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Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.
The majority of cases of community-acquired pneumonia are caused by Streptococcus pneumoniae and most studies on pneumococcal host interaction are based on cell culture or animal experiments. Thus, little is known about infections in human lung tissue.
Cyclooxygenase-2 and its metabolites play an important regulatory role in lung inflammation. Therefore, we established a pneumococcal infection model on human lung tissue demonstrating mitogen-activated protein kinase (MAPK)-dependent induction of cyclooxygenase-2 and its related metabolites.
In addition to alveolar macrophages and the vascular endothelium, cyclooxygenase-2 was upregulated in alveolar type II but not type I epithelial cells, which was confirmed in lungs of patients suffering from acute pneumonia. Moreover, we demonstrated the expression profile of all four E prostanoid receptors at the mRNA level and showed functionality of the E prostanoid(4) receptor by cyclic adenosine monophosphate production. Additionally, in comparison to previous studies, cyclooxygenase-2/prostaglandin E-2 related pro- and anti-inflammatory mediator regulation was partly confirmed in human lung tissue after pneumococcal infection.
Overall, cell type-specific and MAPK-dependent cyclooxygenase-2 expression and prostaglandin E-2 formation in human lung tissue may play an important role in the early phase of pneumococcal infections.
Proteins and peptides play a predominant role in biochemical reactions of living cells. In these complex environments, not only the constitution of the molecules but also their three-dimensional configuration defines their functionality. This so-called secondary structure of proteins is crucial for understanding their function in living matter. Misfolding, for example, is suspected as the cause of neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease. Ultimately, it is necessary to study a single protein and its folding dynamics. Here, we report a first step in this direction, namely ultrasensitive detection and discrimination of in vitro polypeptide folding and unfolding processes using resonant plasmonic nanoantennas for surface-enhanced vibrational spectroscopy. We utilize poly-l-lysine as a model system which has been functionalized on the gold surface. By in vitro infrared spectroscopy of a single molecular monolayer at the amide I vibrations we directly monitor the reversible conformational changes between α-helix and β-sheet states induced by controlled external chemical stimuli. Our scheme in combination with advanced positioning of the peptides and proteins and more brilliant light sources is highly promising for ultrasensitive in vitro studies down to the single protein level.
The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners.
The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies.
This technical report presents results of research projects executed in 2018. Selected projects have presented their results on April 17th and November 14th 2017 at the Future SOC Lab Day events.
Classical methods to analyze the surface composition of atmosphereless planetary objects from an orbiter are IR and gamma ray spectroscopy and neutron backscatter measurements. The idea to analyze surface properties with an in-situ instrument has been proposed by Johnson et al. (1998). There, it was suggested to analyze Europa's thin atmosphere with an ion and neutral gas spectrometer. Since the atmospheric components are released by sputtering of the moon's surface, they provide a link to surface composition. Here we present an improved, complementary method to analyze rocky or icy dust particles as samples of planetary objects from which they were ejected. Such particles, generated by the ambient meteoroid bombardment that erodes the surface, are naturally present on all atmosphereless moons and planets. The planetary bodies are enshrouded in clouds of ballistic dust particles, which are characteristic samples of their surfaces. In situ mass spectroscopic analysis of these dust particles impacting onto a detector of an orbiting spacecraft reveals their composition. Recent instrumental developments and tests allow the chemical characterization of ice and dust particles encountered at speeds as low as 1 km/s and an accurate reconstruction of their trajectories. Depending on the sampling altitude, a dust trajectory sensor can trace back the origin of each analyzed grain with about 10 km accuracy at the surface. Since the detection rates are of the order of thousand per orbit, a spatially resolved mapping of the surface composition can be achieved. Certain bodies (e.g., Europa) with particularly dense dust clouds, could provide impact statistics that allow for compositional mapping even on single flybys. Dust impact velocities are in general sufficiently high at orbiters about planetary objects with a radius > 1000 km and with only a thin or no atmosphere. In this work we focus on the scientific benefit of a dust spectrometer on a spacecraft orbiting Earth's Moon as well as Jupiter's Galilean satellites. This 'dust spectrometer' approach provides key chemical and isotopic constraints for varying provinces or geological formations on the surfaces, leading to better understanding of the body's geological evolution.
Riverine ecosystems provide various ecosystem services. One of these services is the biological control of eutrophication by grazing macroinvertebrates.
However, riverine ecosystems are subject to numerous stressors that affect community structure, functions, and stability properties. To manage rivers in response to these stressors, a better understanding of the ecological functions underlying services is needed.
This requires consideration of local and regional processes, which requires a metacommunity approach that links local food webs through drift and dispersal. This takes into account long-distance interactions that can compensate for local effects of stressors.
Our modular model MASTIFF (Multiple Aquatic STressors In Flowing Food webs) is stage-structured, spatially explicit, and includes coupled food webs consisting of benthic resource-consumer interactions between biofilm and three competing macroinvertebrate functional types. River segments are unidirectionally connected through organismal drift and bidirectionally connected through dispersal. Climate and land use stressors along the river can be accounted for. Biocontrol of biofilm eutrophication is used as an exemplary functional indicator.
We present the model and the underlying considerations, and show in an exemplary application that explicit consideration of drift and dispersal is essential for understanding the spatiotemporal biocontrol of eutrophication.
The combination of drift and dispersal reduced eutrophication events. While dispersal events were linked to specific periods in the species life cycles and therefore had limited potential to control, drift was ubiquitous and thus responded more readily to changing habitat conditions.
This indicates that drift is an important factor for coping with stress situations.
Finally, we outline and discuss the potential and possibilities of MASTIFF as a tool for mechanistic, cross-scale analyses of multiple stressors to advance knowledge of riverine ecosystem functioning.
Model-derived relationships between chlorophyll a (Chl-a) and nutrients and temperature have fundamental implications for understanding complex interactions among water quality measures used for lake classification, yet accuracy comparisons of different approaches are scarce. Here, we (1) compared Chl-a model performances across linear and nonlinear statistical approaches; (2) evaluated single and combined effects of nutrients, depth, and temperature as lake surface water temperature (LSWT) or altitude on Chl-a; and (3) investigated the reliability of the best water quality model across 13 lakes from perialpine and central Balkan mountain regions. Chl-a was modelled using in situ water quality data from 157 European lakes; elevation data and LSWT in situ data were complemented by remote sensing measurements. Nonlinear approaches performed better, implying complex relationships between Chl-a and the explanatory variables. Boosted regression trees, as the best performing approach, accommodated interactions among predictor variables. Chl-a-nutrient relationships were characterized by sigmoidal curves, with total phosphorus having the largest explanatory power for our study region. In comparison with LSWT, utilization of altitude, the often-used temperature surrogate, led to different influence directions but similar predictive performances. These results support utilizing altitude in models for Chl-a predictions. Compared to Chl-a observations, Chl-a predictions of the best performing approach for mountain lakes (oligotrophic-eutrophic) led to minor differences in trophic state categorizations. Our findings suggest that both models with LSWT and altitude are appropriate for water quality predictions of lakes in mountain regions and emphasize the importance of incorporating interactions among variables when facing lake management challenges.
Model-derived relationships between chlorophyll a (Chl-a) and nutrients and temperature have fundamental implications for understanding complex interactions among water quality measures used for lake classification, yet accuracy comparisons of different approaches are scarce. Here, we (1) compared Chl-a model performances across linear and nonlinear statistical approaches; (2) evaluated single and combined effects of nutrients, depth, and temperature as lake surface water temperature (LSWT) or altitude on Chl-a; and (3) investigated the reliability of the best water quality model across 13 lakes from perialpine and central Balkan mountain regions. Chl-a was modelled using in situ water quality data from 157 European lakes; elevation data and LSWT in situ data were complemented by remote sensing measurements. Nonlinear approaches performed better, implying complex relationships between Chl-a and the explanatory variables. Boosted regression trees, as the best performing approach, accommodated interactions among predictor variables. Chl-a-nutrient relationships were characterized by sigmoidal curves, with total phosphorus having the largest explanatory power for our study region. In comparison with LSWT, utilization of altitude, the often-used temperature surrogate, led to different influence directions but similar predictive performances. These results support utilizing altitude in models for Chl-a predictions. Compared to Chl-a observations, Chl-a predictions of the best performing approach for mountain lakes (oligotrophic-eutrophic) led to minor differences in trophic state categorizations. Our findings suggest that both models with LSWT and altitude are appropriate for water quality predictions of lakes in mountain regions and emphasize the importance of incorporating interactions among variables when facing lake management challenges.
Alles auf Anfang!
(2019)
Im Zuge der Bologna-Reform ist an Hochschulen vieles in Bewegung gekommen. Studium und Lehre sind stärker ins Blickfeld gerückt. Dabei kommt der Studieneingangsphase besondere Bedeutung zu, werden doch hier die Weichen für ein erfolgreiches Studium gestellt. Deshalb ist es verständlich, dass die Hauptanstrengungen der Hochschulen auf den Studieneingang gerichtet sind – ganz nach dem Motto: „Auf den Anfang kommt es an!“. Konsens herrscht dahingehend, dass der Studieneingang neu zu gestalten ist, doch beim „Wie?“ gibt es unterschiedliche Antworten. Zugleich wird immer deutlicher, dass eine wirksame Neugestaltung der Eingangsphase nur mit einer umfassenden Reform des Studiums gelingen kann.
Ziel des vierten Bandes der Potsdamer Beiträge zur Hochschulforschung ist es, eine Zwischenbilanz der Debatte zum Studieneingang zu ziehen. Auf der Basis empirischer Studien werden unterschiedliche Perspektiven auf den Studieneingang eingenommen und Empfehlungen zur Optimierung des Studieneingangs abgeleitet. Die zahlreichen Untersuchungsergebnisse Potsdamer Forschergruppen werden durch weitere nationale sowie internationale Perspektiven ergänzt. Der Band richtet sich an alle, die sich für die Entwicklung an Hochschulen interessieren.