Development and validation of two self-reported tools for insulin resistance and hypertension risk assessment in a European cohort : the Feel4Diabetes-study

Early identification of type 2 diabetes mellitus (T2DM) and hypertension (HTN) risk may improve prevention and promote public health. Implementation of self-reported scores for risk assessment provides an alternative cost-effective tool. The study aimed to develop and validate two easy-to-apply screening tools identifying high-risk individuals for insulin resistance (IR) and HTN in a European cohort. Sociodemographic, lifestyle, anthropometric and clinical data obtained from 1581 and 1350 adults (baseline data from the Feel4Diabetes-study) were used for the European IR and the European HTN risk assessment index respectively. Body mass index, waist circumference, sex, age, breakfast consumption, alcohol, legumes and sugary drinks intake, physical activity and sedentary behavior were significantly correlated with Homeostatic Model Assessment of IR (HOMA-IR) and/or HTN and incorporated in the two models. For the IR index, the Area Under the Curve (AUC), sensitivity and specificity for identifying individuals above the 75th and 95th of HOMA-IR percentiles were 0.768 (95%CI: 0.721–0.815), 0.720 and 0.691 and 0.828 (95%CI: 0.766–0.890), 0.696 and 0.778 respectively. For the HTN index, the AUC, sensitivity and specificity were 0.778 (95%CI: 0.680–0.876), 0.667 and 0.797. The developed risk assessment tools are easy-to-apply, valid, and low-cost, identifying European adults at high risk for developing T2DM or having HTN

Sigref – A Symbolic Bisimulation Tool Box

We present a uniform signature-based approach to compute the most popular bisimulations. Our approach is implemented symbolically using BDDs, which enables the handling of very large transition systems. Signatures for the bisimulations are built up from a few generic building blocks, which naturally correspond to efficient BDD operations. Thus, the definition of an appropriate signature is the key for a rapid development of algorithms for other types of bisimulation. We provide experimental evidence of the viability of this approach by presenting computational results for many bisimulations on real-world instances. The experiments show cases where our framework can handle state spaces efficiently that are far too large to handle for any tool that requires an explicit state space description. This work was partly supported by the German Research Council (DFG) as part of the Transregional Collaborative Research Center “Automatic Verification and Analysis of Complex Systems” (SFB/TR 14 AVACS). See www.avacs.org for more information

Acute myeloid leukemia maturation lineage influences residual disease and relapse following differentiation therapy

Acute myeloid leukemia (AML) is a malignancy of immature progenitor cells. AML differentiation therapies trigger leukemia maturation and can induce remission, but relapse is prevalent and its cellular origin is unclear. Here we describe high resolution analysis of differentiation therapy response and relapse in a mouse AML model. Triggering leukemia differentiation in this model invariably produces two phenotypically distinct mature myeloid lineages in vivo. Leukemia-derived neutrophils dominate the initial wave of leukemia differentiation but clear rapidly and do not contribute to residual disease. In contrast, a therapyinduced population of mature AML-derived eosinophil-like cells persists during remission, often in extramedullary organs. Using genetic approaches we show that restricting therapy induced leukemia maturation to the short-lived neutrophil lineage markedly reduces relapse rates and can yield cure. These results indicate that relapse can originate from therapy resistant mature AML cells, and suggest differentiation therapy combined with targeted eradication of mature leukemia-derived lineages may improve disease outcome.Steven Ngo, Ethan P. Oxley, Margherita Ghisi, Maximilian M. Garwood, Mark D. McKenzie, Helen L. Mitchell, Peter Kanellakis, Olivia Susanto, Michael J. Hickey, Andrew C. Perkins, Benjamin T. Kile, Ross A. Dickin

Depletion of B2 but Not B1a B Cells in BAFF Receptor-Deficient ApoE−/− Mice Attenuates Atherosclerosis by Potently Ameliorating Arterial Inflammation

We have recently identified conventional B2 cells as atherogenic and B1a cells as atheroprotective in hypercholesterolemic ApoE−/− mice. Here, we examined the development of atherosclerosis in BAFF-R deficient ApoE−/− mice because B2 cells but not B1a cells are selectively depleted in BAFF-R deficient mice. We fed BAFF-R−/− ApoE−/− (BaffR.ApoE DKO) and BAFF-R+/+ApoE−/− (ApoE KO) mice a high fat diet (HFD) for 8-weeks. B2 cells were significantly reduced by 82%, 81%, 94%, 72% in blood, peritoneal fluid, spleen and peripheral lymph nodes respectively; while B1a cells and non-B lymphocytes were unaffected. Aortic atherosclerotic lesions assessed by oil red-O stained-lipid accumulation and CD68+ macrophage accumulation were decreased by 44% and 50% respectively. B cells were absent in atherosclerotic lesions of BaffR.ApoE DKO mice as were IgG1 and IgG2a immunoglobulins produced by B2 cells, despite low but measurable numbers of B2 cells and IgG1 and IgG2a immunoglobulin concentrations in plasma. Plasma IgM and IgM deposits in atherosclerotic lesions were also reduced. BAFF-R deficiency in ApoE−/− mice was also associated with a reduced expression of VCAM-1 and fewer macrophages, dendritic cells, CD4+ and CD8+ T cell infiltrates and PCNA+ cells in lesions. The expression of proinflammatory cytokines, TNF-α, IL1-β and proinflammatory chemokine MCP-1 was also reduced. Body weight and plasma cholesterols were unaffected in BaffR.ApoE DKO mice. Our data indicate that B2 cells are important contributors to the development of atherosclerosis and that targeting the BAFF-R to specifically reduce atherogenic B2 cell numbers while preserving atheroprotective B1a cell numbers may be a potential therapeutic strategy to reduce atherosclerosis by potently reducing arterial inflammation