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Jurisdiction
(2022)
BACKGROUND: The orbitofrontal cortex (OFC) is implicated in depression. The hypothesis investigated was whether the OFC sensitivity to reward and nonreward is related to the severity of depressive symptoms.
METHODS: Activations in the monetary incentive delay task were measured in the IMAGEN cohort at ages 14 years (n = 1877) and 19 years (n = 1140) with a longitudinal design. Clinically relevant subgroups were compared at ages 19 (high-severity group: n = 116; low-severity group: n = 206) and 14.
RESULTS: The medial OFC exhibited graded activation increases to reward, and the lateral OFC had graded activation increases to nonreward. In this general population, the medial and lateral OFC activations were associated with concurrent depressive symptoms at both ages 14 and 19 years. In a stratified high-severity depressive symptom group versus control group comparison, the lateral OFC showed greater sensitivity for the magnitudes of activations related to nonreward in the high-severity group at age 19 (p = .027), and the medial OFC showed decreased sensitivity to the reward magnitudes in the high-severity group at both ages 14 (p = .002) and 19 (p = .002). In a longitudinal design, there was greater sensitivity to nonreward of the lateral OFC at age 14 for those who exhibited high depressive symptom severity later at age 19 (p = .003).
CONCLUSIONS: Activations in the lateral OFC relate to sensitivity to not winning, were associated with high depressive symptom scores, and at age 14 predicted the depressive symptoms at ages 16 and 19. Activations in the medial OFC were related to sensitivity to winning, and reduced reward sensitivity was associated with concurrent high depressive symptom scores.
White mica and tourmaline are the dominant hydrothermal alteration minerals at the world-class Panasqueira W-Sn-Cu deposit in Portugal. Thus, understanding the controls on their chemical composition helps to constrain ore formation processes at this deposit and determine their usefulness as pathfinder minerals for mineralization in general. We combine whole-rock geochemistry of altered and unaltered metasedimentary host rocks with in situ LA-ICP-MS measurements of tourmaline and white mica from the alteration halo. Principal component analysis (PCA) is used to better identify geochemical patterns and trends of hydrothermal alteration in the datasets. The hydrothermally altered metasediments are enriched in As, Sn, Cs, Li, W, F, Cu, Rb, Zn, Tl, and Pb relative to unaltered samples. In situ mineral analyses show that most of these elements preferentially partition into white mica over tourmaline (Li, Rb, Cs, Tl, W, and Sn), whereas Zn is enriched in tourmaline. White mica has distinct compositions in different settings within the deposit (greisen, vein selvages, wall rock alteration zone, late fault zone), indicating a compositional evolution with time. In contrast, tourmaline from different settings overlaps in composition, which is ascribed to a stronger dependence on host rock composition and also to the effects of chemical zoning and microinclusions affecting the LA-ICP-MS analyses. Hence, in this deposit, white mica is the better recorder of the fluid composition. The calculated trace-element contents of the Panasqueira mineralizing fluid based on the mica data and estimates of mica-fluid partition coefficients are in good agreement with previous fluid-inclusion analyses. A compilation of mica and tourmaline trace-element compositions from Panasqueira and other W-Sn deposits shows that white mica has good potential as a pathfinder mineral, with characteristically high Li, Cs, Rb, Sn, and W contents. The trace-element contents of hydrothermal tourmaline are more variable. Nevertheless, the compiled data suggest that high Sn and Li contents are distinctive for tourmaline from W-Sn deposits.
In nature, plants are constantly exposed to many transient, but recurring, stresses. Thus, to complete their life cycles, plants require a dynamic balance between capacities to recover following cessation of stress and maintenance of stress memory. Recently, we uncovered a new functional role for macroautophagy/autophagy in regulating recovery from heat stress (HS) and resetting cellular memory of HS inArabidopsis thaliana. Here, we demonstrated that NBR1 (next to BRCA1 gene 1) plays a crucial role as a receptor for selective autophagy during recovery from HS. Immunoblot analysis and confocal microscopy revealed that levels of the NBR1 protein, NBR1-labeled puncta, and NBR1 activity are all higher during the HS recovery phase than before. Co-immunoprecipitation analysis of proteins interacting with NBR1 and comparative proteomic analysis of annbr1-null mutant and wild-type plants identified 58 proteins as potential novel targets of NBR1. Cellular, biochemical and functional genetic studies confirmed that NBR1 interacts with HSP90.1 (heat shock protein 90.1) and ROF1 (rotamase FKBP 1), a member of the FKBP family, and mediates their degradation by autophagy, which represses the response to HS by attenuating the expression ofHSPgenes regulated by the HSFA2 transcription factor. Accordingly, loss-of-function mutation ofNBR1resulted in a stronger HS memory phenotype. Together, our results provide new insights into the mechanistic principles by which autophagy regulates plant response to recurrent HS.
Alcohol use disorder (AUD) is the most common substance use disorder worldwide. Although dopamine-related findings were often observed in AUD, associated neurobiological mechanisms are still poorly understood. Therefore, in the present study, we investigate D2/3 receptor availability in healthy participants, participants at high risk (HR) to develop addiction (not diagnosed with AUD), and AUD patients in a detoxified stage, applying F-18-fallypride positron emission tomography (F-18-PET). Specifically, D2/3 receptor availability was investigated in (1) 19 low-risk (LR) controls, (2) 19 HR participants, and (3) 20 AUD patients after alcohol detoxification. Quality and severity of addiction were assessed with clinical questionnaires and (neuro)psychological tests. PET data were corrected for age of participants and smoking status. In the dorsal striatum, we observed significant reductions of D2/3 receptor availability in AUD patients compared with LR participants. Further, receptor availability in HR participants was observed to be intermediate between LR and AUD groups (linearly decreasing). Still, in direct comparison, no group difference was observed between LR and HR groups or between HR and AUD groups. Further, the score of the Alcohol Dependence Scale (ADS) was inversely correlated with D2/3 receptor availability in the combined sample. Thus, in line with a dimensional approach, striatal D2/3 receptor availability showed a linear decrease from LR participants to HR participants to AUD patients, which was paralleled by clinical measures. Our study shows that a core neurobiological feature in AUD seems to be detectable in an early, subclinical state, allowing more individualized alcohol prevention programs in the future.
Heteromeric HSFA2/HSFA3 complexes drive transcriptional memory after heat stress in Arabidopsis
(2021)
Adaptive plasticity in stress responses is a key element of plant survival strategies. For instance, moderate heat stress (HS) primes a plant to acquire thermotolerance, which allows subsequent survival of more severe HS conditions. Acquired thermotolerance is actively maintained over several days (HS memory) and involves the sustained induction of memory-related genes. Here we show that FORGETTER3/ HEAT SHOCK TRANSCRIPTION FACTOR A3 (FGT3/HSFA3) is specifically required for physiological HS memory and maintaining high memory-gene expression during the days following a HS exposure. HSFA3 mediates HS memory by direct transcriptional activation of memory-related genes after return to normal growth temperatures. HSFA3 binds HSFA2, and in vivo both proteins form heteromeric complexes with additional HSFs. Our results indicate that only complexes containing both HSFA2 and HSFA3 efficiently promote transcriptional memory by positively influencing histone H3 lysine 4 (H3K4) hyper-methylation. In summary, our work defines the major HSF complex controlling transcriptional memory and elucidates the in vivo dynamics of HSF complexes during somatic stress memory. Moderate heat stress primes plants to acquire tolerance to subsequent, more severe heat stress. Here the authors show that the HSFA3 transcription factor forms a heteromeric complex with HSFA2 to sustain activated transcription of genes required for acquired thermotolerance by promoting H3K4 hyper-methylation.
Based on suggested interactions of potential tipping elements in the Earth's climate and in ecological systems, tipping cascades as possible dynamics are increasingly discussed and studied. The activation of such tipping cascades would impose a considerable risk for human societies and biosphere integrity. However, there are ambiguities in the description of tipping cascades within the literature so far. Here we illustrate how different patterns of multiple tipping dynamics emerge from a very simple coupling of two previously studied idealized tipping elements. In particular, we distinguish between a two phase cascade, a domino cascade and a joint cascade. A mitigation of an unfolding two phase cascade may be possible and common early warning indicators are sensitive to upcoming critical transitions to a certain degree. In contrast, a domino cascade may hardly be stopped once initiated and critical slowing down-based indicators fail to indicate tipping of the following element. These different potentials for intervention and anticipation across the distinct patterns of multiple tipping dynamics should be seen as a call to be more precise in future analyses of cascading dynamics arising from tipping element interactions in the Earth system.
This paper studies cosmic-ray (CR) transport in magnetohydrodynamic (MHD) turbulence. CR transport is strongly dependent on the properties of the magnetic turbulence.
We perform test particle simulations to study the interactions of CR with both total MHD turbulence and decomposed MHD modes.
The spatial diffusion coefficients and the pitch angle scattering diffusion coefficients are calculated from the test particle trajectories in turbulence.
Our results confirm that the fast modes dominate the CR propagation, whereas Alfven and slow modes are much less efficient and have shown similar pitch-angle scattering rates.
We investigate the cross field transport on large and small scales. On large/global scales, normal diffusion is observed and the diffusion coefficient is suppressed by M-A(zeta) compared to the parallel diffusion coefficients, with zeta closer to 4 in Alfven modes than that in total turbulence, as theoretically expected.
For the CR transport on scales smaller than the turbulence injection scale, both the local and global magnetic reference frames are adopted. Superdiffusion is observed on such small scales in all the cases. Particularly, CR transport in Alfven modes show clear Richardson diffusion in the local reference frame. The diffusion transitions smoothly from the Richardson's one with index 1.5 to normal diffusion as the particle mean free path decreases from lambda(parallel to) >> L to lambda(parallel to) << L, where L is the injection/coherence length of turbulence.
Our results have broad applications to CRs in various astrophysical environments.
Successful conservation efforts have led to recent increases of large mammals such as European bison Bison bonasus, moose Alces alces and grey wolf Canis lupus and their return to former habitats in central Europe.
While embraced by some, the recovery of these species is a controversial topic and holds potential for human-wildlife conflicts.
Involving the public has been suggested to be an effective method for monitoring wildlife and mitigating associated conflicts.
To assess two interrelated prerequisites for engaging people in Citizen Science (CS)-knowledge of returning species and respondents' readiness to participate in CS activities for monitoring and managing these species-we conducted a survey (questionnaire) in two wildlife parks located in different states of Germany.
Based on 472 complete questionnaires, we developed generalized linear models to understand how sociodemographic variables and exposure to the species affected visitors' knowledge of each species, and to investigate if sociodemographic variables and knowledge influenced the likelihood of visitors to participate in CS activities.
Almost all visitors were aware of the returning wolf population, while knowledge and awareness about bison and moose were significantly lower.
Knowledge of the two herbivores differed geographically (higher knowledge of moose in the north-eastern state), possibly indicating a positive association between exposure to the species and knowledge.
However, models generally performed poorly in predicting knowledge about wildlife, suggesting that such specific knowledge is insufficiently explained by sociodemographic variables. Our model, which explained stated willingness in CS indicated that younger participants and those with higher knowledge scores in the survey were more willing to engage in CS activities.
Overall, our analyses highlight how exposure to large mammals, knowledge about wildlife and human demographics are interrelated-insights that are helpful for effectively recruiting citizen scientists for wildlife conservation.
Read the free Plain Language Summary for this article on the Journal blog.
Cirrus is the only cloud type capable of inducing daytime cooling or heating at the top of the atmosphere (TOA) and the sign of its radiative effect highly depends on its optical depth. However, the investigation of its geometrical and optical properties over the Arctic is limited. In this work the long-term properties of cirrus clouds are explored for the first time over an Arctic site (Ny-Alesund, Svalbard) using lidar and radiosonde measurements from 2011 to 2020. The optical properties were quality assured, taking into account the effects of specular reflections and multiple-scattering. Cirrus clouds were generally associated with colder and calmer wind conditions compared to the 2011-2020 climatology. However, the dependence of cirrus properties on temperature and wind speed was not strong. Even though the seasonal cycle was not pronounced, the winter-time cirrus appeared under lower temperatures and stronger wind conditions. Moreover, in winter, geometrically- and optically-thicker cirrus were found and their ice particles tended to be more spherical. The majority of cirrus was associated with westerly flow and westerly cirrus tended to be geometrically-thicker. Overall, optically-thinner layers tended to comprise smaller and less spherical ice crystals, most likely due to reduced water vapor deposition on the particle surface. Compared to lower latitudes, the cirrus layers over Ny-Alesund were more absorbing in the visible spectral region and they consisted of more spherical ice particles.
MALDI-TOF-MS-based identification of monoclonal murine Anti-SARS-CoV-2 antibodies within one hour
(2022)
During the SARS-CoV-2 pandemic, many virus-binding monoclonal antibodies have been developed for clinical and diagnostic purposes. This underlines the importance of antibodies as universal bioanalytical reagents. However, little attention is given to the reproducibility crisis that scientific studies are still facing to date. In a recent study, not even half of all research antibodies mentioned in publications could be identified at all. This should spark more efforts in the search for practical solutions for the traceability of antibodies. For this purpose, we used 35 monoclonal antibodies against SARS-CoV-2 to demonstrate how sequence-independent antibody identification can be achieved by simple means applied to the protein. First, we examined the intact and light chain masses of the antibodies relative to the reference material NIST-mAb 8671. Already half of the antibodies could be identified based solely on these two parameters. In addition, we developed two complementary peptide mass fingerprinting methods with MALDI-TOF-MS that can be performed in 60 min and had a combined sequence coverage of over 80%. One method is based on the partial acidic hydrolysis of the protein by 5 mM of sulfuric acid at 99 degrees C. Furthermore, we established a fast way for a tryptic digest without an alkylation step. We were able to show that the distinction of clones is possible simply by a brief visual comparison of the mass spectra. In this work, two clones originating from the same immunization gave the same fingerprints. Later, a hybridoma sequencing confirmed the sequence identity of these sister clones. In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0. This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.
Supergenes are nonrecombining genomic regions ensuring the coinheritance of multiple, coadapted genes. Despite the importance of supergenes in adaptation, little is known on how they originate. A classic example of supergene is the S locus controlling heterostyly, a floral heteromorphism occurring in 28 angiosperm families. In Primula, heterostyly is characterized by the cooccurrence of two complementary, self-incompatible floral morphs and is controlled by five genes clustered in the hemizygous, ca. 300-kb S locus. Here, we present the first chromosome-scale genome assembly of any heterostylous species, that of Primula veris (cowslip). By leveraging the high contiguity of the P. veris assembly and comparative genomic analyses, we demonstrated that the S-locus evolved via multiple, asynchronous gene duplications and independent gene translocations. Furthermore, we discovered a new whole-genome duplication in Ericales that is specific to the Primula lineage. We also propose a mechanism for the origin of S-locus hemizygosity via nonhomologous recombination involving the newly discovered two pairs of CFB genes flanking the S locus. Finally, we detected only weak signatures of degeneration in the S locus, as predicted for hemizygous supergenes. The present study provides a useful resource for future research addressing key questions on the evolution of supergenes in general and the S locus in particular: How do supergenes arise? What is the role of genome architecture in the evolution of complex adaptations? Is the molecular architecture of heterostyly supergenes across angiosperms similar to that of Primula?
N-of-1 trials are the gold standard study design to evaluate individual treatment effects and derive personalized treatment strategies. Digital tools have the potential to initiate a new era of N-of-1 trials in terms of scale and scope, but fully functional platforms are not yet available.
Here, we present the open source StudyU platform, which includes the StudyU Designer and StudyU app.
With the StudyU Designer, scientists are given a collaborative web application to digitally specify, publish, and conduct N-of-1 trials.
The StudyU app is a smartphone app with innovative user-centric elements for participants to partake in trials published through the StudyU Designer to assess the effects of different interventions on their health.
Thereby, the StudyU platform allows clinicians and researchers worldwide to easily design and conduct digital N-of-1 trials in a safe manner.
We envision that StudyU can change the landscape of personalized treatments both for patients and healthy individuals, democratize and personalize evidence generation for self-optimization and medicine, and can be integrated in clinical practice.
Complex networks are abundant in nature and many share an important structural property: they contain a few nodes that are abnormally highly connected (hubs). Some of these hubs are called influencers because they couple strongly to the network and play fundamental dynamical and structural roles. Strikingly, despite the abundance of networks with influencers, little is known about their response to stochastic forcing. Here, for oscillatory dynamics on influencer networks, we show that subjecting influencers to an optimal intensity of noise can result in enhanced network synchronization. This new network dynamical effect, which we call coherence resonance in influencer networks, emerges from a synergy between network structure and stochasticity and is highly nonlinear, vanishing when the noise is too weak or too strong. Our results reveal that the influencer backbone can sharply increase the dynamical response in complex systems of coupled oscillators. Influencer networks include a small set of highly-connected nodes and can reach synchrony only via strong node interaction. Tonjes et al. show that introducing an optimal amount of noise enhances synchronization of such networks, which may be relevant for neuroscience or opinion dynamics applications.
Ice-rich permafrost has been subject to abrupt thaw and thermokarst formation in the past and is vulnerable to current global warming. The ice-rich permafrost domain includes Yedoma sediments that have never thawed since deposition during the late Pleistocene and Alas sediments that were formed by previous thermokarst processes during the Lateglacial and Holocene warming. Permafrost thaw unlocks organic carbon (OC) and minerals from these deposits and exposes OC to mineralization. A portion of the OC can be associated with iron (Fe), a redox-sensitive element acting as a trap for OC. Post-depositional thaw processes may have induced changes in redox conditions in these deposits and thereby affected Fe distribution and interactions between OC and Fe, with knock-on effects on the role that Fe plays in mediating present day OC mineralization. To test this hypothesis, we measured Fe concentrations and proportion of Fe oxides and Fe complexed with OC in unthawed Yedoma and previously thawed Alas deposits. Total Fe concentrations were determined on 1,292 sediment samples from the Yedoma domain using portable X-ray fluorescence; these concentrations were corrected for trueness using a calibration based on a subset of 144 samples measured by inductively coupled plasma optical emission spectrometry after alkaline fusion (R (2) = 0.95). The total Fe concentration is stable with depth in Yedoma deposits, but we observe a depletion or accumulation of total Fe in Alas deposits, which experienced previous thaw and/or flooding events. Selective Fe extractions targeting reactive forms of Fe on unthawed and previously thawed deposits highlight that about 25% of the total Fe is present as reactive species, either as crystalline or amorphous oxides, or complexed with OC, with no significant difference in proportions of reactive Fe between Yedoma and Alas deposits. These results suggest that redox driven processes during past thermokarst formation impact the present-day distribution of total Fe, and thereby the total amount of reactive Fe in Alas versus Yedoma deposits. This study highlights that ongoing thermokarst lake formation and drainage dynamics in the Arctic influences reactive Fe distribution and thereby interactions between Fe and OC, OC mineralization rates, and greenhouse gas emissions.
How biased are our models?
(2021)
Geophysical process simulations play a crucial role in the understanding of the subsurface. This understanding is required to provide, for instance, clean energy sources such as geothermal energy. However, the calibration and validation of the physical models heavily rely on state measurements such as temperature. In this work, we demonstrate that focusing analyses purely on measurements introduces a high bias. This is illustrated through global sensitivity studies. The extensive exploration of the parameter space becomes feasible through the construction of suitable surrogate models via the reduced basis method, where the bias is found to result from very unequal data distribution. We propose schemes to compensate for parts of this bias. However, the bias cannot be entirely compensated. Therefore, we demonstrate the consequences of this bias with the example of a model calibration.
Urban air pollution is a substantial threat to human health. Traffic emissions remain a large contributor to air pollution in urban areas. The mobility restrictions put in place in response to the COVID-19 pandemic provided a large-scale real-world experiment that allows for the evaluation of changes in traffic emissions and the corresponding changes in air quality. Here we use observational data, as well as modelling, to analyse changes in nitrogen dioxide, ozone, and particulate matter resulting from the COVID-19 restrictions at the height of the lockdown period in Spring of 2020. Accounting for the influence of meteorology on air quality, we found that reduction of ca. 30-50 % in traffic counts, dominated by changes in passenger cars, corresponded to reductions in median observed nitrogen dioxide concentrations of ca. 40 % (traffic and urban background locations) and a ca. 22 % increase in ozone (urban background locations) during weekdays. Lesser reductions in nitrogen dioxide concentrations were observed at urban background stations at weekends, and no change in ozone was observed. The modelled reductions in median nitrogen dioxide at urban background locations were smaller than the observed reductions and the change was not significant. The model results showed no significant change in ozone on weekdays or weekends. The lack of a simulated weekday/weekend effect is consistent with previous work suggesting that NOx emissions from traffic could be significantly underestimated in European cities by models. These results indicate the potential for improvements in air quality due to policies for reducing traffic, along with the scale of reductions that would be needed to result in meaningful changes in air quality if a transition to sustainable mobility is to be seriously considered. They also confirm once more the highly relevant role of traffic for air quality in urban areas.
Design thinking is a well-established practical and educational approach to fostering high-level creativity and innovation, which has been refined since the 1950s with the participation of experts like Joy Paul Guilford and Abraham Maslow. Through real-world projects, trainees learn to optimize their creative outcomes by developing and practicing creative cognition and metacognition. This paper provides a holistic perspective on creativity, enabling the formulation of a comprehensive theoretical framework of creative metacognition. It focuses on the design thinking approach to creativity and explores the role of metacognition in four areas of creativity expertise: Products, Processes, People, and Places. The analysis includes task-outcome relationships (product metacognition), the monitoring of strategy effectiveness (process metacognition), an understanding of individual or group strengths and weaknesses (people metacognition), and an examination of the mutual impact between environments and creativity (place metacognition). It also reviews measures taken in design thinking education, including a distribution of cognition and metacognition, to support students in their development of creative mastery. On these grounds, we propose extended methods for measuring creative metacognition with the goal of enhancing comprehensive assessments of the phenomenon. Proposed methodological advancements include accuracy sub-scales, experimental tasks where examinees explore problem and solution spaces, combinations of naturalistic observations with capability testing, as well as physiological assessments as indirect measures of creative metacognition.
Case report
(2023)
The increasing prevalence of Long COVID is an imminent public health disaster, and established approaches have not provided adequate diagnostics or treatments. Recently, anesthetic blockade of the stellate ganglion was reported to improve Long COVID symptoms in a small case series, purportedly by "rebooting" the autonomic nervous system. Here, we present a novel diagnostic approach based on the Adaptive Force (AF), and report sustained positive outcome for one severely affected Long COVID patient using individualized pulsed electromagnetic field (PEMF) at the area C7/T1. AF reflects the capacity of the neuromuscular system to adapt adequately to external forces in an isometric holding manner. In case, maximal isometric AF (AFiso(max)) is exceeded, the muscle merges into eccentric muscle action. Thereby, the force usually increases further until maximal AF (AFmax) is reached. In case adaptation is optimal, AFiso(max) is similar to 99-100% of AFmax. This holding capacity (AFiso(max)) was found to be vulnerable to disruption by unpleasant stimulus and, hence, was regarded as functional parameter. AF was assessed by an objectified manual muscle test using a handheld device. Prior to treatment, AFiso(max) was considerably lower than AFmax for hip flexors (62 N = similar to 28% AFmax) and elbow flexors (71 N = similar to 44% AFmax); i.e., maximal holding capacity was significantly reduced, indicating dysfunctional motor control. We tested PEMF at C7/T1, identified a frequency that improved neuromuscular function, and applied it for similar to 15 min. Immediately post-treatment, AFiso(max) increased to similar to 210 N (similar to 100% AFmax) at hip and 184 N (similar to 100% AFmax) at elbow. Subjective Long COVID symptoms resolved the following day. At 4 weeks post-treatment, maximal holding capacity was still on a similarly high level as for immediately post-treatment (similar to 100% AFmax) and patient was symptom-free. At 6 months the patient's Long COVID symptoms have not returned. This case report suggests (1) AF could be a promising diagnostic for post-infectious illness, (2) AF can be used to test effective treatments for post-infectious illness, and (3) individualized PEMF may resolve post-infectious symptoms.
Alcohol intoxication is known to affect many aspects of human behavior and cognition; one of such affected systems is articulation during speech production. Although much research has revealed that alcohol negatively impacts pronunciation in a first language (L1), there is only initial evidence suggesting a potential beneficial effect of inebriation on articulation in a non-native language (L2). The aim of this study was thus to compare the effect of alcohol consumption on pronunciation in an L1 and an L2. Participants who had ingested different amounts of alcohol provided speech samples in their L1 (Dutch) and L2 (English), and native speakers of each language subsequently rated the pronunciation of these samples on their intelligibility (for the L1) and accent nativelikeness (for the L2). These data were analyzed with generalized additive mixed modeling. Participants' blood alcohol concentration indeed negatively affected pronunciation in L1, but it produced no significant effect on the L2 accent ratings. The expected negative impact of alcohol on L1 articulation can be explained by reduction in fine motor control. We present two hypotheses to account for the absence of any effects of intoxication on L2 pronunciation: (1) there may be a reduction in L1 interference on L2 speech due to decreased motor control or (2) alcohol may produce a differential effect on each of the two linguistic subsystems.
Objective:
Depression and coronary heart disease (CHD) are highly comorbid conditions. Brain-derived neurotrophic factor (BDNF) plays an important role in cardiovascular processes. Depressed patients typically show decreased BDNF concentrations. We analysed the relationship between BDNF and depression in a sample of patients with CHD and additionally distinguished between cognitive-affective and somatic depression symptoms. We also investigated whether BDNF was associated with somatic comorbidity burden, acute coronary syndrome (ACS) or congestive heart failure (CHF).
Methods:
The following variables were assessed for 225 hospitalised patients with CHD: BDNF concentrations, depression [Patient Health Questionnaire-9 (PHQ-9)], somatic comorbidity (Charlson Comorbidity Index), CHF, ACS, platelet count, smoking status and antidepressant treatment.
Results:
Regression models revealed that BDNF was not associated with severity of depression. Although depressed patients (PHQ-9 score >7) had significantly lower BDNF concentrations compared to non-depressed patients (p = 0.04), this was not statistically significant after controlling for confounders (p = 0.15). Cognitive-affective symptoms and somatic comorbidity burden each closely missed a statistically significant association with BDNF concentrations (p = 0.08, p = 0.06, respectively). BDNF was reduced in patients with CHF (p = 0.02). There was no covariate-adjusted, significant association between BDNF and ACS.
Conclusion:
Serum BDNF concentrations are associated with cardiovascular dysfunction. Somatic comorbidities should be considered when investigating the relationship between depression and BDNF.
Gender stereotypes influence subjective beliefs about the world, and this is reflected in our use of language. But do gender biases in language transparently reflect subjective beliefs? Or is the process of translating thought to language itself biased? During the 2016 United States (N = 24,863) and 2017 United Kingdom (N = 2,609) electoral campaigns, we compared participants' beliefs about the gender of the next head of government with their use and interpretation of pronouns referring to the next head of government. In the United States, even when the female candidate was expected to win, she pronouns were rarely produced and induced substantial comprehension disruption. In the United Kingdom, where the incumbent female candidate was heavily favored, she pronouns were preferred in production but yielded no comprehension advantage. These and other findings suggest that the language system itself is a source of implicit biases above and beyond previously known biases, such as those measured by the Implicit Association Test.
Due to their ability to capture attention, emotional stimuli tend to benefit from enhanced perceptual processing, which can be helpful when such stimuli are task-relevant but hindering when they are task-irrelevant. Altered emotion-attention interactions have been associated with symptoms of affective disturbances, and emerging research focuses on improving emotion-attention interactions to prevent or treat affective disorders. In line with the Human Affectome Project's emphasis on linguistic components, we also analyzed the language used to describe attention-related aspects of emotion, and highlighted terms related to domains such as conscious awareness, motivational effects of attention, social attention, and emotion regulation. These terms were discussed within a broader review of available evidence regarding the neural correlates of (1) Emotion-Attention Interactions in Perception, (2) Emotion-Attention Interactions in Learning and Memory, (3) Individual Differences in Emotion-Attention Interactions, and (4) Training and Interventions to Optimize Emotion-Attention Interactions. This comprehensive approach enabled an integrative overview of the current knowledge regarding the mechanisms of emotion-attention interactions at multiple levels of analysis, and identification of emerging directions for future investigations.
Cyanobacteria are important primary producers in temperate freshwater ecosystems. However, studies on the seasonal and spatial distribution of cyanobacteria in deep lakes based on high-throughput DNA sequencing are still rare. In this study, we combined monthly water sampling and monitoring in 2019, amplicon sequence variants analysis (ASVs; a proxy for different species) and quantitative PCR targeting overall cyanobacteria abundance to describe the seasonal and spatial dynamics of cyanobacteria in the deep hard-water oligo-mesotrophic Lake Tiefer See, NE Germany. We observed significant seasonal variation in the cyanobacterial community composition (p < 0.05) in the epi- and metalimnion layers, but not in the hypolimnion. In winter-when the water column is mixed-picocyanobacteria (Synechococcus and Cyanobium) were dominant. With the onset of stratification in late spring, we observed potential niche specialization and coexistence among the cyanobacteria taxa driven mainly by light and nutrient dynamics. Specifically, ASVs assigned to picocyanobacteria and the genus Planktothrix were the main contributors to the formation of deep chlorophyll maxima along a light gradient. While Synechococcus and different Cyanobium ASVs were abundant in the epilimnion up to the base of the euphotic zone from spring to fall, Planktothrix mainly occurred in the metalimnetic layer below the euphotic zone where also overall cyanobacteria abundance was highest in summer. Our data revealed two potentially psychrotolerant (cold-adapted) Cyanobium species that appear to cope well under conditions of lower hypolimnetic water temperature and light as well as increasing sediment-released phosphate in the deeper waters in summer. The potential cold-adapted Cyanobium species were also dominant throughout the water column in fall and winter. Furthermore, Snowella and Microcystis-related ASVs were abundant in the water column during the onset of fall turnover. Altogether, these findings suggest previously unascertained and considerable spatiotemporal changes in the community of cyanobacteria on the species level especially within the genus Cyanobium in deep hard-water temperate lakes.
Many animals form aggregations with individuals of the same species (single-species aggregations, SSA). Less frequently, individuals may also aggregate with individuals of other species (mixed-species aggregations, MSA). Although the benefits and costs of SSA have been intensively studied, the same is not true for MSA. Here, we first review the cases of MSA in harvestmen, an arachnid order in which the records of MSA are more frequent than other arthropod orders. We then propose several benefits and costs of MSA in harvestmen, and contrast them with those of SSA. Second, using field-gathered data we describe gregariousness in seven species of Prionostemma harvestmen from Costa Rica. These species form MSA, but individuals are also found solitarily or in SSA. We tested one possible benefit and one possible cost of gregariousness in Prionostemma harvestmen. Regarding the benefit, we hypothesized that individuals missing legs would be more exposed to predation than eight-legged individuals and thus they should be found preferentially in aggregations, where they would be more protected from predators. Our data, however, do not support this hypothesis. Regarding the cost, we hypothesized that gregariousness increases the chances of parasitism. We found no support for this hypothesis either because both mite prevalence and infestation intensity did not differ between solitary or aggregated individuals. Additionally, the type of aggregation (SSA or MSA) was not associated with the benefit or the cost we explored. This lack of effect may be explained by the fluid membership of the aggregations, as we found high turnover over time in the number of individuals and species composition of the aggregations. In conclusion, we hope our review and empirical data stimulate further studies on MSA, which remains one of the most elusive forms of group living in animals.
Do stereotypes strike twice?
(2019)
Stereotypes influence teachers' perception of and behaviour towards students, thus shaping students' learning opportunities. The present study investigated how 315 Australian pre-service teachers' stereotypes about giftedness and gender are related to their perception of students' intellectual ability, adjustment, and social-emotional ability, using an experimental vignette approach and controlling for social desirability in pre-service teachers' responses. Repeated-measures ANOVA showed that pre-service teachers associated giftedness with higher intellectual ability, but with less adjustment compared to average-ability students. Furthermore, pre-service teachers perceived male students as less socially and emotionally competent and less adjusted than female students. Additionally, pre-service teachers seemed to perceive female average-ability students' adjustment as most favourable compared to male average-ability students and gifted students. Findings point to discrepancies between actual characteristics of gifted female and male students and stereotypes in teachers' beliefs. Consequences of stereotyping and implications for teacher education are discussed.
Making sense of the world
(2020)
For human infants, the first years after birth are a period of intense exploration-getting to understand their own competencies in interaction with a complex physical and social environment. In contemporary neuroscience, the predictive-processing framework has been proposed as a general working principle of the human brain, the optimization of predictions about the consequences of one's own actions, and sensory inputs from the environment. However, the predictive-processing framework has rarely been applied to infancy research. We argue that a predictive-processing framework may provide a unifying perspective on several phenomena of infant development and learning that may seem unrelated at first sight. These phenomena include statistical learning principles, infants' motor and proprioceptive learning, and infants' basic understanding of their physical and social environment. We discuss how a predictive-processing perspective can advance the understanding of infants' early learning processes in theory, research, and application.
We are glad to introduce the Second Journal Club of Volume Five, Second Issue. This edition is focused on relevant studies published in the last few years in the field of resistance training, chosen by our Editorial Board members and their colleagues. We hope to stimulate your curiosity in this field and to share with you the passion for the sport, seen also from the scientific point of view. The Editorial Board members wish you an inspiring lecture.
Surface melting of the Greenland Ice Sheet contributes a large amount to current and future sea level rise. Increased surface melt may lower the reflectivity of the ice sheet surface and thereby increase melt rates: the so-called melt-albedo feedback describes this self-sustaining increase in surface melting. In order to test the effect of the melt-albedo feedback in a prognostic ice sheet model, we implement dEBM-simple, a simplified version of the diurnal Energy Balance Model dEBM, in the Parallel Ice Sheet Model (PISM). The implementation includes a simple representation of the melt-albedo feedback and can thereby replace the positive-degree-day melt scheme. Using PISM-dEBM-simple, we find that this feedback increases ice loss through surface warming by 60 % until 2300 for the high-emission scenario RCP8.5 when compared to a scenario in which the albedo remains constant at its present-day values. With an increase of 90 % compared to a fixed-albedo scenario, the effect is more pronounced for lower surface warming under RCP2.6. Furthermore, assuming an immediate darkening of the ice surface over all summer months, we estimate an upper bound for this effect to be 70 % in the RCP8.5 scenario and a more than 4-fold increase under RCP2.6. With dEBM-simple implemented in PISM, we find that the melt-albedo feedback is an essential contributor to mass loss in dynamic simulations of the Greenland Ice Sheet under future warming.
Knowing the source and runout of debris flows can help in planning strategies aimed at mitigating these hazards. Our research in this paper focuses on developing a novel approach for optimizing runout models for regional susceptibility modelling, with a case study in the upper Maipo River basin in the Andes of Santiago, Chile. We propose a two-stage optimization approach for automatically selecting parameters for estimating runout path and distance. This approach optimizes the random-walk and Perla et al.'s (PCM) two-parameter friction model components of the open-source Gravitational Process Path (GPP) modelling framework. To validate model performance, we assess the spatial transferability of the optimized runout model using spatial crossvalidation, including exploring the model's sensitivity to sample size. We also present diagnostic tools for visualizing uncertainties in parameter selection and model performance. Although there was considerable variation in optimal parameters for individual events, we found our runout modelling approach performed well at regional prediction of potential runout areas. We also found that although a relatively small sample size was sufficient to achieve generally good runout modelling performance, larger samples sizes (i.e. >= 80) had higher model performance and lower uncertainties for estimating runout distances at unknown locations. We anticipate that this automated approach using the open-source R software and the System for Automated Geoscientific Analyses geographic information system (SAGA-GIS) will make process-based debris-flow models more readily accessible and thus enable researchers and spatial planners to improve regional-scale hazard assessments.
Only the right noise?
(2020)
Seminal work by Werker and colleagues (Stager & Werker [1997]Nature, 388, 381-382) has found that 14-month-old infants do not show evidence for learning minimal pairs in the habituation-switch paradigm. However, when multiple speakers produce the minimal pair in acoustically variable ways, infants' performance improves in comparison to a single speaker condition (Rost & McMurray [2009]Developmental Science, 12, 339-349). The current study further extends these results and assesses how different kinds of input variability affect 14-month-olds' minimal pair learning in the habituation-switch paradigm testing German learning infants. The first two experiments investigated word learning when the labels were spoken by a single speaker versus when the labels were spoken by multiple speakers. In the third experiment we studied whether non-acoustic variability, implemented by visual variability of the objects presented together with the labels, would also affect minimal pair learning. We found enhanced learning in the multiple speakers compared to the single speaker condition, confirming previous findings with English-learning infants. In contrast, visual variability of the presented objects did not support learning. These findings both confirm and better delimit the beneficial role of speech-specific variability in minimal pair learning. Finally, we review different proposals on the mechanisms via which variability confers benefits to learning and outline what may be likely principles that underlie this benefit. We highlight among these the multiplicity of acoustic cues signalling phonemic contrasts and the presence of relations among these cues. It is in these relations where we trace part of the source for the apparent paradoxical benefit of variability in learning.
This study addresses the question of whether and how growing up with more than one language shapes a child's language impairment. Our focus is on Specific Language Impairment (SLI) in bilingual (Turkish-German) children. We specifically investigated a range of phenomena related to the so-called CP (Complementizer Phrase) in German, the hierarchically highest layer of syntactic clause structure, which has been argued to be particularly affected in children with SLI. Spontaneous speech data were examined from bilingual children with SLI in comparison to two comparison groups: (i) typically-developing bilingual children, (ii) monolingual children with SLI. We found that despite persistent difficulty with subject-verb agreement, the two groups of children with SLI did not show any impairment of the CP-domain. We conclude that while subject-verb agreement is a suitable linguistic marker of SLI in German-speaking children, for both monolingual and bilingual ones, 'vulnerability of the CP-domain' is not.
In his essay, Mel Ainscow looks at inclusion and equity from an international perspective and makes suggestions on how to develop inclusive education in a ‘whole-system approach’. After discussing different conceptions of inclusion and equity, he describes international policies which address them. From this international macro-level, Ainscow zooms in to the meso-level of the school and its immediate environment, defining dimensions to be considered for an inclusive school development. One of these dimensions is the ‘use of evidence’. In my comment, I want to focus on this dimension and discuss its scope and the potential to apply it in inclusive education development. As a first and important precondition, Ainscow explains that different circumstances lead to different linguistic uses of the term ‘inclusive education’. Thus, the term ‘inclusive education’ does not refer to an identical set of objectives across countries, and neither does the term ‘equity’.
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.
Objective:
Stunting (height-for-age < −2 SD) is one of the forms of undernutrition and is frequent among children of low- and middle-income countries. But stunting perSe is not a synonym of undernutrition. We investigated association between body height and indicators of energetic undernutrition at three critical thresholds for thinness used in public health: (1) BMI SDS < −2; (2) mid-upper arm circumference divided by height (MUAC (mm) × 10/height (cm) < 1·36) and (3) mean skinfold thickness (SF) < 7 mm and to question the reliability of thresholds as indicators of undernutrition.
Design:
Cross-sectional study; breakpoint analysis.
Setting:
Rural and urban regions of Indonesia and Guatemala – different socio-economic status (SES).
Participants:
1716 Indonesian children (6·0–13·2 years) and 3838 Guatemalan children (4·0–18·9 years) with up to 50 % stunted children.
Results:
When separating the regression of BMI, MUAC or SF, on height into distinguishable segments (breakpoint analysis), we failed to detect relevant associations between height, and BMI, MUAC or SF, even in the thinnest and shortest children. For BMI and SF, the breakpoint analysis either failed to reach statistical significance or distinguished at breakpoints above critical thresholds. For MUAC, the breakpoint analysis yielded negative associations between MUAC/h and height in thin individuals. Only in high SES Guatemalan children, SF and height appeared mildly associated with R2 = 0·017.
Conclusions:
Currently used lower thresholds of height-for-age (stunting) do not show relevant associations with anthropometric indicators of energetic undernutrition. We recommend using the catch-up growth spurt during early re-feeding instead as immediate and sensitive indicator of past undernourishment. We discuss the primacy of education and social-economic-political-emotional circumstances as responsible factors for stunting.
Forage availability has been suggested as one driver of the observed decline in honey bees. However, little is known about the effects of its spatiotemporal variation on colony success. We present a modeling framework for assessing honey bee colony viability in cropping systems. Based on two real farmland structures, we developed a landscape generator to design cropping systems varying in crop species identity, diversity, and relative abundance. The landscape scenarios generated were evaluated using the existing honey bee colony model BEEHAVE, which links foraging to in-hive dynamics. We thereby explored how different cropping systems determine spatiotemporal forage availability and, in turn, honey bee colony viability (e.g., time to extinction, TTE) and resilience (indicated by, e.g., brood mortality). To assess overall colony viability, we developed metrics,P(H)andP(P,)which quantified how much nectar and pollen provided by a cropping system per year was converted into a colony's adult worker population. Both crop species identity and diversity determined the temporal continuity in nectar and pollen supply and thus colony viability. Overall farmland structure and relative crop abundance were less important, but details mattered. For monocultures and for four-crop species systems composed of cereals, oilseed rape, maize, and sunflower,P(H)andP(P)were below the viability threshold. Such cropping systems showed frequent, badly timed, and prolonged forage gaps leading to detrimental cascading effects on life stages and in-hive work force, which critically reduced colony resilience. Four-crop systems composed of rye-grass-dandelion pasture, trefoil-grass pasture, sunflower, and phacelia ensured continuous nectar and pollen supply resulting in TTE > 5 yr, andP(H)(269.5 kg) andP(P)(108 kg) being above viability thresholds for 5 yr. Overall, trefoil-grass pasture, oilseed rape, buckwheat, and phacelia improved the temporal continuity in forage supply and colony's viability. Our results are hypothetical as they are obtained from simplified landscape settings, but they nevertheless match empirical observations, in particular the viability threshold. Our framework can be used to assess the effects of cropping systems on honey bee viability and to develop land-use strategies that help maintain pollination services by avoiding prolonged and badly timed forage gaps.
We present a chronology framework named LegacyAge 1.0 containing harmonized chronologies for 2831 pollen records (downloaded from the Neotoma Paleoecology Database and the supplementary Asian datasets) together with their age control points and metadata in machine-readable data formats.
All chronologies use the Bayesian framework implemented in Bacon version 2.5.3. Optimal parameter settings of priors (accumulation.shape, memory.strength, memory.mean, accumulation.rate, and thickness) were identified based on information in the original publication or iteratively after preliminary model inspection.
The most common control points for the chronologies are radiocarbon dates (86.1 %), calibrated by the latest calibration curves (IntCal20 and SHCal20 for the terrestrial radiocarbon dates in the Northern Hemisphere and Southern Hemisphere and Marine20 for marine materials).
The original publications were consulted when dealing with outliers and inconsistencies. Several major challenges when setting up the chronologies included the waterline issue (18.8% of records), reservoir effect (4.9 %), and sediment deposition discontinuity (4.4 %).
Finally, we numerically compare the LegacyAge 1.0 chronologies to those published in the original publications and show that the reliability of the chronologies of 95.4% of records could be improved according to our assessment.
Our chronology framework and revised chronologies provide the opportunity to make use of the ages and age uncertainties in synthesis studies of, for example, pollen-based vegetation and climate change.
The LegacyAge 1.0 dataset, including metadata, datings, harmonized chronologies, and R code used, is openaccess and available at PANGAEA (https://doi.org/10.1594/PANGAEA.933132; Li et al., 2021) and Zenodo (https://doi.org/10.5281/zenodo.5815192; Li et al., 2022), respectively.
Nils-Hendrik Grohmann beschäftigt sich mit dem noch andauernden Stärkungsprozess der UN-Menschenrechtsvertragsorgane. Er analysiert, welche rechtlichen Befugnisse die Ausschüsse haben, ob sie von sich aus Vorschläge einbringen können und inwieweit sie ihre Verfahrensweisen bisher aufeinander abgestimmt haben. Ein weiterer Schwerpunkt liegt auf der Zusammenarbeit zwischen den verschiedenen Ausschüssen und der Frage, welche Rolle das Treffen der Vorsitzenden bei der Stärkung spielen kann.
Predicting the electron population of Earth's ring current during geomagnetic storms still remains a challenging task.
In this work, we investigate the sensitivity of 10 keV ring current electrons to different driving processes, parameterised by the Kp index, during several moderate and intense storms.
Results are validated against measurements from the Van Allen Probes satellites. Perturbing the Kp index allows us to identify the most dominant processes for moderate and intense storms respectively.
We find that during moderate storms (Kp < 6) the drift velocities mostly control the behaviour of low energy electrons, while loss from wave-particle interactions is the most critical parameter for quantifying the evolution of intense storms (Kp > 6). Perturbations of the Kp index used to drive the boundary conditions at GEO and set the plasmapause location only show a minimal effect on simulation results over a limited L range.
It is further shown that the flux at L & SIM; 3 is more sensitive to changes in the Kp index compared to higher L shells, making it a good proxy for validating the source-loss balance of a ring current model.
Nils-Hendrik Grohmann beschäftigt sich mit dem noch andauernden Stärkungsprozess der UN-Menschenrechtsvertragsorgane. Er analysiert, welche rechtlichen Befugnisse die Ausschüsse haben, ob sie von sich aus Vorschläge einbringen können und inwieweit sie ihre Verfahrensweisen bisher aufeinander abgestimmt haben. Ein weiterer Schwerpunkt liegt auf der Zusammenarbeit zwischen den verschiedenen Ausschüssen und der Frage, welche Rolle das Treffen der Vorsitzenden bei der Stärkung spielen kann.
Drought and the availability of mineable phosphorus minerals used for fertilization are two of the important issues agriculture is facing in the future. High phosphorus availability in soils is necessary to maintain high agricultural yields. Drought is one of the major threats for terrestrial ecosystem performance and crop production in future. Among the measures proposed to cope with the upcoming challenges of intensifying drought stress and to decrease the need for phosphorus fertilizer application is the fertilization with silica (Si). Here we tested the importance of soil Si fertilization on wheat phosphorus concentration as well as wheat performance during drought at the field scale. Our data clearly showed a higher soil moisture for the Si fertilized plots. This higher soil moisture contributes to a better plant performance in terms of higher photosynthetic activity and later senescence as well as faster stomata responses ensuring higher productivity during drought periods. The plant phosphorus concentration was also higher in Si fertilized compared to control plots. Overall, Si fertilization or management of the soil Si pools seem to be a promising tool to maintain crop production under predicted longer and more serve droughts in the future and reduces phosphorus fertilizer requirements.
Identification of protein complexes from protein-protein interaction (PPI) networks is a key problem in PPI mining, solved by parameter-dependent approaches that suffer from small recall rates. Here we introduce GCC-v, a family of efficient, parameter-free algorithms to accurately predict protein complexes using the (weighted) clustering coefficient of proteins in PPI networks. Through comparative analyses with gold standards and PPI networks from Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens, we demonstrate that GCC-v outperforms twelve state-of-the-art approaches for identification of protein complexes with respect to twelve performance measures in at least 85.71% of scenarios. We also show that GCC-v results in the exact recovery of similar to 35% of protein complexes in a pan-plant PPI network and discover 144 new protein complexes in Arabidopsis thaliana, with high support from GO semantic similarity. Our results indicate that findings from GCC-v are robust to network perturbations, which has direct implications to assess the impact of the PPI network quality on the predicted protein complexes. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
Deliberative and paternalistic interaction styles for conversational agents in digital health
(2021)
Background:
Recent years have witnessed a constant increase in the number of people with chronic conditions requiring ongoing medical support in their everyday lives. However, global health systems are not adequately equipped for this extraordinarily time-consuming and cost-intensive development. Here, conversational agents (CAs) can offer easily scalable and ubiquitous support. Moreover, different aspects of CAs have not yet been sufficiently investigated to fully exploit their potential. One such trait is the interaction style between patients and CAs. In human-to-human settings, the interaction style is an imperative part of the interaction between patients and physicians. Patient-physician interaction is recognized as a critical success factor for patient satisfaction, treatment adherence, and subsequent treatment outcomes. However, so far, it remains effectively unknown how different interaction styles can be implemented into CA interactions and whether these styles are recognizable by users.
Objective:
The objective of this study was to develop an approach to reproducibly induce 2 specific interaction styles into CA-patient dialogs and subsequently test and validate them in a chronic health care context.
Methods:
On the basis of the Roter Interaction Analysis System and iterative evaluations by scientific experts and medical health care professionals, we identified 10 communication components that characterize the 2 developed interaction styles: deliberative and paternalistic interaction styles. These communication components were used to develop 2 CA variations, each representing one of the 2 interaction styles. We assessed them in a web-based between-subject experiment. The participants were asked to put themselves in the position of a patient with chronic obstructive pulmonary disease. These participants were randomly assigned to interact with one of the 2 CAs and subsequently asked to identify the respective interaction style. Chi-square test was used to assess the correct identification of the CA-patient interaction style.
Results:
A total of 88 individuals (42/88, 48% female; mean age 31.5 years, SD 10.1 years) fulfilled the inclusion criteria and participated in the web-based experiment. The participants in both the paternalistic and deliberative conditions correctly identified the underlying interaction styles of the CAs in more than 80% of the assessments (X-1(,8)8(2)=38.2; P<.001; phi coefficient r(phi)=0.68). The validation of the procedure was hence successful.
Conclusions:
We developed an approach that is tailored for a medical context to induce a paternalistic and deliberative interaction style into a written interaction between a patient and a CA. We successfully tested and validated the procedure in a web-based experiment involving 88 participants. Future research should implement and test this approach among actual patients with chronic diseases and compare the results in different medical conditions. This approach can further be used as a starting point to develop dynamic CAs that adapt their interaction styles to their users.
Pathogens and animal pests (P&A) are a major threat to global food security as they directly affect the quantity and quality of food. The Southern Amazon, Brazil's largest domestic region for soybean, maize and cotton production, is particularly vulnerable to the outbreak of P&A due to its (sub)tropical climate and intensive farming systems. However, little is known about the spatial distribution of P&A and the related yield losses. Machine learning approaches for the automated recognition of plant diseases can help to overcome this research gap. The main objectives of this study are to (1) evaluate the performance of Convolutional Neural Networks (ConvNets) in classifying P&A, (2) map the spatial distribution of P&A in the Southern Amazon, and (3) quantify perceived yield and economic losses for the main soybean and maize P&A. The objectives were addressed by making use of data collected with the smartphone application Plantix. The core of the app's functioning is the automated recognition of plant diseases via ConvNets. Data on expected yield losses were gathered through a short survey included in an "expert" version of the application, which was distributed among agronomists. Between 2016 and 2020, Plantix users collected approximately 78,000 georeferenced P&A images in the Southern Amazon. The study results indicate a high performance of the trained ConvNets in classifying 420 different crop-disease combinations. Spatial distribution maps and expert-based yield loss estimates indicate that maize rust, bacterial stalk rot and the fall armyworm are among the most severe maize P&A, whereas soybean is mainly affected by P&A like anthracnose, downy mildew, frogeye leaf spot, stink bugs and brown spot. Perceived soybean and maize yield losses amount to 12 and 16%, respectively, resulting in annual yield losses of approximately 3.75 million tonnes for each crop and economic losses of US$2 billion for both crops together. The high level of accuracy of the trained ConvNets, when paired with widespread use from following a citizen-science approach, results in a data source that will shed new light on yield loss estimates, e.g., for the analysis of yield gaps and the development of measures to minimise them.
Water bodies are a highly abundant feature of Arctic permafrost ecosystems and strongly influence their hydrology, ecology and biogeochemical cycling. While very high resolution satellite images enable detailed mapping of these water bodies, the increasing availability and abundance of this imagery calls for fast, reliable and automatized monitoring. This technical work presents a largely automated and scalable workflow that removes image noise, detects water bodies, removes potential misclassifications from infrastructural features, derives lake shoreline geometries and retrieves their movement rate and direction on the basis of ortho-ready very high resolution satellite imagery from Arctic permafrost lowlands. We applied this workflow to typical Arctic lake areas on the Alaska North Slope and achieved a successful and fast detection of water bodies. We derived representative values for shoreline movement rates ranging from 0.40-0.56 m yr(-1) for lake sizes of 0.10 ha-23.04 ha. The approach also gives an insight into seasonal water level changes. Based on an extensive quantification of error sources, we discuss how the results of the automated workflow can be further enhanced by incorporating additional information on weather conditions and image metadata and by improving the input database. The workflow is suitable for the seasonal to annual monitoring of lake changes on a sub-meter scale in the study areas in northern Alaska and can readily be scaled for application across larger regions within certain accuracy limitations.
The subsurface is a temporally dynamic and spatially heterogeneous compartment of the Earth's critical zone, and biogeochemical transformations taking place in this compartment are crucial for the cycling of nutrients.
The impact of spatial heterogeneity on such microbially mediated nutrient cycling is not well known, which imposes a severe challenge in the prediction of in situ biogeochemical transformation rates and further of nutrient loading contributed by the groundwater to the surface water bodies.
Therefore, we used a numerical modelling approach to evaluate the sensitivity of groundwater microbial biomass distribution and nutrient cycling to spatial heterogeneity in different scenarios accounting for various residence times.
The model results gave us an insight into domain characteristics with respect to the presence of oxic niches in predominantly anoxic zones and vice versa depending on the extent of spatial heterogeneity and the flow regime.
The obtained results show that microbial abundance, distribution, and activity are sensitive to the applied flow regime and that the mobile (i.e. observable by groundwater sampling) fraction of microbial biomass is a varying, yet only a small, fraction of the total biomass in a domain. Furthermore, spatial heterogeneity resulted in anaerobic niches in the domain and shifts in microbial biomass between active and inactive states. The lack of consideration of spatial heterogeneity, thus, can result in inaccurate estimation of microbial activity. In most cases this leads to an overestimation of nutrient removal (up to twice the actual amount) along a flow path.
We conclude that the governing factors for evaluating this are the residence time of solutes and the Damkohler number (Da) of the biogeochemical reactions in the domain. We propose a relationship to scale the impact of spatial heterogeneity on nutrient removal governed by the logioDa.
This relationship may be applied in upscaled descriptions of microbially mediated nutrient cycling dynamics in the subsurface thereby resulting in more accurate predictions of, for example, carbon and nitrogen cycling in groundwater over long periods at the catchment scale.
Changing climatic conditions and unsustainable land use are major threats to savannas worldwide. Historically, many African savannas were used intensively for livestock grazing, which contributed to widespread patterns of bush encroachment across savanna systems. To reverse bush encroachment, it has been proposed to change the cattle-dominated land use to one dominated by comparatively specialized browsers and usually native herbivores. However, the consequences for ecosystem properties and processes remain largely unclear. We used the ecohydrological, spatially explicit model EcoHyD to assess the impacts of two contrasting, herbivore land-use strategies on a Namibian savanna: grazer- versus browser-dominated herbivore communities. We varied the densities of grazers and browsers and determined the resulting composition and diversity of the plant community, total vegetation cover, soil moisture, and water use by plants. Our results showed that plant types that are less palatable to herbivores were best adapted to grazing or browsing animals in all simulated densities. Also, plant types that had a competitive advantage under limited water availability were among the dominant ones irrespective of land-use scenario. Overall, the results were in line with our expectations: under high grazer densities, we found heavy bush encroachment and the loss of the perennial grass matrix. Importantly, regardless of the density of browsers, grass cover and plant functional diversity were significantly higher in browsing scenarios. Browsing herbivores increased grass cover, and the higher total cover in turn improved water uptake by plants overall. We concluded that, in contrast to grazing-dominated land-use strategies, land-use strategies dominated by browsing herbivores, even at high herbivore densities, sustain diverse vegetation communities with high cover of perennial grasses, resulting in lower erosion risk and bolstering ecosystem services.
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
Studies have evaluated the effectiveness of dual career (DC) support services among student-athletes by examining scholastic performances.
These studies investigated self-reported grades student-athletes or focused on career choices student-athletes made after leaving school. Most of these studies examined scholastic performances cross-sectionally among lower secondary school student-athletes or student-athletes in higher education.
The present longitudinal field study in a quasi-experimental design aims to evaluate the development of scholastic performances among upper secondary school students aged 16-19 by using standardized scholastic assessments and grade points in the subject English over a course of 3-4 years.
A sample of 159 students (54.4% females) at three German Elite Sport Schools (ESS) and three comprehensive schools participated in the study. The sample was split into six groups according to three criteria: (1) students' athletic engagement, (2) school type attendance, and (3) usage of DC support services in secondary school.
Repeated-measurement analyses of variance were conducted in order to evaluate the impact of the three previously mentioned criteria as well as their interaction on the development of scholastic performances.
Findings indicated that the development of English performance levels differ among the six groups.
Current attempts to prevent and manage type 2 diabetes have been moderately effective, and a better understanding of the molecular roots of this complex disease is important to develop more successful and precise treatment options.
Recently, we initiated the collective diabetes cross, where four mouse inbred strains differing in their diabetes susceptibility were crossed with the obese and diabetes-prone NZO strain and identified the quantitative trait loci (QTL) Nidd13/NZO, a genomic region on chromosome 13 that correlates with hyperglycemia in NZO allele carriers compared to B6 controls.
Subsequent analysis of the critical region, harboring 644 genes, included expression studies in pancreatic islets of congenic Nidd13/NZO mice, integration of single-cell data from parental NZO and B6 islets as well as haplotype analysis.
Finally, of the five genes (Acot12, S100z, Ankrd55, Rnf180, and Iqgap2) within the polymorphic haplotype block that are differently expressed in islets of B6 compared to NZO mice, we identified the calcium-binding protein S100z gene to affect islet cell proliferation as well as apoptosis when overexpressed in MINE cells. In summary, we define S100z as the most striking gene to be causal for the diabetes QTL Nidd13/NZO by affecting beta-cell proliferation and apoptosis. Thus, S100z is an entirely novel diabetes gene regulating islet cell function.
Model uncertainty quantification is an essential component of effective data assimilation. Model errors associated with sub-grid scale processes are often represented through stochastic parameterizations of the unresolved process. Many existing Stochastic Parameterization schemes are only applicable when knowledge of the true sub-grid scale process or full observations of the coarse scale process are available, which is typically not the case in real applications. We present a methodology for estimating the statistics of sub-grid scale processes for the more realistic case that only partial observations of the coarse scale process are available. Model error realizations are estimated over a training period by minimizing their conditional sum of squared deviations given some informative covariates (e.g., state of the system), constrained by available observations and assuming that the observation errors are smaller than the model errors. From these realizations a conditional probability distribution of additive model errors given these covariates is obtained, allowing for complex non-Gaussian error structures. Random draws from this density are then used in actual ensemble data assimilation experiments. We demonstrate the efficacy of the approach through numerical experiments with the multi-scale Lorenz 96 system using both small and large time scale separations between slow (coarse scale) and fast (fine scale) variables. The resulting error estimates and forecasts obtained with this new method are superior to those from two existing methods.
The nature of the sources powering nebular He II emission in star-forming galaxies remains debated, and various types of objects have been considered, including Wolf-Rayet stars, X-ray binaries, and Population III stars.
Modern X-ray observations show the ubiquitous presence of hot gas filling star-forming galaxies. We use a collisional ionization plasma code to compute the specific He II ionizing flux produced by hot gas and show that if its temperature is not too high (less than or similar to 2.5 MK), then the observed levels of soft diffuse X-ray radiation could explain He II ionization in galaxies.
To gain a physical understanding of this result, we propose a model that combines the hydrodynamics of cluster winds and hot superbubbles with observed populations of young massive clusters in galaxies. We find that in low-metallicity galaxies, the temperature of hot gas is lower and the production rate of He II ionizing photons is higher compared to high-metallicity galaxies. The reason is that the slower stellar winds of massive stars in lower-metallicity galaxies input less mechanical energy in the ambient medium.
Furthermore, we show that ensembles of star clusters up to similar to 10-20 Myr old in galaxies can produce enough soft X-rays to induce nebular He II emission. We discuss observations of the template low-metallicity galaxy I Zw 18 and suggest that the He II nebula in this galaxy is powered by a hot superbubble.
Finally, appreciating the complex nature of stellar feedback, we suggest that soft X-rays from hot superbubbles are among the dominant sources of He II ionizing flux in low-metallicity star-forming galaxies.
Who has the future in mind?
(2022)
An individual's relation to time may be an important driver of pro-environmental behaviour. We studied whether young individual's gender and time-orientation are associated with pro-environmental behaviour. In a controlled laboratory environment with students in Germany, participants earned money by performing a real-effort task and were then offered the opportunity to invest their money into an environmental project that supports climate protection. Afterwards, we controlled for their time-orientation. In this consequential behavioural setting, we find that males who scored higher on future-negative orientation showed significantly more pro-environmental behaviour compared to females who scored higher on future-negative orientation and males who scored lower on future-negative orientation. Interestingly, our results are completely reversed when it comes to past-positive orientation. These findings have practical implications regarding the most appropriate way to address individuals in order to achieve more pro-environmental behaviour.
Enhancing economic efficiency in modular production systems through deep reinforcement learning
(2024)
In times of increasingly complex production processes and volatile customer demands, the production adaptability is crucial for a company's profitability and competitiveness. The ability to cope with rapidly changing customer requirements and unexpected internal and external events guarantees robust and efficient production processes, requiring a dedicated control concept at the shop floor level. Yet in today's practice, conventional control approaches remain in use, which may not keep up with the dynamic behaviour due to their scenario-specific and rigid properties. To address this challenge, deep learning methods were increasingly deployed due to their optimization and scalability properties. However, these approaches were often tested in specific operational applications and focused on technical performance indicators such as order tardiness or total throughput. In this paper, we propose a deep reinforcement learning based production control to optimize combined techno-financial performance measures. Based on pre-defined manufacturing modules that are supplied and operated by multiple agents, positive effects were observed in terms of increased revenue and reduced penalties due to lower throughput times and fewer delayed products. The combined modular and multi-staged approach as well as the distributed decision-making further leverage scalability and transferability to other scenarios.
Shape-memory hydrogels (SMH) are multifunctional, actively-moving polymers of interest in biomedicine. In loosely crosslinked polymer networks, gelatin chains may form triple helices, which can act as temporary net points in SMH, depending on the presence of salts. Here, we show programming and initiation of the shape-memory effect of such networks based on a thermomechanical process compatible with the physiological environment. The SMH were synthesized by reaction of glycidylmethacrylated gelatin with oligo(ethylene glycol) (OEG) alpha,omega-dithiols of varying crosslinker length and amount. Triple helicalization of gelatin chains is shown directly by wide-angle X-ray scattering and indirectly via the mechanical behavior at different temperatures. The ability to form triple helices increased with the molar mass of the crosslinker. Hydrogels had storage moduli of 0.27-23 kPa and Young's moduli of 215-360 kPa at 4 degrees C. The hydrogels were hydrolytically degradable, with full degradation to water-soluble products within one week at 37 degrees C and pH = 7.4. A thermally-induced shape-memory effect is demonstrated in bending as well as in compression tests, in which shape recovery with excellent shape-recovery rates R-r close to 100% were observed. In the future, the material presented here could be applied, e.g., as self-anchoring devices mechanically resembling the extracellular matrix.
Starting from the observation that the reduced state of a system strongly coupled to a bath is, in general, an athermal state, we introduce and study a cyclic battery-charger quantum device that is in thermal equilibrium, or in a ground state, during the charge storing stage. The cycle has four stages: the equilibrium storage stage is interrupted by disconnecting the battery from the charger, then work is extracted from the battery, and then the battery is reconnected with the charger; finally, the system is brought back to equilibrium. At no point during the cycle are the battery-charger correlations artificially erased. We study the case where the battery and charger together comprise a spin-1/2 Ising chain, and show that the main characteristics-the extracted energy and the thermodynamic efficiency-can be enhanced by operating the cycle close to the quantum phase transition point. When the battery is just a single spin, we find that the output work and efficiency show a scaling behavior at criticality and derive the corresponding critical exponents. Due to always present correlations between the battery and the charger, operations that are equivalent from the perspective of the battery can entail different energetic costs for switching the battery-charger coupling. This happens only when the coupling term does not commute with the battery's bare Hamiltonian, and we use this purely quantum leverage to further optimize the performance of the device.
Charitable giving
(2023)
We investigate how different levels of information influence the allocation decisions of donors who are entitled to freely distribute a fixed monetary endowment between themselves and a charitable organization in both giving and taking frames. Participants donate significantly higher amounts, when the decision is described as taking rather than giving. This framing effect becomes smaller if more information about the charity is provided.
Scaling agriculture to the globally rising population demands new approaches for future crop production such as multilayer and multitrophic indoor farming. Moreover, there is a current trend towards sustainable local solutions for aquaculture and saline agriculture. In this context, halophytes are becoming increasingly important for research and the food industry. As Salicornia europaea is a highly salt-tolerant obligate halophyte that can be used as a food crop, indoor cultivation with saline water is of particular interest. Therefore, finding a sustainable alternative to the use of seawater in non-coastal regions is crucial. Our goal was to determine whether natural brines, which are widely distributed and often available in inland areas, provide an alternative water source for the cultivation of saline organisms. This case study investigated the potential use of natural brines for the production of S. europaea. In the control group, which reflects the optimal growth conditions, fresh weight was increased, but there was no significant difference between the treatment groups comparing natural brines with artificial sea water. A similar pattern was observed for carotenoids and chlorophylls. Individual components showed significant differences. However, within treatments, there were mostly no changes. In summary, we showed that the influence of the different chloride concentrations was higher than the salt composition. Moreover, nutrient-enriched natural brine was demonstrated to be a suitable alternative for cultivation of S. europaea in terms of yield and nutritional quality. Thus, the present study provides the first evidence for the future potential of natural brine waters for the further development of aquaculture systems and saline agriculture in inland regions.
Sarcopenic obesity is increasingly found in youth, but its health consequences remain unclear.
Therefore, we studied the prevalence of sarcopenia and its association with cardiometabolic risk factors as well as muscular and cardiorespiratory fitness using data from the German Children's Health InterventionaL Trial (CHILT III) programme.
In addition to anthropometric data and blood pressure, muscle and fat mass were determined with bioelectrical impedance analysis.
Sarcopenia was classified via muscle-to-fat ratio. A fasting blood sample was taken, muscular fitness was determined using the standing long jump, and cardiorespiratory fitness was determined using bicycle ergometry. Of the 119 obese participants included in the analysis (47.1% female, mean age 12.2 years), 83 (69.7%) had sarcopenia. Affected individuals had higher gamma-glutamyl transferase, higher glutamate pyruvate transaminase, higher high-sensitivity C-reactive protein, higher diastolic blood pressure, and lower muscular and cardiorespiratory fitness (each p < 0.05) compared to participants who were 'only' obese.
No differences were found in other parameters. In our study, sarcopenic obesity was associated with various disorders in children and adolescents.
However, the clinical value must be tested with larger samples and reference populations to develop a unique definition and appropriate methods in terms of identification but also related preventive or therapeutic approaches.
Nocardioides alcanivorans sp. nov., a novel hexadecane-degrading species isolated from plastic waste
(2022)
Strain NGK65(T), a novel hexadecane degrading, non-motile, Gram-positive, rod-to-coccus shaped, aerobic bacterium, was isolated from plastic polluted soil sampled at a landfill.
Strain NGK65(T) hydrolysed casein, gelatin, urea and was catalase-positive. It optimally grew at 28 degrees C. in 0-1% NaCl and at pH 7.5-8.0. Glycerol, D-glucose, arbutin, aesculin, salicin, potassium 5-ketogluconate. sucrose, acetate, pyruvate and hexadecane were used as sole carbon sources.
The predominant membrane fatty acids were iso-C-16:0 followed by iso-C(17:)0 and C-18:1 omega 9c. The major polar lipids were phosphatidylglycerol, phosphatidylethanolamine, phosphatidylinositol and hydroxyphosphatidylinositol.
The cell-wall peptidoglycan type was A3 gamma, with LL-diaminopimelic acid and glycine as the diagnostic amino acids. MK 8 (H-4) was the predominant menaquinone. Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain NGK65(T) belongs to the genus Nocardioides (phylum Actinobacteria). appearing most closely related to Nocardioides daejeonensis MJ31(T) (98.6%) and Nocardioides dubius KSL-104(T) (98.3%).
The genomic DNA G+C content of strain NGK65(T) was 68.2%.
Strain NGK65(T) and the type strains of species involved in the analysis had average nucleotide identity values of 78.3-71.9% as well as digital DNA-DNA hybridization values between 22.5 and 19.7%, which clearly indicated that the isolate represents a novel species within the genus Nocardioides.
Based on phenotypic and molecular characterization, strain NGK65(T) can clearly be differentiated from its phylogenetic neighbours to establish a novel species, for which the name Nocardioides alcanivorans sp. nov. is proposed.
The type strain is NGK65(T) (=DSM 113112(T)=NCCB 100846(T)).
In the present paper we empirically investigate the psychometric properties of some of the most famous statistical and logical cognitive illusions from the "heuristics and biases" research program by Daniel Kahneman and Amos Tversky, who nearly 50 years ago introduced fascinating brain teasers such as the famous Linda problem, the Wason card selection task, and so-called Bayesian reasoning problems (e.g., the mammography task). In the meantime, a great number of articles has been published that empirically examine single cognitive illusions, theoretically explaining people's faulty thinking, or proposing and experimentally implementing measures to foster insight and to make these problems accessible to the human mind. Yet these problems have thus far usually been empirically analyzed on an individual-item level only (e.g., by experimentally comparing participants' performance on various versions of one of these problems). In this paper, by contrast, we examine these illusions as a group and look at the ability to solve them as a psychological construct. Based on an sample of N = 2,643 Luxembourgian school students of age 16-18 we investigate the internal psychometric structure of these illusions (i.e., Are they substantially correlated? Do they form a reflexive or a formative construct?), their connection to related constructs (e.g., Are they distinguishable from intelligence or mathematical competence in a confirmatory factor analysis?), and the question of which of a person's abilities can predict the correct solution of these brain teasers (by means of a regression analysis).
We and AI
(2021)
Many phenomena of high relevance for economic development such as human capital, geography and climate vary considerably within countries as well as between them. Yet, global data sets of economic output are typically available at the national level only, thereby limiting the accuracy and precision of insights gained through empirical analyses. Recent work has used interpolation and downscaling to yield estimates of sub-national economic output at a global scale, but respective data sets based on official, reported values only are lacking. We here present DOSE — the MCC-PIK Database Of Sub-national Economic Output. DOSE contains harmonised data on reported economic output from 1,661 sub-national regions across 83 countries from 1960 to 2020. To avoid interpolation, values are assembled from numerous statistical agencies, yearbooks and the literature and harmonised for both aggregate and sectoral output. Moreover, we provide temporally- and spatially-consistent data for regional boundaries, enabling matching with geo-spatial data such as climate observations. DOSE provides the opportunity for detailed analyses of economic development at the subnational level, consistent with reported values.
Although the literature on the determinants of training has considered individual and firm-related characteristics, it has generally neglected regional factors. This is surprising, given the fact that labour markets differ by regions. Regional factors are often ignored because (both in Germany and abroad) many data sets covering training information do not include detailed geographical identifiers that would allow a merging of information on the regional level. The regional identifiers of the National Educational Panel Study (Starting Cohort 6) offer opportunities to advance research on several regional factors. This article summarizes the results from two studies that exploit these unique opportunities to investigate the relationship between training participation and (a) the local level of firm competition for workers within specific sectors of the economy and (b) the regional supply of training measured as the number of firms offering courses or seminars for potential training participants.
Atwood analyzes the effects of the 1963 U.S. measles vaccination on long-run labor market outcomes, using a generalized difference-in-differences approach. We reproduce the results of this paper and perform a battery of robustness checks. Overall, we confirm that the measles vaccination had positive labor market effects. While the negative effect on the likelihood of living in poverty and the positive effect on the probability of being employed are very robust across the different specifications, the headline estimate—the effect on earnings—is more sensitive to the exclusion of certain regions and survey years.
This study is dedicated to the interdependencies between digital sovereignty and sustainable digitalization, which need to be explicitly linked to an increasing degree in political discourse, academia, and societal debates. Digital skills are the prerequisites for shaping digitalization in the interest of society and sustainable development.
The fluxes of water and solutes in the subsurface compartment of the Critical Zone are temporally dynamic and it is unclear how this impacts microbial mediated nutrient cycling in the spatially heterogeneous subsurface. To investigate this, we undertook numerical modeling, simulating the transport in a wide range of spatially heterogeneous domains, and the biogeochemical transformation of organic carbon and nitrogen compounds using a complex microbial community with four (4) distinct functional groups, in water saturated subsurface compartments. We performed a comprehensive uncertainty analysis accounting for varying residence times and spatial heterogeneity. While the aggregated removal of chemical species in the domains over the entire simulation period was approximately the same as that in steady state conditions, the sub-scale temporal variation of microbial biomass and chemical discharge from a domain depended strongly on the interplay of spatial heterogeneity and temporal dynamics of the forcing. We showed that the travel time and the Damkohler number (Da) can be used to predict the temporally varying chemical discharge from a spatially heterogeneous domain. In homogeneous domains, chemical discharge in temporally dynamic conditions could be double of that in the steady state conditions while microbial biomass varied up to 75% of that in steady state conditions. In heterogeneous domains, the interquartile range of uncertainty in chemical discharge in reaction dominated systems (log(10)Da > 0) was double of that in steady state conditions. However, high heterogeneous domains resulted in outliers where chemical discharge could be as high as 10-20 times of that in steady state conditions in high flow periods. And in transport dominated systems (log(10)Da < 0), the chemical discharge could be half of that in steady state conditions in unusually low flow conditions. In conclusion, ignoring spatio-temporal heterogeneities in a numerical modeling approach may exacerbate inaccurate estimation of nutrient export and microbial biomass. The results are relevant to long-term field monitoring studies, and for homogeneous soil column-scale experiments investigating the role of temporal dynamics on microbial redox dynamics.
The Influence of acute sprint interval training on cognitive performance of healthy younger adults
(2022)
There is considerable evidence showing that an acute bout of physical exercises can improve cognitive performance, but the optimal exercise characteristics (e.g., exercise type and exercise intensity) remain elusive. In this regard, there is a gap in the literature to which extent sprint interval training (SIT) can enhance cognitive performance. Thus, this study aimed to investigate the effect of a time-efficient SIT, termed as "shortened-sprint reduced-exertion high-intensity interval training" (SSREHIT), on cognitive performance. Nineteen healthy adults aged 20-28 years were enrolled and assessed for attentional performance (via the d2 test), working memory performance (via Digit Span Forward/Backward), and peripheral blood lactate concentration immediately before and 10 min after an SSREHIT and a cognitive engagement control condition (i.e., reading). We observed that SSREHIT can enhance specific aspects of attentional performance, as it improved the percent error rate (F%) in the d-2 test (t (18) = -2.249, p = 0.037, d = -0.516), which constitutes a qualitative measure of precision and thoroughness. However, SSREHIT did not change other measures of attentional or working memory performance. In addition, we observed that the exercise-induced increase in the peripheral blood lactate levels correlated with changes in attentional performance, i.e., the total number of responses (GZ) (r(m) = 0.70, p < 0.001), objective measures of concentration (SKL) (r(m) = 0.73, p < 0.001), and F% (r(m) = -0.54, p = 0.015). The present study provides initial evidence that a single bout of SSREHIT can improve specific aspects of attentional performance and conforming evidence for a positive link between cognitive improvements and changes in peripheral blood lactate levels.
Understanding the key factors influencing the water quality of large river systems forms an important basis for the assessment and protection of cross-regional ecosystems and the implementation of adapted water management concepts. However, identifying these factors requires in-depth comprehension of the unique environmental systems, which can only be achieved by detailed water quality monitoring.
Within the scope of the joint science and sports event "Elbschwimmstaffel" (swimming relay on the river Elbe) in June/July 2017 organized by the German Ministry of Education and Research, water quality data were acquired along a 550 km long stretch of the Elbe River in Germany. During the survey, eight physiochemical water quality parameters were recorded in high spatial and temporal resolution with the BIOFISH multisensor system. Multivariate statistical methods were applied to identify and delineate processes influencing the water quality.
The BIOFISH dataset revealed that phytoplankton activity has a major impact on the water quality of the Elbe River in the summer months. The results suggest that phytoplankton biomass constitutes a substantial proportion of the suspended particles and that photosynthetic activity of phytoplankton is closely related to significant temporal changes in pH and oxygen saturation.
An evaluation of the BIOFISH data based on the combination of statistical analysis with weather and discharge data shows that the hydrological and meteorological history of the sampled water body was the main driver of phytoplankton dynamics. This study demonstrates the capacity of longitudinal river surveys with the BIOFISH or similar systems for water quality assessment, the identification of pollution sources and their utilization for online in situ monitoring of rivers.
Basal ice-shelf melting is the key driver of Antarctica's increasing sea-level contribution. In diminishing the buttressing force of the ice shelves that fringe the ice sheet, the melting increases the ice discharge into the ocean.
Here we contrast the influence of basal melting in two different ice-shelf regions on the time-dependent response of an isothermal, inherently buttressed ice-sheet-shelf system. In the idealized numerical simulations, the basal-melt perturbations are applied close to the grounding line in the ice-shelf's (1) ice-stream region, where the ice shelf is fed by the fastest ice masses that stream through the upstream bed trough and (2) shear margins, where the ice flow is slower.
The results show that melting below one or both of the shear margins can cause a decadal to centennial increase in ice discharge that is more than twice as large compared to a similar perturbation in the ice-stream region. We attribute this to the fact that melt-induced ice-shelf thinning in the central grounding-line region is attenuated very effectively by the fast flow of the central ice stream. In contrast, the much slower ice dynamics in the lateral shear margins of the ice shelf facilitate sustained ice-shelf thinning and thereby foster buttressing reduction.
Regardless of the melt location, a higher melt concentration toward the grounding line generally goes along with a stronger response. Our results highlight the vulnerability of outlet glaciers to basal melting in stagnant, buttressing-relevant ice-shelf regions, a mechanism that may gain importance under future global warming.
We welcome you to the 53rd Hawaii International Conference on System Sciences (HICSS) conference. After joining with Intentional Forgetting Minitrack last year, this is the fourth year of the Organizational Learning Minitrack. We add Unlearning, and Intentional Forgetting to proudly bring you the latest research focused on organizational learning issues within the Knowledge Innovation and Entrepreneurial Systems Track. The ability to update, change and use current knowledge effectively, especially in light of the ongoing knowledge explosion, can be costly for any organization. Organizations that consider themselves “learning” or “knowledge-based” organizations must develop a competent workforce using KM strategies. Success in organizations involves developing a variety of human factors for changing competencies. With technological change, modification and revisions, many skills require updating for a competitive advantage in the marketplace. The focus on new techniques and insights into how individuals and organizations use their knowledge is our focus for the improvement of organizational learning in this Minitrack.
We welcome you to the 54th Hawaii International Conference on System Sciences (HICSS-54) conference. This is the fifth year for the Organizational Learning Minitrack which has had the usual growing pains: two years ago, we added the topic of Unlearning and joined with the Intentional Forgetting Minitrack - as these topics are all organizationally-based knowledge management issues. We proudly bring you the latest research focused on the methods to develop and maintain organizational learning within the Knowledge Innovation and Entrepreneurial Systems Track. The ability to update, change and use current knowledge effectively, especially in light of the ongoing knowledge explosion, can be costly for any organization. Organizations that consider themselves “learning” or “knowledge-based” organizations must develop a competent workforce using KM strategies. Success in organizations involves developing a variety of human factors for changing competencies. With technological change, modification and revisions, many skills require updating for a competitive advantage in the marketplace. The focus on new techniques and insights into how individuals and organizations use their knowledge is our focus for the improvement of organizational
learning in this Minitrack.
Omics and male infertility
(2022)
Male infertility is a multifaceted disorder affecting approximately 50% of male partners in infertile couples.
Over the years, male infertility has been diagnosed mainly through semen analysis, hormone evaluations, medical records and physical examinations, which of course are fundamental, but yet inefficient, because 30% of male infertility cases remain idiopathic. This dilemmatic status of the unknown needs to be addressed with more sophisticated and result-driven technologies and/or techniques.
Genetic alterations have been linked with male infertility, thereby unveiling the practicality of investigating this disorder from the "omics" perspective.
Omics aims at analyzing the structure and functions of a whole constituent of a given biological function at different levels, including the molecular gene level (genomics), transcript level (transcriptomics), protein level (proteomics) and metabolites level (metabolomics). In the current study, an overview of the four branches of omics and their roles in male infertility are briefly discussed; the potential usefulness of assessing transcriptomic data to understand this pathology is also elucidated.
After assessing the publicly obtainable transcriptomic data for datasets on male infertility, a total of 1385 datasets were retrieved, of which 10 datasets met the inclusion criteria and were used for further analysis.
These datasets were classified into groups according to the disease or cause of male infertility.
The groups include non-obstructive azoospermia (NOA), obstructive azoospermia (OA), non-obstructive and obstructive azoospermia (NOA and OA), spermatogenic dysfunction, sperm dysfunction, and Y chromosome microdeletion.
Findings revealed that 8 genes (LDHC, PDHA2, TNP1, TNP2, ODF1, ODF2, SPINK2, PCDHB3) were commonly differentially expressed between all disease groups.
Likewise, 56 genes were common between NOA versus NOA and OA (ADAD1, BANF2, BCL2L14, C12orf50, C20orf173, C22orf23, C6orf99, C9orf131, C9orf24, CABS1, CAPZA3, CCDC187, CCDC54, CDKN3, CEP170, CFAP206, CRISP2, CT83, CXorf65, FAM209A, FAM71F1, FAM81B, GALNTL5, GTSF1, H1FNT, HEMGN, HMGB4, KIF2B, LDHC, LOC441601, LYZL2, ODF1, ODF2, PCDHB3, PDHA2, PGK2, PIH1D2, PLCZ1, PROCA1, RIMBP3, ROPN1L, SHCBP1L, SMCP, SPATA16, SPATA19, SPINK2, TEX33, TKTL2, TMCO2, TMCO5A, TNP1, TNP2, TSPAN16, TSSK1B, TTLL2, UBQLN3).
These genes, particularly the above-mentioned 8 genes, are involved in diverse biological processes such as germ cell development, spermatid development, spermatid differentiation, regulation of proteolysis, spermatogenesis and metabolic processes.
Owing to the stage-specific expression of these genes, any mal-expression can ultimately lead to male infertility.
Therefore, currently available data on all branches of omics relating to male fertility can be used to identify biomarkers for diagnosing male infertility, which can potentially help in unravelling some idiopathic cases.
The application of the fractional calculus in the mathematical modelling of relaxation processes in complex heterogeneous media has attracted a considerable amount of interest lately.
The reason for this is the successful implementation of fractional stochastic and kinetic equations in the studies of non-Debye relaxation.
In this work, we consider the rotational diffusion equation with a generalised memory kernel in the context of dielectric relaxation processes in a medium composed of polar molecules. We give an overview of existing models on non-exponential relaxation and introduce an exponential resetting dynamic in the corresponding process.
The autocorrelation function and complex susceptibility are analysed in detail.
We show that stochastic resetting leads to a saturation of the autocorrelation function to a constant value, in contrast to the case without resetting, for which it decays to zero. The behaviour of the autocorrelation function, as well as the complex susceptibility in the presence of resetting, confirms that the dielectric relaxation dynamics can be tuned by an appropriate choice of the resetting rate.
The presented results are general and flexible, and they will be of interest for the theoretical description of non-trivial relaxation dynamics in heterogeneous systems composed of polar molecules.
The stability of the Greenland Ice Sheet under global warming is governed by a number of dynamic processes and interacting feedback mechanisms in the ice sheet, atmosphere and solid Earth.
Here we study the long-term effects due to the interplay of the competing melt-elevation and glacial isostatic adjustment (GIA) feedbacks for different temperature step forcing experiments with a coupled ice-sheet and solid-Earth model.
Our model results show that for warming levels above 2 degrees C, Greenland could become essentially ice-free within several millennia, mainly as a result of surface melting and acceleration of ice flow. These ice losses are mitigated, however, in some cases with strong GIA feedback even promoting an incomplete recovery of the Greenland ice volume. We further explore the full-factorial parameter space determining the relative strengths of the two feedbacks: our findings suggest distinct dynamic regimes of the Greenland Ice Sheets on the route to destabilization under global warming - from incomplete recovery, via quasi-periodic oscillations in ice volume to ice-sheet collapse.
In the incomplete recovery regime, the initial ice loss due to warming is essentially reversed within 50 000 years, and the ice volume stabilizes at 61 %-93 % of the present-day volume. For certain combinations of temperature increase, atmospheric lapse rate and mantle viscosity, the interaction of the GIA feedback and the melt-elevation feedback leads to self-sustained, long-term oscillations in ice-sheet volume with oscillation periods between 74 000 and over 300 000 years and oscillation amplitudes between 15 %-70 % of present-day ice volume.
This oscillatory regime reveals a possible mode of internal climatic variability in the Earth system on timescales on the order of 100 000 years that may be excited by or synchronized with orbital forcing or interact with glacial cycles and other slow modes of variability. Our findings are not meant as scenario-based near-term projections of ice losses but rather providing insight into of the feedback loops governing the "deep future" and, thus, long-term resilience of the Greenland Ice Sheet.
Geostatistics as a subfield of statistics accounts for the spatial correlations encountered in many applications of, for example, earth sciences. Valuable information can be extracted from these correlations, also helping to address the often encountered burden of data scarcity. Despite the value of additional data, the use of geostatistics still falls short of its potential. This problem is often connected to the lack of user-friendly software hampering the use and application of geostatistics. We therefore present GSTools, a Python-based software suite for solving a wide range of geostatistical problems. We chose Python due to its unique balance between usability, flexibility, and efficiency and due to its adoption in the scientific community. GSTools provides methods for generating random fields; it can perform kriging, variogram estimation and much more. We demonstrate its abilities by virtue of a series of example applications detailing their use.
In this paper, we present a study comparing the depth to diameter (d/D) ratio of small simple craters (200-1000 m) of an area between -88.5 degrees to -90 degrees latitude at the lunar south pole containing Permanent Shadowed Regions (PSRs) versus craters without PSRs. As PSRs can reach temperatures of 110 K and are capable of harboring volatiles, especially water ice, we analyzed the relationship of depth versus diameter ratios and its possible implications for harboring water ice. Variations in the d/D ratios can also be caused by other processes such as degradation, isostatic adjustment, or differences in surface properties. The conducted d/D ratio analysis suggests that a differentiation between craters containing PSRs versus craters without PSRs occurs. Thus, a possible direct relation between d/D ratio, PSRs, and water ice harboring might exist. Our results suggest that differences in the target's surface properties may explain the obtained results. The resulting d/D ratios of craters with PSRs can help to select target areas for future In-Situ Resource Utilization (ISRU) missions.
Analysis of physicians' probability estimates of a medical outcome based on a sequence of events
(2022)
IMPORTANCE
The probability of a conjunction of 2 independent events is the product of the probabilities of the 2 components and therefore cannot exceed the probability of either component; violation of this basic law is called the conjunction fallacy. A common medical decision-making scenario involves estimating the probability of a final outcome resulting from a sequence of independent events; however, little is known about physicians' ability to accurately estimate the overall probability of success in these situations.
OBJECTIVE
To ascertain whether physicians are able to correctly estimate the overall probability of a medical outcome resulting from 2 independent events.
DESIGN, SETTING, AND PARTICIPANTS
This survey study consisted of 3 separate substudies, in which 215 physicians were asked via internet-based survey to estimate the probability of success of each of 2 components of a diagnostic or prognostic sequence as well as the overall probability of success of the 2-step sequence. Substudy 1 was performed from April 2 to 4, 2021, substudy 2 from November 2 toll, 2021, and substudy 3 from May 13 to 19, 2021. All physicians were board certified or board eligible in the primary specialty germane to the substudy (ie, obstetrics and gynecology for substudies land 3 and pulmonology for substudy 2), were recruited from a commercial survey service, and volunteered to participate in the study.
EXPOSURES
Case scenarios presented in an online survey.
MAIN OUTCOMES AND MEASURES
Respondents were asked to provide their demographic information in addition to 3 probability estimates. The first substudy included a scenario describing a brow presentation discovered during labor; the 2 conjuncts were the probabilities that the brow presentation would resolve and that the delivery would be vaginal. The second substudy involved a diagnostic evaluation of an incidentally discovered pulmonary nodule; the 2 conjuncts were the probabilities that the patient had a malignant condition and that a technically successful transthoracic needle biopsy would reveal a malignant condition. The third substudy included a modification of the first substudy in an attempt to debias the conjunction fallacy prevalent in the first substudy. Respondents' own probability estimates of the individual events were used to calculate the mathematically correct conjunctive probability.
RESULTS
Among 215 respondents, the mean (SD) age was 54.0 (9.5) years; 142 respondents (66.0%) were male. Data on race and ethnicity were not collected. A total of 168 physicians (78.1%) estimated the probability of the 2-step sequence to be greater than the probability of at least 1 of the 2 component events. Compared with the product of their 2 estimated components, respondents overestimated the combined probability by 12.8% (95% CI, 9.6%-16.1%; P < .001) in substudy 1, 19.8% (95% Cl, 16.6%-23.0%; P < .001) in substudy 2, and 18.0% (95% CI, 13.4%-22.5%; P < .001) in substudy 3, results that were mathematically incoherent (ie, formally illogical and mathematically incorrect).
CONCLUSIONS AND RELEVANCE
In this survey study of 215 physicians, respondents consistently overestimated the combined probability of 2 events compared with the probability calculated from their own estimates of the individual events. This biased estimation, consistent with the conjunction fallacy, may have substantial implications for diagnostic and prognostic decision-making.
New technological applications such as Augmented Reality or Massive Open Online Courses (MOOCs) lead to alternative ways of learning. In order to be able to use this to its potential, the promotion of digital competencies “Digital Competence is the set of knowledge, skills, attitudes, abilities, strategies, and awareness that are required when using ICT and digital media to perform tasks; solve problems; communicate; manage information; collaborate; create and share content; and build knowledge effectively, efficiently, appropriately, critically, creatively, autonomously, flexibly, ethically, reflectively for work, le sure, participation, learning, and socialising.” (Ferrari, 2012). and a corresponding amount of practical "learning-by-doing" effects is required (cf. Ecker/Campbell 2019, p. 154). For this purpose, spaces and framework conditions must be created for application-based learning, which is also increasingly required by the employment market. In this context, we take a closer look at a new emerging subculture in university infrastructure called Maker Movement (MM). Our research work aims at investigating the pedagogical potential of particularly university-integrated makerspaces (MS) to enhance experiential learning with digital tools. To decode the innovative potential, we collected qualitative data from nine in-depth, semi-structured interviews with lab managers and researchers at European MS in six different countries.
We present a new set of global and local sea‐level projections at example tide gauge locations under the RCP2.6, RCP4.5, and RCP8.5 emissions scenarios. Compared to the CMIP5‐based sea‐level projections presented in IPCC AR5, we introduce a number of methodological innovations, including (i) more comprehensive treatment of uncertainties, (ii) direct traceability between global and local projections, and (iii) exploratory extended projections to 2300 based on emulation of individual CMIP5 models. Combining the projections with observed tide gauge records, we explore the contribution to total variance that arises from sea‐level variability, different emissions scenarios, and model uncertainty. For the period out to 2300 we further breakdown the model uncertainty by sea‐level component and consider the dependence on geographic location, time horizon, and emissions scenario. Our analysis highlights the importance of local variability for sea‐level change in the coming decades and the potential value of annual‐to‐decadal predictions of local sea‐level change. Projections to 2300 show a substantial degree of committed sea‐level rise under all emissions scenarios considered and highlight the reduced future risk associated with RCP2.6 and RCP4.5 compared to RCP8.5. Tide gauge locations can show large ( > 50%) departures from the global average, in some cases even reversing the sign of the change. While uncertainty in projections of the future Antarctic ice dynamic response tends to dominate post‐2100, we see substantial differences in the breakdown of model variance as a function of location, time scale, and emissions scenario.
We show that, although the equilibrium band dispersion of the Shockley-type surface state of two-dimensional Au(111) quantum films grown on W(110) does not deviate from the expected free-electron-like behavior, its nonequilibrium energy-momentum dispersion probed by time- and angle-resolved photoemission exhibits a remarkable kink above the Fermi level due to a significant enhancement of the effective mass. The kink is pronounced for certain thicknesses of the Au quantum well and vanishes in the very thin limit. We identify the kink as induced by the coupling between the Au(111) surface state and emergent quantum-well states which probe directly the buried gold-tungsten interface. The signatures of the coupling are further revealed by our time-resolved measurements which show that surface state and quantum-well states thermalize together behaving as dynamically locked electron populations. In particular, relaxation of hot carriers following laser excitation is similar for both surface state and quantum-well states and much slower than expected for a bulk metallic system. The influence of quantum confinement on the interplay between elementary scattering processes of the electrons at the surface and ultrafast carrier transport in the direction perpendicular to the surface is shown to be the reason for the slow electron dynamics.
Global change is shifting the timing of biological events, leading to temporal mismatches between biological events and resource availability. These temporal mismatches can threaten species' populations. Importantly, temporal mismatches not only exert strong pressures on the population dynamics of the focal species, but can also lead to substantial changes in pairwise species interactions such as host-pathogen systems. We adapted an established individual-based model of host-pathogen dynamics. The model describes a viral agent in a social host, while accounting for the host's explicit movement decisions. We aimed to investigate how temporal mismatches between seasonal resource availability and host life-history events affect host-pathogen coexistence, that is, disease persistence. Seasonal resource fluctuations only increased coexistence probability when in synchrony with the hosts' biological events. However, a temporal mismatch reduced host-pathogen coexistence, but only marginally. In tandem with an increasing temporal mismatch, our model showed a shift in the spatial distribution of infected hosts. It shifted from an even distribution under synchronous conditions toward the formation of disease hotspots, when host life history and resource availability mismatched completely. The spatial restriction of infected hosts to small hotspots in the landscape initially suggested a lower coexistence probability due to the critical loss of susceptible host individuals within those hotspots. However, the surrounding landscape facilitated demographic rescue through habitat-dependent movement. Our work demonstrates that the negative effects of temporal mismatches between host resource availability and host life history on host-pathogen coexistence can be reduced through the formation of temporary disease hotspots and host movement decisions, with implications for disease management under disturbances and global change.
In many species, dispersal is decisive for survival in a changing climate. Simulation models for population dynamics under climate change thus need to account for this factor. Moreover, large numbers of species inhabiting agricultural landscapes are subject to disturbances induced by human land use. We included dispersal in the HiLEG model that we previously developed to study the interaction between climate change and agricultural land use in single populations. Here, the model was parameterized for the large marsh grasshopper (LMG) in cultivated grasslands of North Germany to analyze (1) the species development and dispersal success depending on the severity of climate change in subregions, (2) the additional effect of grassland cover on dispersal success, and (3) the role of dispersal in compensating for detrimental grassland mowing. Our model simulated population dynamics in 60-year periods (2020-2079) on a fine temporal (daily) and high spatial (250 x 250 m(2)) scale in 107 subregions, altogether encompassing a range of different grassland cover, climate change projections, and mowing schedules. We show that climate change alone would allow the LMG to thrive and expand, while grassland cover played a minor role. Some mowing schedules that were harmful to the LMG nevertheless allowed the species to moderately expand its range. Especially under minor climate change, in many subregions dispersal allowed for mowing early in the year, which is economically beneficial for farmers. More severe climate change could facilitate LMG expansion to uninhabited regions but would require suitable mowing schedules along the path. These insights can be transferred to other species, given that the LMG is considered a representative of grassland communities. For more specific predictions on the dynamics of other species affected by climate change and land use, the publicly available HiLEG model can be easily adapted to the characteristics of their life cycle.
Cell-free protein synthesis (CFPS) represents a versatile key technology for the production of toxic proteins. As a cell lysate, rather than viable cells, is used, the toxic effects on the host organism can be circumvented. The open nature of cell-free systems allows for the addition of supplements affecting protein concentration and folding. Here, we present the cell-free synthesis and functional characterization of two AB(5) toxins, namely the cholera toxin (Ctx) and the heat-labile enterotoxin (LT), using two eukaryotic cell-free systems based on Chinese hamster ovary (CHO) and Spodoptera frugiperda (Sf21) cells. Through an iterative optimization procedure, the synthesis of the individual AB(5) toxins was established, and the formation of multimeric structures could be shown by autoradiography. A functional analysis was performed using cell-based assays, thereby demonstrating that the LT complex induced the characteristic cell elongation of target cells after 24 h. The LT complex induced cell death at higher concentrations, starting at an initial concentration of 5 nM. The initial toxic effects of the Ctx multimer could already be detected at 4 nM. The detection and characterization of such AB(5) toxins is of utmost importance, and the monitoring of intracellular trafficking facilitates the further identification of the mechanism of action of these toxins. We showed that the B-subunit of LT (LTB) could be fluorescently labeled using an LTB-Strep fusion protein, which is a proof-of-concept for future Trojan horse applications. Further, we performed a mutational analysis of the CtxA subunit as its template was modified, and an amber stop codon was inserted into CtxA's active site. Subsequently, a non-canonical amino acid was site-specifically incorporated using bio-orthogonal systems. Finally, a fluorescently labeled CtxA protein was produced using copper-catalyzed click reactions as well as a Staudinger ligation. As expected, the modified Ctx multimer no longer induced toxic effects. In our study, we showed that CFPS could be used to study the active centers of toxins by inserting mutations. Additionally, this methodology can be applied for the design of Trojan horses and targeted toxins, as well as enabling the intracellular trafficking of toxins as a prerequisite for the analysis of the toxin's mechanism of action.
Vegetation with an adequate supply of water might contribute to cooling the land surface around it through the latent heat flux of transpiration. This study investigates the potential estimation of evaporative cooling at plot scale, using soybean as example. Some of the plants' physiological parameters were monitored and sampled at weekly intervals. A physics-based model was then applied to estimate the irrigation-induced cooling effect within and above the canopy during the middle and late season of the soybean growth period. We then examined the results of the temperature changes at a temporal resolution of ten minutes between every two irrigation rounds. During the middle and late season of growth, the cooling effects caused by evapotranspiration within and above the canopy were, on average, 4.4 K and 2.9 K, respectively. We used quality indicators such as R-squared (R-2) and mean absolute error (MAE) to evaluate the performance of the model simulation. The performance of the model in this study was better above the canopy (R-2 = 0.98, MAE = 0.3 K) than below (R-2 = 0.87, MAE = 0.9 K) due to the predefined thermodynamic condition used to estimate evaporative cooling. Moreover, the study revealed that canopy cooling contributes to mitigating heat stress conditions during the middle and late seasons of crop growth.
In the aftermath of the Shoah and the ostensible triumph of nationalism, it became common in historiography to relegate Jews to the position of the “eternal other” in a series of binaries: Christian/Jewish, Gentile/Jewish, European/Jewish, non-Jewish/Jewish, and so forth. For the longest time, these binaries remained characteristic of Jewish historiography, including in the Central European context. Assuming instead, as the more recent approaches in Habsburg studies do, that pluriculturalism was the basis of common experience in formerly Habsburg Central Europe, and accepting that no single “majority culture” existed, but rather hegemonies were imposed in certain contexts, then the often used binaries are misleading and conceal the complex and sometimes even paradoxical conditions that shaped Jewish life in the region before the Shoah.
The very complexity of Habsburg Central Europe both in synchronic and diachronic perspective precludes any singular historical narrative of “Habsburg Jewry,” and it is not the intention of this volume to offer an overview of “Habsburg Jewish history.” The selected articles in this volume illustrate instead how important it is to reevaluate categories, deconstruct historical narratives, and reconceptualize implemented approaches in specific geographic, temporal, and cultural contexts in order to gain a better understanding of the complex and pluricultural history of the Habsburg Empire and the region as a whole.
At the interface between the lithosphere and the atmosphere, the critical zone records the complex interactions between erosion, climate, geologic substrate, and life and can be directly monitored. Long data records (30 consecutive years for sediment yields) collected in the sparsely vegetated, steep, and small marly badland catchments of the Draix-Bleone Critical Zone Observatory (CZO), SE France, allow analyzing potential climatic controls on regolith dynamics and sediment export. Although widely accepted as a first-order control, rainfall variability does not fully explain the observed interannual variability in sediment export. Previous studies in this area have suggested that frost-weathering processes could drive regolith production and potentially modulate the observed pattern of sediment export. Here, we define sediment export anomalies as the residuals from a predictive model with annual rainfall intensity above a threshold as the control. We then use continuous soil temperature data recorded at different locations over multiple years to highlight the role of different frost-weathering processes (i.e., ice segregation versus volumetric expansion) in regolith production. Several proxies for different frost-weathering processes have been calculated from these data and compared to the sediment export anomalies, with careful consideration of field data quality. Our results suggest that frost-cracking intensity (linked to ice segregation) can explain about half (47 %-64 %) of the sediment export anomalies. In contrast, the number of freeze-thaw cycles (linked to volumetric expansion) has only a minor impact on catchment sediment response. The time spent below 0 degrees C also correlates well with the sediment export anomalies and requires fewer field data to be calculated than the frost-cracking intensity. Thus, frost-weathering processes modulate sediment export by controlling regolith production in these catchments and should be taken into account when building predictive models of sediment export from these badlands under a changing climate.
Land degradation and water availability in semi-arid regions are interdependent challenges for management that are influenced by climatic and anthropogenic changes. Erosion and high sediment loads in rivers cause reservoir siltation and decrease storage capacity, which pose risk on water security for citizens, agriculture, and industry. In regions where resources for management are limited, identifying spatial-temporal variability of sediment sources is crucial to decrease siltation. Despite widespread availability of rigorous methods, approaches simplifying spatial and temporal variability of erosion are often inappropriately applied to very data sparse semi-arid regions. In this work, we review existing approaches for mapping erosional hotspots, and provide an example of spatial-temporal mapping approach in two case study regions. The barriers limiting data availability and their effects on erosion mapping methods, their validation, and resulting prioritization of leverage management areas are discussed.
Understanding the hydrologic connectivity between kettle holes and shallow groundwater, particularly in reaction to the highly variable local meteorological conditions, is of paramount importance for tracing water in a hydro(geo)logically complex landscape and thus for integrated water resource management. This article is aimed at identifying the dominant hydrological processes affecting the kettle holes' water balance and their interactions with the shallow groundwater domain in the Uckermark region, located in the north-east of Germany. For this reason, based on the stable isotopes of oxygen (delta O-18) and hydrogen (delta H-2), an isotopic mass balance model was employed to compute the evaporative loss of water from the kettle holes from February to August 2017. Results demonstrated that shallow groundwater inflow may play the pivotal role in the processes taking part in the hydrology of the kettle holes in the Uckermark region. Based on the calculated evaporation/inflow (E/I) ratios, most of the kettle holes (86.7%) were ascertained to have a partially open, flow-through-dominated system. Moreover, we identified an inverse correlation between E/I ratios and the altitudes of the kettle holes. The same holds for electrical conductivity (EC) and the altitudes of the kettle holes. In accordance with the findings obtained from this study, a conceptual model explaining the interaction between the shallow groundwater and the kettle holes of Uckermark was developed. The model exhibited that across the highest altitudes, the recharge kettle holes are dominant, where a lower ratio of E/I and a lower EC was detected. By contrast, the lowest topographical depressions represent the discharge kettle holes, where a higher ratio of E/I and EC could be identified. The kettle holes existing in between were categorized as flow-through kettle holes through which the recharge takes place from one side and discharge from the other side.
An exceptionally strong stationary planetary wave with Zonal Wavenumber 1 led to a sudden stratospheric warming (SSW) in the Southern Hemisphere in September 2019. Ionospheric data from European Space Agency's Swarm satellite constellation mission show prominent 6-day variations in the dayside low-latitude region at this time, which can be attributed to forcing from the middle atmosphere by the Rossby normal mode "quasi-6-day wave" (Q6DW). Geopotential height measurements by the Microwave Limb Sounder aboard National Aeronautics and Space Administration's Aura satellite reveal a burst of global Q6DW activity in the mesosphere and lower thermosphere during the SSW, which is one of the strongest in the record. The Q6DW is apparently generated in the polar stratosphere at 30-40 km, where the atmosphere is unstable due to strong vertical wind shear connected with planetary wave breaking. These results suggest that an Antarctic SSW can lead to ionospheric variability through wave forcing from the middle atmosphere.
Plain Language Summary: A sudden stratospheric warming (SSW) is an extreme wintertime polar meteorological phenomenon occurring mostly over the Arctic region. Studies have shown that Arctic SSW can influence the entire atmosphere. In September 2019, a rare SSW event occurred in the Antarctic region, providing an opportunity to investigate its broader impact on the whole atmosphere. We present observations from the middle atmosphere and ionosphere during this event, noting unusually strong wave activity throughout this region. Our results suggest that an Antarctic SSW can have a significant impact on the whole atmosphere system similar to those due to Arctic events.
Point-of-care and in-vivo bio-diagnostic tools are the current need for the present critical scenarios in the healthcare industry. The past few decades have seen a surge in research activities related to solving the challenges associated with precise on-site bio-sensing. Cutting-edge fiber optic technology enables the interaction of light with functionalized fiber surfaces at remote locations to develop a novel, miniaturized and cost-effective lab on fiber technology for bio-sensing applications. The recent remarkable developments in the field of nanotechnology provide innumerable functionalization methodologies to develop selective bio-recognition elements for label free biosensors. These exceptional methods may be easily integrated with fiber surfaces to provide highly selective light-matter interaction depending on various transduction mechanisms. In the present review, an overview of optical fiber-based biosensors has been provided with focus on physical principles used, along with the functionalization protocols for the detection of various biological analytes to diagnose the disease. The design and performance of these biosensors in terms of operating range, selectivity, response time and limit of detection have been discussed. In the concluding remarks, the challenges associated with these biosensors and the improvement required to develop handheld devices to enable direct target detection have been highlighted.
Selection of high-performance lines with respect to traits of interest is a key step in plant breeding. Genomic prediction allows to determine the genomic estimated breeding values of unseen lines for trait of interest using genetic markers, e.g. single-nucleotide polymorphisms (SNPs), and machine learning approaches, which can therefore shorten breeding cycles, referring to genomic selection (GS). Here, we applied GS approaches in two populations of Solanaceous crops, i.e. tomato and pepper, to predict morphometric and colorimetric traits. The traits were measured by using scoring-based conventional descriptors (CDs) as well as by Tomato Analyzer (TA) tool using the longitudinally and latitudinally cut fruit images. The GS performance was assessed in cross-validations of classification-based and regression-based machine learning models for CD and TA traits, respectively. The results showed the usage of TA traits and tag SNPs provide a powerful combination to predict morphology and color-related traits of Solanaceous fruits. The highest predictability of 0.89 was achieved for fruit width in pepper, with an average predictability of 0.69 over all traits. The multi-trait GS models are of slightly better predictability than single-trait models for some colorimetric traits in pepper. While model validation performs poorly on wild tomato accessions, the usage as many as one accession per wild species in the training set can increase the transferability of models to unseen populations for some traits (e.g. fruit shape for which predictability in unseen scenario increased from zero to 0.6). Overall, GS approaches can assist the selection of high-performance Solanaceous fruits in crop breeding.
Boreal forests of Siberia play a relevant role in the global carbon cycle. However, global warming threatens the existence of summergreen larch-dominated ecosystems, likely enabling a transition to evergreen tree taxa with deeper active layers. Complex permafrost-vegetation interactions make it uncertain whether these ecosystems could develop into a carbon source rather than continuing atmospheric carbon sequestration under global warming. Consequently, shedding light on the role of current and future active layer dynamics and the feedbacks with the apparent tree species is crucial to predict boreal forest transition dynamics and thus for aboveground forest biomass and carbon stock developments. Hence, we established a coupled model version amalgamating a one-dimensional permafrost multilayer forest land-surface model (CryoGrid) with LAVESI, an individual-based and spatially explicit forest model for larch species (Larix Mill.), extended for this study by including other relevant Siberian forest species and explicit terrain. <br /> Following parameterization, we ran simulations with the coupled version to the near future to 2030 with a mild climate-warming scenario. We focus on three regions covering a gradient of summergreen forests in the east at Spasskaya Pad, mixed summergreen-evergreen forests close to Nyurba, and the warmest area at Lake Khamra in the southeast of Yakutia, Russia. Coupled simulations were run with the newly implemented boreal forest species and compared to runs allowing only one species at a time, as well as to simulations using just LAVESI. Results reveal that the coupled version corrects for overestimation of active layer thickness (ALT) and soil moisture, and large differences in established forests are simulated. We conclude that the coupled version can simulate the complex environment of eastern Siberia by reproducing vegetation patterns, making it an excellent tool to disentangle processes driving boreal forest dynamics.
Previous studies have explored the consequences of flood events for exposed households and companies by focusing on single flood events. Less is known about the consequences of experiencing repeated flood events for the resilience of households and companies. In this paper, we therefore explore how multiple floods experience affects the resilience of exposed households and companies. Resilience was made operational through individual appraisals of households and companies' ability to withstand and recover from material as well as health and psychological impacts of the 2013 flood in Germany. The paper is based on three different datasets including more than 2000 households and 300 companies that were affected by the 2013 flood. The surveys revealed that the resilience of households seems to increase, but only with regard to their subjectively appraised ability to withstand impacts on mobile goods and equipment (e.g., cars, TV, and radios). In regard to the ability of households to withstand overall financial consequences of repetitive floods, evidence for nonlinear (quadratic) trends can be found. With regard to psychological and health-related consequences, the findings are mixed but provide tentative evidence for eroding resilience among households. Companies' resilience increased with respect to material assets but appears to decrease with respect to ability to recover. We conclude by arguing that clear and operational definitions of resilience are required so that evidence-based resilience baselines can be established to assess whether resilience is eroding or improving over time.
Being born large for gestational age is associated with increased global placental DNA methylation
(2020)
Being born small (SGA) or large for gestational age (LGA) is associated with adverse birth outcomes and metabolic diseases in later life of the offspring. It is known that aberrations in growth during gestation are related to altered placental function. Placental function is regulated by epigenetic mechanisms such as DNA methylation. Several studies in recent years have demonstrated associations between altered patterns of DNA methylation and adverse birth outcomes. However, larger studies that reliably investigated global DNA methylation are lacking. The aim of this study was to characterize global placental DNA methylation in relationship to size for gestational age. Global DNA methylation was assessed in 1023 placental samples by LC-MS/MS. LGA offspring displayed significantly higher global placental DNA methylation compared to appropriate for gestational age (AGA; p<0.001). ANCOVA analyses adjusted for known factors impacting on DNA methylation demonstrated an independent association between placental global DNA methylation and LGA births (p<0.001). Tertile stratification according to global placental DNA methylation levels revealed a significantly higher frequency of LGA births in the third tertile. Furthermore, a multiple logistic regression analysis corrected for known factors influencing birth weight highlighted an independent positive association between global placental DNA methylation and the frequency of LGA births (p=0.001).
The hyperthermal events of the Cenozoic, including the Paleocene-Eocene Thermal Maximum, provide an opportunity to investigate the potential effects of climate warming on marine ecosystems. Here, we examine the shallow benthic marine communities preserved in the late Cretaceous to Eocene strata on the Gulf Coastal Plain (United States). In stark contrast to the ecological shifts following the end-Cretaceous mass extinction, our data show that the early Cenozoic hyperthermals did not have a long-term impact on the generic diversity nor composition of the Gulf Coastal Plain molluscan communities. We propose that these communities were resilient to climate change because molluscs are better adapted to high temperatures than other taxa, as demonstrated by their physiology and evolutionary history. In terms of resilience, these communities differ from other shallow-water carbonate ecosystems, such as reef communities, which record significant changes during the early Cenozoic hyperthermals. These data highlight the strikingly different responses of community types, i.e., the almost imperceptible response of molluscs versus the marked turnover of foraminifera and reef faunas. The impact on molluscan communities may have been low because detrimental conditions did not devastate the entire Gulf Coastal Plain, allowing molluscs to rapidly recolonise vacated areas once harsh environmental conditions ameliorated.