An integrated fluid–structure interaction and thrombosis model for type B aortic dissection

False lumen thrombosis (FLT) in type B aortic dissection has been associated with the progression of dissection and treatment outcome. Existing computational models mostly assume rigid wall behavior which ignores the effect of flap motion on flow and thrombus formation within the FL. In this study, we have combined a fully coupled fluid–structure interaction (FSI) approach with a shear-driven thrombosis model described by a series of convection–diffusion reaction equations. The integrated FSI-thrombosis model has been applied to an idealized dissection geometry to investigate the interaction between vessel wall motion and growing thrombus. Our simulation results show that wall compliance and flap motion can influence the progression of FLT. The main difference between the rigid and FSI models is the continuous development of vortices near the tears caused by drastic flap motion up to 4.45 mm. Flap-induced high shear stress and shear rates around tears help to transport activated platelets further to the neighboring region, thus speeding up thrombus formation during the accelerated phase in the FSI models. Reducing flap mobility by increasing the Young’s modulus of the flap slows down the thrombus growth. Compared to the rigid model, the predicted thrombus volume is 25% larger using the FSI-thrombosis model with a relatively mobile flap. Furthermore, our FSI-thrombosis model can capture the gradual effect of thrombus growth on the flow field, leading to flow obstruction in the FL, increased blood viscosity and reduced flap motion. This model is a step closer toward simulating realistic thrombus growth in aortic dissection, by taking into account the effect of intimal flap and vessel wall motion.

     

Fuzzy rule-based Fine–Kinney risk assessment approach for rail transportation systems

Rail transportation is one of the most crucial public transportation types for big and crowded cities. In rail transportation systems, stakeholders face serious issues involved in workshops, stations, lines and their environments, and general office buildings. In order to reach an increased awareness and better occupational health and safety (OHS) management, a new risk assessment approach is proposed in this study. This approach includes a combination of Fine–Kinney method and a fuzzy rule-based expert system. It captures nonlinear causal relationships between Fine–Kinney parameters. Since there is a high level of vagueness involved in the OHS risk assessment data, the rule-based expert system is developed for probability (P), exposure (E), and consequence (C) for evaluating risk score. A case study is carried out in a rail transportation system in Istanbul/Turkey, and a comparison with the classical Fine–Kinney method is discussed. Results of the case study reveal risk clusters and corresponding control measures that should be taken into consideration. The study methodologically contributes to risk assessment in the knowledge, while case study in a real rail transportation system offers an insight into public transport industry in safety improvement.     

Scientific data and theories for salmonellosis dose–response assessment

An “expansive” risk assessment approach is illustrated, characterizing dose–response relationships for salmonellosis in light of the full body of evidence for human and murine superorganisms. Risk assessments often require analysis of costs and benefits for supporting public health decisions. Decision-makers and the public need to understand uncertainty in such analyses for two reasons. Uncertainty analyses provide a range of possibilities within a framework of present scientific knowledge, thus helping to avoid undesirable consequences associated with the selected policies. And, it encourages the risk assessors to scrutinize all available data and models, thus helping avoid subjective or systematic errors. Without the full analysis of uncertainty, decisions could be biased by judgments based solely on default assumptions, beliefs, and statistical analyses of selected correlative data. Alternative data and theories that incorporate variability and heterogeneity for the human and murine superorganisms, particularly colonization resistance, are emerging as major influences for microbial risk assessment. Salmonellosis risk assessments are often based on conservative default models derived from selected sets of outbreak data that overestimate illness. Consequently, the full extent of uncertainty of estimates of annual number of illnesses is not incorporated in risk assessments and the presently used models may be incorrect.     

An integrated in silico approach to understand protein–protein interactions: human meprin-β with fetuin-A

Abstract

Human meprin-β, a zinc metalloprotease belonging to the astacin family, have been found to be associated with many pathological conditions like inflammatory bowel disease, fibrosis and neurodegenerative disease. The inhibition of meprin-β by various inhibitors, both macromolecular and small molecules, is crucial in the control of several diseases. Human fetuin-A, a negative acute phase protein involved in inflammatory disease, has recently been identified as an endogenous inhibitor for meprin-β. In this computational study, an integrated in silico approach was performed using existing structural information of meprin-β coupled with ab initio modelling of human fetuin-A to predict a rational model of the complex through protein–protein docking. Further, the models were optimized and validated to generate an ensemble of conformations through extensive molecular dynamics simulation. Virtual alanine scanning mutagenesis was explored to identify hotspot residues on both proteins significant for protein–protein interaction (PPI). The results of the study provide structural insight into PPI between meprin-β and fetuin-A which can be useful in designing molecules to modulate meprin-β activity.

Communicated by Ramaswamy H. Sarma     

Reaction modelling and simulation to assess the integrated use of transketolase and ω-transaminase for the synthesis of an aminotriol

The most attractive, as well as challenging, multistep organic syntheses would preferably be carried out in a single reactor, as a one-pot synthesis. For biocatalytic syntheses, multistep reactions in one-pot mode bring a number of advantages, while at the same time raising unique challenges such as the compatibility of different biocatalysts. In this paper, we have developed a transketolase–transaminase (TK-TAm) two-step one-pot aminotriol synthesis reaction model, which integrates reaction kinetic models with process characterization (consisting of component degradation as a function of pH and concentration, aldehyde toxicity towards the enzyme, and ketol donor and acceptor side-reactions with TAm). Based on the analysis of the effect of the TAm/TK activity ratio on product yield, simulations provided guidance for further process and biocatalyst development.     

An overview of integrated hydro-ecological studies in the MELMARINA Project: monitoring and modelling coastal lagoons—making management tools for aquatic resources in North Africa

As landscape disturbance and climate conspire to accelerate global environmental change towards unprecedented levels in the twenty-first century, the populated coastal regions of many countries are facing major threats to sustainability. Coastal water resources are particularly vulnerable in dry regions. In view of the expected severity of future environmental change in the Southern Mediterranean Region, the European Commission supported an integrated multidisciplinary project, MELMARINA, on monitoring and modelling coastal lagoons in Morocco, Tunisia and Egypt. This is a region where water management for people and for agriculture has been intense particularly during the twentieth century, yet long-term environmental monitoring and management of wetland ecosystems are under developed. Not only are biodiversity aspects at risk in coastal lagoons and wetlands but the goods and services that affect human welfare are also generally in decline. Co-ordinated hydro-ecological monitoring at key wetland lagoons was begun in 2003 with a view to establishing environmental baselines and calibrating site-specified hydro-ecological models. This article introduces the project and its results that range from lagoon typification and hydro-ecology to the application of hydro-ecological models. Detailed results and evaluations are presented in a linked series of themed scientific articles within this special issue. The present condition of the lagoons investigated essentially results from various hydrological modifications combined with eutrophication problems, yet all still remain valuable aquatic ecosystems. Adequate monitoring data are an essential part of reliable predictive modelling and, despite several data gaps, nutrient load reduction scenarios were undertaken to help target restoration aims. Implementation of aspects of the EU Water Framework Directive for achieving good ecological status of transitional waters is advocated. Nevertheless, as the twenty-first century advances the effects of global climate change are expected to amplify current stresses making intervention restoration and adaptation management even more imperative. Long-term sustainability depends upon detecting and measuring environmental change (long-term water quality and ecological quality) and incorporating the results into appropriate hydro-ecological models to facilitate the development of appropriate management initiatives. Guest editors: J. R. Thompson & R. J. Flower Hydro-ecological Monitoring and Modelling of North African Coastal Lagoons     

An Iodine-Chemisorption Binder for High-Loading and Shuttle-Free Zn–Iodine Batteries

Aqueous zinc–iodine (Zn–I₂) batteries have attracted considerable research interest as an alternative energy storage system due to their high specific capacity, intrinsic safety, and low cost. However, the notorious shuttle effect of soluble polyiodides causes severe capacity loss and poor electrochemical reversibility, restricting their practical usage. Herein, this study reports a bifunctional binder (polyacrylonitrile copolymer, as known as LA133) with strong iodine-chemisorption capability for aqueous Zn–I₂ batteries to suppress polyiodide shuttling. From both calculation and experimental data, this study reveals that the amide and carboxyl groups in LA133 binder can strongly bond to polyiodides, significantly immobilizing them at cathode side. As a result, fewer byproducts, slower hydrogen evolution, and lesser Zn dendrite in the Zn–I₂ battery are observed. Consequently, the battery shows high specific capacity (202.8 mAh g⁻¹) with high iodine utilization efficiency (96.1%), and long cycling lifespan (2700 cycles). At the high mass loading of 7.82 mg cm⁻², the battery can still retain 83.3% of its initial capacity after 1000 cycles. The specific capacity based on total cathode slurry mass reaches 71.2 mAh g⁻¹, higher than most of the recent works. The strategy opens a new avenue to address the shuttling challenge of Zn–I₂ batteries through bifunctional binder.     

Electrophoretic protein analysis for the identification of doubled haploid 1A–1R, 1B–1R wheat-rye double translocation lines and for the assessment of their genetic stability

Eighteen available doubled haploid wheat lines with a cytologically proven 1A–1R, 1B–1R double translocation, which where derived via anther culture from four crosses of the 1A–1R wheat-rye translocation cv Amigo with several 1B–1R wheat-rye translocation forms, were subjected to electrophoretic seed protein analysis. Besides, the five parents used in the crosses and some other wheat cultivars and doubled haploid lines (19 with a 1B–1R single translocation, 10 with a 1A–1R translocation and 7 without any 1R translocation) were also included in the investigation. It was found that the gliadin patterns visualized after SDS polyacrylamide gel electrophoresis of alcohol-soluble seed protein extracts can differentiate not only 1B–1R and 1A–1R translocation forms from wheats without any 1R-translocation chromosome, but also 1B–1R and 1A–1R wheats from each other. Moreover, 1A–1R, 1B–1R double translocation lines can be distinguished as well due to characteristic differences revealed between 1A–1R and 1B–1R translocation forms. Thus, all of tested dh₁- and dh₂-grains of the double translocation lines showed the expected doublet: the 1A–1R translocation (Amigo)-typical rye band and the 1B–1R translocation (Kawkas)-typical rye band. Consequently, gliadin patterns estimated after SDS electrophoresis may be used as markers for the fast detection of the desired 1A–1R, 1B–1R double translocation forms among 1A–1R single translocation lines, 1B–1R single translocation lines and lines without any 1R-translocation in the progenies of appropriate crosses. Furthermore, by means of gliadin tests on the dh₂-generation the excellent stability of the double translocation 1A–1R, 1B–1R during more than one propagation phase has been proven. Estimations of high-molecular weight (HMW) glutenin subunits coded by 1A and 1B chromosomes are compatible with the double translocation constitution. A few deviating results can be explained by crossing-over events. Seed protein analysis revealed that it is possible to produce 1A–1R, 1B–1R double translocation lines with good glutenin compositions provided that adequate favourable parents are used.Former name: Department of Physiology of Institute for Cereal Research     

Where can switchgrass production be more profitable than corn and soybean? An integrated subfield assessment in Iowa,USA

Perennial bioenergy crops are considered an important feedstock for a growing bioeconomy. However, in the USA, production of biofuel from these dedicated, nonfood crops is lagging behind federal mandates and markets have yet to develop. Most studies on the economic potential of perennial biofuel crops have concluded that even high‐yielding bioenergy grasses are unprofitable compared to corn/soybeans, the prevailing crops in the United States Corn Belt. However, they did not account for opportunities precision agriculture presents to integrate perennials into agronomically and economically underperforming parts of corn/soybean fields. Using publicly available subfield data and market projections, we identified an upper bound to the areas in Iowa, United States, where the conversion from corn/soybean cropland to an herbaceous bioenergy crop, switchgrass, could be economically viable under different price, land tenancy, and yield scenarios. Assuming owned land, medium crop prices, and a biomass price of US$ 55 Mg^?1, we showed that 4.3% of corn/soybean cropland could break even when converted to switchgrass yielding up to 10.08 Mg ha^?1. The annualized change in net present value on each converted subfield patch ranged from just above US$ 0 ha^?1 to 692 ha^?1. In the three counties of highest economic opportunity, total annualized producer benefits from converting corn/soybean to switchgrass summed to US$ 2.6 million, 3.4 million, and 7.6 million, respectively. This is the first study to quantify an upper bound to the potential private economic benefits from targeted conversion of unfavorable corn/soybean cropland to switchgrass, leaving arable land already under perennial cover unchanged. Broadly, we conclude that areas with high within‐field yield variation provide highest economic opportunities for switchgrass conversion. Our results are relevant for policy design intended to improve the sustainability of agricultural production. While focused on Iowa, this approach is applicable to other intensively farmed regions globally with similar data availability.     

An information-theoretic classification of amino acids for the assessment of interfaces in protein–protein docking

Docking represents a versatile and powerful method to predict the geometry of protein–protein complexes. However, despite significant methodical advances, the identification of good docking solutions among a large number of false solutions still remains a difficult task. We have previously demonstrated that the formalism of mutual information (MI) from information theory can be adapted to protein docking, and we have now extended this approach to enhance its robustness and applicability. A large dataset consisting of 22,934 docking decoys derived from 203 different protein–protein complexes was used for an MI-based optimization of reduced amino acid alphabets representing the protein–protein interfaces. This optimization relied on a clustering analysis that allows one to estimate the mutual information of whole amino acid alphabets by considering all structural features simultaneously, rather than by treating them individually. This clustering approach is fast and can be applied in a similar fashion to the generation of reduced alphabets for other biological problems like fold recognition, sequence data mining, or secondary structure prediction. The reduced alphabets derived from the present work were converted into a scoring function for the evaluation of docking solutions, which is available for public use via the web service score-MI: http://score-MI.biochem.uni-erlangen.de     

Effects of saline root environment (NaCl) on nitrate and potassium uptake kinetics for rose plants: a Michaelis–Menten modelling approach

Greenhouse-grown cut flower roses are often irrigated with moderately saline irrigation water. The salt/ballast ions are either present initially in poor quality raw water or reclaimed municipal water, or accumulated in greenhouse irrigation water that is captured and reused. Such ions can inhibit root absorption of essential nutrients. The objective of this work was to quantify the influence of NaCl concentration on the uptake of nitrate and potassium by roses and develop a predictive model of uptake inhibition based on NaCl, NO₃ ^?, and K⁺ concentration. One year-old rose plants (Rosa spp. ‘Kardinal’ on ‘Natal Briar’ rootstock) were moved into growth chambers where nitrogen and potassium depletion were monitored during 6 days. Eight different initial NaCl treatments varying from zero to 65 mol m^?3 were used and within these there were two initial NO₃ ^? and K⁺ concentrations: high concentration (HC, 7.0 mol m^?3 and 2.6 mol m^?3 NO₃ ^? and K⁺ respectively) or low concentration (LC, 3.5 mol m^?3 and 1.3 mol m^?3 NO₃ ^? and K⁺ respectively). Plant NO₃ ^? uptake was negatively affected by NaCl concentration. NO₃ ^? maximum influx (I_max) declined from 5.1 µmol to 2.5 µmol per gram of plant dry weight per hour as NaCl concentration increased from zero to 65 mol m^?3. A modified Michaelis–Menten (M–M) equation taking into account inhibition by NaCl provided the best fit for NO₃ ^? uptake in response to varying NaCl concentration. K⁺ uptake was unaffected by NaCl concentration. A M–M equation that did not include inhibition was suitable for describing K⁺ uptake at varying NaCl concentration. The resulting empirical models could assist with decision making, such as: adjustment of NO₃ ^? fertilization based on NaCl concentration, necessity of water desalinization, or determination of the desired leaching fraction.     

Antibody gene therapy： an attractive approach for the treatment of cancers and other chronic diseases

Monoclonal antibodies(mAb)have been successfullyapplied to the treatment of chronic diseases,such as cancer,inflammation and immune diseases.With the technicaladvances in antibody engineering,development of smallrecombinant antibody fragments as high affinity therapeu-tics with reduced immunogenicity has become under thespotlight.A popular format of the engineered recombinantantibody fragments is the single-chain fixed-variable(scFv)molecules,in which the VH and VL regions of the parentalantibody are jointed together by a polypeptide linker.ThescFv fragment retains the target specificity and antigen-binding affinity of the intact antibody,and can be geneti-cally designed and produced in large quantity by ectopicallyexpressing both VH and VL regions from a single cDNAin cells.Due to its smaller size,the scFv molecule showsimproved pharmacokinetics in tumor penetration and isbetter tolerated by the host immune system.Despite thesepotential advantages of using scFv molecules for immu-notherapy,especially for chronic diseases such as cancers,the treatment efficacy,however,is often compromised bythe rapid blood clearance and insufficient concentration ofthe infused scFv fragments at the target site.To achievehigh local concentrations in the target tissues,large amountof the recombinant scFv proteins(hundreds milligrams or     

Is RAD‐seq suitable for phylogenetic inference? An in silico assessment and optimization

Inferring phylogenetic relationships between closely related taxa can be hindered by three factors: (1) the lack of informative molecular variation at short evolutionary timescale; (2) the lack of established markers in poorly studied taxa; and (3) the potential phylogenetic conflicts among different genomic regions due to incomplete lineage sorting or introgression. In this context, Restriction site Associated DNA sequencing (RAD‐seq) seems promising as this technique can generate sequence data from numerous DNA fragments scattered throughout the genome, from a large number of samples, and without preliminary knowledge on the taxa under study. However, divergence beyond the within‐species level will necessarily reduce the number of conserved and non‐duplicated restriction sites, and therefore the number of loci usable for phylogenetic inference. Here, we assess the suitability of RAD‐seq for phylogeny using a simulated experiment on the 12 Drosophila genomes, with divergence times ranging from 5 to 63 million years. These simulations show that RAD‐seq allows the recovery of the known Drosophila phylogeny with strong statistical support, even for relatively ancient nodes. Notably, this conclusion is robust to the potentially confounding effects of sequencing errors, heterozygosity, and low coverage. We further show that clustering RAD‐seq data using the BLASTN and SiLiX programs significantly improves the recovery of orthologous RAD loci compared with previously proposed approaches, especially for distantly related species. This study therefore validates the view that RAD sequencing is a powerful tool for phylogenetic inference.