59 research outputs found

    Theranostics of Glioblastoma Multiforme: In Vitro Characterization of Targeted Nanoemulsions and Creation of a 3D Statistical Heatmap to Visualize Nanoemulsion Uptake

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    Glioblastoma Multiforme (GBM) continues to be a leading form of malignant brain cancer. GBM presents a high variability patient to patient. This provides a need for a theranostic system capable of both delivering therapeutic and in real-time visually observe results. Current methods involve months between treatment application and available results. Based on Nemucore Medical Innovation’s drug delivery vehicles, nanoemulsions (NE) containing chemotherapeutics are being utilized to target cancer cells and reduce systemic toxicity. Through the automation of required statistical analysis and creation of a wire-frame rat brain model with 174 defined brain regions a software capable of providing ‘real-time’ pharmacodynamics analysis of Gd3+ annotated, receptor-targeted NE is one step closer

    A theorem proving approach for automatically synthesizing visualizations of flow cytometry data

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    Abstract Background Polychromatic flow cytometry is a popular technique that has wide usage in the medical sciences, especially for studying phenotypic properties of cells. The high-dimensionality of data generated by flow cytometry usually makes it difficult to visualize. The naive solution of simply plotting two-dimensional graphs for every combination of observables becomes impractical as the number of dimensions increases. A natural solution is to project the data from the original high dimensional space to a lower dimensional space while approximately preserving the overall relationship between the data points. The expert can then easily visualize and analyze this low-dimensional embedding of the original dataset. Results This paper describes a new method, SANJAY, for visualizing high-dimensional flow cytometry datasets. This technique uses a decision procedure to automatically synthesize two-dimensional and three-dimensional projections of the original high-dimensional data while trying to minimize distortion. We compare SANJAY to the popular multidimensional scaling (MDS) approach for visualization of small data sets drawn from a representative set of benchmarks, and our experiments show that SANJAY produces distortions that are 1.44 to 4.15 times smaller than those caused due to MDS. Our experimental results show that SANJAY also outperforms the Random Projections technique in terms of the distortions in the projections. Conclusions We describe a new algorithmic technique that uses a symbolic decision procedure to automatically synthesize low-dimensional projections of flow cytometry data that typically have a high number of dimensions. Our algorithm is the first application, to our knowledge, of using automated theorem proving for automatically generating highly-accurate, low-dimensional visualizations of high-dimensional data

    A Theorem Proving Approach For Automatically Synthesizing Visualizations Of Flow Cytometry Data

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    Background: Polychromatic flow cytometry is a popular technique that has wide usage in the medical sciences, especially for studying phenotypic properties of cells. The high-dimensionality of data generated by flow cytometry usually makes it difficult to visualize. The naive solution of simply plotting two-dimensional graphs for every combination of observables becomes impractical as the number of dimensions increases. A natural solution is to project the data from the original high dimensional space to a lower dimensional space while approximately preserving the overall relationship between the data points. The expert can then easily visualize and analyze this low-dimensional embedding of the original dataset. Results: This paper describes a new method, SANJAY, for visualizing high-dimensional flow cytometry datasets. This technique uses a decision procedure to automatically synthesize two-dimensional and three-dimensional projections of the original high-dimensional data while trying to minimize distortion. We compare SANJAY to the popular multidimensional scaling (MDS) approach for visualization of small data sets drawn from a representative set of benchmarks, and our experiments show that SANJAY produces distortions that are 1.44 to 4.15 times smaller than those caused due to MDS. Our experimental results show that SANJAY also outperforms the Random Projections technique in terms of the distortions in the projections. Conclusions: We describe a new algorithmic technique that uses a symbolic decision procedure to automatically synthesize low-dimensional projections of flow cytometry data that typically have a high number of dimensions. Our algorithm is the first application, to our knowledge, of using automated theorem proving for automatically generating highly-accurate, low-dimensional visualizations of high-dimensional data

    Women in Science 2014

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    Women in Science 2014 summarizes research done by Smith College’s Summer Research Fellowship (SURF) Program participants. Ever since its 1967 start, SURF has been a cornerstone of Smith’s science education. In 2014, 150 students participated in SURF (141 hosted on campus and nearby eld sites), supervised by 61 faculty mentor-advisors drawn from the Clark Science Center and connected to its eighteen science, mathematics, and engineering departments and programs and associated centers and units. At summer’s end, SURF participants were asked to summarize their research experiences for this publication.https://scholarworks.smith.edu/clark_womeninscience/1003/thumbnail.jp

    Technology 2002: the Third National Technology Transfer Conference and Exposition, Volume 1

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    The proceedings from the conference are presented. The topics covered include the following: computer technology, advanced manufacturing, materials science, biotechnology, and electronics

    Uncertainty in Artificial Intelligence: Proceedings of the Thirty-Fourth Conference

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    2010-2011, University of Memphis bulletin

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    University of Memphis bulletin containing the graduate catalog for 2010-2011.https://digitalcommons.memphis.edu/speccoll-ua-pub-bulletins/1430/thumbnail.jp

    2009-2010, University of Memphis bulletin

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    University of Memphis bulletin containing the graduate catalog for 2009-2010.https://digitalcommons.memphis.edu/speccoll-ua-pub-bulletins/1429/thumbnail.jp
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