Indigenous practices of water management for sustainable services : Case of Borana and Konso, Ethiopia

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Article Bilateral Collaboration in Municipal Water and Wastewater Services in Finland

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The amino-terminal oligomerization domain of angiopoietin-2 affects vascular remodeling, mammary for gland tumor growth, and lung metastasis in mice

Abstract Angiopoietin-2 (ANGPT2) is a context-dependent TIE2 agonistic or antagonistic ligand that induces diverse responses in cancer. Blocking ANGPT2 provides a promising strategy for inhibiting tumor growth and metastasis, yet variable effects of targeting ANGPT2 have complicated drug development. ANGPT2₄₄₃ is a naturally occurring, lower oligomeric protein isoform whose expression is increased in cancer. Here, we use a knock-in mouse line (mice expressing Angpt2₄₄₃), a genetic model for breast cancer and metastasis (MMTV-PyMT), a syngeneic melanoma lung colonization model (B16F10), and orthotopic injection of E0771 breast cancer cells to show that alternative forms increase the diversity of Angpt2 function. In a mouse retina model of angiogenesis, expression of Angpt2₄₄₃ caused impaired venous development, suggesting enhanced function as a competitive antagonist for Tie2. In mammary gland tumor models, Angpt2₄₄₃ differentially affected primary tumor growth and vascularization; these varying effects were associated with Angpt2 protein localization in the endothelium or in the stromal extracellular matrix as well as the frequency of Tie2-positive tumor blood vessels. In the presence of metastatic cells, Angpt2₄₄₃ promoted destabilization of pulmonary vasculature and lung metastasis. In vitro, ANGPT2₄₄₃ was susceptible to proteolytical cleavage, resulting in a monomeric ligand (ANGPT2DAP) that inhibited ANGPT1- or ANGPT4-induced TIE2 activation but did not bind to alternative ANGPT2 receptor α5β1 integrin. Collectively, these data reveal novel roles for the ANGPT2 N-terminal domain in blood vessel remodeling, tumor growth, metastasis, integrin binding, and proteolytic regulation

SCORE2 risk prediction algorithms : new models to estimate 10-year risk of cardiovascular disease in Europe

Aims The aim of this study was to develop, validate, and illustrate an updated prediction model (SCORE2) to estimate 10-year fatal and non-fatal cardiovascular disease (CVD) risk in individuals without previous CVD or diabetes aged 40-69 years in Europe. Methods and results We derived risk prediction models using individual-participant data from 45 cohorts in 13 countries (677 684 individuals, 30 121 CVD events). We used sex-specific and competing risk-adjusted models, including age, smoking status, systolic blood pressure, and total- and HDL-cholesterol. We defined four risk regions in Europe according to country-specific CVD mortality, recalibrating models to each region using expected incidences and risk factor distributions. Region-specific incidence was estimated using CVD mortality and incidence data on 10 776 466 individuals. For external validation, we analysed data from 25 additional cohorts in 15 European countries (1 133 181 individuals, 43 492 CVD events). After applying the derived risk prediction models to external validation cohorts, C-indices ranged from 0.67 (0.65-0.68) to 0.81 (0.76-0.86). Predicted CVD risk varied several-fold across European regions. For example, the estimated 10-year CVD risk for a 50-year-old smoker, with a systolic blood pressure of 140 mmHg, total cholesterol of 5.5 mmol/L, and HDL-cholesterol of 1.3 mmol/L, ranged from 5.9% for men in low- risk countries to 14.0% for men in very high-risk countries, and from 4.2% for women in low-risk countries to 13.7% for women in very high-risk countries. Conclusion SCORE2-a new algorithm derived, calibrated, and validated to predict 10-year risk of first-onset CVD in European populations-enhances the identification of individuals at higher risk of developing CVD across Europe