Modular Set Research Articles

Expanding One-Pot Cell-Free Protein Synthesis and Immobilization for On-Demand Manufacturing of Biomaterials.

Fabrication of protein-based biomaterials is an arduous and time-consuming procedure with multiple steps. In this work, we describe a portable toolkit that integrates both cell-free protein synthesis (CFPS) and protein immobilization in one pot just by mixing DNA, solid materials, and a CFPS system. We have constructed a modular set of plasmids that fuse the N-terminus of superfolded green fluorescent protein (sGFP) with different peptide tags (poly(6X)Cys, poly(6X)His, and poly(6X)Lys), which drive the immobilization of the protein on the tailored material (agarose beads with different functionalities, gold nanorods, and silica nanoparticles). This system also enables the incorporation of azide-based amino acids into the nascent protein for its selective immobilization through copper-free click reactions. Finally, this technology has been expanded to the synthesis and immobilization of enzymes and antibody-binding proteins for the fabrication of functional biomaterials. This synthetic biological platform has emerged as a versatile tool for on-demand fabrication of therapeutic, diagnostic, and sensing biomaterials.

MODULAR ROBOT DESIGN AND APPLICATION FOR CHILDREN’S DEVELOPMENT IN MECHATRONICS AND AUTOMATION

The effect of activity sets in the education of primary students in science class was examined using modular automation sets in this study. It is aimed to understand their scientific process skills and motivation towards other integrated technologies. The study group of this research consists of the 4th grade students of a private school on the Anatolian side of Istanbul. Students were given an activity to carry out within the scope of this research by using these automation sets which were procured by the school. A model from the set was designed by the students and the students were requested to make improvements on this model with the guidance and directions of their teacher. The changed parts in the improved model were designed and printed out from a 3D printer. A touch sensor was installed on the finished model and the program software was reconstructed. Finally the students in the study group were subjected to a comprehension test and the results were evaluated. The result of the study shows that students have positive inclination towards building and programming their own designs. Also the use of visual blocks in the system software has shown an increase in student attention and it’s been observed that this contributes to easier understanding of the software by the students.

Optimization of postponement process for a two stage modular manufacturer

Purpose Firms have increasingly been using postponement as one of the supply chain strategies to respond to rapid changes in customers’ demands. The purpose of this study is to identify the optimum level of postponement in the context of two-stage modular manufacturing setting, given the information about trade-off between level of postponement and associated cost is known. Design/methodology/approach A critical ratio for the manufacturer to determine whether postponement process is to be continued or not is identified. An algebraic formula for the critical ratio is obtained using which managers can identify the optimal level of postponement using differential calculus. Findings The authors have analytically arrived at the solution which gives the manager the optimum level of postponement. Here, they identify the optimum level of postponement in the context of manufacturing, given the trade-off between level of postponement and associated cost. They calculate the expected total profit with different demand scenarios. The parametric analysis in this study shows that if price of the product decreases, then optimal amount of postponement also decreases. Research limitations/implications It is important for a manager to identify the optimum level of postponement. In practice, managers usually take this decision on the basis of their judgment and trivial analysis of trade-off between costs and benefits of postponement. Originality/value In this study, the authors find an optimum amount of postponement for a firm to find an optimal balance between the cost and the benefit garnered by the postponement process.

Temperature and velocity measurements in a buoyant flow induced by a heat source array on a vertical plate

Heat source arrays are common in engineering applications. Natural convection is a reliable and silent cooling strategy. Therefore, an array of flush-mounted heat sources has been studied under conjugate conduction and natural convection condition. This studies was performed for a system with relatively large dimensions, typical for power electronics, and a modified Rayleigh number up to 2·1010. A modular set of heaters was designed to vary the distribution of heat sources on the plate and investigate the influence of the spacing. Velocity and temperature were measured in the convective flow with particle image velocimetry and micro-thermocouple. The velocity field was analyzed with proper orthogonal decomposition. The first instabilities of the convective flows were described. The results gave a better understanding of the heat transfers in these configurations and are valuable for model validation.

Rapid salinity measurements for fluid flow characterisation using minimal invasive sensors

For the hydrodynamic characterisation of reactors handling aqueous liquids, especially in conjunction with the validation of numerical simulations, data with high temporal resolution is essential. This paper describes the design of a rapid, flat, and low-cost sensor array for parallel salinity measurements, which allows to perform the required measurements in nearly any reactor type with minimal impact on the flow characteristics due to its very thin (125μm) and flexible structure. Sample measurements for the sensor array system are shown using a step change in aqueous salinity and the resulting response of a thin-layer cascade algae reactor unit as well as performing measurements of a pulse in salinity in the circularly operated algae reactor containing a feedback loop. The system’s response, mixing, and cycle time can be easily extracted from the generated data sets. The sensors provide measurements with an accuracy of about 2% for a linear range of 0–10gl−1 NaCl solution.In its default configuration one device consists of up to eight sensors, which are distributed on two stripes (220×25mm, 125μm thick) each containing four sensor spots, that are positioned 5cm apart from each other. The modular set up of the sensor array facilitates simple modification depending on individual requirements.

A modular set of synthetic spectral energy distributions for young stellar objects

In this paper, I present a new set of synthetic spectral energy distributions (SEDs) for young stellar objects (YSOs) spanning a wide range of evolutionary stages, from the youngest deeply embedded protostars to pre-main-sequence stars with few or no disks. These models include significant improvements on the previous generation of published models: in particular, the new models cover a much wider and more uniform region of parameter space, do not include highly model-dependent parameters, and include a number of improvements that make them more suited to modeling far-infrared and sub-mm observations of forming stars. Rather than all being part of a single monolithic set of models, the new models are split up into sets of varying complexity. The aim of the new set of models is not to provide the most physically realistic models for young stars, but rather to provide deliberately simplified models for initial modeling, which allows a wide range of parameter space to be explored. I present the design of the model set, and show examples of fitting these models to real observations to show how the new grid design can help us better understand what can be determined from limited unresolved observations. The models, as well as a Python-based fitting tool are publicly available to the community.

Commentary: Aiming for Study Comparability in Parkinson's Disease: Proposal for a Modular Set of Biomarker Assessments to be Used in Longitudinal Studies.

We read the conclusions of Lerche et al. (2016) with great interest. Various definitions exist in the literature for biological markers (often shortened to biomarkers). In medicine, a biomarker may refer to an indicator based upon which an inference about the person's health can be made. The National Health Institute's Biomarkers Definitions Working Group (Biomarkers Definitions Working Group, 2001) defines a biomarker as “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacological responses to a therapeutic intervention.” Despite the recent interest in finding biomarkers for Parkinson's disease (PD; as evident from the number of “Parkinson's disease biomarker” articles indexed by the MEDLINE® Database; see Figure ​Figure1),1), an acceptable biomarker for PD remains to be elusive. Given the complexity underpinning PD's pathological processes, a useful single biomarker is unlikely to encompass the plethora of disease facets. However, the diverse features of PD's aetiological process and manifestations lend it particularly suited to have a number of biomarkers (of different categories and types) that serve distinct purposes at various stages of the disease. Figure 1 Increasing numbers of PD biomarker-related articles, as indexed by MEDLINE® as of January 2016, are appearing in the literature. Challenges facing PD biomarker research As with other neurodegenerative disorders, several hurdles face biomarker discovery in PD. Such challenges include the general complexity of the human CNS, limited access and availability of tissue for histological diagnosis during the patient's lifetime and the restricted number of clinical end-points and the lack of validation models for present ones (Dunckley et al., 2005). Added to these general obstacles are the diagnostic uncertainties surrounding PD, including disease heterogeneity and the potential for atypical parkinsonian syndromes. The multiplicity of disease aspects of PD make it difficult for a single all-purpose biomarker to ever exist. This is evident from the current lack of such a “Holy Grail” biomarker to date. By the same token, “reductionist”-type biomarkers focusing on single aspects of PD molecular neuropathology are unlikely to be overly clinically useful in the general schema of disease (Mielke and Maetzler, 2014). It seems, therefore, that several biomarkers of different types may be utilized in conjunction to identify the person's disease stage. Taking PD diagnosis as an example, no one single biomarker to date has demonstrated perfect sensitivity and specificity; even post-mortem pathological examinations can be inconclusive at times (Lees et al., 2009; Berg et al., 2013). Instead, the suggested tier-based system of different types of biomarkers (e.g., clinical assessment by a specialist, biofluid analysis, genetic testing and/or imaging studies) used in concert is much more likely to yield much needed diagnostic accuracy (Streffer et al., 2012; Schlossmacher and Mollenhauer, 2014).

New optimal modular Sidon sets

Sidon set and its related problems including modular Sidon set have many applications in information theory and communication system. They have been widely studied in radio frequency selection, radio antennae placement and error correcting codes. In this paper, we establish a backtracking algorithm with pruning techniques to construct modular Sidon sets. By using master-slave parallel model, 50 new optimal modular Sidon sets are constructed.

New optimal modular Sidon sets

Sidon set and its related problems including modular Sidon set have many applications in information theory and communication system. They have been widely studied in radio frequency selection, radio antennae placement and error correcting codes. In this paper, we establish a backtracking algorithm with pruning techniques to construct modular Sidon sets. By using master-slave parallel model, 50 new optimal modular Sidon sets are constructed.

Application of SiPM for Modern Nuclear Physics Practical Workshop

Silicon PhotoMultipliers (SiPM) are state of the art light detectors with very high single photon sensitivity and photon number resolving capability, representing a breakthrough in several fundamental and applied Science domains. So, introduction of SiPM in to the education is important process increasing the number of specialists involved in the SiPM development and application. As a result of collaborative efforts between industry and academic institutions modular set of instruments based on SiPM light sensors has been developed by CAEN s.p.a. It is developed for educational purposes mainly and allows performing a series of experiments including photon detection, gamma spectrometry, cosmic ray observation and beta and gamma ray absorption. In addition, an educational experiments based on a SiPM set-up guides students towards a comprehensive knowledge of SiPM technology while experiencing the quantum nature of light and exploring the statistical properties of the light pulses emitted by a LED. The toolbox is actually an open platform in continuous evolution thanks to the contribution of the research community and cooperation with high schools.

Experimental research regarding static rigidity in transversal direction of “normal“ module

The paper presents some experimental results regarding the total deformation of ”normal” modules found in the structure of modular sets. The study presents the main aspect regarding the experimental methodology used for the determination of static rigidity in the transversal direction, the measuring scheme and test stand used. Modules deformations were analysed, under the action of transversal static force, in the presence of axial pretension force, using advanced equipment. The research conducted showed that modules with symmetric structure present increased stiffness compared to the asymmetric modules and T cross channels.

MMinte: an application for predicting metabolic interactions among the microbial species in a community.

BackgroundThe explosive growth of microbiome research has yielded great quantities of data. These data provide us with many answers, but raise just as many questions. 16S rDNA—the backbone of microbiome analyses—allows us to assess α-diversity, β-diversity, and microbe-microbe associations, which characterize the overall properties of an ecosystem. However, we are still unable to use 16S rDNA data to directly assess the microbe-microbe and microbe-environment interactions that determine the broader ecology of that system. Thus, properties such as competition, cooperation, and nutrient conditions remain insufficiently analyzed. Here, we apply predictive community metabolic models of microbes identified with 16S rDNA data to probe the ecology of microbial communities.ResultsWe developed a methodology for the large-scale assessment of microbial metabolic interactions (MMinte) from 16S rDNA data. MMinte assesses the relative growth rates of interacting pairs of organisms within a community metabolic network and whether that interaction has a positive or negative effect. Moreover, MMinte’s simulations take into account the nutritional environment, which plays a strong role in determining the metabolism of individual microbes. We present two case studies that demonstrate the utility of this software. In the first, we show how diet influences the nature of the microbe-microbe interactions. In the second, we use MMinte’s modular feature set to better understand how the growth of Desulfovibrio piger is affected by, and affects the growth of, other members in a simplified gut community under metabolic conditions suggested to be determinant for their dynamics.ConclusionBy applying metabolic models to commonly available sequence data, MMinte grants the user insight into the metabolic relationships between microbes, highlighting important features that may relate to ecological stability, susceptibility, and cross-feeding. These relationships are at the foundation of a wide range of ecological questions that impact our ability to understand problems such as microbially-derived toxicity in colon cancer.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1230-3) contains supplementary material, which is available to authorized users.

The Invention Coach: Integrating Data and Theory in the Design of an Exploratory Learning Environment

This design case describes the development of the Invention Coach, an intelligent exploratory learning environment (ELE) for the constructivist activity of Invention. The Invention Coach scaffolds students as they invent mathematical formulas to describe contrasting cases. In this paper, we detail our process and rationale for three key design decisions made with the goal of providing optimal guidance for Invention: (a) engaging in systematic analysis of teachers guiding students as a starting point for development; (b) developing a style of guidance that problematizes students’ work through constraints, contrasts, and prompts for explanation; and (c) structuring the space through a nonlinear, modular set of activities focused on problem subgoals. We revisit the age-old assistance dilemma, discussing the unique difficulties of designing guidance and support in a computer environment for exploratory learning. Throughout, we discuss the tensions between providing adequate guidance and encouraging student exploration. We end by considering the trade-offs and unforeseen challenges that have come out of our design.

Prodromal Markers in Parkinson’s Disease: Limitations in Longitudinal Studies and Lessons Learned

A growing body of evidence supports a prodromal neurodegenerative process preceding the clinical onset of Parkinson’s disease (PD). Studies have identified several different prodromal markers that may have the potential to predict the conversion from healthy to clinical PD but use considerably different approaches. We systematically reviewed 35 longitudinal studies reporting prodromal PD features and evaluated the methodological quality across 10 different predefined domains. We found limitations in the following domains: PD diagnosis (57% of studies), prodromal marker assessments (51%), temporal information on prodromal markers or PD diagnosis (34%), generalizability of results (17%), statistical methods (accounting for at least age as confounder; 17%), study design (14%), and sample size (9%). However, no limitations regarding drop-out (or bias investigation), or report of inclusion/exclusion criteria or prodromal marker associations were revealed. Lessons learned from these limitations and additional aspects of current prodromal marker studies in PD are discussed to provide a basis for the evaluation of findings and the improvement of future research in prodromal PD. The observed heterogeneity of studies, limitations and analyses might be addressed in future longitudinal studies using a, yet to be established, modular minimal set of assessments improving comparability of findings and enabling data sharing and combined analyses across studies.

Fast estimation of space-robots inertia parameters: A modular mathematical formulation

This work aims to propose a new technique that considerably helps enhance time and precision needed to identify “Inertia Parameters (IPs)” of a typical Autonomous Space-Robot (ASR). Operations might include, capturing an unknown Target Space-Object (TSO), “active space-debris removal” or “automated in-orbit assemblies”. In these operations generating precise successive commands are essential to the success of the mission. We show how a generalized, repeatable estimation-process could play an effective role to manage the operation. With the help of the well-known Force-Based approach, a new “modular formulation” has been developed to simultaneously identify IPs of an ASR while it captures a TSO. The idea is to reorganize the equations with associated IPs with a “Modular Set” of matrices instead of a single matrix representing the overall system dynamics. The devised Modular Matrix Set will then facilitate the estimation process. It provides a conjugate linear model in mass and inertia terms. The new formulation is, therefore, well-suited for “simultaneous estimation processes” using recursive algorithms like RLS. Further enhancements would be needed for cases the effect of center of mass location becomes important. Extensive case studies reveal that estimation time is drastically reduced which in-turn paves the way to acquire better results.

Aiming for Study Comparability in Parkinson's Disease: Proposal for a Modular Set of Biomarker Assessments to be Used in Longitudinal Studies.

Parkinson's disease (PD) is an example for a complex field of research, which is driven by the multifactorial etiology, the heterogeneity in phenotype and the variability in disease progression, as well as the presence of a long pre-diagnostic period, called prodromal PD, lasting up to decades (Postuma et al., 2010). The very slow, so far inevitably progressive, neurodegenerative process and the multidimensional heterogeneity of symptoms in kind (motor and non-motor), time of onset and speed of progression call for prediction markers and progression markers to understand the onset of neurodegeneration and its course. These markers would also help to establish endpoints for neuroprotective treatment strategies aiming to modify disease progression. Because of the complexity, heterogeneity, and the progressive nature of PD, such predictive and progression markers can only be identified in large cohorts and in studies with a longitudinal design. A considerable number of longitudinal cohort studies in PD patients, as well as in individuals at risk, are currently being performed, and extensive effort has gone into the characterization of the individuals assessed. Although each study has its own value and merits, many important research questions cannot be answered as the numbers of participants are too small (e.g., when studying conversion to PD in at-risk populations). Moreover, the pivotal combination of data and findings across studies is hampered by the lack of comparability of symptoms/factors that are being assessed and the specific assessments that are being applied. Therefore, a common approach is needed to enable harmonization and combination of data across studies to define and validate predictive and progression markers. Based on the need for harmonized assessments of symptoms/markers in PD, the working group: Harmonization of biomarker assessment in longitudinal cohort studies in Parkinson's Disease (BioLoC-PD) of the Joint Programme for Neurodegenerative Diseases (JPND), set out to develop an assessment battery that includes the most useful clinical, laboratory, and brain imaging assessments for (longitudinal) studies in PD. We here describe the result of the process to find a way to harmonize assessments across studies and propose a modular set of biomarker assessments agreed upon by the group of experts who were included in the working group (all authors of this manuscript).

Periprosthetic humeral fractures: Strategies and techniques of revision arthroplasty

The primary aims when performing revision arthroplasty of periprosthetic humeral fractures (PHF) are preservation of bone stock, achieving fracture healing and preserving a stable prosthesis with the focus on regaining the preoperative shoulder-arm function. The indications for revision arthroplasty are given in PHF in combination with loosening of the stem. In addition, further factors must be independently clarified in the case of an anatomical arthroplasty. In this context secondary glenoid erosion as well as rotator cuff insufficiency are potential factors for an extended revision procedure. For the performance of revision surgery modular revision sets including long stems, revision glenoid and metaglene components as well as plate and cerclage systems are obligatory besides the explantation instrumentation. Despite a loosened prosthesis, a transhumeral removal of the stem along with a subpectoral fenestration are often required. Length as well as bracing of revision stems need to bridge the fracture by at least twice the humeral diameter. Moreover, in many cases a combined procedure using an additional distal open reduction and internal fixation (ORIF) plus cable cerclages as well as biological augmentation might be needed. Assuming an adequate preparation, the experienced surgeon is able to achieve a high fracture union rate along with an acceptable or even good shoulder function and to avoid further complications.

On Submodularity and Controllability in Complex Dynamical Networks

Controllability and observability have long been recognized as fundamental structural properties of dynamical systems, but have recently seen renewed interest in the context of large, complex networks of dynamical systems. A basic problem is sensor and actuator placement: choose a subset from a finite set of possible placements to optimize some real-valued controllability and observability metrics of the network. Surprisingly little is known about the structure of such combinatorial optimization problems. In this paper, we show that several important classes of metrics based on the controllability and observability Gramians have a strong structural property that allows for either efficient global optimization or an approximation guarantee by using a simple greedy heuristic for their maximization. In particular, the mapping from possible placements to several scalar functions of the associated Gramian is either a modular or submodular set function. The results are illustrated on randomly generated systems and on a problem of power electronic actuator placement in a model of the European power grid.

Dynamic Transient Responses of Muscle Fibers with a Heterogeneous Populations of Isoforms and Mutation

Predicting the dynamic behaviour of a muscle fibre containing a heterogeneous mixture of isoforms (e.g. fast and slow isoforms mutant and wt protein) is difficult since responses may be non-linear. We have implemented in a computational platform MUSICO the ability to predict the transient responses for a muscle fibre containing a variable ratio of isoforms based on the properties of pure isoforms. The MUSICO platform traces the action of each myosin head or regulatory protein in the 3D sarcomere lattice and quantitatively predicts muscle fiber responses for various calcium transients and mechanical loading conditions. The modular set up of the software provides an opportunity to distribute different isoforms randomly or in an ordered fashion and associate each isoform with its appropriate kinetic properties. For the prediction of mechanical and energetic response of variable ratios of human alpha and beta myosin isoforms we established an eight step ATPase cycle and allow actin, myosin, substrate ATP and product ADP & Pi concentrations to be fixed or varied. From the experiments in solution we extracted realistic rate constants to each step of the cycle for any well-defined myosin isoform. The MUSICO prediction for various ratios of alpha and beta myosin isoforms shows that in a steady state the mechanical and energetic (e.g. ATPase) responses are proportional to the ratio of the isoform concentrations. However, the response to rapid changes in calcium concentrations (twitch or during force development and relaxation) we observed that: (i) during the fast rise in force the response is biased toward the fast isoform and (ii) during relaxation toward the slow isoform response. Overall, this approach will be a useful tool to explore the behavior of different mixed myosin and troponin populations.

PRIDE Inspector Toolsuite: Moving Toward a Universal Visualization Tool for Proteomics Data Standard Formats and Quality Assessment of ProteomeXchange Datasets

The original PRIDE Inspector tool was developed as an open source standalone tool to enable the visualization and validation of mass-spectrometry (MS)-based proteomics data before data submission or already publicly available in the Proteomics Identifications (PRIDE) database. The initial implementation of the tool focused on visualizing PRIDE data by supporting the PRIDE XML format and a direct access to private (password protected) and public experiments in PRIDE.The ProteomeXchange (PX) Consortium has been set up to enable a better integration of existing public proteomics repositories, maximizing its benefit to the scientific community through the implementation of standard submission and dissemination pipelines. Within the Consortium, PRIDE is focused on supporting submissions of tandem MS data. The increasing use and popularity of the new Proteomics Standards Initiative (PSI) data standards such as mzIdentML and mzTab, and the diversity of workflows supported by the PX resources, prompted us to design and implement a new suite of algorithms and libraries that would build upon the success of the original PRIDE Inspector and would enable users to visualize and validate PX “complete” submissions. The PRIDE Inspector Toolsuite supports the handling and visualization of different experimental output files, ranging from spectra (mzML, mzXML, and the most popular peak lists formats) and peptide and protein identification results (mzIdentML, PRIDE XML, mzTab) to quantification data (mzTab, PRIDE XML), using a modular and extensible set of open-source, cross-platform libraries. We believe that the PRIDE Inspector Toolsuite represents a milestone in the visualization and quality assessment of proteomics data. It is freely available at http://github.com/PRIDE-Toolsuite/.