Relationship of different feeding groups of true bugs (Hemiptera: Heteroptera) with habitat and landscape features in Pannonic salt grasslands

Eastern European grasslands are still inhabited by a rich arthropod fauna, but the drivers and mechanisms influencing their communities have to be understood to ensure their future survival. Heteroptera communities were studied in 20 plot-pairs in Pannonic salt steppe–salt marsh mosaics in Hungary. The effects of vegetation characteristics, landscape diversity and the proportion of surrounding grasslands on the composition, species richness and abundance of different feeding groups of true bugs (carnivores, specialist and generalist herbivores) were examined using ordinations and mixed-effect models. We found distinct herbivorous assemblages corresponding to microtopography-driven differences in water regime and vegetation between steppe and marsh plots, but this pattern was less pronounced in carnivorous assemblages. A higher species richness of true bugs was found in the more diverse steppe vegetation than in the salt marsh vegetation, while the abundance pattern of true bugs was opposite. Landscape diversity had a positive effect on the species richness and abundance of generalist herbivores and carnivores. Our results suggested that generalist herbivores and carnivores appear to drive diversity patterns in the local landscape due to their high dispersal abilities and the broader range of resources they can utilize. Specialist herbivores strongly influence the local insect biomass in relation to the distribution and density of their host plants. The present study highlights the importance of both habitat and landscape diversity for local insect diversity in Pannonic salt grasslands and suggests that the main threats for arthropod diversity are those processes and activities that homogenize these areas.     

Diversity of spiders and orthopterans respond to intra-seasonal and spatial environmental changes

Our understanding of arthropod responses to environmental pressures is limited, especially for the poorly studied Mediterranean region. In the light of likely further environmental change and the need for protocols for rapid biodiversity assessment, we measured how the abundance and species richness of two taxa, ground spiders and Orthoptera, belonging to different functional groups, fluctuates intra- seasonally (early-mid-late summer) and across habitat types (grasslands, maquis, forests). We also tested their surrogate value. Spiders were found to have higher species richness and abundance almost throughout the investigation. Orthoptera had lower species richness and abundance in forests compared to grasslands and maquis, while no significant difference between habitats was revealed for spiders. Early-summer was the richest period for spiders while mid-summer was the richest for Orthoptera. Canopy cover was found to significantly influence community composition of both groups, while herb height and cover of stones was a determinant factor for Orthoptera only. There was a significant congruence between the two groups and Orthoptera provided the best complementary network. Our results show that diversity patterns of both spiders and Orthoptera are sensitive to environmental changes even over short time-scales (e.g. within the summer period) and space (e.g. across different habitat types), suggesting that small inexpensive experimental designs may still reveal community dynamics. For conservation purposes, we advise a focus on variables regulating habitat heterogeneity and microhabitat characteristics. We provide a list of the most influential species and propose the most effective network for obtaining information on the local fauna.     

Mapping QTLs and meta-QTLs for two inflorescence architecture traits in multiple maize populations under different watering environments

Drought significantly affects the architectural development of maize inflorescence, which leads to massive losses in grain yield. However, the genetic mechanism for traits involved in inflorescence architecture in different watering environments, remains poorly understood in maize. In this study, 19 QTLs for tassel primary branch number (TBN) and ear number per plant (EN) were detected in 2 F_2:3 populations under both well-watered and water-stressed environments by single environment mapping with composite interval mapping (CIM); 11/19 QTLs were detected under water-stressed environments. Moreover, 21 QTLs were identified in the 2 F_2:3 populations by joint analysis of all environments with a mixed linear model based on composite interval mapping (MCIM), 11 QTLs were involved in QTL × environment interactions, seven epistatic interactions were identified with additive by additive/dominance effects. Remarkably, 12 stable QTLs (sQTLs) were simultaneously detected by single environment mapping with CIM and joint analysis through MCIM, which were concentrated in ten bins across the chromosomes: 1.05_1.07, 1.08_1.10, 2.01_2.04, 3.01, 4.06, 4.09, 5.06_5.07, 6.05, 7.00, and 7.04 regions. Twenty meta-QTLs (mQTLs) were detected across 19 populations under 51 watering environments using a meta-analysis, and 34 candidate genes were predicted in corresponding mQTLs regions to be involved in the regulation of inflorescence development and drought resistance. Therefore, these results provide valuable information for finding quantitative trait genes and to reveal the genetic mechanisms responsible for TBN and EN under different watering environments. Furthermore, alleles for TBN and EN provide useful targets for marker-assisted selection to generate high-yielding maize varieties.     

Interpolating and extrapolating with hmsIST: seeking a t<Subscript>max</Subscript> for optimal sensitivity,resolution and frequency accuracy

Non-Uniform Sampling has the potential to exploit the optimal resolution of high-field NMR instruments. This is not possible in 3D and 4D NMR experiments when using traditional uniform sampling due to the long overall measurement time. Nominally, uniformly sampled time domain data acquired to a maximum evolution time t_max can be extended to high resolution via a virtual maximum evolution time t*_max while extrapolating with linear prediction or iterative soft thresholding (IST). At the high resolution obtainable with extrapolation of US data, however, the accuracy of peak positions is compromised as observed when comparing inter- and intra-residue peaks in a 3D HNCA experiment. However, the accuracy of peak positions is largely improved by spreading the same number of acquired time domain data points non-uniformly over a larger evolution time to an optimal t_max followed by extrapolation to a total t*_max and processing the data with an appropriate reconstruction method, such as hmsIST. To explore the optimum value of experimentally measured t_max to be reached non-uniformly with a given number of sampling points we have created test situations of time-equivalent experiments and evaluate sensitivity and accuracy of peak positions. Here we use signal-to-maximum-noise ratio as the decisive measure of sensitivity. We find that both sensitivity and resolution are optimal when PoissonGap sampling to a t_max of about ½*T₂ ^*. Digital resolution is further enhanced by extrapolating the range of acquired time domain data to 2*T₂ ^* but without measuring experimental points beyond ½*T₂ ^*.     

Parkinson’s disease: what the model systems have taught us so far

Parkinson’s disease (PD) is a debilitating neurodegenerative disorder, for which people above the age of 60 show an increased risk. Although there has been great advancement in understanding the disease-related abnormalities in brain circuitry and development of symptomatic treatments, a cure for PD remains elusive. The discovery of PD associated gene mutations and environmental toxins have yielded animal models of the disease. These models could recapitulate several key aspects of PD, and provide more insights into the disease pathogenesis. They have also revealed novel aspects of the disease mechanism including noncell autonomous events and spreading of pathogenic protein species across the brain. Nevertheless, none of these models so far can comprehensively represent all aspects of the human disease. While the field is still searching for the perfect model system, recent developments in stem cell biology have provided a new dimension to modelling PD, especially doing it in a patient-specific manner. In the current review, we attempt to summarize the key findings in the areas discussed above, and highlight how the core PD pathology distinguishes itself from other neurodegenerative disorders while also resembling them in many aspects.     

Morpho-anatomical and physiological responses to waterlogging stress in different barley (<Emphasis Type="Italic">Hordeum vulgare</Emphasis> L.) genotypes

Waterlogging is one of the major stresses limiting crop production worldwide. The understanding of the mechanisms of plant adaptations to waterlogging stress helps improve plant tolerance to stress. In this study, physiological responses and morpho-anatomical adaptations of seven different barley genotypes were investigated under waterlogging stress. The results showed that the waterlogging-tolerant varieties (TX9425, Yerong, TF58) showed less reduction in plant height, SPAD (soil–plant analyses development analyses) value, tillers, shoot and root biomasses than did the waterlogging-sensitive varieties (Franklin, Naso Nijo, TF57). Under waterlogging stress condition, the tolerant genotypes also showed a much larger number of adventitious roots than did the sensitive genotypes. More intercellular spaces and better integrated chloroplast membrane structures were observed in the leaves of the waterlogging-tolerant cultivars, which is likely due to increased ethylene content, decreased ABA content and less accumulation of O₂^.?. The ability to form new adventitious roots and intercellular spaces in shoots can also be used as selection criteria in breeding barley for waterlogging tolerance.     

Orexin A/Hypocretin Modulates Leptin Receptor-Mediated Signaling by Allosteric Modulations Mediated by the Ghrelin GHS-R1A Receptor in Hypothalamic Neurons

The hypothalamus is a key integrator of nutrient-seeking signals in the form of hormones and metabolites originated in both the central nervous system and the periphery. The main autocrine and paracrine target of orexinergic-related hormones such as leptin, orexin/hypocretin, and ghrelin are neuropeptide Y neurons located in the arcuate nucleus of the hypothalamus. The aim of this study was to investigate the expression and the molecular and functional relationships between leptin, orexin/hypocretin and ghrelin receptors. Biophysical studies in a heterologous system showed physical interactions between them, with potential formation of heterotrimeric complexes. Functional assays showed robust allosteric interactions particularly different when the three receptors are expressed together. Further biochemical and pharmacological assays provided evidence of heterotrimer functional expression in primary cultures of hypothalamic neurons. These findings constitute evidence of close relationships in the action of the three hormones already starting at the receptor level in hypothalamic cells.     

Autonomic Adaption to Clinical Simulation in Psychology Students: Teaching Applications

Simulation is used to facilitate new learning in a variety of situations. One application of simulation could be to help therapists gain therapeutic skills prior to seeing clients. This particular study was interested in measuring changes in stress response by looking at subjective and objective measures of distress (as measured by SUDS, HR, and HRV) over three sessions of simulated therapy. 16 second year psychology students participated in three sessions, and had their HR and HRV measured by Polar watches. Over the three sessions, there was a decrease in perceived distress, as measured by SUDS ratings. During and between sessions, there was inconclusive change in physiological parameters.     

Conservative populist politics and the remaking of the “white working class” in the USA

For decades, scholars and journalists have intricately tied presidential elections to the idea of a struggling “white working class.” They explained the 2016 presidential election by investigating the politics of low- or middle-income white conservative voters. This article instead focuses on the way in which white low-wage and unemployed small town residents question, distrust, and embrace conservative populist politics. The paper first explores how conservative populism and the media response are remaking the white working class along cultural and racial lines. Drawing from research conducted in a predominantly white former manufacturing town in central Maine, I then document that some poor and low-wage white workers distrust conservative populist politicians and are angry about being pushed aside by business-first politics. While populist and neoliberal politics have contributed to a remaking of the white working class around a white worker ideal, the concomitant decline in the social safety net and good jobs has been generating a sense of betrayal among those who are struggling the most. The article thus offers an alternative to the white working class caricature and argues that a contradictory consciousness results from workers living within and reacting against economic precarity and conservative populism.