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Garnet brought to the surface by late Miocene granitoids at La Galite Archipelago (Central Mediterranean, Tunisia) contains abundant primary melt and fluid inclusions. Microstructural observations and mineral chemistry define the host garnet as a peritectic phase produced by biotite incongruent melting at ~800 degrees C and 0.5GPa, under fluid-present conditions. The trapped melt is leucogranitic with an unexpected metaluminous and almost peralkaline character. Fluid inclusions are one phase at room temperature, and contain a CO2-dominated fluid, with minor H2O, N-2 and CH4. Siderite and an OH-bearing phase were identified by Raman and IR spectroscopy within every analysed inclusion, and are interpreted as products of a post-entrapment carbonation/hydration reaction between the fluid and the host during cooling. The fluid present during anatexis is therefore inferred to have been originally richer in both H2O and CO2. The production of anatectic melt with a metaluminous signature can be explained as the result of partial melting of relatively Al-poor protoliths assisted by CO2-rich fluids.
Background Exercise rehabilitation is highly recommended by current guidelines on prevention of cardiovascular disease, but its implementation is still poor. Many clinicians experience difficulties in prescribing exercise in the presence of different concomitant cardiovascular diseases and risk factors within the same patient. It was aimed to develop a digital training and decision support system for exercise prescription in cardiovascular disease patients in clinical practice: the European Association of Preventive Cardiology Exercise Prescription in Everyday Practice and Rehabilitative Training (EXPERT) tool. Methods EXPERT working group members were requested to define (a) diagnostic criteria for specific cardiovascular diseases, cardiovascular disease risk factors, and other chronic non-cardiovascular conditions, (b) primary goals of exercise intervention, (c) disease-specific prescription of exercise training (intensity, frequency, volume, type, session and programme duration), and (d) exercise training safety advices. The impact of exercise tolerance, common cardiovascular medications and adverse events during exercise testing were further taken into account for optimized exercise prescription. Results Exercise training recommendations and safety advices were formulated for 10 cardiovascular diseases, five cardiovascular disease risk factors (type 1 and 2 diabetes, obesity, hypertension, hypercholesterolaemia), and three common chronic non-cardiovascular conditions (lung and renal failure and sarcopaenia), but also accounted for baseline exercise tolerance, common cardiovascular medications and occurrence of adverse events during exercise testing. An algorithm, supported by an interactive tool, was constructed based on these data. This training and decision support system automatically provides an exercise prescription according to the variables provided. Conclusion This digital training and decision support system may contribute in overcoming barriers in exercise implementation in common cardiovascular diseases.