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Die Elektrosprayionisation (ESI) ist eine der weitverbreitetsten Ionisationstechniken für flüssige Pro-ben in der Massen- und Ionenmobilitäts(IM)-Spektrometrie. Aufgrund ihrer schonenden Ionisierung wird ESI vorwiegend für empfindliche, komplexe Moleküle in der Biologie und Medizin eingesetzt. Überdies ist sie allerdings für ein sehr breites Spektrum an Substanzklassen anwendbar. Die IM-Spektrometrie wurde ursprünglich zur Detektion gasförmiger Proben entwickelt, die hauptsächlich durch radioaktive Quellen ionisiert werden. Sie ist die einzige analytische Methode, bei der Isomere in Echtzeit getrennt und über ihre charakteristische IM direkt identifiziert werden können. ESI wurde in den 90ger Jahren durch die Hill Gruppe in die IM-Spektrometrie eingeführt. Die Kombination wird bisher jedoch nur von wenigen Gruppen verwendet und hat deshalb noch ein hohes Entwick-lungspotential. Ein vielversprechendes Anwendungsfeld ist der Einsatz in der Hochleistungs-flüssigkeitschromatographie (HPLC) zur mehrdimensionalen Trennung. Heutzutage ist die HPLC die Standardmethode zur Trennung komplexer Proben in der Routineanalytik. HPLC-Trennungsgänge sind jedoch häufig langwierig und der Einsatz verschiedener Laufmittel, hoher Flussraten, von Puffern, sowie Laufmittelgradienten stellt hohe Anforderungen an die Detektoren. Die ESI-IM-Spektrometrie wurde in einigen Studien bereits als HPLC-Detektor eingesetzt, war dort bisher jedoch auf Flussratensplitting oder geringe Flussraten des Laufmittels beschränkt.
In dieser kumulativen Doktorarbeit konnte daher erstmals ein ESI IM-Spektrometer als HPLC-Detektor für den Flussratenbereich von 200-1500 μl/min entwickelt werden. Anhand von fünf Publi-kationen wurden (1) über eine umfassende Charakterisierung die Eignung des Spektrometers als HPLC-Detektor festgestellt, (2) ausgewählte komplexe Trenngänge präsentiert und (3) die Anwen-dung zum Reaktionsmonitoring und (4, 5) mögliche Weiterentwicklungen gezeigt.
Erfolgreich konnten mit dem selbst-entwickelten ESI IM-Spektrometer typische HPLC-Bedingungen wie Wassergehalte im Laufmittel von bis zu 90%, Pufferkonzentrationen von bis zu 10 mM, sowie Nachweisgrenzen von bis zu 50 nM erreicht werden. Weiterhin wurde anhand der komplexen Trennungsgänge (24 Pestizide/18 Aminosäuren) gezeigt, dass die HPLC und die IM-Spektrometrie eine hohe Orthogonalität besitzen. Eine effektive Peakkapazität von 240 wurde so realisiert. Auf der HPLC-Säule koeluierende Substanzen konnten über die Driftzeit getrennt und über ihre IM identifi-ziert werden, sodass die Gesamttrennzeiten erheblich minimiert werden konnten. Die Anwend-barkeit des ESI IM-Spektrometers zur Überwachung chemischer Synthesen wurde anhand einer dreistufigen Reaktion demonstriert. Es konnten die wichtigsten Edukte, Zwischenprodukte und Produkte aller Stufen identifiziert werden. Eine quantitative Auswertung war sowohl über eine kurze HPLC-Vortrennung als auch durch die Entwicklung eines eigenen Kalibrierverfahrens, welches die Ladungskonkurrenz bei ESI berücksichtigt, ohne HPLC möglich. Im zweiten Teil der Arbeit werden zwei Weiterentwicklungen des Spektrometers präsentiert. Eine Möglichkeit ist die Reduzierung des Drucks in den intermediären Bereich (300 - 1000 mbar) mit dem Ziel der Verringerung der benötigten Spannungen. Mithilfe von Streulichtbildern und Strom-Spannungs-Kurven wurden für geringe Drücke eine verminderte Freisetzung der Analyt-Ionen aus den Tropfen festgestellt. Die Verluste konnten jedoch über höhere elektrische Feldstärken ausgeglichen werden, sodass gleiche Nachweisgrenzen bei 500 mbar und bei 1 bar erreicht wurden. Die zweite Weiterentwicklung ist ein neuartiges Ionentors mit Pulsschaltung, welches eine Verdopplung der Auflösung auf bis zu R > 100 bei gleicher Sensitivität ermöglichte. Eine denkbare Anwendung im Bereich der Peptidanalytik wurde mit beachtlichen Auflösungen der Peptide von R = 90 gezeigt.
Spotlight on the underdogs
(2017)
Alternaria (A.) is a genus of widespread fungi capable of producing numerous, possibly health-endangering Alternaria toxins (ATs), which are usually not the focus of attention. The formation of ATs depends on the species and complex interactions of various environmental factors and is not fully understood. In this study the influence of temperature (7 °C, 25 °C), substrate (rice, wheat kernels) and incubation time (4, 7, and 14 days) on the production of thirteen ATs and three sulfoconjugated ATs by three different Alternaria isolates from the species groups A. tenuissima and A. infectoria was determined. High-performance liquid chromatography coupled with tandem mass spectrometry was used for quantification. Under nearly all conditions, tenuazonic acid was the most extensively produced toxin. At 25 °C and with increasing incubation time all toxins were formed in high amounts by the two A. tenuissima strains on both substrates with comparable mycotoxin profiles. However, for some of the toxins, stagnation or a decrease in production was observed from day 7 to 14. As opposed to the A. tenuissima strains, the A. infectoria strain only produced low amounts of ATs, but high concentrations of stemphyltoxin III. The results provide an essential insight into the quantitative in vitro AT formation under different environmental conditions, potentially transferable to different field and storage conditions
With recent advances in the area of information extraction, automatically extracting structured information from a vast amount of unstructured textual data becomes an important task, which is infeasible for humans to capture all information manually. Named entities (e.g., persons, organizations, and locations), which are crucial components in texts, are usually the subjects of structured information from textual documents. Therefore, the task of named entity mining receives much attention. It consists of three major subtasks, which are named entity recognition, named entity linking, and relation extraction.
These three tasks build up an entire pipeline of a named entity mining system, where each of them has its challenges and can be employed for further applications. As a fundamental task in the natural language processing domain, studies on named entity recognition have a long history, and many existing approaches produce reliable results. The task is aiming to extract mentions of named entities in text and identify their types. Named entity linking recently received much attention with the development of knowledge bases that contain rich information about entities. The goal is to disambiguate mentions of named entities and to link them to the corresponding entries in a knowledge base. Relation extraction, as the final step of named entity mining, is a highly challenging task, which is to extract semantic relations between named entities, e.g., the ownership relation between two companies.
In this thesis, we review the state-of-the-art of named entity mining domain in detail, including valuable features, techniques, evaluation methodologies, and so on. Furthermore, we present two of our approaches that focus on the named entity linking and relation extraction tasks separately.
To solve the named entity linking task, we propose the entity linking technique, BEL, which operates on a textual range of relevant terms and aggregates decisions from an ensemble of simple classifiers. Each of the classifiers operates on a randomly sampled subset of the above range. In extensive experiments on hand-labeled and benchmark datasets, our approach outperformed state-of-the-art entity linking techniques, both in terms of quality and efficiency.
For the task of relation extraction, we focus on extracting a specific group of difficult relation types, business relations between companies. These relations can be used to gain valuable insight into the interactions between companies and perform complex analytics, such as predicting risk or valuating companies. Our semi-supervised strategy can extract business relations between companies based on only a few user-provided seed company pairs. By doing so, we also provide a solution for the problem of determining the direction of asymmetric relations, such as the ownership_of relation. We improve the reliability of the extraction process by using a holistic pattern identification method, which classifies the generated extraction patterns. Our experiments show that we can accurately and reliably extract new entity pairs occurring in the target relation by using as few as five labeled seed pairs.
In einer prospektiven Längsschnittstudie wurden Auswirkungen früher psychosozialer Risiken bis ins junge Erwachsenenalter untersucht und dabei die Rolle von affektiver und behavioraler Dysregulation im Kindesalter als vermittelndem Faktor überprüft. Drei Monate nach der Geburt wurde das Vorliegen von 11 psychosozialen Belastungsfaktoren erfasst. Im Alter von 8 – 15 Jahren wurde dreimal das Child Behavior Checklist-Dysregulationsprofil (CBCL-DP) erhoben. Mit 25 Jahren wurde ein Strukturiertes Klinisches Interview durchgeführt und 309 der Teilnehmer füllten den Young Adult Self-Report aus. Frühe psychosoziale Risiken gingen mit einem erhöhten Risiko für das Vorliegen eines Substanzmissbrauchs im jungen Erwachsenenalter sowie mit erhöhtem externalisierendem und internalisierendem Problemverhalten einher. Der Zusammenhang zwischen frühen psychosozialen Risiken und späterem externalisierendem bzw. internalisierendem Problemverhalten wurde durch das CBCL-DP vermittelt.
Die langfristigen Auswirkungen von Frühgeburtlichkeit auf kognitive Entwicklung und Schulerfolg
(2017)
In einer prospektiven Längsschnittstudie wurde der Zusammenhang zwischen früher Responsivität der Mutter und kognitiver Entwicklung ihrer früh- bzw. reifgeborenen Kinder untersucht. Im Alter von drei Monaten wurde dafür die Mutter-Kind-Interaktion mittels Verhaltensbeobachtung erfasst. Bei n=351 der teilnehmenden Kinder (101 frühgeboren) wurde die allgemeine Intelligenz (IQ) im Alter von 11 Jahren und bei n=313 (85 frühgeboren) zusätzlich der höchste erreichte Schulabschluss bis 25 Jahren erhoben. Frühgeborene wiesen mit 11 Jahren einen signifikant niedrigeren IQ als Reifgeborene auf, nachdem für mögliche konfundierende Faktoren kontrolliert worden war. Nur bei Früh-, nicht aber bei Reifgeborenen zeigte sich ein signifikanter positiver Zusammenhang zwischen mütterlicher Responsivität und IQ. Für die Wahrscheinlichkeit einen höheren Schulabschluss (mind. Fachabitur) zu erreichen, fand sich weder ein signifikanter Effekt von Frühgeburtlichkeit noch von mütterlicher Responsivität.
Organic matter deposited in ancient, ice-rich permafrost sediments is vulnerable to climate change and may contribute to the future release of greenhouse gases; it is thus important to get a better characterization of the plant organic matter within such sediments. From a Late Quaternary permafrost sediment core from the Buor Khaya Peninsula, we analysed plant-derived sedimentary ancient DNA (sedaDNA) to identify the taxonomic composition of plant organic matter, and undertook palynological analysis to assess the environmental conditions during deposition. Using sedaDNA, we identified 154 taxa and from pollen and non-pollen palynomorphs we identified 83 taxa. In the deposits dated between 54 and 51 kyr BP, sedaDNA records a diverse low-centred polygon plant community including recurring aquatic pond vegetation while from the pollen record we infer terrestrial open-land vegetation with relatively dry environmental conditions at a regional scale. A fluctuating dominance of either terrestrial or swamp and aquatic taxa in both proxies allowed the local hydrological development of the polygon to be traced. In deposits dated between 11.4 and 9.7 kyr BP (13.4-11.1 cal kyr BP), sedaDNA shows a taxonomic turnover to moist shrub tundra and a lower taxonomic richness compared to the older samples. Pollen also records a shrub tundra community, mostly seen as changes in relative proportions of the most dominant taxa, while a decrease in taxonomic richness was less pronounced compared to sedaDNA. Our results show the advantages of using sedaDNA in combination with palynological analyses when macrofossils are rarely preserved. The high resolution of the sedaDNA record provides a detailed picture of the taxonomic composition of plant-derived organic matter throughout the core, and palynological analyses prove valuable by allowing for inferences of regional environmental conditions.
Information on the contemporary in-situ stress state of the earth’s crust is essential for geotechnical applications and physics-based seismic hazard assessment. Yet, stress data records for a data point are incomplete and their availability is usually not dense enough to allow conclusive statements. This demands a thorough examination of the in-situ stress field which is achieved by 3D geomechanicalnumerical models. However, the models spatial resolution is limited and the resulting local stress state is subject to large uncertainties that confine the significance of the findings. In addition, temporal variations of the in-situ stress field are naturally or anthropogenically induced. In my thesis I address these challenges in three manuscripts that investigate (1) the current crustal stress field orientation, (2) the 3D geomechanical-numerical modelling of the in-situ stress state, and (3) the phenomenon of injection induced temporal stress tensor rotations. In the first manuscript I present the first comprehensive stress data compilation of Iceland with 495 data records. Therefore, I analysed image logs from 57 boreholes in Iceland for indicators of the orientation of the maximum horizontal stress component. The study is the first stress survey from different kinds of stress indicators in a geologically very young and tectonically active area of an onshore spreading ridge. It reveals a distinct stress field with a depth independent stress orientation even very close to the spreading centre. In the second manuscript I present a calibrated 3D geomechanical-numerical modelling approach of the in-situ stress state of the Bavarian Molasse Basin that investigates the regional (70x70x10km³) and local (10x10x10km³) stress state. To link these two models I develop a multi-stage modelling approach that provides a reliable and efficient method to derive from the larger scale model initial and boundary conditions for the smaller scale model. Furthermore, I quantify the uncertainties in the models results which are inherent to geomechanical-numerical modelling in general and the multi-stage approach in particular. I show that the significance of the models results is mainly reduced due to the uncertainties in the material properties and the low number of available stress magnitude data records for calibration. In the third manuscript I investigate the phenomenon of injection induced temporal stress tensor rotation and its controlling factors. I conduct a sensitivity study with a 3D generic thermo-hydro-mechanical model. I show that the key control factors for the stress tensor rotation are the permeability as the decisive factor, the injection rate, and the initial differential stress. In particular for enhanced geothermal systems with a low permeability large rotations of the stress tensor are indicated. According to these findings the estimation of the initial differential stress in a reservoir is possible provided the permeability is known and the angle of stress rotation is observed. I propose that the stress tensor rotations can be a key factor in terms of the potential for induced seismicity on pre-existing faults due to the reorientation of the stress field that changes the optimal orientation of faults.
Self-adaptive data quality
(2017)
Carrying out business processes successfully is closely linked to the quality of the data inventory in an organization. Lacks in data quality lead to problems: Incorrect address data prevents (timely) shipments to customers. Erroneous orders lead to returns and thus to unnecessary effort. Wrong pricing forces companies to miss out on revenues or to impair customer satisfaction. If orders or customer records cannot be retrieved, complaint management takes longer. Due to erroneous inventories, too few or too much supplies might be reordered.
A special problem with data quality and the reason for many of the issues mentioned above are duplicates in databases. Duplicates are different representations of same real-world objects in a dataset. However, these representations differ from each other and are for that reason hard to match by a computer. Moreover, the number of required comparisons to find those duplicates grows with the square of the dataset size. To cleanse the data, these duplicates must be detected and removed. Duplicate detection is a very laborious process. To achieve satisfactory results, appropriate software must be created and configured (similarity measures, partitioning keys, thresholds, etc.). Both requires much manual effort and experience.
This thesis addresses automation of parameter selection for duplicate detection and presents several novel approaches that eliminate the need for human experience in parts of the duplicate detection process.
A pre-processing step is introduced that analyzes the datasets in question and classifies their attributes semantically. Not only do these annotations help understanding the respective datasets, but they also facilitate subsequent steps, for example, by selecting appropriate similarity measures or normalizing the data upfront. This approach works without schema information.
Following that, we show a partitioning technique that strongly reduces the number of pair comparisons for the duplicate detection process. The approach automatically finds particularly suitable partitioning keys that simultaneously allow for effective and efficient duplicate retrieval. By means of a user study, we demonstrate that this technique finds partitioning keys that outperform expert suggestions and additionally does not need manual configuration. Furthermore, this approach can be applied independently of the attribute types.
To measure the success of a duplicate detection process and to execute the described partitioning approach, a gold standard is required that provides information about the actual duplicates in a training dataset. This thesis presents a technique that uses existing duplicate detection results and crowdsourcing to create a near gold standard that can be used for the purposes above. Another part of the thesis describes and evaluates strategies how to reduce these crowdsourcing costs and to achieve a consensus with less effort.
Mosses are a major component of the arctic vegetation, particularly in wetlands. We present C / N atomic ratio, delta C-13 and delta N-15 data of 400 brown-moss samples belonging to 10 species that were collected along hydrological gradients within polygonal mires located on the southern Taymyr Peninsula and the Lena River delta in northern Siberia. Additionally, n-alkane patterns of six of these species (16 samples) were investigated. The aim of the study is to see whether the inter-and intraspecific differences in C / N, isotopic compositions and n-alkanes are indicative of habitat, particularly with respect to water level. Overall, we find high variability in all investigated parameters for two different moisture-related groups of moss species. The C / N ratios range between 11 and 53 (median: 32) and show large variations at the intraspecific level. However, species preferring a dry habitat (xero-mesophilic mosses) show higher C / N ratios than those preferring a wet habitat (meso-hygrophilic mosses). The delta C-13 values range between 37.0 and 22.5% (median D 27.8 %). The delta N-15 values range between 6.6 and C 1.7%(median D 2.2 %). We find differences in delta C-13 and delta N-15 compositions between both habitat types. For some species of the meso-hygrophilic group, we suggest that a relationship between the individ-ual habitat water level and isotopic composition can be inferred as a function of microbial symbiosis. The n-alkane distribution also shows differences primarily between xeromesophilic and meso-hygrophilic mosses, i. e. having a dominance of n-alkanes with long (n-C29, n-C31 /and intermediate (n-C25 /chain lengths, respectively. Overall, our results reveal that C / N ratios, isotopic signals and n-alkanes of studied brown-moss taxa from polygonal wetlands are characteristic of their habitat.
The all-female Amazon molly (Poecilia formosa) is the result of a hybridization of the Atlantic molly (P. mexicana) and the sailfin molly (P. latipinna) approximately 120,000 years ago. As a gynogenetic species, P. formosa needs to copulate with heterospecific males including males from one of its bisexual ancestral species. However, the sperm only triggers embryogenesis of the diploid eggs. The genetic information of the sperm donor typically will not contribute to the next generation of P. formosa. Hence, P. formosa possesses generally one allele from each of its ancestral species at any genetic locus. This raises the question whether both ancestral alleles are equally expressed in P. formosa. Allele-specific expression (ASE) has been previously assessed in various organisms, e.g., human and fish, and ASE was found to be important in the context of phenotypic variability and disease. In this study, we utilized Real-Time PCR techniques to estimate ASE of the androgen receptor alpha (arα) gene in several distinct tissues of Amazon mollies. We found an allelic bias favoring the maternal ancestor (P. mexicana) allele in ovarian tissue. This allelic bias was not observed in the gill or the brain tissue. Sequencing of the promoter regions of both alleles revealed an association between an Indel in a known CpG island and differential expression. Future studies may reveal whether our observed cis-regulatory divergence is caused by an ovary-specific trans-regulatory element, preferentially activating the allele of the maternal ancestor.
To what extent cities can be made sustainable under the mega-trends of urbanization and climate change remains a matter of unresolved scientific debate. Our inability in answering this question lies partly in the deficient knowledge regarding pivotal humanenvironment interactions. Regarded as the most well documented anthropogenic climate modification, the urban heat island (UHI) effect – the warmth of urban areas relative to the rural hinterland – has raised great public health concerns globally. Worse still, heat waves are being observed and are projected to increase in both frequency and intensity, which further impairs the well-being of urban dwellers. Albeit with a substantial increase in the number of publications on UHI in the recent decades, the diverse urban-rural definitions applied in previous studies have remarkably hampered the general comparability of results achieved. In addition, few studies have attempted to synergize the land use data and thermal remote sensing to systematically assess UHI and its contributing factors.
Given these research gaps, this work presents a general framework to systematically quantify the UHI effect based on an automated algorithm, whereby cities are defined as clusters of maximum spatial continuity on the basis of land use data, with their rural hinterland being defined analogously. By combining land use data with spatially explicit surface skin temperatures from satellites, the surface UHI intensity can be calculated in a consistent and robust manner. This facilitates monitoring, benchmarking, and categorizing UHI intensities for cities across scales. In light of this innovation, the relationship between city size and UHI intensity has been investigated, as well as the contributions of urban form indicators to the UHI intensity.
This work delivers manifold contributions to the understanding of the UHI, which have complemented and advanced a number of previous studies. Firstly, a log-linear relationship between surface UHI intensity and city size has been confirmed among the 5,000 European cities. The relationship can be extended to a log-logistic one, when taking a wider range of small-sized cities into account. Secondly, this work reveals a complex interplay between UHI intensity and urban form. City size is found to have the strongest influence on the UHI intensity, followed by the fractality and the anisometry. However, their relative contributions to the surface UHI intensity depict a pronounced regional heterogeneity, indicating the importance of considering spatial patterns of UHI while implementing UHI adaptation measures.
Lastly, this work presents a novel seasonality of the UHI intensity for individual clusters in the form of hysteresis-like curves, implying a phase shift between the time series of UHI intensity and background temperatures. Combining satellite observation and urban boundary layer simulation, the seasonal variations of UHI are assessed from both screen and skin levels. Taking London as an example, this work ascribes the discrepancies between the seasonality observed at different levels mainly to the peculiarities of surface skin temperatures associated with the incoming solar radiation. In addition, the efforts in classifying cities according to their UHI characteristics highlight the important role of regional climates in determining the UHI.
This work serves as one of the first studies conducted to systematically and statistically scrutinize the UHI. The outcomes of this work are of particular relevance for the overall spatial planning and regulation at meso- and macro levels in order to harness the benefits of rapid urbanization, while proactively minimizing its ensuing thermal stress.
Ionogels (IGs) based on poly(methyl methacrylate) (PMMA) and the metal-containing ionic liquids (ILs) bis-1-butyl-3-methlimidazolium tetrachloridocuprate(II), tetrachloride cobaltate(II), and tetrachlorido manganate(II) have been synthesized and their mechanical and electrical properties have been correlated with their microstructure. Unlike many previous examples, the current IGs show a decreasing stability in stress-strain experiments on increasing IL fractions. The conductivities of the current IGs are lower than those observed in similar examples in the literature. Both effects are caused by a two-phase structure with micrometer-sized IL-rich domains homogeneously dispersed an IL-deficient continuous PMMA phase. This study demonstrates that the IL-polymer miscibility and the morphology of the IGs are key parameters to control the (macroscopic) properties of IGs.
We consider synchronization properties of arrays of spin-torque nano-oscillators coupled via an RC load. We show that while the fully synchronized state of identical oscillators may be locally stable in some parameter range, this synchrony is not globally attracting. Instead, regimes of different levels of compositional complexity are observed. These include chimera states (a part of the array forms a cluster while other units are desynchronized), clustered chimeras (several clusters plus desynchronized oscillators), cluster state (all oscillators form several clusters), and partial synchronization (no clusters but a nonvanishing mean field). Dynamically, these states are also complex, demonstrating irregular and close to quasiperiodic modulation. Remarkably, when heterogeneity of spin-torque oscillators is taken into account, dynamical complexity even increases: close to the onset of a macroscopic mean field, the dynamics of this field is rather irregular.
Molecularly imprinted polymers (MIPs) have the potential to complement antibodies in bioanalysis, are more stable under harsh conditions, and are potentially cheaper to produce. However, the affinity and especially the selectivity of MIPs are in general lower than those of their biological pendants. Enzymes are useful tools for the preparation of MIPs for both low and high-molecular weight targets: As a green alternative to the well-established methods of chemical polymerization, enzyme-initiated polymerization has been introduced and the removal of protein templates by proteases has been successfully applied. Furthermore, MIPs have been coupled with enzymes in order to enhance the analytical performance of biomimetic sensors: Enzymes have been used in MIP-sensors as tracers for the generation and amplification of the measuring signal. In addition, enzymatic pretreatment of an analyte can extend the analyte spectrum and eliminate interferences.
Shifts among Eukaryota, Bacteria, and Archaea define the vertical organization of a lake sediment
(2017)
Background
Lake sediments harbor diverse microbial communities that cycle carbon and nutrients while being constantly colonized and potentially buried by organic matter sinking from the water column. The interaction of activity and burial remained largely unexplored in aquatic sediments. We aimed to relate taxonomic composition to sediment biogeochemical parameters, test whether community turnover with depth resulted from taxonomic replacement or from richness effects, and to provide a basic model for the vertical community structure in sediments.
Methods
We analyzed four replicate sediment cores taken from 30-m depth in oligo-mesotrophic Lake Stechlin in northern Germany. Each 30-cm core spanned ca. 170 years of sediment accumulation according to 137Cs dating and was sectioned into layers 1–4 cm thick. We examined a full suite of biogeochemical parameters and used DNA metabarcoding to examine community composition of microbial Archaea, Bacteria, and Eukaryota.
Results
Community β-diversity indicated nearly complete turnover within the uppermost 30 cm. We observed a pronounced shift from Eukaryota- and Bacteria-dominated upper layers (<5 cm) to Bacteria-dominated intermediate layers (5–14 cm) and to deep layers (>14 cm) dominated by enigmatic Archaea that typically occur in deep-sea sediments. Taxonomic replacement was the prevalent mechanism in structuring the community composition and was linked to parameters indicative of microbial activity (e.g., CO2 and CH4 concentration, bacterial protein production). Richness loss played a lesser role but was linked to conservative parameters (e.g., C, N, P) indicative of past conditions.
Conclusions
By including all three domains, we were able to directly link the exponential decay of eukaryotes with the active sediment microbial community. The dominance of Archaea in deeper layers confirms earlier findings from marine systems and establishes freshwater sediments as a potential low-energy environment, similar to deep sea sediments. We propose a general model of sediment structure and function based on microbial characteristics and burial processes. An upper “replacement horizon” is dominated by rapid taxonomic turnover with depth, high microbial activity, and biotic interactions. A lower “depauperate horizon” is characterized by low taxonomic richness, more stable “low-energy” conditions, and a dominance of enigmatic Archaea.
Background: Healthy university students have been shown to use psychoactive substances, expecting them to be functional means for enhancing their cognitive capacity, sometimes over and above an essentially proficient level. This behavior called Neuroenhancement (NE) has not yet been integrated into a behavioral theory that is able to predict performance. Job Demands Resources (JD-R) Theory for example assumes that strain (e.g. burnout) will occur and influence performance when job demands are high and job resources are limited at the same time. The aim of this study is to investigate whether or not university students’ self-reported NE can be integrated into JD-R Theory’s comprehensive approach to psychological health and performance.
Methods: 1,007 students (23.56 ± 3.83 years old, 637 female) participated in an online survey. Lifestyle drug, prescription drug, and illicit substance NE together with the complete set of JD-R variables (demands, burnout, resources, motivation, and performance) were measured. Path models were used in order to test our data’s fit to hypothesized main effects and interactions.
Results: JD-R Theory could successfully be applied to describe the situation of university students. NE was mainly associated with the JD-R Theory’s health impairment process: Lifestyle drug NE (p < .05) as well as prescription drug NE (p < .001) is associated with higher burnout scores, and lifestyle drug NE aggravates the study demands-burnout interaction. In addition, prescription drug NE mitigates the protective influence of resources on burnout and on motivation.
Conclusion: According to our results, the uninformed trying of NE (i.e., without medical supervision) might result in strain. Increased strain is related to decreased performance. From a public health perspective, intervention strategies should address these costs of non-supervised NE. With regard to future research we propose to model NE as a means to reach an end (i.e. performance enhancement) rather than a target behavior itself. This is necessary to provide a deeper understanding of the behavioral roots and consequences of the phenomenon.
Molecules often fragment after photoionization in the gas phase. Usually, this process can only be investigated spectroscopically as long as there exists electron correlation between the photofragments. Important parameters, like their kinetic energy after separation, cannot be investigated. We are reporting on a femtosecond time-resolved Auger electron spectroscopy study concerning the photofragmentation dynamics of thymine. We observe the appearance of clearly distinguishable signatures from thymine′s neutral photofragment isocyanic acid. Furthermore, we observe a time-dependent shift of its spectrum, which we can attribute to the influence of the charged fragment on the Auger electron. This allows us to map our time-dependent dataset onto the fragmentation coordinate. The time dependence of the shift supports efficient transformation of the excess energy gained from photoionization into kinetic energy of the fragments. Our method is broadly applicable to the investigation of photofragmentation processes.
Die zerstörungsfreien Prüfungen von Bauwerken mit Hilfe von Ultraschallmessverfahren haben in den letzten Jahren an Bedeutung gewonnen. Durch Ultraschallmessungen können die Geometrien von Bauteilen bestimmt sowie von außen nicht sichtbare Fehler wie Delaminationen und Kiesnester erkannt werden.
Mit neuartigen, in das Betonbauteil eingebetteten Ultraschallprüfköpfen sollen nun Bauwerke dauerhaft auf Veränderungen überprüft werden. Dazu werden Ultraschallsignale direkt im Inneren eines Bauteils erzeugt, was die Möglichkeiten der herkömmlichen Methoden der Bauwerksüberwachung wesentlich erweitert. Ein Ultraschallverfahren könnte mit eingebetteten Prüfköpfen ein Betonbauteil kontinuierlich integral überwachen und damit auch stetig fortschreitende Gefügeänderungen, wie beispielsweise Mikrorisse, registrieren.
Sicherheitsrelevante Bauteile, die nach dem Einbau für Messungen unzugänglich oder mittels Ultraschall, beispielsweise durch zusätzliche Beschichtungen der Oberfläche, nicht prüfbar sind, lassen sich mit eingebetteten Prüfköpfen überwachen. An bereits vorhandenen Bauwerken können die Ultraschallprüfköpfe mithilfe von Bohrlöchern und speziellem Verpressmörtel auch nachträglich in das Bauteil integriert werden. Für Fertigbauteile bieten sich eingebettete Prüfköpfe zur Herstellungskontrolle sowie zur Überwachung der Baudurchführung als Werkzeug der Qualitätssicherung an. Auch die schnelle Schadensanalyse eines Bauwerks nach Naturkatastrophen, wie beispielsweise einem Erdbeben oder einer Flut, ist denkbar.
Durch die gute Ankopplung ermöglichen diese neuartigen Prüfköpfe den Einsatz von empfindlichen Auswertungsmethoden, wie die Kreuzkorrelation, die Coda-Wellen-Interferometrie oder die Amplitudenauswertung, für die Signalanalyse. Bei regelmäßigen Messungen können somit sich anbahnende Schäden eines Bauwerks frühzeitig erkannt werden.
Da die Schädigung eines Bauwerks keine direkt messbare Größe darstellt, erfordert eine eindeutige Schadenserkennung in der Regel die Messung mehrerer physikalischer Größen die geeignet verknüpft werden. Physikalische Größen können sein: Ultraschalllaufzeit, Amplitude des Ultraschallsignals und Umgebungstemperatur. Dazu müssen Korrelationen zwischen dem Zustand des Bauwerks, den Umgebungsbedingungen und den Parametern des gemessenen Ultraschallsignals untersucht werden.
In dieser Arbeit werden die neuartigen Prüfköpfe vorgestellt. Es wird beschrieben, dass sie sich, sowohl in bereits errichtete Betonbauwerke als auch in der Konstruktion befindliche, einbauen lassen. Experimentell wird gezeigt, dass die Prüfköpfe in mehreren Ebenen eingebettet sein können da ihre Abstrahlcharakteristik im Beton nahezu ungerichtet ist. Die Mittenfrequenz von rund 62 kHz ermöglicht Abstände, je nach Betonart und SRV, von mindestens 3 m zwischen Prüfköpfen die als Sender und Empfänger arbeiten. Die Empfindlichkeit der eingebetteten Prüfköpfe gegenüber Veränderungen im Beton wird an Hand von zwei Laborexperimenten gezeigt, einem Drei-Punkt-Biegeversuch und einem Versuch zur Erzeugung von Frost-Tau-Wechsel Schäden. Die Ergebnisse werden mit anderen zerstörungsfreien Prüfverfahren verglichen. Es zeigt sich, dass die Prüfköpfe durch die Anwendung empfindlicher Auswertemethoden, auftretende Risse im Beton detektieren, bevor diese eine Gefahr für das Bauwerk darstellen. Abschließend werden Beispiele von Installation der neuartigen Ultraschallprüfköpfe in realen Bauteilen, zwei Brücken und einem Fundament, gezeigt und basierend auf dort gewonnenen ersten Erfahrungen ein Konzept für die Umsetzung einer Langzeitüberwachung aufgestellt.
Background: Consumption of whole-grain, coffee, and red meat were consistently related to the risk of developing type 2 diabetes in prospective cohort studies, but potentially underlying biological mechanisms are not well understood. Metabolomics profiles were shown to be sensitive to these dietary exposures, and at the same time to be informative with respect to the risk of type 2 diabetes. Moreover, graphical network-models were demonstrated to reflect the biological processes underlying high-dimensional metabolomics profiles.
Aim: The aim of this study was to infer hypotheses on the biological mechanisms that link consumption of whole-grain bread, coffee, and red meat, respectively, to the risk of developing type 2 diabetes. More specifically, it was aimed to consider network models of amino acid and lipid profiles as potential mediators of these risk-relations.
Study population: Analyses were conducted in the prospective EPIC-Potsdam cohort (n = 27,548), applying a nested case-cohort design (n = 2731, including 692 incident diabetes cases). Habitual diet was assessed with validated semiquantitative food-frequency questionnaires. Concentrations of 126 metabolites (acylcarnitines, phosphatidylcholines, sphingomyelins, amino acids) were determined in baseline-serum samples. Incident type 2 diabetes cases were assed and validated in an active follow-up procedure. The median follow-up time was 6.6 years.
Analytical design: The methodological approach was conceptually based on counterfactual causal inference theory. Observations on the network-encoded conditional independence structure restricted the space of possible causal explanations of observed metabolomics-data patterns. Given basic directionality assumptions (diet affects metabolism; metabolism affects future diabetes incidence), adjustment for a subset of direct neighbours was sufficient to consistently estimate network-independent direct effects. Further model-specification, however, was limited due to missing directionality information on the links between metabolites. Therefore, a multi-model approach was applied to infer the bounds of possible direct effects. All metabolite-exposure links and metabolite-outcome links, respectively, were classified into one of three categories: direct effect, ambiguous (some models indicated an effect others not), and no-effect.
Cross-sectional and longitudinal relations were evaluated in multivariable-adjusted linear regression and Cox proportional hazard regression models, respectively. Models were comprehensively adjusted for age, sex, body mass index, prevalence of hypertension, dietary and lifestyle factors, and medication.
Results: Consumption of whole-grain bread was related to lower levels of several lipid metabolites with saturated and monounsaturated fatty acids. Coffee was related to lower aromatic and branched-chain amino acids, and had potential effects on the fatty acid profile within lipid classes. Red meat was linked to lower glycine levels and was related to higher circulating concentrations of branched-chain amino acids. In addition, potential marked effects of red meat consumption on the fatty acid composition within the investigated lipid classes were identified.
Moreover, potential beneficial and adverse direct effects of metabolites on type 2 diabetes risk were detected. Aromatic amino acids and lipid metabolites with even-chain saturated (C14-C18) and with specific polyunsaturated fatty acids had adverse effects on type 2 diabetes risk. Glycine, glutamine, and lipid metabolites with monounsaturated fatty acids and with other species of polyunsaturated fatty acids were classified as having direct beneficial effects on type 2 diabetes risk.
Potential mediators of the diet-diabetes links were identified by graphically overlaying this information in network models. Mediation analyses revealed that effects on lipid metabolites could potentially explain about one fourth of the whole-grain bread effect on type 2 diabetes risk; and that effects of coffee and red meat consumption on amino acid and lipid profiles could potentially explain about two thirds of the altered type 2 diabetes risk linked to these dietary exposures.
Conclusion: An algorithm was developed that is capable to integrate single external variables (continuous exposures, survival time) and high-dimensional metabolomics-data in a joint graphical model. Application to the EPIC-Potsdam cohort study revealed that the observed conditional independence patterns were consistent with the a priori mediation hypothesis: Early effects on lipid and amino acid metabolism had the potential to explain large parts of the link between three of the most widely discussed diabetes-related dietary exposures and the risk of developing type 2 diabetes.
Decades of research have demonstrated that physical stress (PS) stimulates bone remodeling and affects bone structure and function through complex mechanotransduction mechanisms. Recent research has laid ground to the hypothesis that mental stress (MS) also influences bone biology, eventually leading to osteoporosis and increased bone fracture risk. These effects are likely exerted by modulation of hypothalamic–pituitary–adrenal axis activity, resulting in an altered release of growth hormones, glucocorticoids and cytokines, as demonstrated in human and animal studies. Furthermore, molecular cross talk between mental and PS is thought to exist, with either synergistic or preventative effects on bone disease progression depending on the characteristics of the applied stressor. This mini review will explain the emerging concept of MS as an important player in bone adaptation and its potential cross talk with PS by summarizing the current state of knowledge, highlighting newly evolving notions (such as intergenerational transmission of stress and its epigenetic modifications affecting bone) and proposing new research directions.