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Manganese (Mn) is an essential micronutrient for development and function of the nervous system. Deficiencies in Mn transport have been implicated in the pathogenesis of Huntington's disease (HD), an autosomal dominant neurodegenerative disorder characterized by loss of medium spiny neurons of the striatum. Brain Mn levels are highest in striatum and other basal ganglia structures, the most sensitive brain regions to Mn neurotoxicity. Mouse models of HD exhibit decreased striatal Mn accumulation and HD striatal neuron models are resistant to Mn cytotoxicity. We hypothesized that the observed modulation of Mn cellular transport is associated with compensatory metabolic responses to HD pathology. Here we use an untargeted metabolomics approach by performing ultraperformance liquid chromatography-ion mobility-mass spectrometry (UPLC-IM-MS) on control and HD immortalized mouse striatal neurons to identify metabolic disruptions under three Mn exposure conditions, low (vehicle), moderate (non-cytotoxic) and high (cytotoxic). Our analysis revealed lower metabolite levels of pantothenic acid, and glutathione (GSH) in HD striatal cells relative to control cells. HD striatal cells also exhibited lower abundance and impaired induction of isobutyryl carnitine in response to increasing Mn exposure. In addition, we observed induction of metabolites in the pentose shunt pathway in HD striatal cells after high Mn exposure. These findings provide metabolic evidence of an interaction between the HD genotype and biologically relevant levels of Mn in a striatal cell model with known HD by Mn exposure interactions. The metabolic phenotypes detected support existing hypotheses that changes in energetic processes underlie the pathobiology of both HD and Mn neurotoxicity.
Experiments in research on memory, language, and in other areas of cognitive science are increasingly being analyzed using Bayesian methods. This has been facilitated by the development of probabilistic programming languages such as Stan, and easily accessible front-end packages such as brms. The utility of Bayesian methods, however, ultimately depends on the relevance of the Bayesian model, in particular whether or not it accurately captures the structure of the data and the data analyst's domain expertise. Even with powerful software, the analyst is responsible for verifying the utility of their model. To demonstrate this point, we introduce a principled Bayesian workflow (Betancourt, 2018) to cognitive science. Using a concrete working example, we describe basic questions one should ask about the model: prior predictive checks, computational faithfulness, model sensitivity, and posterior predictive checks. The running example for demonstrating the workflow is data on reading times with a linguistic manipulation of object versus subject relative clause sentences. This principled Bayesian workflow also demonstrates how to use domain knowledge to inform prior distributions. It provides guidelines and checks for valid data analysis, avoiding overfitting complex models to noise, and capturing relevant data structure in a probabilistic model. Given the increasing use of Bayesian methods, we aim to discuss how these methods can be properly employed to obtain robust answers to scientific questions.
Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe
(2020)
Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that similar to 75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least onethird of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes.
After the United Kingdom has left the European Union it remains unclear whether the two parties can successfully negotiate and sign a trade agreement within the transition period. Ongoing negotiations, practical obstacles and resulting uncertainties make it highly unlikely that economic actors would be fully prepared to a “no-trade-deal” situation. Here we provide an economic shock simulation of the immediate aftermath of such a post-Brexit no-trade-deal scenario by computing the time evolution of more than 1.8 million interactions between more than 6,600 economic actors in the global trade network. We find an abrupt decline in the number of goods produced in the UK and the EU. This sudden output reduction is caused by drops in demand as customers on the respective other side of the Channel incorporate the new trade restriction into their decision-making. As a response, producers reduce prices in order to stimulate demand elsewhere. In the short term consumers benefit from lower prices but production value decreases with potentially severe socio-economic consequences in the longer term.
Nonstationary coherence-incoherence patterns in nonlocally coupled heterogeneous phase oscillators
(2020)
We consider a large ring of nonlocally coupled phase oscillators and show that apart from stationary chimera states, this system also supports nonstationary coherence-incoherence patterns (CIPs). For identical oscillators, these CIPs behave as breathing chimera states and are found in a relatively small parameter region only. It turns out that the stability region of these states enlarges dramatically if a certain amount of spatially uniform heterogeneity (e.g., Lorentzian distribution of natural frequencies) is introduced in the system. In this case, nonstationary CIPs can be studied as stable quasiperiodic solutions of a corresponding mean-field equation, formally describing the infinite system limit. Carrying out direct numerical simulations of the mean-field equation, we find different types of nonstationary CIPs with pulsing and/or alternating chimera-like behavior. Moreover, we reveal a complex bifurcation scenario underlying the transformation of these CIPs into each other. These theoretical predictions are confirmed by numerical simulations of the original coupled oscillator system.
The current awareness of the high importance of urban green leads to a stronger need for tools to comprehensively represent urban green and its benefits. A common scientific approach is the development of urban ecosystem services (UES) based on remote sensing methods at the city or district level. Urban planning, however, requires fine-grained data that match local management practices. Hence, this study linked local biotope and tree mapping methods to the concept of ecosystem services. The methodology was tested in an inner-city district in SW Germany, comparing publicly accessible areas and non-accessible courtyards. The results provide area-specific [m(2)] information on the green inventory at the microscale, whereas derived stock and UES indicators form the basis for comparative analyses regarding climate adaptation and biodiversity. In the case study, there are ten times more micro-scale green spaces in private courtyards than in the public space, as well as twice as many trees. The approach transfers a scientific concept into municipal planning practice, enables the quantitative assessment of urban green at the microscale and illustrates the importance for green stock data in private areas to enhance decision support in urban development. Different aspects concerning data collection and data availability are critically discussed.
While previous research underscores the role of leaders in stimulating employee voice behaviour, comparatively little is known about what affects leaders' support for such constructive but potentially threatening employee behaviours. We introduce leader member exchange quality (LMX) as a central predictor of leaders' support for employees' ideas for constructive change. Apart from a general benefit of high LMX for leaders' idea support, we propose that high LMX is particularly critical to leaders' idea support if the idea voiced by an employee constitutes a power threat to the leader. We investigate leaders' attribution of prosocial and egoistic employee intentions as mediators of these effects. Hypotheses were tested in a quasi-experimental vignette study (N = 160), in which leaders evaluated a simulated employee idea, and a field study (N = 133), in which leaders evaluated an idea that had been voiced to them at work. Results show an indirect effect of LMX on leaders' idea support via attributed prosocial intentions but not via attributed egoistic intentions, and a buffering effect of high LMX on the negative effect of power threat on leaders' idea support. Results differed across studies with regard to the main effect of LMX on idea support.
The Sea-level Response to Ice Sheet Evolution (SeaRISE) effort explores the sensitivity of the current generation of ice sheet models to external forcing to gain insight into the potential future contribution to sea level from the Greenland and Antarctic ice sheets. All participating models simulated the ice sheet response to three types of external forcings: a change in oceanic condition, a warmer atmospheric environment, and enhanced basal lubrication. Here an analysis of the spatial response of the Greenland ice sheet is presented, and the impact of model physics and spin-up on the projections is explored. Although the modeled responses are not always homogeneous, consistent spatial trends emerge from the ensemble analysis, indicating distinct vulnerabilities of the Greenland ice sheet. There are clear response patterns associated with each forcing, and a similar mass loss at the full ice sheet scale will result in different mass losses at the regional scale, as well as distinct thickness changes over the ice sheet. All forcings lead to an increased mass loss for the coming centuries, with increased basal lubrication and warmer ocean conditions affecting mainly outlet glaciers, while the impacts of atmospheric forcings affect the whole ice sheet.
Neodymium isotopic composition (epsilon Nd) has enjoyed widespread use as a palaeotracer, principally because it behaves quasi-conservatively in the modern ocean. However, recent bottom water epsilon Nd reconstructions from the eastern North Atlantic are difficult to interpret under assumptions of conservative behaviour. The observation that this apparent departure from conservative behaviour increases with enhanced ice-rafted debris (IRD) fluxes has resulted in the suggestion that IRD leads to the overprinting of bottom water epsilon Nd through reversible scavenging. In this study, a simple water column model successfully reproduces epsilon Nd reconstructions from the eastern North Atlantic at the Last Glacial Maximum and Heinrich Stadial 1, and demonstrates that the changes in scavenging intensity required for good model-data fit is in good agreement with changes in the observed IRD flux. Although uncertainties in model parameters preclude a more definitive conclusion, the results indicate that the suggestion of IRD as a source of non-conservative behaviour in the epsilon Nd tracer is reasonable and that further research into the fundamental chemistry underlying the marine neodymium cycle is necessary to increase confidence in assumptions of conservative epsilon Nd behaviour in the past.
Paradoxical leadership behaviour (PLB) represents an emerging leadership construct that can help leaders deal with conflicting demands. In this paper, we report three studies that add to this nascent literature theoretically, methodologically, and empirically. In Study 1, we validate an effective short-form measure of global PLB using three different samples. In Studies 2 and 3, we draw on the job demands-resources model to propose that paradoxical leaders promote followers' work engagement by simultaneously fostering follower goal clarity and work autonomy. The results of survey data from Studies 2 and 3 largely confirm our model. Specifically, our findings show that PLB is positively associated with follower goal clarity and work autonomy, and that PLB exerts an indirect effect on work engagement via these variables. Moreover, our results support a hypothesized interaction effect of goal clarity and work autonomy to predict followers' work engagement, as well as a conditional indirect effect of PLB on work engagement via the interactive effect. We discuss the practical implications for leaders and organizations.
Practitioner points
To effectively engage followers in their work, leaders should create work environments in which followers know exactly what to do (i.e., have high goal clarity), but at the same time can determine on their own how to do their work (i.e., have high work autonomy)
To foster both goal clarity and work autonomy, leaders should combine communal (e.g., other-centred, flexibility-providing) and agentic aspects of leadership (e.g., maintaining decision control and enforcing performance standards).
HR departments should design leadership trainings that help leaders to combine seemingly opposing, yet ultimately synergistic behaviours.