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Current molecular biology laboratories rely heavily on the purification and manipulation of nucleic acids. Yet, commonly used centrifuge- and column-based protocols require specialised equipment, often use toxic reagents, and are not economically scalable or practical to use in a high-throughput manner. Although it has been known for some time that magnetic beads can provide an elegant answer to these issues, the development of open-source protocols based on beads has been limited. In this article, we provide step-by-step instructions for an easy synthesis of functionalised magnetic beads, and detailed protocols for their use in the high-throughput purification of plasmids, genomic DNA, RNA and total nucleic acid (TNA) from a range of bacterial, animal, plant, environmental and synthetic sources. We also provide a bead-based protocol for bisulfite conversion and size selection of DNA and RNA fragments. Comparison to other methods highlights the capability, versatility, and extreme cost-effectiveness of using magnetic beads. These open-source protocols and the associated webpage (https://bomb.bio) can serve as a platform for further protocol customisation and community engagement.

ObjectivesHeterogeneity in outcomes measured across trials of glucose-lowering interventions for people with type 2 diabetes impacts on the ability to compare findings and may mean that the results have little importance to healthcare professionals and the patients that they care for. The SCORE-IT study (Selecting Core Outcomes for Randomised Effectiveness trials In Type 2 diabetes) has addressed this issue by establishing consensus on the most important outcomes for non-surgical interventions for hyperglycemia in type 2 diabetes.Research design and methodsA comprehensive list of outcomes was developed from registered clinical trials, online patient resources, qualitative literature and long-term studies in the field. This list was then scored in a two-round online Delphi survey completed by healthcare professionals, people with type 2 diabetes, researchers in the field and healthcare policymakers. The results of this online Delphi were discussed and ratified at a face-to-face consensus meeting.Results173 people completed both rounds of the online survey (116 people with type 2 diabetes, 37 healthcare professionals, 14 researchers and 6 policymakers), 20 of these attended the consensus meeting (13 people with type 2 diabetes and 7 healthcare professionals). Consensus was reached on 18 core outcomes across five domains, which include outcomes related to diabetes care, quality of life and long-term diabetes-related complications.ConclusionsImplementation of the core outcome set in future trials will ensure that outcomes of importance to all stakeholders are measured and reported, enhancing the relevance of trial findings and facilitating the comparison of results across trials.

Chloroplast protrusions (CPs) have frequently been observed in plants, but their significance to plant metabolism remains largely unknown. We investigated in the alpine plant Ranunculus glacialis L. treated under various CO₂ concentrations if CP formation is related to photorespiration, specifically focusing on hydrogen peroxide (H₂O₂) metabolism. Immediately after exposure to different CO₂ concentrations, the formation of CPs in leaf mesophyll cells was assessed and correlated to catalase (CAT) and ascorbate peroxidase (APX) activities. Under natural irradiation, the relative proportion of chloroplasts with protrusions (rCP) was highest (58.7 %) after exposure to low CO₂ (38 ppm) and was lowest (3.0 %) at high CO₂ (10,000 ppm). The same relationship was found for CAT activity, which decreased from 34.7 nkat mg⁻¹ DW under low CO₂ to 18.4 nkat mg⁻¹ DW under high CO₂, while APX activity did not change significantly. When exposed to natural CO₂ concentration (380 ppm) in darkness, CP formation was significantly lower (18.2 %) compared to natural solar irradiation (41.3 %). In summary, CP formation and CAT activity are significantly increased under conditions that favour photorespiration, while in darkness or at high CO₂ concentration under light, CP formation is significantly lower, providing evidence for an association between CPs and photorespiration.

Using ten sermons from five prominent and politically active evangelical megachurch pastors taken from the 2016 presidential campaign season, this case study utilizes frame analysis to understand the political relevance of modern evangelical sermonizing. An inductive frame analysis allows the concept of a collective action frame to be observed as a process and for patterns to emerge from the source text. Within these sermons, ministers offer self-identifying evangelicals a vocabulary with which to understand and describe their own identity. In this context, the Bible is a powerful cultural symbol that represents an allegiance to traditions that are framed as the bedrock of American exceptionalism. The boundaries that are drawn and vociferously maintained in this sample emphasize exclusion over inclusion, especially in terms of salvation and righteousness, which can emotionally motivate action. In an election year, this sample demonstrates how evangelical identity is mobilized as an electoral force.

Abstract Endemism in mountain ranges is considered to be the result of a number of factors, including restriction to refugia during Pleistocene climate fluctuations. However, isolation in glacial refugia cannot explain the origin of narrowly endemic taxa restricted to formerly heavily glaciated areas. Here, we investigate the phylogeny of two narrowly endemic species, Euphrasia inopinata and E. sinuata (Orobanchaceae), found exclusively in formerly heavily glaciated areas of the eastern European Alps. As both species are diploid and very similar to the widespread (allo)polyploid E. minima, we test whether the restricted distributions of E. inopinata and E. sinuata are relictual, i.e. the two species are ancestral diploid remnants of a polyploid complex, or whether they are derived, i.e. the two species are peripheral segregates of a more widespread diploid. Based on internal transcribed spacer (ITS) sequence and amplified fragment length polymorphism (AFLP) fingerprint data it is shown that E. inopinata and E. sinuata, whose diploid ploidy level is confirmed for all analysed individuals via flow cytometry, are phylogenetically closely related to diploid E. alpina s. l. (series Alpinae) instead of E. minima (series Parviflorae). In addition, there is no evidence that these two diploid species participated in the formation of allotetraploid E. minima. Thus, E. inopinata and E. sinuata are interpreted as peripheral segregates of the widespread E. alpina s. l. Shifts in pollination system from allogamy in E. alpina s. l. to autogamy in E. inopinata and E. sinuata, genetic drift in small populations and geographic isolation at the periphery of the range of E. alpina s. str. probably contributed to the morphological and ecological differentiation of E. inopinata and E. sinuata. The origin of range-restricted diploid species confined to formerly heavily glaciated areas is little understood. A suitable system to address this question is a group of two autogamous eyebright species, Euphrasia inopinata and E. sinuata, each known only from a few sites in the eastern European Alps. Previous hypotheses suggested these species to be either remnants of the diploid ancestor of the equally autogamous but widespread and polyploid E. minima or as peripheral segregates of a more widespread allogamous diploid species.

We present a new structure-preserving model order reduction (MOR) framework for large-scale port-Hamiltonian descriptor systems (pH-DAEs). Our method exploits the structural properties of the Rosenbrock system matrix for this system class and utilizes condensed forms which often arise in applications and reveal the solution behaviour of a system. Provided that the original system has such a form, our method produces reduced-order models (ROMs) of minimal dimension, which tangentially interpolate the original model's transfer function and are guaranteed to be again in pH-DAE form. This allows the ROM to be safely coupled with other dynamical systems when modelling large system networks, which is useful, for instance, in electric circuit simulation.

Bacteria survive in nature by forming biofilms on surfaces and probably most, if not all, bacteria （and fungi） are capable of forming biofilms. A biofilm is a structured consortium of bacteria embedded in a self-produced polymer matrix consisting of polysaccharide, protein and extracellular DNA. Bacterial biofilms are resistant to antibiotics, disinfectant chemicals and to phagocytosis and other components of the innate and adaptive inflammatory defense system of the body. It is known, for example, that persistence of staphylococcal infections related to foreign bodies is due to biofilm formation. Likewise, chronic Pseudomonas aeruginosa lung infections in cystic fibrosis patients are caused by biofilm growing mucoid strains. Gradients of nutrients and oxygen exist from the top to the bottom of biofilms and the bacterial cells located in nutrient poor areas have decreased metabolic activity and increased doubling times. These more or less dormant cells are therefore responsible for some of the tolerance to antibiotics. Biofilm growth is associated with an increased level of mutations. Bacteria in biofilms communicate by means of molecules, which activates certain genes responsible for production of virulence factors and, to some extent, biofilm structure. This phenomenon is called quorum sensing and depends upon the concentration of the quorum sensing molecules in a certain niche, which depends on the number of the bacteria. Biofilms can be prevented by antibiotic prophylaxis or early aggressive antibiotic therapy and they can be treated by chronic suppressive antibiotic therapy. Promising strategies may include the use of compounds which can dissolve the biofilm matrix and quorum sensing inhibitors, which increases biofilm susceptibility to antibiotics and phagocytosis.

We present a new optimization-based structure-preserving model order reduction (MOR) method for port-Hamiltonian descriptor systems (pH-DAEs) with differentiation index two. Our method is based on a novel parameterization that allows us to represent any linear time-invariant pH-DAE with a minimal number of parameters, which makes it well-suited to model reduction. We propose two algorithms which directly optimize the parameters of a reduced model to approximate a given large-scale model with respect to either the H-infinity or the H-2 norm. This approach has several benefits. Our parameterization ensures that the reduced model is again a pH-DAE system and enables a compact representation of the algebraic part of the large-scale model, which in projection-based methods often requires a more involved treatment. The direct optimization is entirely based on transfer function evaluations of the large-scale model and is therefore independent of the system matrices' structure. Numerical experiments are conducted to illustrate the high accuracy and small reduced model orders in comparison to other structure-preserving MOR methods.

We develop optimization-based structure-preserving model order reduction (MOR) methods for port-Hamiltonian (pH) descriptor systems of differentiation index one. Descriptor systems in pH form permit energy-based modeling and intuitive coupling of physical systems across different physical domains, scales, and accuracies. This makes pH models well-suited building-blocks for component-wise modeling of large system networks. In this context, it is often necessary to preserve the pH structure during MOR. We discuss current projection-based and structure-preserving MOR algorithms for pH systems and present a new optimization-based framework for that task. The benefits of our method include a simplified treatment of algebraic constraints and often a higher accuracy of the resulting reduced-order model, which is demonstrated by several numerical examples.