Automated ‘X‐Y’ robot for peptide synthesis with microwave heating: application to difficult peptide sequences and protein domains

Precise microwave heating has emerged as a valuable method to aid solid‐phase peptide synthesis (SPPS). New methods and reliable protocols, as well as their embodiment in automated instruments, are required to fully use this potential. Here we describe a new automated robotic instrument for SPPS with microwave heating, report protocols for its reliable use and report the application to the synthesis of long sequences, including the β‐amyloid 1‐42 peptide. The instrument is built around a valve‐free robot originally developed for parallel peptide synthesis, where the robotic arm transports reagents instead of pumping reagents via valves. This is the first example of an ‘X‐Y’ robotic microwave‐assisted synthesizer developed for the assembly of long peptides. Although the instrument maintains its capability for parallel synthesis at room temperature, in this paper, we focus on sequential peptide synthesis with microwave heating. With this valve‐free instrument and the protocols developed for its use, fast and efficient syntheses of long and difficult peptide sequences were achieved. Copyright © 2010 European Peptide Society and John Wiley & Sons, Ltd.     

Assembly Process Design for Managing Manufacturing Complexities Because of Product Varieties

This paper comprehensively studies assembly process design (APD) to handle variety and presents a new approach to strategically manage manufacturing complexities because of product varieties. It links the chronological steps of APD to a general approach with a view to reduce both short and long term wastes. It synthesizes two strategic approaches, product and process-based, while exploiting the APD of an entire product family. A new evaluation method for measuring the complexities of an assembly system at different stages of design has been introduced by applying information entropy. The developed evaluation methodology explains the available techniques related to design, interprets them from a design for variety point of view, and leads to techniques to manage complexities in manufacturing. The suggested methodology has been applied to examples from automobile part manufacturers and has been found to be effective in understanding the complexities in manufacturing and leading to some strategies to manage variety.     

Microtechnology applications for medical instrumentation.

The recent progresses in microtechnologies open new possibilities in terms of design, cost reductions, improve performances and, moreover, open new fields of applications in surgical instrumentation. Microtechnology techniques will lead to reconsider the design of medical instrumentation. Surgical tools should not be thought as mechanical systems but as surgical components ("surgical chips") designed with micro-technologies and including microsensors/microactuactors.     

Vision-Based Framework of Single Master Dual Slave Semi-Autonomous Surgical Robot System

BackgroundIn the traditional Robot assisted minimally invasive surgery (RMIS) scenario, the instruments are fully controlled by the surgeon through tele-operation. Recent works have widely explored the surgical intelligence by integrating advanced approaches to enhance the surgical operating room (OR) outcomes.MethodsWe propose a novel single-master dual-slave framework for semi-autonomous suturing task, laparoscope information is introduced to feed back into the robotic control loop to guide the movement of surgical instrument.ResultsExperimental results demonstrate that the proposed method can handle the single-master dual-slave semi-autonomous suturing subtask. Furthermore, the framework exhibits compelling performance leading to the efficiency of surgical OR.ConclusionsAdding vision information into the robotic control loop can achieve the semi-autonomous operation, improve the surgical OR efficiency, this capability yields new level of intelligence for the RMIS.     

Proposal of a hydric index to support industrial site location decision-making applying a fuzzy multi-attribute methodology

This paper proposes a practical water resources-related index methodology (Hydric Index for Location of Industrial Facilities – HILIF) to provide preliminary guidance for location-based decision-making processes for new industrial sites, based on the likely effects on water resources in river watersheds, as applied to the conceptual phase of a project design. The framework of HILIF is established on the integration of three hydric factors: consumptive water availability, river carrying capacity, and flood vulnerability and effects of the drainage project. The proposed methodology for the application of HILIF is founded on Multi-Attribute Decision Making (MADM) using fuzzy logic (fuzzy MADM) to combine seven indicators into nine possible recommendation levels. Additionally, in order to illustrate the HILIF methodological approach, a case study of a project design using a cyclical analysis based on a hypothetical scenario was developed. In this context, three alternative sites (AA, BB, and CC) were considered for a nitrogen fertilizer plant in the Contas River Basin in the state of Bahia, Brazil. The results demonstrate that the HILIF methodology can support the conceptual project design by identifying the most adequate site alternatives for an industrial location within an integrated hydric perspective. In addition, the possibility of implementing modifications during the initial conceptual project was observed through cyclical analysis using multiple rounds for the same locational alternatives. For the present case study, the locational alternative preferred by project designers (Alternative CC) shifted from a classification of Not Indicated (NI) in the first round of HILIF application to a Fairly-Good Recommendation in the second round after modifications in the initial conceptual project. Thus, Alternative CC became nearly as adequate as Alternative BB, which was the best alternative site in terms of water, classified as a Good Recommendation in the first HILIF round. On a complementary basis, the results generated by the application of HILIF can also be utilized to support further complex studies for licensing proposes within the context of Environmental Impact Assessment (EIA) or Strategic Environmental Assessment (SEA).     

Development of a new transcervical artificial insemination method for sheep: effects of a new transcervical artificial insemination catheter and traversing the cervix on semen quality and fertility

The difficulty of traversing the cervix severely limits transcervical artificial insemination (TC AI) in sheep. Cervical trauma and poorly designed instruments can reduce fertility after AI. To overcome problems associated with TC AI, we developed a new TC AI catheter. Three bench experiments were conducted to determine the effects of the new TC AI catheter on semen quality independent of the effects of moving the catheter through the cervix. In each of the three bench experiments, the standard laparoscopic instrument for intrauterine AI in sheep was used as the control for the TC AI catheter. In Experiment 1, the total volume of semen extender expelled and void volumes for both types of AI instrument (TC versus laparoscopic) were determined. In Experiment 2, the effects of each type of AI instrument (TC versus laparoscopic) on semen quality, estimated as percentage motility and percentage forward progressive motility, of frozen-thawed semen was determined. In Experiment 3, the effects of both types of AI instrument (TC versus laparoscopic) on number of spermatozoa expelled was determined. The type of AI instrument affected neither semen quality nor the number of spermatozoa expelled. However, void volume differed (P < 0.01) between the two instruments. After differences in void volume were taken into account, an in vivo experiment was conducted to determine whether using our new TC AI catheter for TC or surgical intrauterine AI affected fertilization and pregnancy rates. For this, ewes were assigned to one of three treatments: (1) TC AI using the new TC AI catheter + sham AI via laparotomy (n = 9); (2) sham TC AI + AI via laparotomy using a laparoscopic AI instrument (n = 8); and (3) sham TC AI + AI via laparotomy using the new TC Al catheter (n = 10). To synchronize estrus, progestogenated pessaries were inserted and left in place for 12 days. On Day 5 after pessary insertion, PGF2alpha (15 mg) was given i.m. At pessary removal, 400 IU of eCG were administered i.m. Ewes were inseminated 48-52 h after pessary removal using fresh diluted semen (200 x 10(6) to 350 x 10(6) spermatozoa per 0.2 ml) pooled from the same four rams each day during the experiment. At 72 h after AI, uteri were collected postmortem and flushed. Oocytes and embryos were recovered and evaluated. Treatments did not affect (P > 0.01) ovum and embryo recovery rate (mean = 87.3%), fertilization rate (59.3%), or Day 3 pregnancy rate (mean = 66.6%). We conclude from these data that the use of our new TC AI catheter for TC AI or intrauterine AI should not impair the success of AI in sheep.     

Tensile forces attenuate estrogen-stimulated collagen synthesis in the ACL

The purpose of this study was to examine whether mechanical tensile forces affect estrogen regulation of collagen synthesis of anterior cruciate ligament fibroblasts at the mRNA level. Estrogen was studied at three physiologic levels, 10(-11), 10(-10), and 10(-9)M. The results revealed that estrogen alone stimulated Type I and III collagen synthesis at the mRNA level, and application of mechanical force decreased the expression of collagen Type I and III genes at all tested estrogen levels. These findings suggest that estrogen may directly regulate ligament structure and function by alteration of Type I and III collagen synthesis. This regulation is dependent on mechanical loading.     

Time-Based Competition in Multistage Manufacturing: Stream-of-Variation Analysis (SOVA) Methodology—Review

Frequency of model change and the vast amounts of time and cost required to make a changeover, also called time-based competition, has become a characteristic feature of modern manufacturing and new product development in automotive, aerospace, and other industries. This paper discusses the concept of time-based competition in manufacturing and design based on a review of on-going research related to stream-of-variation (SOVA or SoV) methodology. The SOVA methodology focuses on the development of modeling, analysis, and control of dimensional variation in complex multistage assembly processes (MAP) such as the automotive, aerospace, appliance, and electronics industries. The presented methodology can help in eliminating costly trial-and-error fine-tuning of new-product assembly processes attributable to unforeseen dimensional errors throughout the assembly process from design through ramp-up and production. Implemented during the product design phase, the method will produce math-based predictions of potential downstream assembly problems, based on evaluations of the design and a large array of process variables. By integrating product and process design in a pre-production simulation, SOVA can head off individual assembly errors that contribute to an accumulating set of dimensional variations, which ultimately result in out-of-tolerance parts and products. Once in the ramp-up stage of production, SOVA will be able to compare predicted misalignments with actual measurements to determine the degree of mismatch in the assemblies, diagnose the root causes of errors, isolate the sources from other assembly steps, and then, on the basis of the SOVA model and product measurements, recommend solutions.     

Lightweight Design of Mechanical Structures based on Structural Bionic Methodology

With increasing concern over the excessive energy consumption and environment pollution, structural bionics is a viable new tool of lightweight design by mechanical engineers. The structural solutions derived from nature can be successfully transferred into technical construction for maximum structural efficiency from minimal resources. The goal of the study is to develop a standard methodology for bionic mechanical structures with dead-load reduction and performance improvement. Similarity theory and fuzzy assessment method are deployed for selection of analogical samples and analysis based on structure, loading and function similarities. The type spectrum of lightweight design is established for selection convenience and principle extraction, vital to concept designs. Finite element method is used as an effective tool for mechanical performance simulation and comparison. The rapid prototyping, investment casting and Numerical Control (NC) machining are discussed for model fabrication. The static and dynamic test results indicate that the bionic models are lighter but stiffer than the original ones. So by mimicking biological structural principles, the structural bionic design offers a new solution for updating traditional design concepts and achieving maximum structural efficiency.     

Approximate Life-Cycle Assessment of Product Concepts Using Learning Systems

Parametric life-cycle assessment (LCA) models have been integrated with traditional design tools and used to demonstrate the rapid elucidation of holistic, analytical trade-offs among detailed design variations. A different approach is needed, however, if analytical environmental assessment is to be incorporated in very early design stages. During early stages, there may be competing product concepts with dramatic differences. Detailed information is scarce, and decisions must be made quickly.
This article explores an approximate method for providing preliminary LCAs. In this method, learning algorithms trained using the known characteristics of existing products might allow environmental aspects of new product concepts to be approximated quickly during conceptual design without defining new models. Artificial neural networks are trained to generalize on product attributes, which are characteristics of product concepts, and environmental inventory data from pre-existing LCAs. The product design team then queries the trained artificial model with new high-level attributes to quickly obtain an impact assessment for a new product concept. Foundations for the learning system approach are established, and then an application within the distributed object-based modeling environment (DOME) is provided. Tests have shown that it is possible to predict life-cycle energy consumption, and that the method could be used to predict solid waste, greenhouse effect, ozone depletion, acidification, eutrophication, winter and summer smog.     

Biotemplates in the green synthesis of silver nanoparticles

This article recapitulates the scientific advancement towards the greener synthesis of silver nanoparticles. Applications of noble metals have increased throughout human civilization, and the uses for nano-sized particles are even more remarkable. “Green” nanoparticle synthesis has been achieved using environmentally acceptable solvent systems and eco-friendly reducing and capping agents. Numerous microorganisms and plant extracts have been applied to synthesize inorganic nanostructures either intracellularly or extracellularly. The use of nanoparticles derived from noble metals has spread to many areas including jewelery, medical fields, electronics, water treatment and sport utilities, thus improving the longevity and comfort in human life. The application of nanoparticles as delivery vehicles for bactericidal agents represents a new paradigm in the design of antibacterial therapeutics. Orientation, size and physical properties of nanoparticles influences the performance and reproducibility of a potential device, thus making the synthesis and assembly of shape- and size-controlled nanocrystals an essential component for any practical application. This need has motivated researchers to explore different synthesis protocols.     

Minireview: Challenges of High Throughput Screening Against Cell Surface Receptors

Abstract

Excessive or inappropriate activation of cell surface receptors can mediate the development of disease. Receptors, therefore, are a focus for drug discovery activities. Empirical screening is important in the search for novel compounds acting at receptors. Technical developments and the application of molecular biology have facilitated access to receptors of interest and have provided efficient screening methods capable of very high throughput. Reliability in high throughput screening requires the use of appropriate methodology, good screen design and effective validation and quality control processes. Validation should aim to establish that the basic experimental design is sound. In developing software to handle high throughput screening data, a fundamental requirement is to provide performance monitoring and error trapping facilities. Additional requirements are automatic data capture from instruments, on-line data reduction and analysis and transfer of results to central databases. As data volumes increase through effective high throughput screening, conventional interrogation methods become less appropriate and are being augmented by newer computing techniques referred to as knowledge mapping or database mining. Targeting cell surface receptors has been very successful as an approach to drug discovery. If the challenges of high throughput empirical screening are addressed effectively, cell surface receptors will provide new opportunities for improved therapy in the coming years.     

A methodology for in silico endovascular repair of abdominal aortic aneurysms

Endovascular aneurysm repair (EVAR) can involve some unfavorable complications such as endoleaks or stent-graft (SG) migration. Such complications, resulting from the complex mechanical interaction of vascular tissue, SG and blood flow or incompatibility of SG design and vessel geometry, are difficult to predict. Computational vascular mechanics models can be a predictive tool for the selection, sizing and placement process of SGs depending on the patient-specific vessel geometry and hence reduce the risk of potential complications after EVAR. In this contribution, we present a new in silico EVAR methodology to predict the final state of the deployed SG after intervention and evaluate the mechanical state of vessel and SG, such as contact forces and wall stresses. A novel method to account for residual strains and stresses in SGs, resulting from the precompression of stents during the assembly process of SGs, is presented. We suggest a parameter continuation approach to model various different sizes of SGs within one in silico EVAR simulation which can be a valuable tool when investigating the issue of SG oversizing. The applicability and robustness of the proposed methods are demonstrated on the example of a synthetic abdominal aortic aneurysm geometry.     

Flow infusion electrospray ionisation mass spectrometry for high throughput,non-targeted metabolite fingerprinting: a review

Producing a comprehensive overview of the chemical content of biologically-derived material is a major challenge. Apart from ensuring adequate metabolome coverage and issues of instrument dynamic range, mass resolution and sensitivity, there are major technical difficulties associated with data pre-processing and signal identification when attempting large scale, high-throughput experimentation. To address these factors direct infusion or flow infusion electrospray mass spectrometry has been finding utility as a high throughput metabolite fingerprinting tool. With little sample pre-treatment, no chromatography and instrument cycle times of less than 5 min it is feasible to analyse more than 1,000 samples per week. Data pre-processing is limited to aligning extracted mass spectra and mass-intensity matrices are generally ready in a working day for a month’s worth of data mining and hypothesis generation. ESI-MS fingerprinting has remained rather qualitative by nature and as such ion suppression does not generally compromise data information content as originally suggested when the methodology was first introduced. This review will describe how the quality of data has improved through use of nano-flow infusion and mass-windowing approaches, particularly when using high resolution instruments. The increasingly wider availability of robust high accurate mass instruments actually promotes ESI-MS from a merely fingerprinting tool to the ranks of metabolite profiling and combined with MS/MS capabilities of hybrid instruments improved structural information is available concurrently. We summarise current applications in a wide range of fields where ESI-MS fingerprinting has proved to be an excellent tool for “first pass” metabolome analysis of complex biological samples. The final part of the review describes a typical workflow with reference to recently published data to emphasise key aspects of overall experimental design.

     

Flow infusion electrospray ionisation mass spectrometry for high throughput,non-targeted metabolite fingerprinting: a review

Producing a comprehensive overview of the chemical content of biologically-derived material is a major challenge. Apart from ensuring adequate metabolome coverage and issues of instrument dynamic range, mass resolution and sensitivity, there are major technical difficulties associated with data pre-processing and signal identification when attempting large scale, high-throughput experimentation. To address these factors direct infusion or flow infusion electrospray mass spectrometry has been finding utility as a high throughput metabolite fingerprinting tool. With little sample pre-treatment, no chromatography and instrument cycle times of less than 5 min it is feasible to analyse more than 1,000 samples per week. Data pre-processing is limited to aligning extracted mass spectra and mass-intensity matrices are generally ready in a working day for a month’s worth of data mining and hypothesis generation. ESI-MS fingerprinting has remained rather qualitative by nature and as such ion suppression does not generally compromise data information content as originally suggested when the methodology was first introduced. This review will describe how the quality of data has improved through use of nano-flow infusion and mass-windowing approaches, particularly when using high resolution instruments. The increasingly wider availability of robust high accurate mass instruments actually promotes ESI-MS from a merely fingerprinting tool to the ranks of metabolite profiling and combined with MS/MS capabilities of hybrid instruments improved structural information is available concurrently. We summarise current applications in a wide range of fields where ESI-MS fingerprinting has proved to be an excellent tool for “first pass” metabolome analysis of complex biological samples. The final part of the review describes a typical workflow with reference to recently published data to emphasise key aspects of overall experimental design.     

The Multidimensional Assessment of Interoceptive Awareness (MAIA)

This paper describes the development of a multidimensional self-report measure of interoceptive body awareness. The systematic mixed-methods process involved reviewing the current literature, specifying a multidimensional conceptual framework, evaluating prior instruments, developing items, and analyzing focus group responses to scale items by instructors and patients of body awareness-enhancing therapies. Following refinement by cognitive testing, items were field-tested in students and instructors of mind-body approaches. Final item selection was achieved by submitting the field test data to an iterative process using multiple validation methods, including exploratory cluster and confirmatory factor analyses, comparison between known groups, and correlations with established measures of related constructs. The resulting 32-item multidimensional instrument assesses eight concepts. The psychometric properties of these final scales suggest that the Multidimensional Assessment of Interoceptive Awareness (MAIA) may serve as a starting point for research and further collaborative refinement.     

Allocation in recycling systems

‘Design for Recycling’ and dematerialization by enhancing the durability of products are major aspects of the quest for sustainable products. This article presents an LCA-based model for the integrated analyses of the product chain, its recycling systems, and its waste treatment systems at the ‘End of Life’ stage. The model is an extension of the EVR (Eco-costs/Value Ratio) model which has been published in this journal (Vogtländer et al. 2001), but can also be applied to other life cycle interpretation models, since the model as such is not restricted to the use of the eco-costs as a single indicator. The model has been developed to evaluate the design alternatives of complex products like buildings and cars. These products comprise several subsystems, each with its own special solution at the End of Life stage: Extending of the product life, object renovation, re-use of components, re-use of materials, useful application of waste materials, immobilization with and without useful applications, incineration with and without energy recovery, land fill. Since complex product systems always comprise a combination of these design alternatives, a methodology is given to calculate and allocate the eco-costs of the total system in order to select the best solution for sustainability. The methodology is characterized by:

1. A main allocation model of the recycling flow based on physical relationships,
2. a strict separation of the market value, the costs and the ecocosts in the system,
3. a main allocation model for extension of lifetime based on ‘depreciation of eco-costs’, parallel to economic depreciation.

     

A cross-cultural adaptation of a psychiatric epidemiologic instrument: The diagnostic interview schedule's adaptation in Puerto Rico

The advent of the use of structured interview schedules that generate psychiatric diagnoses in epidemiologic studies has promoted an intense interest in its cross-cultural use. However, the valid use of these instruments across cultures requires a careful adaptation process which goes beyond mere language translation. In this article the authors illustrate the application of a comprehensive cross-cultural adaptation model to both the translation into Spanish and the adaptation to the population of Puerto Rico of a widely used psychiatric epidemiologic research instrument: the Diagnostic Interview Schedule (DIS). The process aimed to ensure the development of a research instrument that is not only in correct Spanish and comprehensible for most Spanish-speaking people, but also culturally adapted to Puerto Rico's population. Various steps were taken (including bilingual committee, back-translation, instrument testing and diagnostic comparisons) to address cross-cultural validity in five important dimensions (i.e., semantic, technical, content, criterion and conceptual equivalence). The result is an interview schedule that is not only linguistically and culturally adequate for the targeted population but also includes elements which can contribute to the development of the instrument both in its original English language and in its translated versions.