Nuclear processes associated with plant immunity and pathogen susceptibility

Plants are sessile organisms that have evolved exquisite and sophisticated mechanisms to adapt to their biotic and abiotic environment. Plants deploy receptors and vast signalling networks to detect, transmit and respond to a given biotic threat by inducing properly dosed defence responses. Genetic analyses and, more recently, next-generation -omics approaches have allowed unprecedented insights into the mechanisms that drive immunity. Similarly, functional genomics and the emergence of pathogen genomes have allowed reciprocal studies on the mechanisms governing pathogen virulence and host susceptibility, collectively allowing more comprehensive views on the processes that govern disease and resistance. Among others, the identification of secreted pathogen molecules (effectors) that modify immunity-associated processes has changed the plant–microbe interactions conceptual landscape. Effectors are now considered both important factors facilitating disease and novel probes, suited to study immunity in plants. In this review, we will describe the various mechanisms and processes that take place in the nucleus and help regulate immune responses in plants. Based on the premise that any process required for immunity could be targeted by pathogen effectors, we highlight and describe a number of functional assays that should help determine effector functions and their impact on immune-related processes. The identification of new effector functions that modify nuclear processes will help dissect nuclear signalling further and assist us in our bid to bolster immunity in crop plants

Towards the drivers of value creation in the biogas industry:enablers and inhibiters in the Netherlands

The Dutch biogas industry is developing slowly and in many instances still unviable. Insights in the drivers of value creation may help to create viable biogas business networks. This research explores these related drivers and accordingly, proposes a new and comprehensive definition of a driver of value creation. This definition focuses on the enabling and inhibiting factors of value creation in a business network and forms the backbone of three case studies. The results suggest the presence of four specific drivers as necessary for a viable biogas business network: stability and certainty, partner alignment, local opportunities and economies of scale

An assessment framework of business modelling ontologies to ensure the viability of business models

Organisations operate in an increasingly dynamic environment. Consequently, the business models span several organisations, dealing with multiple stakeholders and their competing interests. As a result, the enterprise information systems supporting this new market setting are highly distributed, and their components are owned and managed by different stakeholders. For successful businesses to exist it is crucial that their enterprise architectures are derived from and aligned with viable business models. Business model ontologies (BMOs) are effective tools for designing and evaluating business models. However, the viability perspective has been largely neglected. In this paper, current BMOs have been assessed on their capabilities to support the design and evaluation of viable business models. As such, a list of criteria is derived from literature to evaluate BMOs from a viability perspective. These criteria are subsequently applied to six well-established BMOs, to identify a BMO best suited for design and evaluation of viable business models. The analysis reveals that, although none of the BMOs satisfy all the criteria, e3-value is the most appropriate BMO for designing and evaluating business models from a viability perspective. Furthermore, the identified deficits provide clear areas for enhancing the assessed BMOs from a viability perspective

DNA-binding protein prediction using plant specific support vector machines:validation and application of a new genome annotation tool

There are currently 151 plants with draft genomes available but levels of functional annotation for putative protein products are low. Therefore, accurate computational predictions are essential to annotate genomes in the first instance, and to provide focus for the more costly and time consuming functional assays that follow. DNA-binding proteins are an important class of proteins that require annotation, but current computational methods are not applicable for genome wide predictions in plant species. Here, we explore the use of species and lineage specific models for the prediction of DNA-binding proteins in plants. We show that a species specific support vector machine model based on Arabidopsis sequence data is more accurate (accuracy 81%) than a generic model (74%), and based on this we develop a plant specific model for predicting DNA-binding proteins. We apply this model to the tomato proteome and demonstrate its ability to perform accurate high-throughput prediction of DNA-binding proteins. In doing so, we have annotated 36 currently uncharacterised proteins by assigning a putative DNA-binding function. Our model is publically available and we propose it be used in combination with existing tools to help increase annotation levels of DNA-binding proteins encoded in plant genomes

Increased frequency of circulating IL-21 producing Th-cells in patients with granulomatosis with polyangiitis (GPA).

INTRODUCTION: The present study aimed to explore a possible role for IL-21 producing Th-cells in the immunopathogenesis of granulomatosis with polyangiitis (GPA). METHODS: Peripheral blood from 42 GPA patients in remission and 29 age-matched healthy controls (HCs) were stimulated in vitro, and the frequencies of IL-21 producing Th-cells were determined by flow cytometry. Since Th17-cells produce a low level of IL-21, IL-17 was also included in the analysis. Given that IL-21 is a hallmark cytokine for T follicular helper cells (T(FH)), we next evaluated the expression of their key transcription factor BCL-6 by RT-PCR and flow cytometry. To investigate the effect of IL-21 on autoantibody-production, PBMCs from GPA patients were stimulated in vitro with BAFF/IL-21 and total IgG and ANCA levels were measured in supernatants. In addition, the expression of IL-21-receptor on B-cells was analyzed. RESULTS: Percentages of IL-21 producing Th-cells were significantly elevated in GPA-patients compared to HCs, and were restricted to ANCA-positive patients. The expression of BCL-6 was significantly higher in ANCA-positive GPA-patients, as compared with ANCA-negative patients and HCs. IL-21 enhanced the production of IgG and ANCA in vitro in stimulated PBMCs from GPA patients. No difference was found in the expression of the IL-21-receptor on B-cells between ANCA-negative patients, ANCA-positive patients, and HCs. CONCLUSION: The increased frequency of circulating IL-21 producing Th-cells in ANCA-positive GPA patients and the stimulating capacity of IL-21 on ANCA-production suggest a role for these cells in the immunopathogenesis of GPA. Blockade of IL-21 could constitute a new therapeutic strategy for GPA

Alternative mechanism for bacteriophage adsorption to the motile bacterium Caulobacter crescentus

2D and 3D cryo-electron microscopy, together with adsorption kinetics assays of ϕCb13 and ϕCbK phage-infected Caulobacter crescentus, provides insight into the mechanisms of infection. ϕCb13 and ϕCbK actively interact with the flagellum and subsequently attach to receptors on the cell pole. We present evidence that the first interaction of the phage with the bacterial flagellum takes place through a filament on the phage head. This contact with the flagellum facilitates concentration of phage particles around the receptor (i.e., the pilus portals) on the bacterial cell surface, thereby increasing the likelihood of infection. Phage head filaments have not been well characterized and their function is described here. Phage head filaments may systematically underlie the initial interactions of phages with their hosts in other systems and possibly represent a widespread mechanism of efficient phage propagation

Scaling mechanisms of energy communities:A comparison of 28 initiatives

Energy communities have mushroomed over the past decades. These initiatives have scaled, that is replicated their experiences, expanded membership, and diversified involved actors and technologies. The picture existing literature paints is hopeful that the scaling of local-scale action may translate into global-scale impact and thus effectively contribute to combating climate change. However, important gaps remain in understanding the (combinations of) conditions which are necessary for scaling with this goal in mind. This article pushes the boundaries of knowledge further by examining and comparing 28 energy communities through a fuzzy set Qualitative Comparative Analysis (QCA) and by identifying the necessary conditions of actionable scaling mechanisms. Our analysis identifies a high number (8) of necessary (combinations of) conditions for scaling. Addressing a strong need amongst policy makers to facilitate broader scaling of community initiatives, this article offers concrete insights on mechanisms that need to be in place to scale energy communities. Insights are developed on – for example – the type of capacity support needed, support structures and the tools needed for connecting communities with each other. These insights help corroborate empirically, for the first time the crucial leverage points that will support strategies for upscaling the impact of energy communities, and will enable them to flourish as an essential element of the global climate governance system.</p

Predictive control for multi-market trade of aggregated demand response using a black box approach

Aggregated demand response for smart grid services is a growing field of interest especially for market participation. To minimize economic and network instability risks, flexibility characteristics such as shiftable capacity must be known. This is traditionally done using lower level, end user, device specifications. However, with these large numbers, having lower level information, has both privacy and computational limitations. Previous studies have shown that black box forecasting of shiftable capacity, using machine learning techniques, can be done accurately for a homogeneous cluster of heating devices. This paper validates the machine learning model for a heterogeneous virtual power plant. Further it applies this model to a control strategy to offer flexibility on an imbalance market while maintaining day ahead market obligations profitably. It is shown that using a black box approach 89% optimal economic performance is met. Further, by combining profits made on imbalance market and the day ahead costs, the overall monthly electricity costs are reduced 20%

Climate change adaptation in European river basins

This paper contains an assessment and standardized comparative analysis of the current water management regimes in four case-studies in three European river basins: the Hungarian part of the Upper Tisza, the Ukrainian part of the Upper Tisza (also called Zacarpathian Tisza), Alentejo Region (including the Alqueva Reservoir) in the Lower Guadiana in Portugal, and Rivierenland in the Netherlands. The analysis comprises several regime elements considered to be important in adaptive and integrated water management: agency, awareness raising and education, type of governance and cooperation structures, information management and—exchange, policy development and—implementation, risk management, and finances and cost recovery. This comparative analysis has an explorative character intended to identify general patterns in adaptive and integrated water management and to determine its role in coping with the impacts of climate change on floods and droughts. The results show that there is a strong interdependence of the elements within a water management regime, and as such this interdependence is a stabilizing factor in current management regimes. For example, this research provides evidence that a lack of joint/participative knowledge is an important obstacle for cooperation, or vice versa. We argue that there is a two-way relationship between information management and collaboration. Moreover, this research suggests that bottom-up governance is not a straightforward solution to water management problems in large-scale, complex, multiple-use systems, such as river basins. Instead, all the regimes being analyzed are in a process of finding a balance between bottom-up and top–down governance. Finally, this research shows that in a basin where one type of extreme is dominant—like droughts in the Alentejo (Portugal) and floods in Rivierenland (Netherlands)—the potential impacts of other extremes are somehow ignored or not perceived with the urgency they might deserv