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Narcissists are assumed to lack the motivation and ability to share and understand the mental states of others. Prior empirical research, however, has yielded inconclusive findings and has differed with respect to the specific aspects of narcissism and socioemotional cognition that have been examined. Here, we propose a differentiated facet approach that can be applied across research traditions and that distinguishes between facets of narcissism (agentic vs. antagonistic) on the one hand, and facets of socioemotional cognition ability (SECA; self-perceived vs. actual) on the other. Using five nonclinical samples in two studies (total N = 602), we investigated the effect of facets of grandiose narcissism on aspects of socioemotional cognition across measures of affective and cognitive empathy, Theory of Mind, and emotional intelligence, while also controlling for general reasoning ability. Across both studies, agentic facets of narcissism were found to be positively related to perceived SECA, whereas antagonistic facets of narcissism were found to be negatively related to perceived SECA. However, both narcissism facets were negatively related to actual SECA. Exploratory condition-based regression analyses further showed that agentic narcissists had a higher directed discrepancy between perceived and actual SECA: They self-enhanced their socio-emotional capacities. Implications of these results for the multifaceted theoretical understanding of the narcissism-SECA link are discussed.
This work reviews the literature on an alleged global warming 'pause' in global mean surface temperature (GMST) to determine how it has been defined, what time intervals are used to characterise it, what data are used to measure it, and what methods used to assess it. We test for 'pauses', both in the normally understood meaning of the term to mean no warming trend, as well as for a 'pause' defined as a substantially slower trend in GMST. The tests are carried out with the historical versions of GMST that existed for each pause-interval tested, and with current versions of each of the GMST datasets. The tests are conducted following the common (but questionable) practice of breaking the linear fit at the start of the trend interval ('broken' trends), and also with trends that are continuous with the data bordering the trend interval. We also compare results when appropriate allowance is made for the selection bias problem. The results show that there is little or no statistical evidence for a lack of trend or slower trend in GMST using either the historical data or the current data. The perception that there was a 'pause' in GMST was bolstered by earlier biases in the data in combination with incomplete statistical testing.
Like almost all fields of science, hydrology has benefited to a large extent from the tremendous improvements in scientific instruments that are able to collect long-time data series and an increase in available computational power and storage capabilities over the last decades. Many model applications and statistical analyses (e.g., extreme value analysis) are based on these time series. Consequently, the quality and the completeness of these time series are essential. Preprocessing of raw data sets by filling data gaps is thus a necessary procedure. Several interpolation techniques with different complexity are available ranging from rather simple to extremely challenging approaches. In this paper, various imputation methods available to the hydrological researchers are reviewed with regard to their suitability for filling gaps in the context of solving hydrological questions. The methodological approaches include arithmetic mean imputation, principal component analysis, regression-based methods and multiple imputation methods. In particular, autoregressive conditional heteroscedasticity (ARCH) models which originate from finance and econometrics will be discussed regarding their applicability to data series characterized by non-constant volatility and heteroscedasticity in hydrological contexts. The review shows that methodological advances driven by other fields of research bear relevance for a more intensive use of these methods in hydrology. Up to now, the hydrological community has paid little attention to the imputation ability of time series models in general and ARCH models in particular.
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.
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.
The relevance for in vitro three-dimensional (3D) tissue culture of skin has been present for almost a century. From using skin biopsies in organ culture, to vascularized organotypic full-thickness reconstructed human skin equivalents, in vitro tissue regeneration of 3D skin has reached a golden era. However, the reconstruction of 3D skin still has room to grow and develop. The need for reproducible methodology, physiological structures and tissue architecture, and perfusable vasculature are only recently becoming a reality, though the addition of more complex structures such as glands and tactile corpuscles require advanced technologies. In this review, we will discuss the current methodology for biofabrication of 3D skin models and highlight the advantages and disadvantages of the existing systems as well as emphasize how new techniques can aid in the production of a truly physiologically relevant skin construct for preclinical innovation.
Analytical epigenetics
(2018)
The field of epigenetics describes the relationship between genotype and phenotype, by regulating gene expression without changing the canonical base sequence of DNA. It deals with molecular genomic information that is encoded by a rich repertoire of chemical modifications and molecular interactions. This regulation involves DNA, RNA and proteins that are enzymatically tagged with small molecular groups that alter their physical and chemical properties. It is now clear that epigenetic alterations are involved in development and disease, and thus, are the focus of intensive research. The ability to record epigenetic changes and quantify them in rare medical samples is critical for next generation diagnostics. Optical detection offers the ultimate single-molecule sensitivity and the potential for spectral multiplexing. Here we review recent progress in ultrasensitive optical detection of DNA and histone modifications.
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.
For successful growth and development, plants constantly have to gauge their environment. Plants are capable to monitor their current environmental conditions, and they are also able to integrate environmental conditions over time and store the information induced by the cues. In a developmental context, such an environmental memory is used to align developmental transitions with favourable environmental conditions. One temperature-related example of this is the transition to flowering after experiencing winter conditions, that is, vernalization. In the context of adaptation to stress, such an environmental memory is used to improve stress adaptation even when the stress cues are intermittent. A somatic stress memory has now been described for various stresses, including extreme temperatures, drought, and pathogen infection. At the molecular level, such a memory of the environment is often mediated by epigenetic and chromatin modifications. Histone modifications in particular play an important role. In this review, we will discuss and compare different types of temperature memory and the histone modifications, as well as the reader, writer, and eraser proteins involved.
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.