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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.
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.
This article presents some insights into the German developments of studying Judaism and the Jewish tradition and relates them to the ongoing development of the subject at universities in the Nordic countries in general and Norway in particular. It also aims to present some conclusions concerning why it might be interesting for Norwegian society to intensify the study of Judaism at its universities.
In order to replace bio-macromolecules by stable synthetic materials in separation techniques and bioanalysis biomimetic receptors and catalysts have been developed: Functional monomers are polymerized together with the target analyte and after template removal cavities are formed in the "molecularly imprinted polymer" (MIP) which resemble the active sites of antibodies and enzymes. Starting almost 80 years ago, around 1,100 papers on MIPs were published in 2016. Electropolymerization allows to deposit MIPs directly on voltammetric electrodes or chips for quartz crystal microbalance (QCM) and surface plasmon resonance (SPR). For the readout of MIPs for drugs amperometry, differential pulse voltammetry (DPV) and impedance spectroscopy (EIS) offer higher sensitivity as compared with QCM or SPR. Application of simple electrochemical devices allows both the reproducible preparation of MIP sensors, but also the sensitive signal generation. Electrochemical MIP-sensors for the whole arsenal of drugs, e.g. the most frequently used analgesics, antibiotics and anticancer drugs have been presented in literature and tested under laboratory conditions. These biomimetic sensors typically have measuring ranges covering the lower nano-up to millimolar concentration range and they are stable under extreme pH and in organic solvents like nonaqueous extracts.
Silicon (Si) is considered as a quasiessential element for higher plants as its uptake increases plant growth and resistance against abiotic as well as biotic stresses. Foliar application of fertilizers generally is assumed to be a comparably environment-friendly form of fertilization because only small quantities are needed. The interest in foliar fertilization and the use of Si as a fertilizer in general increased significantly within the last decades, but there are only few publications dealing with the foliar application of Si at all. In the present review, the effects of Si foliar fertilization, including nano-Si fertilizers, on the three most important crops on a global scale, that is, maize, rice, and wheat, are summarized. Additionally, different pathways (i.e., cuticular pathways, stomata, and trichomes) of foliar uptake and functioning of Si foliar fertilizers against biotic (i.e., fungal diseases and harmful insects), as well as abiotic (i.e., water stress, macronutrient imbalance, and heavy metal toxicity) stressors are discussed. Future research should especially focus on (1) the gathering of empirical data from field and greenhouse experiments, (2) the intensification of co-operations between practitioners and scientists, (3) interdisciplinary research, and (4) the analysis of results from multiple studies (meta-analysis, big data) to fully understand effects, uptake, and functioning of Si foliar fertilizers and to evaluate their potential in modern sustainable agriculture concepts.
We review recent progress in the field of light responsive soft nano-objects. These are systems the shape, size, surface area and surface energy of which can be easily changed by low-intensity external irradiation. Here we shall specifically focus on microgels, DNA molecules, polymer brushes and colloidal particles. One convenient way to render these objects photosensitive is to couple them via ionic and/or hydrophobic interactions with azobenzene containing surfactants in a non-covalent way. The advantage of this strategy is that these surfactants can make any type of charged object light responsive without the need for possibly complicated (and irreversible) chemical conjugation. In the following, we will exclusively discuss only photosensitive surfactant systems. These contain a charged head and a hydrophobic tail into which an azobenzene group is incorporated, which can undergo reversible photo-isomerization from a trans-to a cis-configuration under UV illumination. These kinds of photo-isomerizations occur on a picosecond timescale and are fully reversible. The two isomers in general possess different polarity, i.e. the trans-state is less polar with a dipole moment of usually close to 0 Debye, while the cis-isomer has a dipole moment up to 3 Debye or more, depending on additional phenyl ring substituents. As part of the hydrophobic tail of a surfactant molecule, the photo-isomerization also changes the hydrophobicity of the molecule as a whole and hence its solubility, surface energy, and strength of interaction with other substances. Being a molecular actuator, which converts optical energy in to mechanical work, the azobenzene group in the shape of surfactant molecule can be utilized in order to actuate matter on larger time and length scale. In this paper we show several interesting examples, where azobenzene containing surfactants play the role of a transducer mediating between different states of size, shape, surface energy and spatial arrangement of various nanoscale soft-material systems.
Unravelling the spatiotemporal evolution of the Cenozoic Andean (Altiplano-Puna) plateau has been one of the most intriguing problems of South American geology. Despite a number of investigations, the early deformation and uplift history of this area remained largely enigmatic. This paper analyses the Paleogene tectono-sedimentary history of the Casa Grande Basin, in the present-day transition zone between the northern sector of the Puna Plateau and the northern part of the Argentine Eastern Cordillera. Our detailed mapping of synsedimentary structures records the onset of regional contractional deformation during the middle Eocene, revealing reactivation of Cretaceous extensional structures and the development of doubly vergent thrusts. This is in agreement with records from other southern parts of the Puna Plateau and the Eastern Cordillera. These observations indicate the existence of an Eocene broken foreland setting within the region, characterized by low-lying compressional basins and ranges with spatially disparate sectors of deformation, which was subsequently subjected to regional uplift resulting in the attainment of present-day elevations during the Neogene.
Plant roots control uptake of water and nutrients and cope with environmental challenges. The root epidermis provides the first selective interface for nutrient absorption, while the endodermis produces the main apoplastic diffusion barrier in the form of a structure called the Casparian strip. The positioning of root hairs on epidermal cells, and of the Casparian strip around endodermal cells, requires asymmetries along cellular axes (cell polarity). Cell polarity is termed planar polarity, when coordinated within the plane of a given tissue layer. Here, we review recent molecular advances towards understanding both the polar positioning of the proteo-lipid membrane domain instructing root hair initiation, and the cytoskeletal, trafficking and polar tethering requirements of proteins at outer or inner plasma membrane domains. Finally, we highlight progress towards understanding mechanisms of Casparian strip formation and underlying endodermal cell polarity.
To cope with the already large, and ever increasing, amount of information stored in organizational memory, "forgetting," as an important human memory process, might be transferred to the organizational context. Especially in intentionally planned change processes (e.g., change management), forgetting is an important precondition to impede the recall of obsolete routines and adapt to new strategic objectives accompanied by new organizational routines. We first comprehensively review the literature on the need for organizational forgetting and particularly on accidental vs. intentional forgetting. We discuss the current state of the art of theory and empirical evidence on forgetting from cognitive psychology in order to infer mechanisms applicable to the organizational context. In this respect, we emphasize retrieval theories and the relevance of retrieval cues important for forgetting. Subsequently, we transfer the empirical evidence that the elimination of retrieval cues leads to faster forgetting to the forgetting of organizational routines, as routines are part of organizational memory. We then propose a classification of cues (context, sensory, business process-related cues) that are relevant in the forgetting of routines, and discuss a meta-cue called the "situational strength" cue, which is relevant if cues of an old and a new routine are present simultaneously. Based on the classification as business process-related cues (information, team, task, object cues), we propose mechanisms to accelerate forgetting by eliminating specific cues based on the empirical and theoretical state of the art. We conclude that in intentional organizational change processes, the elimination of cues to accelerate forgetting should be used in change management practices.
Lifestyle-related disorders, such as the metabolic syndrome, have become a primary risk factor for the development of liver pathologies that can progress from hepatic steatosis, hepatic insulin resistance, steatohepatitis, fibrosis and cirrhosis, to the most severe condition of hepatocellular carcinoma (HCC). While the prevalence of liver pathologies is steadily increasing in modern societies, there are currently no approved drugs other than chemotherapeutic intervention in late stage HCC. Hence, there is a pressing need to identify and investigate causative molecular pathways that can yield new therapeutic avenues. The transcription factor p53 is well established as a tumor suppressor and has recently been described as a central metabolic player both in physiological and pathological settings. Given that liver is a dynamic tissue with direct exposition to ingested nutrients, hepatic p53, by integrating cellular stress response, metabolism and cell cycle regulation, has emerged as an important regulator of liver homeostasis and dysfunction. The underlying evidence is reviewed herein, with a focus on clinical data and animal studies that highlight a direct influence of p53 activity on different stages of liver diseases. Based on current literature showing that activation of p53 signaling can either attenuate or fuel liver disease, we herein discuss the hypothesis that, while hyper-activation or loss of function can cause disease, moderate induction of hepatic p53 within physiological margins could be beneficial in the prevention and treatment of liver pathologies. Hence, stimuli that lead to a moderate and temporary p53 activation could present new therapeutic approaches through several entry points in the cascade from hepatic steatosis to HCC.
Two decades ago, sphingosine 1-phosphate (S1P) was discovered as a novel bioactive molecule that regulates a variety of cellular functions. The plethora of S1P-mediated effects is due to the fact that the sphingolipid not only modulates intracellular functions but also acts as a ligand of G protein-coupled receptors after secretion into the extracellular environment. In the plasma, S1P is found in high concentrations, modulating immune cell trafficking and vascular endothelial integrity. The liver is engaged in modulating the plasma S1P content, as it produces apolipoprotein M, which is a chaperone for the S1P transport. Moreover, the liver plays a substantial role in glucose and lipid homeostasis. A dysfunction of glucose and lipid metabolism is connected with the development of liver diseases such as hepatic insulin resistance, non-alcoholic fatty liver disease, or liver fibrosis. Recent studies indicate that S1P is involved in liver pathophysiology and contributes to the development of liver diseases. In this review, the current state of knowledge about S1P and its signaling in the liver is summarized with a specific focus on the dysregulation of S1P signaling in obesity-mediated liver diseases. Thus, the modulation of S1P signaling can be considered as a potential therapeutic target for the treatment of hepatic diseases.
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.
Employing electric phenomena for the spatial manipulation of bioparticles from whole cells down to dissolved molecules has become a useful tool in biotechnology and analytics. AC electrokinetic effects like dielectrophoresis and AC electroosmosis are increasingly used to concentrate, separate and immobilize DNA and proteins. With the advance of photolithographical micro- and nanofabrication methods, novel or improved bioanalytical applications benefit from concentrating analytes, signal enhancement and locally controlled immobilization by AC electrokinetic effects. In this review of AC electrokinetics of proteins, the respective studies are classified according to their different electrode geometries: individual electrode pairs, interdigitated electrodes, quadrupole electrodes, and 3D configurations of electrode arrays. Known advantages and disadvantages of each layout are discussed.
Serious knee pain and related disability have an annual prevalence of approximately 25% on those over the age of 55 years. As curative treatments for the common knee problems are not available to date, knee pathologies typically progress and often lead to osteoarthritis (OA). While the roles that the meniscus plays in knee biomechanics are well characterized, biological mechanisms underlying meniscus pathophysiology and roles in knee pain and OA progression are not fully clear. Experimental treatments for knee disorders that are successful in animal models often produce unsatisfactory results in humans due to species differences or the inability to fully replicate disease progression in experimental animals. The use of animals with spontaneous knee pathologies, such as dogs, can significantly help addressing this issue. As microscopic and macroscopic anatomy of the canine and human menisci are similar, spontaneous meniscal pathologies in canine patients are thought to be highly relevant for translational medicine. However, it is not clear whether the biomolecular mechanisms of pain, degradation of extracellular matrix, and inflammatory responses are species dependent. The aims of this review are (1) to provide an overview of the anatomy, physiology, and pathology of the human and canine meniscus, (2) to compare the known signaling pathways involved in spontaneous meniscus pathology between both species, and (3) to assess the relevance of dogs with spontaneous meniscal pathology as a translational model. Understanding these mechanisms in human and canine meniscus can help to advance diagnostic and therapeutic strategies for painful knee disorders and improve clinical decision making.
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.
Up to now pathological health anxiety has been classified primarily as a somatoform disorder or a somatic symptom disorder in ICD and DSM. Theoretical and empirical evidence, however, suggest that pathological health anxiety basically represents an anxiety disorder. In this paper, it is argued that deficits in the treatment and perception of patients with pathological health anxiety as "difficult patients" are partly attributable to a lack of clarity in terms of nosology and with respect to central mechanisms of etiology and pathogenesis. Based on novel theoretical approaches for the explanation of pathological health anxiety, suggestions for an improved therapeutic practice are outlined. This approach focuses on a more intensive use of exposure-based treatment elements that are oriented to the inhibitory learning approach, which has already proven its effectiveness for other anxiety disorders.
Recently, there has been a proliferation of published articles on the effect of plyometric jump training, including several review articles and meta-analyses. However, these types of research articles are generally of narrow scope. Furthermore, methodological limitations among studies (e.g., a lack of active/passive control groups) prevent the generalization of results, and these factors need to be addressed by researchers. On that basis, the aims of this scoping review were to (1) characterize the main elements of plyometric jump training studies (e.g., training protocols) and (2) provide future directions for research. From 648 potentially relevant articles, 242 were eligible for inclusion in this review. The main issues identified related to an insufficient number of studies conducted in females, youths, and individual sports (~ 24.0, ~ 37.0, and ~ 12.0% of overall studies, respectively); insufficient reporting of effect size values and training prescription (~ 34.0 and ~ 55.0% of overall studies, respectively); and studies missing an active/passive control group and randomization (~ 40.0 and ~ 20.0% of overall studies, respectively). Furthermore, plyometric jump training was often combined with other training methods and added to participants’ daily training routines (~ 47.0 and ~ 39.0% of overall studies, respectively), thus distorting conclusions on its independent effects. Additionally, most studies lasted no longer than 7 weeks. In future, researchers are advised to conduct plyometric training studies of high methodological quality (e.g., randomized controlled trials). More research is needed in females, youth, and individual sports. Finally, the identification of specific dose-response relationships following plyometric training is needed to specifically tailor intervention programs, particularly in the long term.