Droughts during the growing season are projected to increase in frequency and severity in Central Europe in the future. Thus, area-wide monitoring of agricultural drought in this region is becoming more and more important. In this context, it is essential to know where and when vegetation growth is primarily water-limited and whether remote sensing-based drought indices can detect agricultural drought in these areas. To answer these questions, we conducted a correlation analysis between the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) within the growing season from 2001 to 2020 in Bavaria (Germany) and investigated the relationship with land cover and altitude. In the second step, we applied the drought indices Temperature Condition Index (TCI), Vegetation Condition Index (VCI), and Vegetation Health Index (VHI) to primarily water-limited areas and evaluated them with soil moisture and agricultural yield anomalies. We found that, especially in the summer months (July and August), on agricultural land and grassland and below 800 m, NDVI and LST are negatively correlated and thus, water is the primary limiting factor for vegetation growth here. Within these areas and periods, the TCI and VHI correlate strongly with soil moisture and agricultural yield anomalies, suggesting that both indices have the potential to detect agricultural drought in Bavaria.

Context Pheochromocytomas/paragangliomas (PPGLs) with pathogenic mutations in the succinate dehydrogenase subunit B (SDHB) are associated with a high metastatic risk. Somatostatin receptor 2 (SSTR2)-dependent imaging is the most sensitive imaging modality for SDHB-related PPGLs, suggesting that SSTR2 expression is a significant cell surface therapeutic biomarker of such tumors. Objective Exploration of the relationship between SSTR2 immunoreactivity and SDHB immunoreactivity, mutational status, and clinical behavior of PPGLs. Evaluation of SSTR-based therapies in metastatic PPGLs. Design Retrospective analysis of a multicenter cohort of PPGLs. Setting Six specialized Endocrine Tumor Centers in Germany, the Netherlands and Switzerland. Patients Patients with PPGLs participating in the ENSAT registry. Methods Clinical data were extracted from medical records and immunohistochemistry (IHC) for SDHB and SSTR2 was performed in patients with available tumor tissue. Immunoreactivity of SSTR2 was investigated using Volante scores. Main outcome measure Association of SSTR2 IHC positivity with genetic and clinic-pathological features of PPGLs. Results Of 202 patients with PPGLs, 50% were SSTR2 positive. SSTR2 positivity was significantly associated with SDHB- and SDHx-related PPGLs, with the strongest SSTR2 staining intensity in SDHB-related PPGLs (p = 0.01). Moreover, SSTR2 expression was significantly associated with metastatic disease independent of SDHB/SDHx mutation status (p < 0.001). In metastatic PPGLs, the disease control rate with first-line SSTR-based radionuclide therapy was 67% (n = 22, n = 11 SDHx), and with first-line “cold” somatostatin analogs 100% (n = 6, n = 3 SDHx). Conclusions SSTR2 expression was independently associated with SDHB/SDHx mutations and metastatic disease. We confirm a high disease control rate of somatostatin receptor-based therapies in metastatic PPGLs.

<p>Real-time on-site observations are the fundamentals for studies of climate change, especially in phenology. The online environmental data collection and analysis platform BAYSICS has been developed for Bavaria, Germany, in order to assist and promote essential climatic related research to citizen scientists. In this study, we focus on presenting a novel aspect from such an integrated network – using interactive web applications to guide citizen scientists through applied climate change topics, and further develop their very own research questions which could be answered with the assistance of shiny apps. The following implemented shiny apps will be introduced in detail: Green Warming Stripes – a simple and direct visualization in coloured stripes showing the effects of climate change on the seasonal development of plants; PhenoInterpol – a map tool to visualize the phenological interpolated map in Bavaria as well as to perform phenological long-term trend analyses as a citizen scientist combining historical and his/her own observations; TECCS – an easy-to-use simulation tool for investigating the possible effects of winter and/or spring warming on bud break. More functionalities have been planned with the aim of building better connections between the scientific community and citizen society. In such a way we believe that not only data-based scientific research can be improved (database, models, and more) but also educational efforts based on “inquiry-based learning” related to climate change can be achieved.</p>