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Regional risk assessments for the potential effects of climate change rely on plausible small-scale climate change scenario data. To bridge the gap between the coarse scale of general circulation models and the local scale of approximately 11000 sample sites of the Austrian National Forest Inventory (AFI), a seasonally stratified statistical downscaling procedure was applied to a control run and 2 transient experiments of ECHAM4/OPYC3, which are based on the trace gas only or trace gas plus sulphate scenario IPCC IS92a. We fitted multiple linear regression (MLR) models for the micro-scale monthly precipitation and temperature for each AFI point. The meteorological data at the AFI sites were obtained by interpolation of measurements from the dense network of Austrian weather stations for the period 1961-1995. The macro-scale predictors were principal components of monthly NCEP/NCAR reanalysis data (850 and 700 hPa geopotential height, 850 hPa temperature and 700 hPa relative humidity). The results show spatial and temporal heterogeneity for both temperature and precipitation. In case of temperature MLR leads to increases from +1.4 to +4.0°C (trace gas only integration) and from +1.1 to +2.9°C (trace gas plus sulphate integration) for a period of about 55 yr relative to the 1961-1995 climatology. The regionalized precipitation changes are both negative and positive. Values range from -44 to + 26% (trace gas only integration) and from -29 to + 26% (trace gas plus sulphate integration). As expected, the explained variability for temperature was higher than for precipitation and depended on the season. From a validation experiment for model calibration we conclude that MLR shows reliable results for temperature. Even in the case of precipitation the method seems to yield plausible results. Both temperature and precipitation were better reproduced for winter than for summer. [ABSTRACT FROM AUTHOR]

On the basis of the positive outcome of animal experiments, several large placebo-controlled trials are underway and aiming for the first time at the prevention of an immune-mediated disease, type 1 diabetes. The first of these trials, The Deutsche Nicotinamide Intervention Study (DENIS), evaluated the clinical efficacy of high doses of nicotinamide in children at high risk for IDDM. Nicotinamide has been shown to protect beta-cells from inflammatory insults and to improve residual beta-cell function in patients after onset of IDDM. Individuals at high risk for developing IDDM within 3 years were identified by screening the siblings (age 3-12 years) of patients with IDDM for the presence of high titer (> or =20 Juvenile Diabetes Foundation [JDF] U) islet cell antibodies. Probands (n = 55) were randomized into placebo and nicotinamide (slow release, 1.2 g x m(-2) x day(-1)) receiving groups and followed prospectively in a controlled clinical trial using a sequential design. Rates of diabetes onset were similar in both groups throughout the observation period (maximum 3.8 years, median 2.1 years). This sequential design provides a 10% probability of a type II error against a reduction of the cumulative diabetes incidence at 3 years from 30 to 6% by nicotinamide. The trial was terminated when the second sequential interim analysis after the eleventh case of diabetes showed that the trial had failed to detect a reduction of the cumulative diabetes incidence at 3 years from 30 to 6% (P = 0.97). The group receiving nicotinamide exhibited decreased first-phase insulin secretion in response to intravenous glucose (P = 0.03). No other side effects were observed. We conclude that in this subgroup of diabetes-prone individuals at very high risk and with an assumed rapid disease progression, nicotinamide treatment did not cause a major decrease or delay of diabetes development. However, the data do not exclude the possibility of a less strong, but potentially meaningful, risk reduction in this cohort, or a major clinical effect of nicotinamide in individuals with less risk of progression to IDDM than studied here.