A graph-based approach to defend agro-ecological systems against water vole outbreaks

The cyclic spread of montane water vole populations in the grasslands of the Jura plateaus causes severe economic, ecological, and public-health problems. Since this phenomenon cannot be managed by massive use of the anticoagulant rodenticide bromadiolone, the challenge is to limit it by reducing regional-level connectivity through landscaping and agro-environmental interventions such as planting hedgerows, ploughing, and cultivating cereals. We used landscape graphs – a spatial modelling approach based on graph theory – to represent the grassland network and identify key areas for intervention. Several strategies were compared in terms of their capacity to fulfil operational requirements by interchanging patches and meta-patches as nodes of the graph, and least-cost distances and resistance distances to weight links. The combination of meta-patches and resistance distances provides a relevant basis on which to design concrete action to decrease regional-level connectivity of grasslands. The results also indicate that the usual removal method applied to the links of the graph would benefit from data on the statistical distribution of cost values along the shortest paths. More broadly, this suggests the modelling approach should be better matched the actual field interventions if the connectivity analysis is to be operational.     

Feasibility of using combined EMG and kinematic signals for prosthesis control: A simulation study using a virtual reality environment

Transhumeral amputation has a significant effect on a person’s independence and quality of life. Myoelectric prostheses have the potential to restore upper limb function, however their use is currently limited due to lack of intuitive and natural control of multiple degrees of freedom. The goal of this study was to evaluate a novel transhumeral prosthesis controller that uses a combination of kinematic and electromyographic (EMG) signals recorded from the person’s proximal humerus. Specifically, we trained a time-delayed artificial neural network to predict elbow flexion/extension and forearm pronation/supination from six proximal EMG signals, and humeral angular velocity and linear acceleration. We evaluated this scheme with ten able-bodied subjects offline, as well as in a target-reaching task presented in an immersive virtual reality environment. The offline training had a target of 4° for flexion/extension and 8° for pronation/supination, which it easily exceeded (2.7° and 5.5° respectively). During online testing, all subjects completed the target-reaching task with path efficiency of 78% and minimal overshoot (1.5%). Thus, combining kinematic and muscle activity signals from the proximal humerus can provide adequate prosthesis control, and testing in a virtual reality environment can provide meaningful data on controller performance.     

Green pathways: Metabolic network analysis of plant systems

Metabolic engineering of plants with enhanced crop yield and value-added compositional traits is particularly challenging as they probably exhibit the highest metabolic network complexity of all living organisms. Therefore, approaches of plant metabolic network analysis, which can provide systems-level understanding of plant physiology, appear valuable as guidance for plant metabolic engineers. Strongly supported by the sequencing of plant genomes, a number of different experimental and computational methods have emerged in recent years to study plant systems at various levels: from heterotrophic cell cultures to autotrophic entire plants. The present review presents a state-of-the-art toolbox for plant metabolic network analysis. Among the described approaches are different in silico modeling techniques, including flux balance analysis, elementary flux mode analysis and kinetic flux profiling, as well as different variants of experiments with plant systems which use radioactive and stable isotopes to determine in vivo plant metabolic fluxes. The fundamental principles of these techniques, the required data input and the obtained flux information are enriched by technical advices, specific to plants. In addition, pioneering and high-impacting findings of plant metabolic network analysis highlight the potential of the field.     

A neural network prediction of environmental determinants of Anopheles sinensis knockdown resistance mutation to pyrethroids in China

Selection pressure caused by long‐term intensive use of insecticides is the key driving force in resistance development. Additional parameters such as environmental conditions may affect both the mosquito response to insecticides and the selection of resistance mechanisms. In this context, we analyzed the environmental determinants of kdr prevalence in Anopheles sinensis across China. We collected kdr frequency from 48 sites across central and southern China, together with key environmental factors including long‐term climatic data, topographic features, main crops, and land cover types. Trend surface analysis found that the distribution of kdr frequency can be partitioned into three regions, namely central China (kdr frequency >80%), western China (kdr frequency varies from 0% to 60%), and southern China (kdr frequency <10%). Seven predictor variables were selected based on a radial basis function neural network model. A multilayer perceptron (MLP) network model revealed that the number of crops in a year was the most important predictor for the kdr mutation rate. Topography, long‐term mean climate and land cover all contributed to the kdr mutation rate. The observed mean kdr frequency was 53.0% and the MLP network model‐predicted mean was 52.6%, a 0.1% relative error. Predicted kdr frequencies closely matched the observed values. The model explained 92% of the total variance in kdr frequency. The results indicated that kdr was associated with the intensity of pesticide usage. Crop cultivation information, together with environmental factors, may well predict the spatial heterogeneity of kdr mutations in An. sinensis in China.     

The impact of a knowledge translation intervention employing educational outreach and a point-of-care reminder tool vs standard lay health worker training on tuberculosis treatment completion rates: study protocol for a cluster randomized controlled trial

BackgroundDespite availability of effective treatment, tuberculosis (TB) remains an important cause of morbidity and mortality globally, with low- and middle-income countries most affected. In many such settings, including Malawi, the high burden of disease and severe shortage of skilled healthcare workers has led to task-shifting of outpatient TB care to lay health workers (LHWs). LHWs improve access to healthcare and some outcomes, including TB completion rates, but lack of training and supervision limit their impact. The goals of this study are to improve TB care provided by LHWs in Malawi by refining, implementing, and evaluating a knowledge translation strategy designed to address a recognized gap in LHWs’ TB and job-specific knowledge and, through this, to improve patient outcomes.Methods/designWe are employing a mixed-methods design that includes a pragmatic cluster randomized controlled trial and a process evaluation using qualitative methods. Trial participants will include all health centers providing TB care in four districts in the South East Zone of Malawi. The intervention employs educational outreach, a point-of-care reminder tool, and a peer support network. The primary outcome is proportion of treatment successes, defined as the total of TB patients cured or completing treatment, with outcomes taken from Ministry of Health treatment records. With an alpha of 0.05, power of 0.80, a baseline treatment success of 0.80, intraclass correlation coefficient of 0.1 based on our pilot study, and an estimated 100 clusters (health centers providing TB care), a minimum of 6 patients per cluster is required to detect a clinically significant 0.10 increase in the proportion of treatment successes. Our process evaluation will include interviews with LHWs and patients, and a document analysis of LHW training logs, quarterly peer trainer meetings, and mentorship meeting notes. An estimated 10–15 LHWs and 10–15 patients will be required to reach saturation in each of 2 planned interview periods, for a total of 40–60 interview participants.DiscussionThis study will directly inform the efforts of knowledge users within TB care and, through extension of the approach, other areas of care provided by LHWs in Malawi and other low- and middle-income countries.

Trial registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT02533089","term_id":"NCT02533089"}}NCT02533089. Registered 20 August 2015. Protocol Date/Version 29 May 2016/Version 2.

Electronic supplementary material

The online version of this article (doi:10.1186/s13063-016-1563-2) contains supplementary material, which is available to authorized users.     

General stress proteins in Bacillus subtilis

Abstract Bacillus cells frequently faced with various adverse environmental factors in nature have evolved different adaptational strategies. The induction of stress proteins is an essential component of this adaptational network. In Bacillus subtilis there are two groups of stress proteins. The first group is factor specific, whereas the second group is induced by growth restrictive conditions in general. The relationship between the stringent response and the induction of stress proteins is discussed.     

洋葱鳞茎内表皮细胞中的微管

用超薄切片和原生质体负染的方法,在电镜下观察到洋葱鳞茎内表皮细胞周质微管的存在。其出现时间、分布状况以及排列形态,基本上与考马斯亮蓝染色法观察到的网状结构物相一致。讨论了包被囊泡和微管组织中心可能的作用。     

Post Golgi apparatus structures and membrane removal in plants

Summary In nongrowing secretory cells of plants, large quantities of membrane are transferred from the Golgi apparatus to the plasma membrane without a corresponding increase in cell surface area or accumulation of internal membranes. Movement and/or redistribution of membrane occurs also in trans Golgi apparatus cisternae which disappear after being sloughed from the dictyosome, and in secretory vesicles which lose much of their membrane in transit to the cell surface. These processes have been visualized in freeze-substituted corn rootcap cells and a structural basis for membrane loss during trafficking is seen. It involves three forms of coated membranes associated with the trans parts of the Golgi apparatus, with cisternae and secretory vesicles, and with plasma membranes. The coated regions of the plasma membrane were predominantly located at sites of recent fusion of secretory vesicles suggesting a vesicular mechanism of membrane removal. The two other forms of coated vesicles were associated with the trans cisternae, with secretory vesicles, and with a post Golgi apparatus tubular/vesicular network not unlike the TGN of animal cells. However, the trans Golgi network in plants, unlike that in animals, appears to derive directly from the trans cisternae and then vesiculate. The magnitude of the coated membrane-mediated contribution of the endocytic pathway to the formation of the TGN in rootcap cells is unknown. Continued formation of new Golgi apparatus cisternae would be required to maintain the relatively constant form of the Golgi apparatus and TGN, as is observed during periods of active secretion.