No abstract

While many authors have described the adverse health effects of poor air quality and meteorological extremes, there remain inconsistencies on a regional scale as well as uncertainty about the single and joint effects of atmospheric predictors. In this context, we investigated the short-term impacts of weather and air quality on moderate extreme cancer-related mortality events for the urban area of Augsburg, Southern Germany, during the period 2000–2017. First, single effects were uncovered by applying a case-crossover routine. The overall impact was assessed by performing a Mann–Whitney U testing scheme. We then compared the results of this procedure to extreme noncancer-related mortality events. In a second step, we found periods with contemporaneous significant predictors and carried out an in-depth analysis of these joint-effect periods. We were interested in the atmospheric processes leading to the emergence of significant conditions. Hence, we applied the Principal Component Analysis to large-scale synoptic conditions during these periods. The results demonstrate a strong linkage between high-mortality events in cancer patients and significantly above-average levels of nitrogen dioxide (NO2) and particulate matter (PM2.5) during the late winter through spring period. These were mainly linked to northerly to easterly weak airflow under stable, high-pressure conditions. Especially in winter and spring, this can result in low temperatures and a ground-level increase and the accumulation of air pollution from heating and traffic as well as eastern lateral advection of polluted air. Additionally, above-average temperatures were shown to occur on the days before mortality events from mid-summer through fall, which was also caused by high-pressure conditions with weak wind flow and intense solar radiation. Our approach can be used to analyse medical data with epidemiological as well as climatological methods while providing a more vivid representation of the underlying atmospheric processes.

Patients with high-grade serous ovarian cancer (HGSOC) have a very poor overall survival. Current therapeutic approaches do not bring benefit to all patients. Although genetic alterations and molecular mechanisms are well characterized, the molecular pathological conditions are poorly investigated. Solute carrier organic anion transporter family member 4A1 (SLCO4A1) encodes OATP4A1, which is an uptake membrane transporter of metabolic products. Its expression may influence various signaling pathways associated with the molecular pathophysiological conditions of HGSOC and consequently tumor progression. RNA sequencing of 33 patient-derived HGSOC cell lines showed that SLCO4A1 expression was diverse by individual tumors, which was further confirmed by RT-qPCR, Western blotting and immunohistochemistry. Gene Set Enrichment Analysis revealed that higher SLCO4A1 level was associated with inflammation-associated pathways including NOD-like receptor, adipocytokine, TALL1, CD40, NF-κB, and TNF-receptor 2 signaling cascades, while low SLCO4A1 expression was associated with the mitochondrial electron transport chain pathway. The overall gene expression pattern in all cell lines was specific to each patient and remained largely unchanged during tumor progression. In addition, genes encoding ABCC3 along with SLCO4A1-antisense RNA 1, were associated with higher expression of the SLCO4A1, indicating their possible involvement in inflammation-associated pathways that are downstream to the prostaglandin E2/cAMP axis. Taken together, increased SLCO4A1/OATP4A1 expression is associated with the upregulation of specific inflammatory pathways, while the decreased level is associated with mitochondrial dysfunction. These molecular pathophysiological conditions are tumor specific and should be taken into consideration by the development of therapies against HGSOC.

<p>The aim of this project is to investigate the influence of health-relevant air-hygienic and climatological parameters on emergency room visits at the University Hospital of Augsburg. This is achieved by quantifying the effects of increased exposure to air substances and weather extremes.</p><p>The emergency admission data from 2017 and 2018 are available as medical data basis. Among the air constituents, ozone, nitrogen dioxide and particulate matter values ​​are used, measured by several stations in Augsburg. The meteorological database contains the daily mean and daily maximum values ​​of several parameters such as air temperature, humidity, and wind. In addition, a catalog of different weather conditions was created. For this purpose, five Principal Component Analyzes were performed, one for each season and one for the entire year.</p><p>The medical data set was broken down according to the seasons and days with specific meteorological conditions (e. g. heat days) or days that exceeded the WHO recommendations for air pollutants. These sub-divisions were undertaken in order to identify differences of the number of admissions under the occurrence of extreme days. To account for the possible delay between exposure and emergency cases, a lead time of up to seven days was included.</p><p>The results so far show that in almost all subgroups of the ICD-10 classification there are highly significant correlations between the weather and air conditions and the number of emergency admissions. These occur almost exclusively on meteorological extreme days or when the WHO air pollution guideline values are exceeded. The strength of the correlations between the individual diagnoses and subgroups differs significantly. The proportion of age, gender and place of residence-specific differences can be classified as low. However, there are individual diseases in almost every main group that are showing very clear differences, sometimes even opposite correlations, between men and women or urban and suburban residents.</p><p>The project is funded by the German Federal Environment Foundation and the German Research Foundation under - project number 408057478.</p>