Diabetes mellitus and autoimmune hepatitis: demographical and clinical description of a relatively rare phenotype

Aims: We studied demographic, metabolic, and clinical characteristics of patients with diabetes and autoimmune hepatitis (AIH) from the German/Austrian DPV registry. Methods: 139 patients with diabetes and AIH were analyzed and compared to 437728 patients with diabetes without AIH. Results: The prevalence of AIH in patients with T1DM (44.8/100,000) seems higher than in the general population, the prevalence of AIH in patients with T2DM (23.6/100,000) does not seem to be increased. Patients with T2DM and AIH had a shorter duration of diabetes (p=0.007) and a higher proportion of females (p<0.001) compared to T2DM without AIH. Patients with diabetes (T1DM or T2DM) and AIH required higher insulin doses (p<0.001 resp. p=0.03) and showed increased liver enzymes (aspartate transaminase, alanine transaminase, gamma-glutamyltransferase) compared to diabetes patients without (all p <0.001). We detected a lower percentage of patients treated with oral antidiabetic drugs (p=0.01) and a higher percentage of patients treated by insulin in patients with T2DM and AIH (p<0.001) compared to patients with T2DM alone. We observed a higher incidence of autoimmune thyroid disease (AIT) in patients with diabetes (T1DM or T2DM) and AIH (p<0.001) compared to diabetes patients without AIH. Conclusions: AIH seems more frequent in patients with T1DM. Patients with diabetes and AIH require intensification of antidiabetic therapy and seem to have a higher prevalence of AIT

Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1.2) and Its Response to Increasing CO2

A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI-ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low-level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO2 forcing, which nonetheless can be represented by a simple two-layer model