39 research outputs found

    Browser-based Data Annotation, Active Learning, and Real-Time Distribution of Artificial Intelligence Models: From Tumor Tissue Microarrays to COVID-19 Radiology.

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    BACKGROUND: Artificial intelligence (AI) is fast becoming the tool of choice for scalable and reliable analysis of medical images. However, constraints in sharing medical data outside the institutional or geographical space, as well as difficulties in getting AI models and modeling platforms to work across different environments, have led to a "reproducibility crisis" in digital medicine. METHODS: This study details the implementation of a web platform that can be used to mitigate these challenges by orchestrating a digital pathology AI pipeline, from raw data to model inference, entirely on the local machine. We discuss how this federated platform provides governed access to data by consuming the Application Program Interfaces exposed by cloud storage services, allows the addition of user-defined annotations, facilitates active learning for training models iteratively, and provides model inference computed directly in the web browser at practically zero cost. The latter is of particular relevance to clinical workflows because the code, including the AI model, travels to the user's data, which stays private to the governance domain where it was acquired. RESULTS: We demonstrate that the web browser can be a means of democratizing AI and advancing data socialization in medical imaging backed by consumer-facing cloud infrastructure such as Box.com. As a case study, we test the accompanying platform end-to-end on a large dataset of digital breast cancer tissue microarray core images. We also showcase how it can be applied in contexts separate from digital pathology by applying it to a radiology dataset containing COVID-19 computed tomography images. CONCLUSIONS: The platform described in this report resolves the challenges to the findable, accessible, interoperable, reusable stewardship of data and AI models by integrating with cloud storage to maintain user-centric governance over the data. It also enables distributed, federated computation for AI inference over those data and proves the viability of client-side AI in medical imaging. AVAILABILITY: The open-source application is publicly available at , with a short video demonstration at

    Tipping the Balance: Sclerotinia sclerotiorum Secreted Oxalic Acid Suppresses Host Defenses by Manipulating the Host Redox Environment

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    Sclerotinia sclerotiorum is a necrotrophic ascomycete fungus with an extremely broad host range. This pathogen produces the non-specific phytotoxin and key pathogenicity factor, oxalic acid (OA). Our recent work indicated that this fungus and more specifically OA, can induce apoptotic-like programmed cell death (PCD) in plant hosts, this induction of PCD and disease requires generation of reactive oxygen species (ROS) in the host, a process triggered by fungal secreted OA. Conversely, during the initial stages of infection, OA also dampens the plant oxidative burst, an early host response generally associated with plant defense. This scenario presents a challenge regarding the mechanistic details of OA function; as OA both suppresses and induces host ROS during the compatible interaction. In the present study we generated transgenic plants expressing a redox-regulated GFP reporter. Results show that initially, Sclerotinia (via OA) generates a reducing environment in host cells that suppress host defense responses including the oxidative burst and callose deposition, akin to compatible biotrophic pathogens. Once infection is established however, this necrotroph induces the generation of plant ROS leading to PCD of host tissue, the result of which is of direct benefit to the pathogen. In contrast, a non-pathogenic OA-deficient mutant failed to alter host redox status. The mutant produced hypersensitive response-like features following host inoculation, including ROS induction, callose formation, restricted growth and cell death. These results indicate active recognition of the mutant and further point to suppression of defenses by the wild type necrotrophic fungus. Chemical reduction of host cells with dithiothreitol (DTT) or potassium oxalate (KOA) restored the ability of this mutant to cause disease. Thus, Sclerotinia uses a novel strategy involving regulation of host redox status to establish infection. These results address a long-standing issue involving the ability of OA to both inhibit and promote ROS to achieve pathogenic success

    Gene expression profiling of alveolar soft-part sarcoma (ASPS)

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    <p>Abstract</p> <p>Background</p> <p>Alveolar soft-part sarcoma (ASPS) is an extremely rare, highly vascular soft tissue sarcoma affecting predominantly adolescents and young adults. In an attempt to gain insight into the pathobiology of this enigmatic tumor, we performed the first genome-wide gene expression profiling study.</p> <p>Methods</p> <p>For seven patients with confirmed primary or metastatic ASPS, RNA samples were isolated immediately following surgery, reverse transcribed to cDNA and each sample hybridized to duplicate high-density human U133 plus 2.0 microarrays. Array data was then analyzed relative to arrays hybridized to universal RNA to generate an unbiased transcriptome. Subsequent gene ontology analysis was used to identify transcripts with therapeutic or diagnostic potential. A subset of the most interesting genes was then validated using quantitative RT-PCR and immunohistochemistry.</p> <p>Results</p> <p>Analysis of patient array data versus universal RNA identified elevated expression of transcripts related to angiogenesis (ANGPTL2, HIF-1 alpha, MDK, c-MET, VEGF, TIMP-2), cell proliferation (PRL, IGFBP1, NTSR2, PCSK1), metastasis (ADAM9, ECM1, POSTN) and steroid biosynthesis (CYP17A1 and STS). A number of muscle-restricted transcripts (ITGB1BP3/MIBP, MYF5, MYF6 and TRIM63) were also identified, strengthening the case for a muscle cell progenitor as the origin of disease. Transcript differentials were validated using real-time PCR and subsequent immunohistochemical analysis confirmed protein expression for several of the most interesting changes (MDK, c-MET, VEGF, POSTN, CYP17A1, ITGB1BP3/MIBP and TRIM63).</p> <p>Conclusion</p> <p>Results from this first comprehensive study of ASPS gene expression identifies several targets involved in angiogenesis, metastasis and myogenic differentiation. These efforts represent the first step towards defining the cellular origin, pathogenesis and effective treatment strategies for this atypical malignancy.</p

    Increased Anion Channel Activity Is an Unavoidable Event in Ozone-Induced Programmed Cell Death

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    Ozone is a major secondary air pollutant often reaching high concentrations in urban areas under strong daylight, high temperature and stagnant high-pressure systems. Ozone in the troposphere is a pollutant that is harmful to the plant. generation by salicylic and abscisic acids. Anion channel activation was also shown to promote the accumulation of transcripts encoding vacuolar processing enzymes, a family of proteases previously reported to contribute to the disruption of vacuole integrity observed during programmed cell death.-induced programmed cell death. Because ion channels and more specifically anion channels assume a crucial position in cells, an understanding about the underlying role(s) for ion channels in the signalling pathway leading to programmed cell death is a subject that warrants future investigation
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