61 research outputs found

    FeatureExplorer: Interactive Feature Selection and Exploration of Regression Models for Hyperspectral Images

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    Feature selection is used in machine learning to improve predictions, decrease computation time, reduce noise, and tune models based on limited sample data. In this article, we present FeatureExplorer, a visual analytics system that supports the dynamic evaluation of regression models and importance of feature subsets through the interactive selection of features in high-dimensional feature spaces typical of hyperspectral images. The interactive system allows users to iteratively refine and diagnose the model by selecting features based on their domain knowledge, interchangeable (correlated) features, feature importance, and the resulting model performance.Comment: To appear in IEEE VIS 2019 Short Paper

    Pathogenic Connexin-31 Forms Constitutively Active Hemichannels to Promote Necrotic Cell Death

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    Mutations in Connexin-31 (Cx31) are associated with multiple human diseases including erythrokeratodermia variabilis (EKV). The molecular action of Cx31 pathogenic mutants remains largely elusive. We report here that expression of EKV pathogenic mutant Cx31R42P induces cell death with necrotic characteristics. Inhibition of hemichannel activity by a connexin hemichannel inhibitor or high extracellular calcium suppresses Cx31R42P-induced cell death. Expression of Cx31R42P induces ER stress resulting in reactive oxygen species (ROS) production, in turn, to regulate gating of Cx31R42P hemichannels and Cx31R42P induced cell death. Moreover, Cx31R42P hemichannels play an important role in mediating ATP release from the cell. In contrast, no hemichannel activity was detected with cells expressing wildtype Cx31. Together, the results suggest that Cx31R42P forms constitutively active hemichannels to promote necrotic cell death. The Cx31R42P active hemichannels are likely resulted by an ER stress mediated ROS overproduction. The study identifies a mechanism of EKV pathogenesis induced by a Cx31 mutant and provides a new avenue for potential treatment strategy of the disease

    Dependency of NELF-E-SLUG-KAT2B epigenetic axis in breast cancer carcinogenesis.

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    Cancer cells undergo transcriptional reprogramming to drive tumor progression and metastasis. Using cancer cell lines and patient-derived tumor organoids, we demonstrate that loss of the negative elongation factor (NELF) complex inhibits breast cancer development through downregulating epithelial-mesenchymal transition (EMT) and stemness-associated genes. Quantitative multiplexed Rapid Immunoprecipitation Mass spectrometry of Endogenous proteins (qPLEX-RIME) further reveals a significant rewiring of NELF-E-associated chromatin partners as a function of EMT and a co-option of NELF-E with the key EMT transcription factor SLUG. Accordingly, loss of NELF-E leads to impaired SLUG binding on chromatin. Through integrative transcriptomic and genomic analyses, we identify the histone acetyltransferase, KAT2B, as a key functional target of NELF-E-SLUG. Genetic and pharmacological inactivation of KAT2B ameliorate the expression of EMT markers, phenocopying NELF ablation. Elevated expression of NELF-E and KAT2B is associated with poorer prognosis in breast cancer patients, highlighting the clinical relevance of our findings. Taken together, we uncover a crucial role of the NELF-E-SLUG-KAT2B epigenetic axis in breast cancer carcinogenesis

    DNA interstrand cross-link repair requires replication fork convergence

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    DNA interstrand cross-links (ICLs) prevent strand separation during DNA replication and transcription and are therefore extremely cytotoxic. In metazoans, a major pathway of ICL repair is coupled to DNA replication and requires the Fanconi anemia pathway. In most current models, collision of a single DNA replication fork with an ICL is sufficient to initiate repair. In contrast, we show here that in Xenopus egg extracts, two DNA replication forks must converge on an ICL to trigger repair. When only one fork reaches the ICL, the replicative CMG helicase fails to unload from the stalled fork, and repair is blocked. Arrival of a second fork, even when substantially delayed, rescues repair. We conclude that ICL repair requires a replication-induced X-shaped DNA structure surrounding the lesion, and we speculate how this requirement helps maintain genomic stability in S phase

    Sorghum biomass prediction using UAV-based remote sensing data and crop model simulation

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    Accurate phenotyping with unmanned aerial vehicles is a remote sensing application that has received recent attention as plant breeders seek to automate the expensive and time consuming traditional manual acquisition of measurements of plant traits. This paper focuses on the prediction of sorghum biomass utilizing high temporal and spatial resolution remote sensing data. Two methods are investigated for biomass prediction. The first uses nonlinear regression models to predict biomass directly from remote sensing data, based on features from Light Detection And Ranging (LiDAR) point clouds and hyperspectral data. The second strategy focuses on the biophysical sorghum crop model, APSIM, first, using remote sensing data to parametrize the crop model, and then simulating the biomass. Results from both approaches are provided and evaluated for an agricultural test field at the Agronomy Center for Research and Education (ACRE) at Purdue University

    Development of a Cumulative Exposure Index (CEI) for Manganese and Comparison with Bone Manganese and Other Biomarkers of Manganese Exposure

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    Manganese (Mn) exposure can result in parkinsonism. However, understanding of manganese neurotoxicity has been limited by the lack of a cumulative Mn biomarker. Therefore, the current goal was to develop Mn cumulative exposure indices (MnCEI), an established method to estimate cumulative exposure, and determine associations of MnCEI with blood Mn (BMn), fingernail Mn (FMn), and bone Mn (BnMn). We completed a cross-sectional study of 60 male Chinese workers. Self-reported occupational history was used to create two MnCEIs reflecting the previous 16 years (MnCEI16) and total work history (MnCEITOT). An in vivo neutron activation analysis system was used to quantify BnMn. BMn and FMn were measured using ICP-MS. Mean (standard deviation) MnCEITOT and MnCEI16 were 37.5 (22.0) and 25.0 (11.3), respectively. Median (interquartile range) BMn, FMn, and BnMn were 14.1 (4.0) μg/L, 13.5 (58.5) μg/g, and 2.6 (7.2) μg/g dry bone, respectively. MnCEI16 was significantly correlated with FMn (Spearman’s ρ = 0.44; p = 0.02), BnMn (ρ = 0.44; p < 0.01), and MnCEITOT (ρ = 0.44; p < 0.01). In adjusted regression models, MnCEI16 was significantly associated with BnMn (β = 0.03; 95% confidence interval = 0.001, 0.05); no other biomarkers were associated with MnCEI. This suggests BnMn may be a useful biomarker of the previous 16 years of Mn exposure, but larger studies are recommended
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