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Carbon nanomaterials doped with some other lightweight elements were recently described as powerful, heterogeneous, metal-free organocatalysts, adding to their high performance in electrocatalysis. Here, recent observations in traditional catalysis are reviewed, and the underlying reaction mechanisms of the catalyzed organic transformations are explored. In some cases, these are due to specific active functional sites, but more generally the catalytic activity relates to collective properties of the conjugated nanocarbon frameworks and the electron transfer from and to the catalytic centers and substrates. It is shown that the !earnings are tightly related to those of electrocatalysis; i.e., the search for better electrocatalysts also improves chemocatalysis, and vice versa. Carbon-carbon heterojunction effects and some perspectives on future possibilities are discussed at the end.
Microplastics (MP) provide a unique and extensive surface for microbial colonization in aquatic ecosystems. The formation of microorganism-microplastic complexes, such as biofilms, maximizes the degradation of organic matter and horizontal gene transfer. In this context, MP affect the structure and function of microbial communities, which in turn render the physical and chemical fate of MP. This new paradigm generates challenges for microbiology, ecology, and ecotoxicology. Dispersal of MP is concomitant with that of their associated microorganisms and their mobile genetic elements, including antibiotic resistance genes, islands of pathogenicity, and diverse metabolic pathways. Functional changes in aquatic microbiomes can alter carbon metabolism and food webs, with unknown consequences on higher organisms or human microbiomes and hence health. Here, we examine a variety of effects of MP pollution from the microbial ecology perspective, whose repercussions on aquatic ecosystems begin to be unraveled. (C) 2018 Elsevier B.V. All rights reserved.
Rezensiertes Werk:
Carsten Schapkow: Role Model and Countermodel. The Golden Age of Iberian Jewry and German Jewish Culture During the Era of Emancipation, übers. von Corey Twitchell, Lanham / Boulder / New York / London: Lexington Books 2016, 305 S.
Terrestrial environmental systems are characterised by numerous feedback links between their different compartments. However, scientific research is organized into disciplines that focus on processes within the respective compartments rather than on interdisciplinary links. Major feedback mechanisms between compartments might therefore have been systematically overlooked so far. Without identifying these gaps, initiatives on future comprehensive environmental monitoring schemes and experimental platforms might fail. We performed a comprehensive overview of feedbacks between compartments currently represented in environmental sciences and explores to what degree missing links have already been acknowledged in the literature. We focused on process models as they can be regarded as repositories of scientific knowledge that compile findings of numerous single studies. In total, 118 simulation models from 23 model types were analysed. Missing processes linking different environmental compartments were identified based on a meta-review of 346 published reviews, model inter-comparison studies, and model descriptions. Eight disciplines of environmental sciences were considered and 396 linking processes were identified and ascribed to the physical, chemical or biological domain. There were significant differences between model types and scientific disciplines regarding implemented interdisciplinary links. The most wide-spread interdisciplinary links were between physical processes in meteorology, hydrology and soil science that drive or set the boundary conditions for other processes (e.g., ecological processes). In contrast, most chemical and biological processes were restricted to links within the same compartment. Integration of multiple environmental compartments and interdisciplinary knowledge was scarce in most model types. There was a strong bias of suggested future research foci and model extensions towards reinforcing existing interdisciplinary knowledge rather than to open up new interdisciplinary pathways. No clear pattern across disciplines exists with respect to suggested future research efforts. There is no evidence that environmental research would clearly converge towards more integrated approaches or towards an overarching environmental systems theory. (c) 2017 Elsevier B.V. All rights reserved.
Methodological and technological advances have recently paved the way for metabolic flux profiling in higher organisms, like plants. However, in comparison with omics technologies, flux profiling has yet to provide comprehensive differential flux maps at a genome-scale and in different cell types, tissues, and organs. Here we highlight the recent advances in technologies to gather metabolic labeling patterns and flux profiling approaches. We provide an opinion of how recent local flux profiling approaches can be used in conjunction with the constraint-based modeling framework to arrive at genome-scale flux maps. In addition, we point at approaches which use metabolomics data without introduction of label to predict either non-steady state fluxes in a time-series experiment or flux changes in different experimental scenarios. The combination of these developments allows an experimentally feasible approach for flux-based large-scale systems biology studies.
Studies over the past several years have demonstrated the important role of sphingolipids in cystic fibrosis (CF), chronic obstructive pulmonary disease and acute lung injury. Ceramide is increased in airway epithelial cells and alveolar macrophages of CF mice and humans, while sphingosine is dramatically decreased. This increase in ceramide results in chronic inflammation, increased death of epithelial cells, release of DNA into the bronchial lumen and thereby an impairment of mucociliary clearance; while the lack of sphingosine in airway epithelial cells causes high infection susceptibility in CF mice and possibly patients. The increase in ceramide mediates an ectopic expression of beta 1-integrins in the luminal membrane of CF epithelial cells, which results, via an unknown mechanism, in a down-regulation of acid ceramidase. It is predominantly this down-regulation of acid ceramidase that results in the imbalance of ceramide and sphingosine in CF cells. Correction of ceramide and sphingosine levels can be achieved by inhalation of functional acid sphingomyelinase inhibitors, recombinant acid ceramidase or by normalization of beta 1-integrin expression and subsequent re-expression of endogenous acid ceramidase. These treatments correct pulmonary inflammation and prevent or treat, respectively, acute and chronic pulmonary infections in CF mice with Staphylococcus aureus and mucoid or non-mucoid Pseudomonas aeruginosa. Inhalation of sphingosine corrects sphingosine levels only and seems to mainly act against the infection. Many antidepressants are functional inhibitors of the acid sphingomyelinase and were designed for systemic treatment of major depression. These drugs could be repurposed to treat CF by inhalation.
Nowadays, the role of trace elements (TE) is of growing interest because dyshomeostasis of selenium (Se), manganese (Mn), zinc (Zn), and copper (Cu) is supposed to be a risk factor for several diseases. Thereby, research focuses on identifying new biomarkers for the TE status to allow for a more reliable description of the individual TE and health status. This review mirrors a lack of well-defined, sensitive, and selective biomarkers and summarizes technical limitations to measure them. Thus, the capacity to assess the relationship between dietary TE intake, homeostasis, and health is restricted, which would otherwise provide the basis to define adequate intake levels of single TE in both healthy and diseased humans. Besides that, our knowledge is even more limited with respect to the real life situation of combined TE intake and putative interactions between single TE.
Moving Beyond ERP Components
(2018)
Relationships between neuroimaging measures and behavior provide important clues about brain function and cognition in healthy and clinical populations. While electroencephalography (EEG) provides a portable, low cost measure of brain dynamics, it has been somewhat underrepresented in the emerging field of model-based inference. We seek to address this gap in this article by highlighting the utility of linking EEG and behavior, with an emphasis on approaches for EEG analysis that move beyond focusing on peaks or "components" derived from averaging EEG responses across trials and subjects (generating the event-related potential, ERP). First, we review methods for deriving features from EEG in order to enhance the signal within single-trials. These methods include filtering based on user-defined features (i.e., frequency decomposition, time-frequency decomposition), filtering based on data-driven properties (i.e., blind source separation, BSS), and generating more abstract representations of data (e.g., using deep learning). We then review cognitive models which extract latent variables from experimental tasks, including the drift diffusion model (DDM) and reinforcement learning (RL) approaches. Next, we discuss ways to access associations among these measures, including statistical models, data-driven joint models and cognitive joint modeling using hierarchical Bayesian models (HBMs). We think that these methodological tools are likely to contribute to theoretical advancements, and will help inform our understandings of brain dynamics that contribute to moment-to-moment cognitive function.
Ecological communities change in time and space, but long-term dynamics at the century-to-millennia scale are poorly documented due to lack of relevant data sets. Nevertheless, understanding long-term dynamics is important for explaining present-day biodiversity patterns and placing conservation goals in a historical context. Here, we use recent examples and new perspectives to highlight how environmental DNA (eDNA) is starting to provide a powerful new source of temporal data for research questions that have so far been overlooked, by helping to resolve the ecological dynamics of populations, communities, and ecosystems over hundreds to thousands of years. We give examples of hypotheses that may be addressed by temporal eDNA biodiversity data, discuss possible research directions, and outline related challenges.
Second harmonic generation (SHG) is a nonlinear optical process that inherently generates signal in non-centrosymmetric materials, such as starch granules, and therefore can be used for label-free imaging. Both intensity and polarization of SHG are determined by material properties that are characterized by the nonlinear susceptibility tensor, ((2)). Examination of the tensor is performed for each focal volume of the image by measuring the outgoing polarization state of the SHG signal for a set of incoming laser beam polarizations. Mapping of nonlinear properties expressed as the susceptibility ratio reveals structural features including the organization of crystalline material within a single starch granule, and the distribution of structural properties in a population of granules. Isolated granules, as well as in situ starch, can be analyzed using polarimetric SHG microscopy. Due to the fast sample preparation and short imaging times, polarimetric SHG microscopy allows for a quick assessment of starch structure and permits rapid feedback for bioengineering applications. This article presents the basics of SHG theory and microscopy applications for starch-containing materials. Quantification of ultrastructural features within individual starch granules is described. New results obtained by polarization resolved SHG microscopy of starch granules are presented for various maize genotypes revealing heterogeneity within a single starch particle and between various granules.
Teaching culturally diverse classrooms starts from embracing beliefs that recognise the strengths of cultural diversity. Research is needed to understand how teacher training contributes to shaping pre-service teachers’ beliefs about cultural diversity. Accordingly, the purpose of this review is to 1) provide a description of main components and contextual characteristics of teacher trainings targeting cultural diversity beliefs, 2) report the training effects, and 3) detail the methodological strengths and weaknesses of these studies. A total of 36 studies published between 2005 and 2015 that used a longitudinal assessment of cultural diversity beliefs were reviewed. The collective results of these studies indicate a large variance amongst trainings, with experiential learning shifting cultural diversity beliefs positively. However, existing studies have significant limitations in the study design and training evaluation that hinder their conclusions regarding internal and external validity and point towards new directions for future research.
(1) Background: Sexual violence (SV) is a major public health problem, with negative socio-economic, physical, mental, sexual, and reproductive health consequences. Migrants, applicants for international protection, and refugees (MARs) are vulnerable to SV. Since many European countries are seeing high migratory pressure, the development of prevention strategies and care paths focusing on victimised MARs is highly needed. To this end, this study reviews evidence on the prevalence of SV among MAR groups in Europe and the challenges encountered in research on this topic. (2) Methods: A critical interpretive synthesis of 25 peer-reviewed academic studies and 22 relevant grey literature documents was conducted based on a socio-ecological model. (3) Results: Evidence shows that SV is highly frequent in MARs in Europe, yet comparison with other groups is still difficult. Methodologically and ethically sound representative studies comparing between populations are still lacking. Challenges in researching SV in MARs are located at the intrapersonal, interpersonal, community, societal, and policy levels. (4) Conclusions: Future research should start with a clear definition of the concerned population and acts of SV to generate comparable data. Participatory qualitative research approaches could be applied to better grasp the complexity of interplaying determinants of SV in MARs.