Pravastatin, a competitive inhibitor of hydroxymethylglutaryl CoA reductase (HMG CoA reductase) is a potent hypocholesterolemic agent in humans as well as experimental animals, including the Watanabe heritable hyperlipidemic (WHHL) rabbit, lacking low density lipoprotein (LDL) receptor activity. We studied the effect of pravastatin on several aspects of cholesterol metabolism in WHHL rabbits. Cholesterol synthesis was measured by intraperitoneal injection of radioacetate and determination of its incorporation into the nonsaponifiable lipid fraction of liver, plasma, adrenal glands and gonads. A single dose of pravastatin (25mg/kg) caused statistically significant inhibition of hepatic cholesterol synthesis at 2, 6, 12, and 24 hours following oral administration. By 48 hours, the inhibitory effect of the drug was no longer demonstrable. The pattern of radioactivity in the plasma was similar to that in the liver. The drug had no statistically significant effect on cholesterol synthesis in adrenal glands and gonads, suggesting a selective effect on the liver. Cholesterol absorption was studied after simultaneous oral administration of [³H] cholesterol and [¹⁴C] β-sitosterol. Pravastatin, 50mg/kg for 10 days had no effect on fecal excretion of the radiolabelled steroids over 4 days. At 24 hours the plasma level of [14C] cholesterol was 1/3 that of control in pravastatin treated animals (p<0.05) but did not undergo an accelerated decline over 6 days. The activity of acyl CoA: cholesterol acyltransferase (ACAT) in intestinal mucosa and the concentration of hepatic cholesterol were similar in animals treated over one year with pravastatin 50mg/kg/day or with placebo. Our data do not allow us to make definitive conclusions about the effect of pravastatin on cholesterol absorption but are compatible with the hypothesis that the drug inhibits the hepatic synthesis as well as the assembly of cholesterol into lipoproteins.

Urban environments experience amplified thermal stress due to the climate change, leading to increased health risks during extreme temperature events. Existing numerical weather prediction systems often lack the spatial resolution required to capture this phenomenon. This study assesses the efficacy of a coupled modeling system, the numerical weather prediction AROME model and the land-surface model SURFace EXternalisée in a stand alone mode (SURFEX-SA), in forecasting air temperatures at high resolutions ($2.5$km to $100$m) across four Austrian cities (Vienna, Linz, Klagenfurt and Innsbruck). The system is updated with the, according to the author’s knowledge, most accurate land use and land cover input to evaluate the added value of incorporating detailed urban environmental representations. The analysis focuses on the years 2019, 2023, and 2024, examining both summer and winter seasons. SURFEX-SA demonstrates improved performance in specific scenarios, particularly during nighttime in rural and suburban areas during the warmer season. By comprehensively analyzing this prediction system with operational and citizen weather stations in a deterministic and probabilistic mode across several time periods and various skill scores, the findings of this study will enable readers to determine whether high-resolution forecasts are necessary in specific use cases.

Zusammenfassung: Dieses Kapitel beschäftigt sich mit den klimatischen, ökologischen und sozioökonomischen treibenden Kräften, welche die Landnutzung in Österreich in der Vergangenheit und der Gegenwart maßgeblich bestimmt haben und die zukünftigen Entwicklungen beeinflussen werden. Es behandelt die in der Vergangenheit beobachteten und in der Zukunft erwarteten treibenden Kräfte von Landnutzungsänderungen in der Landwirtschaft (Abschn. 3.2), der Forstwirtschaft (Abschn. 3.3) und der Siedlungs- und Infrastrukturentwicklung (Abschn. 3.4). Abschließend werden die möglichen und erwarteten Auswirkungen dieser treibenden Kräfte auf die Bereitstellung der Ökosystemleistungen (ÖSL) beschrieben (Abschn. 3.5). Der Abbau von Mineralien wie Schotter oder Metalle wird aus Platzgründen nicht in diesem Kapitel behandelt, wenngleich es unumstritten ist, dass es sich auch dabei um landnutzungsrelevante Aktivitäten handelt. Kap. 3 unterscheidet zwischen natürlichen und anthropogenen Faktoren und wie sich diese auf die Landnutzung ausgewirkt haben und auswirken. Die sozioökonomischen Auswirkungen berücksichtigen dabei allerdings nicht die möglichen Anpassungs- oder Minderungsstrategien der einzelnen Sektoren, da diese in den Kap. 4 und 5 gesondert dargestellt werden.