10 research outputs found

    Predicting Glioblastoma Cellular Motility from In Vivo MRI with a Radiomics Based Regression Model

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    Characterizing the motile properties of glioblastoma tumor cells could provide a useful way to predict the spread of tumors and to tailor the therapeutic approach. Radiomics has emerged as a diagnostic tool in the classification of tumor grade, stage, and prognosis. The purpose of this work is to examine the potential of radiomics to predict the motility of glioblastoma cells. Tissue specimens were obtained from 31 patients undergoing surgical resection of glioblastoma. Mean tumor cell motility was calculated from time-lapse videos of specimen cells. Manual segmentation was used to define the border of the enhancing tumor T1-weighted MR images, and 107 radiomics features were extracted from the normalized image volumes. Model parameter coefficients were estimated using the adaptive lasso technique validated with leave-one-out cross validation (LOOCV) and permutation tests. The R-squared value for the predictive model was 0.60 with p-values for each individual parameter estimate less than 0.0001. Permutation test models trained with scrambled motility failed to produce a model that out-performed the model trained on the true data. The results of this work suggest that it is possible for a quantitative MRI feature-based regression model to non-invasively predict the cellular motility of glioblastomas

    Application of Multistate Modeling to Estimate Salmonid Survival and Movement in Relation to Spatial and Temporal Variation in Metal Exposure in a Mining-Impacted River

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    Multistate modeling was used to estimate survival and movement of brown trout Salmo trutta and westslope cutthroat trout Oncorhynchus clarkii lewisi in relation to copper concentrations in the mining-impacted Clark Fork River, Montana. Survival probability in the uppermost river segment, where dissolved copper concentrations frequently exceeded acute criteria for aquatic life (range, 31-60 d >13.4 ¾g¡L-1), was 2.1 times lower for brown trout and 122 times lower for westslope cutthroat trout compared to survival rates in the lowermost segment that had relatively low dissolved copper (0 d exceedance of acute concentration). Lowest survival for both species occurred in the spring-summer period when dissolved copper concentrations were elevated coincident with higher discharge. Movement among study segments was generally low, and cutthroat trout showed low movement into the uppermost river segment with the most elevated copper levels. Both species showed high rates of movement into tributaries, which coincided with their respective spawning migrations rather than as an apparent avoidance of elevated copper levels. The linkage between survival rate and level of copper exposure for both trout species suggests that additional removal of tailings deposits could improve survival rates.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

    Expression of IL-20 Receptor Subunit β Is Linked to EAE Neuropathology and CNS Neuroinflammation

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    Considerable clinical evidence supports that increased blood–brain barrier (BBB) permeability is linked to immune extravasation of CNS parenchyma during neuroinflammation. Although BBB permeability and immune extravasation are known to be provoked by vascular endothelial growth factor-A (i.e., VEGF-A) and C-X-C motif chemokine ligand 12 (CXCL12), respectively, the mechanisms that link both processes are still elusive. The interleukin-20 (i.e., IL-20) cytokine signaling pathway was previously implicated in VEGF-mediated angiogenesis and is known to induce cellular response by way of signaling through IL-20 receptor subunit β (i.e., IL-20RB). Dysregulated IL-20 signaling is implicated in many inflammatory pathologies, but it’s contribution to neuroinflammation has yet to be reported. We hypothesize that the IL-20 cytokine, and the IL cytokine subfamily more broadly, play a key role in CNS neuroinflammation by signaling through IL-20RB, induce VEGF activity, and enhance both BBB-permeability and CXCL12-mediated immune extravasation. To address this hypothesis, we actively immunized IL-20RB–/– mice and wild-type mice to induce experimental autoimmune encephalomyelitis (EAE) and found that IL-20RB–/– mice showed amelioration of disease progression compared to wild-type mice. Similarly, we passively immunized IL-20RB–/– mice and wild-type mice with myelin-reactive Th1 cells from either IL-20RB–/– and wild-type genotype. Host IL-20RB–/– mice showed lesser disease progression than wild-type mice, regardless of the myelin-reactive Th1 cells genotype. Using multianalyte bead-based immunoassay and ELISA, we found distinctive changes in levels of pro-inflammatory cytokines between IL-20RB–/– mice and wild-type mice at peak of EAE. We also found detectable levels of all cytokines of the IL-20 subfamily within CNS tissues and specific alteration to IL-20 subfamily cytokines IL-19, IL-20, and IL-24, expression levels. Immunolabeling of CNS region-specific microvessels confirmed IL-20RB protein at the spinal cord microvasculature and upregulation during EAE. Microvessels isolated from macaques CNS tissues also expressed IL-20RB. Moreover, we identified the expression of all IL-20 receptor subunits: IL-22 receptor subunit α-1 (IL-22RA1), IL-20RB, and IL-20 receptor subunit α (IL-20RA) in human CNS microvessels. Notably, human cerebral microvasculature endothelial cells (HCMEC/D3) treated with IL-1β showed augmented expression of the IL-20 receptor. Lastly, IL-20-treated HCMEC/D3 showed alterations on CXCL12 apicobasal polarity consistent with a neuroinflammatory status. This evidence suggests that IL-20 subfamily cytokines may signal at the BBB via IL-20RB, triggering neuroinflammation

    Data from an international multi-centre study of statistics and mathematics anxieties and related variables in university students (the SMARVUS dataset)

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    This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website [https://osf.io/mhg94/]

    Data from an international multi-centre study of statistics and mathematics anxieties and related variables in university students (the SMARVUS dataset)

    No full text

    Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

    No full text
    This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments\’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website [https://osf.io/mhg94/]

    Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

    No full text
    This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website [https://osf.io/mhg94/]
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