MutationDistiller is a freely available online tool for user-driven analyses of Whole Exome Sequencing data. It offers a user-friendly interface aimed at clinicians and researchers, who are not necessarily bioinformaticians. MutationDistiller combines Mutation- Taster’s pathogenicity predictions with a phenotypebased approach. Phenotypic information is not limited to symptoms included in the Human Phenotype Ontology (HPO), but may also comprise clinical diagnoses and the suspected mode of inheritance. The search can be restricted to lists of candidate genes (e.g. virtual gene panels) and by tissue-specific gene expression. The inclusion of GeneOntology (GO) and metabolic pathways facilitates the discovery of hitherto unknown disease genes. In a novel approach, we trained MutationDistiller’s HPO-based prioritization on authentic genotype–phenotype sets obtained from ClinVar and found it to match or outcompete current prioritization tools in terms of accuracy. In the output, the program provides a list of potential disease mutations ordered by the likelihood of the affected genes to cause the phenotype. MutationDistiller provides links to gene-related information from various resources. It has been extensively tested by clinicians and their suggestions have been valued in many iterative cycles of revisions. The tool, a comprehensive documentation and examples are freely available at https://www.mutationdistiller.org/

Deep neural networks have led to state-of-the-art results in many medical imaging tasks including Alzheimer’s disease (AD) detection based on structural magnetic resonance imaging (MRI) data. However, the network decisions are often perceived as being highly non-transparent, making it difficult to apply these algorithms in clinical routine. In this study, we propose using layer-wise relevance propagation (LRP) to visualize convolutional neural network decisions for AD based on MRI data. Similarly to other visualization methods, LRP produces a heatmap in the input space indicating the importance/relevance of each voxel contributing to the final classification outcome. In contrast to susceptibility maps produced by guided backpropagation (“Which change in voxels would change the outcome most?”), the LRP method is able to directly highlight positive contributions to the network classification in the input space. In particular, we show that (1) the LRP method is very specific for individuals (“Why does this person have AD?”) with high inter-patient variability, (2) there is very little relevance for AD in healthy controls and (3) areas that exhibit a lot of relevance correlate well with what is known from literature. To quantify the latter, we compute size-corrected metrics of the summed relevance per brain area, e.g., relevance density or relevance gain. Although these metrics produce very individual “fingerprints” of relevance patterns for AD patients, a lot of importance is put on areas in the temporal lobe including the hippocampus. After discussing several limitations such as sensitivity toward the underlying model and computation parameters, we conclude that LRP might have a high potential to assist clinicians in explaining neural network decisions for diagnosing AD (and potentially other diseases) based on structural MRI data.

The melanocortin-4 receptor (MC4R) can be endogenously activated by binding of melanocyte-stimulating hormones (MSH), which mediates anorexigenic effects. In contrast, the agouti-related peptide (AgRP) acts as an endogenous inverse agonist and suppresses ligand-independent basal signaling activity (orexigenic effects). Binding of ligands to MC4R leads to the activation of different G-protein subtypes or arrestin and concomitant signaling pathways. This receptor is a key protein in the hypothalamic regulation of food intake and energy expenditure and naturally-occurring inactivating MC4R variants are the most frequent cause of monogenic obesity. In general, obesity is a growing problem on a global scale and is of social, medical, and economic relevance. A significant goal is to develop optimized pharmacological tools targeting MC4R without adverse effects. To date, this has not been achieved because of inter alia non-selective ligands across the five functionally different MCR subtypes (MC1-5R). This motivates further investigation of (i) the three-dimensional MC4R structure, (ii) binding mechanisms of various ligands, and (iii) the molecular transfer process of signal transduction, with the aim of understanding how structural features are linked with functional-physiological aspects. Unfortunately, experimentally elucidated structural information is not yet available for theMC receptors, a group of class A G-protein coupled receptors (GPCRs). We, therefore, generated MC4R homology models and complexes with interacting partners to describe approximate structural properties associated with signaling mechanisms. In addition, molecular insights from pathogenic mutations were incorporated to discriminate more precisely their individual malfunction of the signal transfer mechanism.

Glucocorticoids regulate fundamental processes of the human body and control cellular functions such as cell metabolism, growth, differentiation, and apoptosis. Moreover, endogenous glucocorticoids link the endocrine and immune system and ensure the correct function of inflammatory events during tissue repair, regeneration, and pathogen elimination via genomic and rapid non-genomic pathways. Due to their strong immunosuppressive, anti-inflammatory and anti-allergic effects on immune cells, tissues and organs, glucocorticoids significantly improve the quality of life of many patients suffering from diseases caused by a dysregulated immune system. Despite the multitude and seriousness of glucocorticoid-related adverse events including diabetes mellitus, osteoporosis and infections, these agents remain indispensable, representing the most powerful, and cost-effective drugs in the treatment of a wide range of rheumatic diseases. These include rheumatoid arthritis, vasculitis, and connective tissue diseases, as well as many other pathological conditions of the immune system. Depending on the therapeutically affected cell type, glucocorticoid actions strongly vary among different diseases. While immune responses always represent complex reactions involving different cells and cellular processes, specific immune cell populations with key responsibilities driving the pathological mechanisms can be identified for certain autoimmune diseases. In this review, we will focus on the mechanisms of action of glucocorticoids on various leukocyte populations, exemplarily portraying different autoimmune diseases as heterogeneous targets of glucocorticoid actions: (i) Abnormalities in the innate immune response play a crucial role in the initiation and perpetuation of giant cell arteritis (GCA). (ii) Specific types of CD4+ T helper (Th) lymphocytes, namely Th1 and Th17 cells, represent important players in the establishment and course of rheumatoid arthritis (RA), whereas (iii) B cells have emerged as central players in systemic lupus erythematosus (SLE). (iv) Allergic reactions are mainly triggered by several different cytokines released by activated Th2 lymphocytes. Using these examples, we aim to illustrate the versatile modulating effects of glucocorticoids on the immune system. In contrast, in the treatment of lymphoproliferative disorders the pro-apoptotic action of glucocorticoids prevails, but their mechanisms differ depending on the type of cancer. Therefore, we will also give a brief insight into the current knowledge of the mode of glucocorticoid action in oncological treatment focusing on leukemia.

Symptoms of schizophrenia (SCZ) are likely to be generated by genetically mediated synaptic dysfunction, which contribute to large-scale functional neural dysconnectivity. Recent electrophysiological studies suggest that this dysconnectivity is present not only at a spatial level but also at a temporal level, operationalized as long-range temporal correlations (LRTCs). Previous research suggests that alpha and beta frequency bands have weaker temporal stability in people with SCZ. This study sought to replicate these findings with high-density electroencephalography (EEG), enabling a spatially more accurate analysis of LRTC differences, and to test associations with characteristic SCZ symptoms and cognitive deficits. A 128-channel EEG was used to record eyes-open resting state brain activity of 23 people with SCZ and 24 matched healthy controls (HCs). LRTCs were derived for alpha (8–12 Hz) and beta (13–25 Hz) frequency bands. As an exploratory analysis, LRTC was source projected using sLoreta. People with SCZ showed an area of significantly reduced beta-band LRTC compared with HCs over bilateral posterior regions. There were no between-group differences in alpha-band activity. Individual symptoms of SCZ were not related to LRTC values nor were cognitive deficits. The study confirms that people with SCZ have reduced temporal stability in the beta frequency band. The absence of group differences in the alpha band may be attributed to the fact that people had, in contrast to previous studies, their eyes open in the current study. Taken together, our study confirms the utility of LRTC as a marker of network instability in people with SCZ and provides a novel empirical perspective for future examinations of network dysfunction salience in SCZ research.

The presence of snow and ice at midlatitudes of Mars cannot be explained by current climatic conditions, as surface ice is unstable. However, a large variety of debris‐covered glaciers have been observed at both midlatitudes. Here, we report the presence of local, small‐scale, and debris‐covered stagnant ice deposits on the floor of a valley system in Terra Cimmeria. These deposits, termed valley fill deposits (VFD), have a distribution that is restricted to the host valley floor and to the extent of the ejecta blanket associated with Tarq impact crater. The VFD are characterized by convex‐upward morphology, various crevasses, sublimation pits, an average area of a few square kilometers, and occasional ejecta streaks on their surface. Our model age estimation points to two possible time frames for the Tarq impact event; thus, we suggest two formation scenarios for VFD: (I) distribution of ice due to impact into shallow ice during the Middle Amazonian and (II) post‐impact deposition of VFD due to precipitation. In both scenarios, ice preservation is most likely due to a lag of dust and debris deposited in the valley's topographic lows. Scenario I is more consistent with our geomorphological observation of the VFD being overlain by ejecta streaks. Our results highlight the importance of local geological events and conditions in the distribution and preservation of buried ice deposits on Mars and suggest that more small‐scale and debris‐covered ice deposits may exist in the midlatitudes than previously thought. These deposits are of high importance for future human exploration missions to Mars.

Analysis of 984 induced microearthquakes from The Geysers geothermal reservoir in California reveals that the retrieved moment tensors depend on the frequency band of the inverted waveforms. The observed dependence is more significant for the percentages of the double‐couple, compensated linear vector dipole, and isotropic (ISO) components than for the focal mechanisms. The average root‐mean‐square of the moment tensors obtained in different frequency bands is correlated with spectra of ambient noise. The percentages of double‐couple and ISO components tend to decrease and increase with the upper cutoff frequency (fu), respectively. This suggests that shear rupture radiates energy preferentially in a lower frequency band and tensile rupture in a higher frequency band. Events displaying a strong increase of the ISO with fu are confined within the same depth interval as the injection points. This might be related to the strong thermoelastic effects in the vicinity of injection points that promote opening of small cracks adjacent to the main fractures.

An efficient water oxidation system is a prerequisite for developing solar energy conversion devices. Using advanced time-resolved spectroscopy, we study the initial catalytic relevant electron transfer events in the light-driven water oxidation system utilizing [Ru(bpy)3]2+ (bpy = 2,2′-bipyridine) as a light harvester, persulfate as a sacrificial electron acceptor, and a high-valent iron clathrochelate complex as a catalyst. Upon irradiation by visible light, the excited state of the ruthenium dye is quenched by persulfate to afford a [Ru(bpy)3]3+/SO4˙− pair, showing a cage escape yield up to 75%. This is followed by the subsequent fast hole transfer from [Ru(bpy)3]3+ to the FeIV catalyst to give the long-lived FeV intermediate in aqueous solution. In the presence of excess photosensitizer, this process exhibits pseudo-first order kinetics with respect to the catalyst with a rate constant of 3.2(1) × 1010 s−1. Consequently, efficient hole scavenging activity of the high-valent iron complex is proposed to explain its high catalytic performance for water oxidation.

Two computational studies provide different sentiment analyses for text segments (e.g., “fearful” passages) and figures (e.g., “Voldemort”) from the Harry Potter books (Rowling, 1997, 1998, 1999, 2000, 2003, 2005, 2007) based on a novel simple tool called SentiArt. The tool uses vector space models together with theory-guided, empirically validated label lists to compute the valence of each word in a text by locating its position in a 2d emotion potential space spanned by the words of the vector space model. After testing the tool's accuracy with empirical data from a neurocognitive poetics study, it was applied to compute emotional figure and personality profiles (inspired by the so-called “big five” personality theory) for main characters from the book series. The results of comparative analyses using different machine-learning classifiers (e.g., AdaBoost, Neural Net) show that SentiArt performs very well in predicting the emotion potential of text passages. It also produces plausible predictions regarding the emotional and personality profile of fiction characters which are correctly identified on the basis of eight character features, and it achieves a good cross-validation accuracy in classifying 100 figures into “good” vs. “bad” ones. The results are discussed with regard to potential applications of SentiArt in digital literary, applied reading and neurocognitive poetics studies such as the quantification of the hybrid hero potential of figures.

This study presents a comprehensive analysis of processes determining heat waves across different climates in Europe for the period 1979–2016. Heat waves are defined using a percentile‐based index and the main processes quantified along trajectories are adiabatic compression by subsidence and local and remote diabatic processes in the upper and lower troposphere. This Lagrangian analysis is complemented by an Eulerian calculation of horizontal temperature advection. During typical summers in Europe, one or two heat waves occur, with an average duration of five days. Whereas high near‐surface temperatures over Scandinavia are accompanied by omega‐like blocking structures at 500 hPa, heat waves over the Mediterranean are connected to comparably flat ridges. Tracing air masses backwards from the heat waves, we identify three trajectory clusters with coherent thermodynamic characteristics, vertical motions, and geographic origins. In all regions, horizontal temperature advection is almost negligible. In two of the three clusters, subsidence in the free atmosphere is very important in establishing high temperatures near the surface, while the air masses in the third cluster are warmed primarily due to diabatic heating near the surface. Large interregional differences occur between the British Isles and western Russia. Over the latter region, near‐surface transport and diabatic heating appear to be very important in determining the intensity of the heat waves, whereas subsidence and adiabatic warming are of first‐order importance for the British Isles. Although the large‐scale pattern is quasistationary during heat wave days, new air masses are entrained steadily into the lower troposphere during the life cycle of a heat wave. Overall, the results of the present study provide a guideline as to which processes and diagnostics weather and climate studies should focus on to understand the severity of heat waves.

Large bioacoustic archives of wild animals are an important source to identify reappearing communication patterns, which can then be related to recurring behavioral patterns to advance the current understanding of intra-specific communication of non-human animals. A main challenge remains that most large-scale bioacoustic archives contain only a small percentage of animal vocalizations and a large amount of environmental noise, which makes it extremely difficult to manually retrieve sufficient vocalizations for further analysis – particularly important for species with advanced social systems and complex vocalizations. In this study deep neural networks were trained on 11,509 killer whale (Orcinus orca) signals and 34,848 noise segments. The resulting toolkit ORCA-SPOT was tested on a large-scale bioacoustic repository – the Orchive – comprising roughly 19,000 hours of killer whale underwater recordings. An automated segmentation of the entire Orchive recordings (about 2.2 years) took approximately 8 days. It achieved a time-based precision or positive-predictive-value (PPV) of 93.2% and an area-under-the-curve (AUC) of 0.9523. This approach enables an automated annotation procedure of large bioacoustics databases to extract killer whale sounds, which are essential for subsequent identification of significant communication patterns. The code will be publicly available in October 2019 to support the application of deep learning to bioaoucstic research. ORCA-SPOT can be adapted to other animal species.

A sustainable economy fulfills societal needs in a fundamentally different way to the current economic system. Improvements to the efficiency of existing technologies or practices appear insufficient for achieving sustainable development within the planetary boundaries. Disruptive, systemic and transformational changes appear necessary in order to replace existing technologies and practices to establish a sustainable economy. Such innovations often start out in niches; however, the scaling up and the ultimate replacement of current socio-technical systems requires governance to allow for the coordination of actors, the reorganization of socio-technical systems and the mobilization and allocation of resources. As governmental institutions are part of the current (non-sustainable) systems and thereby fail to provide coherent, integrated and transformative governance, we explore whether institutional innovation from non-state actors can step in to provide governance of transformation processes. Based on explorative qualitative case studies of networks in the food sector, city planning and reporting tools, we analyze the potential of bottom-up institutional innovations to coordinate actors in transformation processes.

Staphylococcus aureus is a major human pathogen and has to cope with reactive oxygen and chlorine species (ROS, RCS) during infections. The low molecular weight thiol bacillithiol (BSH) is an important defense mechanism of S. aureus for detoxification of ROS and HOCl stress to maintain the reduced state of the cytoplasm. Under HOCl stress, BSH forms mixed disulfides with proteins, termed as S-bacillithiolations, which are reduced by bacilliredoxins (BrxA and BrxB). The NADPH-dependent flavin disulfide reductase YpdA is phylogenetically associated with the BSH synthesis and BrxA/B enzymes and was recently suggested to function as BSSB reductase (Mikheyeva et al., 2019). Here, we investigated the role of the complete bacilliredoxin BrxAB/BSH/YpdA pathway in S. aureus COL under oxidative stress and macrophage infection conditions in vivo and in biochemical assays in vitro. Using HPLC thiol metabolomics, a strongly enhanced BSSB level and a decreased BSH/BSSB ratio were measured in the S. aureus COL ypdA deletion mutant under control and NaOCl stress. Monitoring the oxidation degree (OxD) of the Brx-roGFP2 biosensor revealed that YpdA is required for regeneration of the reduced BSH redox potential (EBSH) upon recovery from oxidative stress. In addition, the ypdA mutant was impaired in H2O2 detoxification as measured with the novel H2O2-specific Tpx-roGFP2 biosensor. Phenotype analyses further showed that BrxA and YpdA are required for survival under NaOCl and H2O2 stress in vitro and inside murine J-774A.1 macrophages in infection assays in vivo. Finally, NADPH-coupled electron transfer assays provide evidence for the function of YpdA in BSSB reduction, which depends on the conserved Cys14 residue. YpdA acts together with BrxA and BSH in de-bacillithiolation of S-bacillithiolated GapDH. In conclusion, our results point to a major role of the BrxA/BSH/YpdA pathway in BSH redox homeostasis in S. aureus during recovery from oxidative stress and under infections.

To get a job as a seafarer in the global maritime industry, thousands of male Filipino youths work for free as ‘utility men’ for manning agencies that supply seafarers to ship operators around the world. Based on ethnographic fieldwork and approached from a moral economy perspective, this article examines how manning agencies and utility men differentially rationalize this exploitative work (utility manning). Manning agencies use it as a technology of servitude that, through physical and verbal abuse and other techniques, enforces docility to prepare utility men for the harsher conditions on-board a ship. In contrast, utility men use it as a technology of imagination, gleaning from it a capacity to shape their future. Faced with few social possibilities in the Philippines, they deploy servitude as a strategy for attaining economic mobility and male adulthood.

Contaminated honey is a common cause of grayanotoxin intoxication in humans. Intoxication of animals, especially cattle, is usually due to ingestion of plants of the Ericaceae family, such as Rhododendron. Here, we report the ingestion of Pieris japonica as the cause of grayanotoxin I intoxication in 2 miniature pigs that were kept as pets. The pigs showed sudden onset of pale oral mucosa, tachycardia, tachypnea, hypersalivation, tremor, and ataxia that progressed to lateral recumbency. The pathological examination of one pig revealed no specific indications for intoxication except for the finding of plant material of Pieris japonica in the intestine. Grayanotoxin I was identified in the ingested plant, gastric content, blood, liver, bile, kidney, urine, lung, and skeletal muscle via HPLC-MS/MS. Grayanotoxin I should be considered as a differential etiological diagnosis in pigs with unspecific signs and discovery of ingested plant material as the only indication in the pathologic examination.

Ever since Evo Morales Ayma became Bolivia's first indigenous president in 2006 and the promulgation of a human-rights-enhancing Constitution (2009) thereafter, indigenous peoples’ rights were gradually recognised. Yet, with the increasing demand for natural resources, indigenous communities have been adversely affected by the state's neo-extractivist policies. While global indigenous rights norms protect their fundamental rights, legal-implementation processes in the country's lowlands reveal dilemmas in terms of the value of laws in practice as well as its reinterpretation on the ground. Namely, in the communities, different positions and camps have emerged in terms of the role and functions of participatory rights. Despite the potential of the latter in strengthening collective-rights regimes and self-determination, community leaders, advisers and other members report how such processes fracture and weaken decision-making mechanisms and human rights claims.

We study the ion density, shear viscosity and electroosmotic mobility of an aqueous monovalent electrolyte at a charged solid surface using molecular dynamics simulations. Upon increasing the surface charge density, ions are displaced first from the diffuse layer to the outer Helmholtz layer, increasing its viscosity, and subsequently to the hydrodynamically stagnant inner Helmholtz layer. The ion redistribution causes both charge inversion and reversal of the electroosmotic mobility. Because of the surface-charge dependent interfacial hydrodynamic properties, however, the charge density of mobility reversal differs from the charge density of charge inversion, depending on the salt concentration and the chemical details of the ions and the surface. Mobility reversal cannot be described by an effective slip boundary condition alone – the spatial dependence of the viscosity is essential.

Two computational studies provide different sentiment analyses for text segments (e.g., ‘fearful’ passages) and figures (e.g., ‘Voldemort’) from the Harry Potter books (Rowling, 1997 - 2007) based on a novel simple tool called SentiArt. The tool uses vector space models together with theory-guided, empirically validated label lists to compute the valence of each word in a text by locating its position in a 2d emotion potential space spanned by the > 2 million words of the vector space model. After testing the tool’s accuracy with empirical data from a neurocognitive study, it was applied to compute emotional figure profiles and personality figure profiles (inspired by the so-called ‚big five’ personality theory) for main characters from the book series. The results of comparative analyses using different machine-learning classifiers (e.g., AdaBoost, Neural Net) show that SentiArt performs very well in predicting the emotion potential of text passages. It also produces plausible predictions regarding the emotional and personality profile of fiction characters which are correctly identified on the basis of eight character features, and it achieves a good cross-validation accuracy in classifying 100 figures into ‘good’ vs. ‘bad’ ones. The results are discussed with regard to potential applications of SentiArt in digital literary, applied reading and neurocognitive poetics studies such as the quantification of the hybrid hero potential of figures.

We analyzed how often and in what ways the Journal Impact Factor (JIF) is currently used in review, promotion, and tenure (RPT) documents of a representative sample of universities from the United States and Canada. 40% of research-intensive institutions and 18% of master’s institutions mentioned the JIF, or closely related terms. Of the institutions that mentioned the JIF, 87% supported its use in at least one of their RPT documents, 13% expressed caution about its use, and none heavily criticized it or prohibited its use. Furthermore, 63% of institutions that mentioned the JIF associated the metric with quality, 40% with impact, importance, or significance, and 20% with prestige, reputation, or status. We conclude that use of the JIF is encouraged in RPT evaluations, especially at research-intensive universities, and that there is work to be done to avoid the potential misuse of metrics like the JIF.

The ocean is key to understanding societal threats including climate change, sea level rise, ocean warming, tsunamis, and earthquakes. Because the ocean is difficult and costly to monitor, we lack fundamental data needed to adequately model, understand, and address these threats. One solution is to integrate sensors into future undersea telecommunications cables. This is the mission of the SMART subsea cables initiative (Science Monitoring And Reliable Telecommunications). SMART sensors would “piggyback” on the power and communications infrastructure of a million kilometers of undersea fiber optic cable and thousands of repeaters, creating the potential for seafloor-based global ocean observing at a modest incremental cost. Initial sensors would measure temperature, pressure, and seismic acceleration. The resulting data would address two critical scientific and societal issues: the long-term need for sustained climate-quality data from the under-sampled ocean (e.g., deep ocean temperature, sea level, and circulation), and the near-term need for improvements to global tsunami warning networks. A Joint Task Force (JTF) led by three UN agencies (ITU/WMO/UNESCO-IOC) is working to bring this initiative to fruition. This paper explores the ocean science and early warning improvements available from SMART cable data, and the societal, technological, and financial elements of realizing such a global network. Simulations show that deep ocean temperature and pressure measurements can improve estimates of ocean circulation and heat content, and cable-based pressure and seismic-acceleration sensors can improve tsunami warning times and earthquake parameters. The technology of integrating these sensors into fiber optic cables is discussed, addressing sea and land-based elements plus delivery of real-time open data products to end users. The science and business case for SMART cables is evaluated. SMART cables have been endorsed by major ocean science organizations, and JTF is working with cable suppliers and sponsors, multilateral development banks and end users to incorporate SMART capabilities into future cable projects. By investing now, we can build up a global ocean network of long-lived SMART cable sensors, creating a transformative addition to the Global Ocean Observing System.