Kidney segmentation using 3D U-Net localized with Expectation Maximization

Kidney volume is greatly affected in several renal diseases. Precise and automatic segmentation of the kidney can help determine kidney size and evaluate renal function. Fully convolutional neural networks have been used to segment organs from large biomedical 3D images. While these networks demonstrate state-of-the-art segmentation performances, they do not immediately translate to small foreground objects, small sample sizes, and anisotropic resolution in MRI datasets. In this paper we propose a new framework to address some of the challenges for segmenting 3D MRI. These methods were implemented on preclinical MRI for segmenting kidneys in an animal model of lupus nephritis. Our implementation strategy is twofold: 1) to utilize additional MRI diffusion images to detect the general kidney area, and 2) to reduce the 3D U-Net kernels to handle small sample sizes. Using this approach, a Dice similarity coefficient of 0.88 was achieved with a limited dataset of n=196. This segmentation strategy with careful optimization can be applied to various renal injuries or other organ systems

A novel inhibitor of the alternative pathway of complement reverses inflammation and bone destruction in experimental arthritis

Complement is an important component of the innate and adaptive immune response, yet complement split products generated through activation of each of the three complement pathways (classical, alternative, and lectin) can cause inflammation and tissue destruction. Previous studies have shown that complement activation through the alternative, but not classical, pathway is required to initiate antibody-induced arthritis in mice, but it is unclear if the alternative pathway (AP) plays a role in established disease. Previously, we have shown that human complement receptor of the immunoglobulin superfamily (CRIg) is a selective inhibitor of the AP of complement. Here, we present the crystal structure of murine CRIg and, using mutants, provide evidence that the structural requirements for inhibition of the AP are conserved in human and mouse. A soluble form of CRIg reversed inflammation and bone loss in two experimental models of arthritis by inhibiting the AP of complement in the joint. Our data indicate that the AP of complement is not only required for disease induction, but also disease progression. The extracellular domain of CRIg thus provides a novel tool to study the effects of inhibiting the AP of complement in established disease and constitutes a promising therapeutic with selectivity for a single complement pathway

Host-Detrimental Role of Esx-1-Mediated Inflammasome Activation in Mycobacterial Infection

The Esx-1 (type VII) secretion system is a major virulence determinant of pathogenic mycobacteria, including Mycobacterium marinum. However, the molecular events and host-pathogen interactions underlying Esx-1-mediated virulence in vivo remain unclear. Here we address this problem in a non-lethal mouse model of M. marinum infection that allows detailed quantitative analysis of disease progression. M. marinum established local infection in mouse tails, with Esx-1-dependent formation of caseating granulomas similar to those formed in human tuberculosis, and bone deterioration reminiscent of skeletal tuberculosis. Analysis of tails infected with wild type or Esx-1-deficient bacteria showed that Esx-1 enhanced generation of proinflammatory cytokines, including the secreted form of IL-1β, suggesting that Esx-1 promotes inflammasome activation in vivo. In vitro experiments indicated that Esx-1-dependent inflammasome activation required the host NLRP3 and ASC proteins. Infection of wild type and ASC-deficient mice demonstrated that Esx-1-dependent inflammasome activation exacerbated disease without restricting bacterial growth, indicating a host-detrimental role of this inflammatory pathway in mycobacterial infection. These findings define an immunoregulatory role for Esx-1 in a specific host-pathogen interaction in vivo, and indicate that the Esx-1 secretion system promotes disease and inflammation through its ability to activate the inflammasome

Quantification of Tumor Burden in a Genetically Engineered Mouse Model of Lung Cancer by Micro-CT and Automated Analysis

AbstractGenetically engineered mouse models (GEMMs) of lung cancer closely recapitulate the human disease but suffer from the difficulty of evaluating tumor growth by conventional methods. Herein, a novel automated image analysis method for estimating the lung tumor burden from in vivo micro-computed tomography (micro-CT) data is described. The proposed tumor burden metric is the segmented soft tissue volume contained within a chest space region of interest, excluding an estimate of the heart volume. The method was validated by comparison with previously published manual analysis methods and applied in two therapeutic studies in a mutant K-ras GEMM of non–small cell lung carcinoma. Mice were imaged by micro-CT pre-treatment and stratified into four treatment groups: an antibody inhibiting vascular endothelial growth factor (anti-VEGF), chemotherapy, combination of anti-VEGF and chemotherapy, or control antibody. In the first study, post-treatment imaging was performed 4 weeks later. In the second study, mice were scanned serially on a high-throughput scanner every 2 weeks for 8 weeks during treatment. In both studies, the automated tumor burden estimates were well correlated with manual metrics (r value range: 0.83-0.93, P < .0001) and showed a similar, significant reduction in tumor growth in mice treated with anti-VEGF alone or in combination with chemotherapy. Given the fully automated nature of this technique, the proposed analysis method can provide a valuable tool in preclinical drug research for screening and randomizing animals into treatment groups and evaluating treatment efficacy in mouse models of lung cancer in a highly robust and efficient manner

A Rare Population of CD24+ITGB4+Notchhi Cells Drives Tumor Propagation in NSCLC and Requires Notch3 for Self-Renewal

Sustained tumor progression has been attributed to a distinct population of tumor-propagating cells (TPCs). To identify TPCs relevant to lung cancer pathogenesis, we investigated functional heterogeneity in tumor cells isolated from Kras-driven mouse models of non-small-cell lung cancer (NSCLC). CD24(+)ITGB4(+)Notch(hi) cells are capable of propagating tumor growth in both a clonogenic and an orthotopic serial transplantation assay. While all four Notch receptors mark TPCs, Notch3 plays a nonredundant role in tumor cell propagation in two mouse models and in human NSCLC. The TPC population is enriched after chemotherapy, and the gene signature of mouse TPCs correlates with poor prognosis in human NSCLC. The role of Notch3 in tumor propagation may provide a therapeutic target for NSCLC