and phosphatases, shedding light on the underlying factors governing HDAC4 translocation

    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    3D Innovations in Personalized Surgery

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    Current practice involves the use of 3D surgical planning and patient-specific solutions in multiple surgical areas of expertise. Patient-specific solutions have been endorsed for several years in numerous publications due to their associated benefits around accuracy, safety, and predictability of surgical outcome. The basis of 3D surgical planning is the use of high-quality medical images (e.g., CT, MRI, or PET-scans). The translation from 3D digital planning toward surgical applications was developed hand in hand with a rise in 3D printing applications of multiple biocompatible materials. These technical aspects of medical care require engineers’ or technical physicians’ expertise for optimal safe and effective implementation in daily clinical routines.The aim and scope of this Special Issue is high-tech solutions in personalized surgery, based on 3D technology and, more specifically, bone-related surgery. Full-papers or highly innovative technical notes or (systematic) reviews that relate to innovative personalized surgery are invited. This can include optimization of imaging for 3D VSP, optimization of 3D VSP workflow and its translation toward the surgical procedure, or optimization of personalized implants or devices in relation to bone surgery

    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

    Multimodal MRI analysis using deep learning methods

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    Magnetic resonance imaging (MRI) has been widely used in scientific and clinical research. It is a non-invasive medical imaging technique that reveals anatomical structures and provides useful information for investigators to explore aging and pathological processes. Different MR modalities offer different useful properties. Automatic MRI analysis algorithms have been developed to address problems in many applications such as classification, segmentation, and disease diagnosis. Segmentation and labeling algorithms applied to brain MRIs enable evaluations of the volumetric changes of specific structures in neurodegenerative diseases. Reconstruction of fiber orientations using diffusion MRI is beneficial to obtain better understanding of the underlying structures. In this thesis, we focused on development of deep learning methods for MRI analysis using different image modalities. Specifically, we applied deep learning techniques on different applications, including segmentation of brain structures and reconstruction of tongue muscle fiber orientations. For segmentation of brain structures, we developed an end-to-end deep learning algorithm for ventricle parcellation of brains with ventriculomegaly using T1-w MR images. The deep network provides robust and accurate segmentation results in subjects with high variability in ventricle shapes and sizes. We developed another deep learning method to automatically parcellate the thalamus into a set of thalamic nuclei using T1-w MRI and features from diffusion MRI. The algorithm incorporates a harmonization step to make the network adapt to input images with different contrasts. We also studied the strains associated with tongue muscles during speech production using multiple MRI modalities. To enable this study, we first developed a deep network to reconstruct crossing tongue muscle fiber orientations using diffusion MRI. The network was specifically designed for the human tongue and accounted for the orthogonality property of the tongue muscles. Next, we proposed a comprehensive pipeline to analyze the strains associated with tongue muscle fiber orientations during speech using diffusion MRI, and tagged and cine MRI. The proposed pipeline provides a solution to analyze the cooperation between muscle groups during speech production
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