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Similar Yet Different
(2020)
The importance of intrinsically disordered late embryogenesis abundant (LEA) proteins in the tolerance to abiotic stresses involving cellular dehydration is undisputed. While structural transitions of LEA proteins in response to changes in water availability are commonly observed and several molecular functions have been suggested, a systematic, comprehensive and comparative study of possible underlying sequence-structure-function relationships is still lacking. We performed molecular dynamics (MD) simulations as well as spectroscopic and light scattering experiments to characterize six members of two distinct, lowly homologous clades of LEA_4 family proteins from Arabidopsis thaliana. We compared structural and functional characteristics to elucidate to what degree structure and function are encoded in LEA protein sequences and complemented these findings with physicochemical properties identified in a systematic bioinformatics study of the entire Arabidopsis thaliana LEA_4 family. Our results demonstrate that although the six experimentally characterized LEA_4 proteins have similar structural and functional characteristics, differences concerning their folding propensity and membrane stabilization capacity during a freeze/thaw cycle are obvious. These differences cannot be easily attributed to sequence conservation, simple physicochemical characteristics or the abundance of sequence motifs. Moreover, the folding propensity does not appear to be correlated with membrane stabilization capacity. Therefore, the refinement of LEA_4 structural and functional properties is likely encoded in specific patterns of their physicochemical characteristics.
Reconstructing democracy
(2020)
Across the world, democracies are suffering from a disconnect between the people and political elites. In communities where jobs and industry are scarce, many feel the government is incapable of understanding their needs or addressing their problems. The resulting frustration has fueled the success of destabilizing demagogues. To reverse this pattern and restore responsible government, we need to reinvigorate democracy at the local level. But what does that mean? Drawing on examples of successful community building in cities large and small, from a shrinking village in rural Austria to a neglected section of San Diego, Reconstructing Democracy makes a powerful case for re-engaging citizens. It highlights innovative grassroots projects and shows how local activists can form alliances and discover their own power to solve problems.
During the phases of mobile warfare, the ethnically and religiously very heterogeneous population in the border regions of the multi-ethnic empires suffered in particular. Even if the real military situation in the course of the war hardly gave cause for concern, the image of disloyal ethnic and national minorities was widespread. This was particularly the case when ethnic groups lived on both sides of the border and social and political tensions had already established themselves along ethnic or religious lines of conflict before the war. Displacements, deportations and mass violence were the result. The genocide of the Armenian population is the most extreme example of this development. This anthology examines the border regions of the Ottoman, Russian and Habsburg empires during the First World War with regard to radical population policy and genocidal violence from a comparative perspective in order to draw a more precise picture of escalating and deescalating factors.
Background
Although associations between cardiovascular diseases and cognitive impairment are well known, the impact of cognitive performance on the success of patient education as a core component of cardiac rehabilitation remains insufficiently investigated so far.
Design
Prospective observational study in two inpatient cardiac rehabilitation centres between September 2014 and August 2015 with a follow-up six months after cardiac rehabilitation.
Method
At admission to and discharge from cardiac rehabilitation, the cognitive performance of 401 patients (54.5 ± 6.3 years, 80% men) following an acute coronary syndrome and/or coronary artery bypass graft was tested using the Montreal Cognitive Assessment. Patients’ disease-related knowledge was determined using a quiz (22 items for medical knowledge and 12 items for healthy lifestyle and behaviour) at both times and at follow-up. The change in knowledge after cardiac rehabilitation was analysed in multivariable regression models. Potentially influencing parameters (e.g. level of education, medication, cardiovascular risk factors, coronary artery bypass graft, comorbidities, exercise capacity) were considered.
Results
During cardiac rehabilitation, disease-related knowledge was significantly enhanced in both scales. At follow-up, the average level of medical knowledge was significantly reduced, while lifestyle knowledge remained at a stable level. The maintenance of knowledge after cardiac rehabilitation was predominantly predicted by prior knowledge, cognitive performance at discharge from cardiac rehabilitation and, in the case of medical knowledge, by coronary artery bypass graft.
Conclusion
Patient education in cardiac rehabilitation led to enhanced disease-related knowledge, but the maintenance of this essentially depended on patients’ cognitive performance, especially after coronary artery bypass graft. Therefore, patient education concepts in cardiac rehabilitation should be reconsidered and adjusted as needed.
Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free statistical modeling of artificial intelligence, is a promising synthesis tool for discovering novel patterns and the source of controversy in a general hypothesis. We apply a decision tree algorithm, assuming that evidence from various contexts can be adequately integrated in a hierarchically nested structure. As a case study, we analyzed 163 articles that studied a prominent hypothesis in invasion biology, the enemy release hypothesis. We explored if any of the nine attributes that classify each study can differentiate conclusions as classification problem. Results corroborated that machine learning can be useful for research synthesis, as the algorithm could detect patterns that had been already focused in previous narrative reviews. Compared with the previous synthesis study that assessed the same evidence collection based on experts' judgement, the algorithm has newly proposed that the studies focusing on Asian regions mostly supported the hypothesis, suggesting that more detailed investigations in these regions can enhance our understanding of the hypothesis. We suggest that machine learning algorithms can be a promising synthesis tool especially where studies (a) reformulate a general hypothesis from different perspectives, (b) use different methods or variables, or (c) report insufficient information for conducting meta-analyses.
The identification of buried soil horizons in agricultural landscapes helps to quantify sediment budgets and erosion-related carbon dynamics. High-resolution mapping of buried horizons using conventional soil surveys is destructive and time consuming. Geoelectrical sensors can offer a fast and non-destructive alternative for determining horizon positions and properties. In this paper, we compare the suitability of several geoelectrical methods for measuring the depth to buried horizons (Apb, Ahb and Hab) in the hummocky ground moraine landscape of northeastern Germany. Soil profile descriptions were developed for 269 locations within a 6-ha experimental field "CarboZALF-D". A stepwise linear discriminant analysis (LDA) estimated the lateral position of the buried horizons using electromagnetic induction data and terrain attributes. To predict the depth of a buried horizon, multiple linear regression (MLR) was used for both a 120-m transect and a 0.2-ha pseudo-three-dimensional (3D) area. At these scales, apparent electrical conductivity (ECa), electrical resistivity (ER) and terrain attributes were used as independent variables. The LDA accurately predicted Apb- and Ahb-horizons (a correct classification of 93%). The LDA of the Hab-horizon had a misclassification of 24%, which was probably related to the smaller test set and the higher depth of this horizon. The MLR predicted the depth of the Apb-, Ahb- and Hab-horizons with relative root mean square errors (RMSEs) of 7, 3 and 13%, respectively, in the pseudo-3D area. MLR had a lower accuracy for the 2D transect compared to the pseudo-3D area. Overall, the use of LDA and MLR has been an efficient methodological approach for predicting buried horizon positions. Highlights The suitability of geoelectrical measurements for digital modelling of diagnostic buried soil horizons was determined. LDA and MLR were used to detect multiple horizons with geoelectrical devices and terrain attributes. Geoelectrical variables were significant predictors of the position of the target soil horizons. The use of these tested digital technologies gives an opportunity to develop high-resolution soil mapping procedures.
Flight behaviour characteristics such as flight altitude and avoidance behaviour determine the species-specific collision risk of birds with wind turbines. However, traditional observational methods exhibit limited positional accuracy. High-resolution GPS telemetry represents a promising method to overcome this drawback. In this study, we used three-dimensional GPS tracking data including high-accuracy tracks recorded at 3-s intervals to investigate the collision risk of breeding male Montagu's Harriers Circus pygargus in the Dutch–German border region. Avoidance of wind turbines was quantified by a novel approach comparing observed flights to a null model of random flight behaviour. On average, Montagu's Harriers spent as much as 8.2 h per day in flight. Most flights were at low altitude, with only 7.1% within the average rotor height range (RHR; 45–125 m). Montagu's Harriers showed significant avoidance behaviour, approaching turbines less often than expected, particularly when flying within the RHR (avoidance rate of 93.5%). For the present state, with wind farms situated on the fringes of the regional nesting range, collision risk models based on our new insights on flight behaviour indicated 0.6–2.0 yearly collisions of adult males (as compared with a population size of c. 40 pairs). However, the erection of a new wind farm inside the core breeding area could markedly increase mortality (up to 9.7 yearly collisions). If repowering of the wind farms was carried out using low-reaching modern turbines (RHR 36–150 m), mortality would more than double, whereas it would stay approximately constant if higher turbines (RHR 86–200 m) were used. Our study demonstrates the great potential of high-resolution GPS tracking for collision risk assessments. The resulting information on collision-related flight behaviour allows for performing detailed scenario analyses on wind farm siting and turbine design, in contrast to current environmental assessment practices. With regard to Montagu's Harriers, we conclude that although the deployment of higher wind turbines represents an opportunity to reduce collision risk for this species, precluding wind energy developments in core breeding areas remains the most important mitigation measure.
Anthropogenic activities have led to a global decline in biodiversity, and monitoring studies indicate that both insect communities and wetland ecosystems are particularly affected. However, there is a need for long-term data (over centennial or millennial timescales) to better understand natural community dynamics and the processes that govern the observed trends. Chironomids (Insecta: Diptera: Chironomidae) are often the most abundant insects in lake ecosystems, sensitive to environmental change, and, because their larval exoskeleton head capsules preserve well in lake sediments, they provide a unique record of insect community dynamics through time. Here, we provide the results of a metadata analysis of chironomid diversity across a range of spatial and temporal scales. First, we analyse spatial trends in chironomid diversity using Northern Hemispheric data sets overall consisting of 837 lakes. Our results indicate that in most of our data sets, summer temperature (T-jul) is strongly associated with spatial trends in modern-day chironomid diversity. We observe a strong increase in chironomid alpha diversity with increasing T-jul in regions with present-day T-jul between 2.5 and 14 degrees C. In some areas with T-jul > 14 degrees C, chironomid diversity stabilizes or declines. Second, we demonstrate that the direction and amplitude of change in alpha diversity in a compilation of subfossil chironomid records spanning the last glacial-interglacial transition (similar to 15,000-11,000 years ago) are similar to those observed in our modern data. A compilation of Holocene records shows that during phases when the amplitude of temperature change was small, site-specific factors had a greater influence on the chironomid fauna obscuring the chironomid diversity-temperature relationship. Our results imply expected overall chironomid diversity increases in colder regions such as the Arctic under sustained global warming, but with complex and not necessarily predictable responses for individual sites.