Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm, and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions.In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams,

BackgroundThe proinflammatory cytokines interleukin 1b (IL-1b) and IL-18 are central players in the pathogenesis of inflammatory bowel disease (IBD). In response to a variety of microbial components and crystalline substances, both cytokines are processed via the caspase-1-activating multiprotein complex, the NLRP3 inflammasome. Here, the role of the NLRP3 inflammasome in experimental colitis induced by dextran sodium sulfate (DSS) was examined. Methods IL-1b production in response to DSS was studied in macrophages of wild-type, caspase-1 e/e , NLRP3e/e , ASC e/e , cathepsin B e/e or cathepsin L e/e mice. Colitis was induced in C57BL/6 and NLRP3

sensitivity of this test (as low as 60% in some reports) might have led to misclassification and diagnostic bias. 7 However, this preliminary report of an association between hypogeusia or hyposmia and COVID19 diagnosis in patients with ILI suggests that these symptoms might be a useful tool for initial diagnostic workup in patients with suspected COVID19. These symptoms, which are easy to collect, could be used for mass screening, by professionals with limited medical knowledge, and through telemedicine. Larger prospective studies are required to confirm these preliminary findings.We declare no competing interests.

Abstract. This paper describes a framework for evaluating airway extraction algorithms in a standardized manner and establishing reference segmentations that can be used for future algorithm development. Because of the sheer difficulty of constructing a complete reference standard manually, we propose to construct a reference using results from the algorithms being compared, by splitting each airway tree segmentation result into individual branch segments that are subsequently visually inspected by trained observers. Using the so constructed reference, a total of seven performance measures covering different aspects of segmentation quality are computed. We evaluated 15 airway tree extraction algorithms from different research groups on a diverse set of 20 chest CT scans from subjects ranging from healthy volunteers to patients with severe lung disease, who were scanned at different sites, with several different CT scanner models, and using a variety of scanning protocols and reconstruction parameters.

Pancreatic ductal adenocarcinoma (PDA) is notoriously aggressive and hard to treat. The tumour microenvironment (TME) in PDA is highly dynamic and has been found to promote tumour progression, metastasis niche formation and therapeutic resistance. Intensive research of recent years has revealed an incredible heterogeneity and complexity of the different components of the TME, including cancer-associated fibroblasts, immune cells, extracellular matrix components, tumour vessels and nerves. It has been hypothesised that paracrine interactions between neoplastic epithelial cells and TME compartments may result in either tumour-promoting or tumour-restraining consequences. A better preclinical understanding of such complex and dynamic network systems is required to develop more powerful treatment strategies for patients. Scientific activity and the number of compelling findings has virtually exploded during recent years. Here, we provide an update of the most recent findings in this area and discuss their translational and clinical implications for basic scientists and clinicians alike.

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The biology of solid tumors is strongly determined by the interactions of cancer cells with their surrounding microenvironment. In this regard, pancreatic cancer (pancreatic ductal adenocarcinoma, PDAC) represents a paradigmatic example for the multitude of possible tumor–stroma interactions. PDAC has proven particularly refractory to novel immunotherapies, which is a fact that is mediated by a unique assemblage of various immune cells creating a strongly immunosuppressive environment in which this cancer type thrives. In this review, we outline currently available knowledge on the cross-talk between tumor cells and the cellular immune microenvironment, highlighting the physiological and pathological cellular interactions, as well as the resulting therapeutic approaches derived thereof. Hopefully a better understanding of the complex tumor–stroma interactions will one day lead to a significant advancement in patient care.

Emerging data demonstrate that the activity of immune cells can be modulated by microbial molecules. Here, we show that the short-chain fatty acids (SCFAs) pentanoate and butyrate enhance the anti-tumor activity of cytotoxic T lymphocytes (CTLs) and chimeric antigen receptor (CAR) T cells through metabolic and epigenetic reprograming. We show that in vitro treatment of CTLs and CAR T cells with pentanoate and butyrate increases the function of mTOR as a central cellular metabolic sensor, and inhibits class I histone deacetylase activity. This reprogramming results in elevated production of effector molecules such as CD25, IFN-γ and TNF-α, and significantly enhances the anti-tumor activity of antigen-specific CTLs and ROR1-targeting CAR T cells in syngeneic murine melanoma and pancreatic cancer models. Our data shed light onto microbial molecules that may be used for enhancing cellular anti-tumor immunity. Collectively, we identify pentanoate and butyrate as two SCFAs with therapeutic utility in the context of cellular cancer immunotherapy.