The coexistence of human immunodeficiency virus (HIV) infection and systemic lupus erythematosus (SLE) is unusual, but the occurrence of SLE after HIV infection is even less common. Both conditions share similar clinical features including constitutional symptoms, facial rash, oral ulcers, alopecia, arthralgias, arthritis, seizures, cytopenias, glomerulonephritis, and antinuclear and antiphospholipid antibodies. This clinical overlap makes the diagnosis of SLE in a patient with pre-existing HIV infection difficult. Furthermore, immune complex glomerulonephritis with features resembling lupus nephritis has been described in HIV-positive patients. We present the case of a 45-year-old Hispanic woman with long-standing HIV infection who developed membranous glomerulonephritis with histological features of lupus nephritis. Five years after onset of renal disease she developed clinically evident SLE.
One of the major goals in gene expression data analysis is to explore and discover groups of genes and groups of biological conditions with meaningful relationships. While this problem can be addressed by algorithms, their results require an analysis within context, since they may be affected by many side processessuch as tissue differentiation-that could hinder the target goal. Visual analytics-based methods for exploratory analysis of the gene expression matrix (GEM) are essential in biomedical research since they allow us to frame the analysis within the user's knowledge domain. In this paper, we present a visual analytics approach to discover relevant connections between genes and samples based on linking a reordered GEM heatmap and dual 2D projections of its rows and columns, which can be recomputed conditioned by subsets of genes and/or samples selected by the user during the analysis. We demonstrate the capability of our approach to discover relevant knowledge in three case studies involving two cancer types plus normal tissue from the TCGA database.
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