Das strikt anaerobe, Endosporen-bildende Bakterium Clostridioides difficile ist der Verursacher von nosokomialen Durchfallerkrankungen bei Mensch und Tier. Eine C. difficile Infektion (CDI) erfolgt meist nach einer Antibiotikabehandlung welche die Darmflora schädigt und bei der Wiederbesiedlung das Auskeimen von C. difficile ermöglicht. Weltweit ist eine Zunahme der Inzidenz so wie ein schwerer Verlauf von CDI zu beobachten was die Gesundheitskosten in die Höhe treibt und verstärkte Maßnahmen zur Infektions-Prävention und Kontrolle der Ausbreitung erfordert. Die Behandlung einer CDI wird dadurch erschwert dass Endosporen resistent gegenüber einer Antibiotikabehandlung sind. Vegetative Zellen und Sporen des Darmbesiedlers C. difficile werden mit den Fäzes ausgeschieden und können so in die Umwelt gelangen. C. difficile wird in Fäkal-belasteten Matrices wie Abwasser, Klärschlamm, Gülle und in mit Fäkalien in Berührung gekommenem Viehfutter oder Silage nachgewiesen. Durch den rasanten Anstieg der Anaerobtechnologie in Biogasanlagen zur Schlamm- oder Güllebehandlung kann davon ausgegangen werden, dass C. difficile in solchen Milieus überlebt oder sich sogar vermehrt und mit den Gär-Rückständen als Dünger in der Umwelt verbreitet wird. Ziel des geplanten Forschungsvorhabens ist, solche fäkal-belasteten Proben zu identifizieren und daraus C. difficile zu quantifizieren und Isolate zu charakterisieren. Neben dem Nachweis der Gene der Virulenzfaktoren für das Enterotoxin A und Cytotoxin B und dem binären Toxin CDT werden die Isolate einer Ribotypisierung und einer Antibiotikaempfindlichkeitstestung zur MHK Bestimmung unterzogen. Zudem sollen auch Antibiotika-Resistenzgene sowie konjugative Transposons nachgewiesen werden. Zum quantitativen Nachweis von C. difficile und dem Antibiotikaresistenz-vermittelnden konjugativen Transposon Tn5397 soll eine qPCR etabliert werden die es ermöglicht, Zellzahlen und Pathogenität von C. difficile in Fäkal-belasteten Proben zu bestimmen. Bedingt durch den hohen Stellenwert der Anaerobtechnologie für die Abwasserreinigung und Güllebehandlung sollen im Labormaßstab Biogasreaktoren aufgebaut und unter 'Realbedingungen' betrieben werden, um das Überleben, eine Vermehrung oder die Reduktion/Elimination von C. difficile Zellen/Sporen sowie die Exkretion des konjugativen Transposons Tn5397 zu testen. Diese Versuche sollen auch in Laboranlagen zur Simulation der konventionellen Güllelagerung sowie nach Behandlung in einer Labor-Ozonierungs- und UV-Entkeimungsanlage durchgeführt werden. Letztere werden unter anderem als vierte Reinigungsstufe zur Abwasserbehandlung in der Praxis empfohlen. Nur in Kombination von Umweltmikrobiologie und Verfahrenstechnik können die gesetzten Ziele erreicht und neues Wissen generiert werden um Aussagen bezüglich der Überlebensfähigkeit, Pathogenität und Verbreitungspfaden von C. difficile zu treffen und um das Infektionsrisiko für Mensch und Tier besser abschätzen zu können.
Zielsetzung: Angaben ueber physiologische Wirkung wasserloeslicher Fraktionen von Rohoelen im Hinblick auf Synergismus mit 'natuerlichen' entwicklungserschwerenden Umweltbedingungen. 1. Laborexperimente zur Abgrenzung von sublet. und subterratogenen Konzentrationen und Dosen. Registrierung von embryonaler Sterblichkeit, Missbildung, Schluepferfolg und Vitalitaet der Larven. Vergleichsbeobachtungen ueber Schwimmverhalten, Nahrungsaufnahme und Wachstumsraten. 2. Chemische Analysen der Organismen: Backgroundkontamierung der Fischovarien. Messung der Ad- und Absorption am Chorion und im Gewebe. Messung der physiologischen Belastungen (Gesamtstoffwechsel), spezielle Untersuchungen ueber Einfluss adsorbierter Stoffe. Untersuchungen ueber ontogenetische Entwicklung der Faehigkeiten zur Metabolierung und Exkretion von Kohlenwasserstoffen. Messungen ueber Rohoel-Loesungskinetik und Alterung von Rohoel-Seewasser-Extrakten.
This data set contains measures of energy-use efficiency, energy flow, and energy storage in units of dry biomass that quantify the multitrophic ecosystem functioning realized in grassland ecosystems of differing plant diversity. Given are both the measures integrated over whole ecosystems (total network measures) as well as the energy dynamics associated with individual ecosystem compartments including the entire biological community and detrital compartments across the above- and belowground parts of the ecosystem.
Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment, see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Study plots are grouped in four blocks in parallel to the river in order to account for any effect of a gradient in abiotic soil properties. Each block contains an equal number of plots of each plant species richness and plant functional group richness level. Plots were maintained in general by bi-annual weeding and mowing. Since 2010, plot size was reduced to 5.5 x 6 m and plots were weeded three times per year.
Trophic-network models were constructed for 80 of the experimental plots, and represent the ecosystem energy budget in the currency of dry-mass (g m-2 for standing stocks and g m-2 d-1 for flows). All trophic networks have the same topology, but they differ in the estimated size of the standing stock biomass of individual compartments (g m-2) and flows among the compartments (g m-2 d-1). Each trophic network contains twelve ecosystem compartments representing distinct trophic groups of the above- and belowground parts of the ecosystem (i.e., plants, soil microbial community, and above- and belowground herbivores, carnivores, omnivores, decomposers, all represented by invertebrate macro- and mesofauna) and detrital pools (i.e., surface litter and soil organic matter). Vertebrates were not considered in our study due to limitations of data availability and because the impact of resident vertebrates in our experimental system is expected to be minimal. Larger grazing vertebrates were excluded by a fence around the field site, though there was some occasional grazing by voles.
Compartments are connected by 41 flows. Flows (fluxes) constitute 30 internal flows within the system, namely feeding (herbivory, predation, decomposition), excretion, mortality, and mechanical transformation of surface litter due to bioturbation plus eleven 11 external flows, i.e. one input (flows entering the system, namely carbon uptake by plants) and ten output flows (flows leaving the system, namely respiration losses). The ecosystem inflow (a flow entering the system) and outflows (flows leaving the system) represent carbon uptake and respiration losses, respectively. In the case of consumer groups, the food consumed (compartment-wide input flow) is further split into excretion (not assimilated organic material that is returned to detrital pools in the form of fecesfaeces) and assimilated organic material, which is further split into respiration (energy lost out of the system to the environment) and biomass production, which is further consumed by higher trophic levels due to predation or returned to detrital pools in the form of mortality (natural mortality or prey residues). In case of detrital pools (i.e. surface litter and soil organic matter), the input flows are in the form of excretion and mortality from the biota compartments, and output flows are in the form of feeding by decomposers and soil microorganisms (i.e. decomposition). Surface litter and soil organic matter are connected by flows in the form of burrowing (mechanical transportation) of organic material from the surface to the soil by soil fauna. Organism immigration and emigration are not considered in our study due to limited data availability.
Flows were quantified using resource processing rates (i.e. the feeding rates at which material is taken from a source) multiplied with the standing biomass of the respective source compartment. To approximate resource processing rates, different approaches were used: (i) experimental measurements (namely the aboveground decomposition, fauna burial activity (bioturbation), microbial respiration, and aboveground herbivory and predation rates); (ii) allometric equations scaled by individual body mass, environmental temperature and phylogenetic group (for the above- and belowground fauna respiration rates and plant respiration); (iii) assimilation rates scaled by diet type (for quantification of belowground fauna excretion and natural mortality); (iv) literature-based rates scaled by biomass of trophic groups (for microbial mortality); and (v) mass-balance assumptions (carbon uptake, plant and aboveground fauna mortality, belowground decomposition, belowground herbivory, and belowground predation). Mass-balance assumption means that the flows are calculated assuming that resource inputs into the compartment (i.e. feeding) balance the rate at which material is lost (i.e. the sum of through excretion, respiration, predation, and natural death). We used constrained nonlinear multivariable optimization to perturb the initial flow rates estimated from the various sources. We assigned confidence ratings for each flow rate, reflecting the quality of empirical data it is based on. We then used the 'fmincon' function from Matlab's optimization toolbox, which utilizes the standard Moore-Penrose pseudoinverse approach to achieve a balanced steady state ecological network model that best reflects the collected field data. Measured data used to parameterize the trophic network models were collected mostly in the year 2010.
Network-wide measures that quantify proxies for different aspects of multitrophic ecosystem functioning were calculated for each experimental plot using the 'enaR' package in R. In particular, total energy flow was measured as the sum of all flows through each ecosystem compartment. Flow uniformity was calculated as the ratio of the mean of summed flows through each individual ecosystem compartment divided by the standard deviation of these means. Total-network standing biomass was determined as the sum of standing biomass across all ecosystem compartments. Community maintenance costs were calculated as the ratio of community-wide respiration related to community-wide biomass.
Over the last twenty-five years it has become evident that exposure to several phthalates can have adverse effects on human health, such as endocrine disruption. This led to a series of EU regulations that resulted in a decrease in the production volumes of the restricted phthalates and an increased production of substitutes. The current study describes the impact of regulations and changes in production and use of phthalates and their substitutes on internal exposure patterns in two European populations since the beginning of the 2000'ies. Using harmonised data from young adults in Denmark (Danish Young Men Study, n = 1,063, spot urine) and Germany (Environmental Specimen Bank, n = 878, 24-h urine) with repeated cross-sectional design (3-11 cycles per biomarker) we applied Locally Estimated Scatterplot Smoothing (LOESS) and Generalized Linear Models (GLMs) to estimate time trends and the role of covariates on the trend (e.g. age, BMI). Time trends of daily excretion (mikrog/24h) are comparable between the two samples for the regulated (DEHP, BBzP, DiNP, DnBP, DiBP, DiDP/DPHP) as well as the non-regulated substances (DMP, DEP, DINCH, DEHTP) although the rate of change differ for some of the compounds. GLM results indicate that the daily excretion of the most regulated phthalates has decreased over time (DEHP yearly about 12-16%, BBzP 5%, DnBP 0.3-17%, and DiBP 4-12%). Interestingly, also the non-regulated phthalates DMP and DEP decreased by 6-18% per year. In sharp contrast, the phthalate substitutes DINCH and DEHTP show very steep annual increases (~10-68% and ~100%, respectively) between 2009 and 2017. We did not find an effect of age, sex, BMI, or education on the time trend. The present study provides comparable insights into how exposure to phthalates and two of their substitutes have changed over the last two decades in Germany and Denmark. © 2022 The Authors
The mycotoxin deoxynivalenol (DON) is a frequently found contaminant in cereals and cereal-based products. As a German contribution to the European Joint Programme HBM4EU, we analysed the total DON concentration (tDON) in 24-h urine samples from the German Environmental Specimen Bank (ESB). In total, 360 samples collected in 1996, 2001, 2006, 2011, 2016, and 2021 from young adults in Muenster (Germany), were measured by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) after enzymatic deconjugation of the glucuronide metabolites. tDON was found in concentrations above the lower limit of quantification (0.3 (micro)g/L) in 99% of the samples. Medians of the measured concentrations and the daily excretion were 4.3 (micro)g/L and 7.9 (micro)g/24 h, respectively. For only nine participants, urinary tDON concentrations exceeded the provisional Human biomonitoring guidance value (HBM GV) of 23 (micro)g/L. Urinary tDON concentrations were significantly higher for male participants. However, 24-h excretion values normalized to the participant's body weight did not exhibit any significant difference between males and females and the magnitude remained unchanged over the sampling years with exception of the sampling year 2001. Daily intakes were estimated from excretion values. Exceedance of the tolerable daily intake (TDI) of 1 (micro)g/kg bw per day was observed for less than 1% of all participants. TDI exceedances were only present in the sampling year 2001 and not in more recent sampling years while exceedance of the HBM guidance value was also observed in 2011 and 2021. © 2023 The Authors