Immunoregulatory functions of paf-acether. VI. Dual effect on human B cell proliferation

The role of paf-acether (paf), a phospholipid cytokine, in the modulation of human B cell function was investigated. Paf, from 1×10⁻⁵ M to 10⁻⁶ M, decreased B cell proliferation induced by both phorbol myristate acetate (PMA) and anti-IgM antibodies (anti-IgM Ab). By contrast, 1×10⁻⁷ M to 1×10⁻⁹ M paf enhanced PMA triggered, but not anti-IgM triggered B cell proliferation. B cell proliferation was modulated between 24 and 72 hr of culture indicating that the effect of paf did not merely reflect a shift in proliferation kinetics. Interestingly, paf also enhanced the spontaneous proliferation of a Burkitt lymphoma-derived B cell line, Raji, which suggests that paf can directly act on B cells. The modulatory effect of paf on peripheral blood B cells was independent of PMA concentration, yet the effect on Raji cells was dependent upon cell density. The data suggest that paf is a potent modulator of B cell function, and may be involved in the control of humoral immune response. Based on a paper presented at the Third International Conference on Platelet-Activating Factor and Structurally Related Alkyl Ether Lipids, Tokyo, Japan, May 1989.     

Determination of the repartition of monomers between sol and gel fractions in copolycondensate glycerol/azelaic acid by radioassay

The distribution of the monomers between sol and gel fractions, theoretically forecasted from network formation theory, is experimentally determined in glycerol/azelaic acid system with tritium labeled glycerol by radioassay.Presented at the 7th Discussion Conference IUPAC Polymer Networks, Karlovy Vary, CSSR, September 15–19, 1980     

Proteomics of plaques and novel sources of potential biomarkers for atherosclerosis

Cardiovascular disease (CVD) is the leading cause of death and loss of productive life years in the world. The underlying syndrome of CVD, atherosclerosis, is a complex disease process, which involves lipid metabolism, inflammation, innate and adaptive immunity, and many other pathophysiological aspects. Furthermore, CVD is influenced by genetic as well as environmental factors. Early detection of CVD and identification of patients at risk are crucial to reduce the burden of disease and to allow personalized treatment. As established risk factors fail to accurately predict which part of the population is likely to suffer from the disease, novel biomarkers are urgently needed. Proteomics can play a significant role in identifying these biomarkers. In this review, we describe the progress made in proteome profiling of the atherosclerotic plaque and several novel sources of potential biomarkers, including circulating cells and plasma extracellular vesicles. The importance of longitudinal biobanking in biomarker discovery is highlighted and exemplified by several plaque proteins identified in the biobank study Athero-Express. Finally, we discuss the PTMs of proteins that are involved in atherosclerosis, which may become one of the foci in the ongoing quest for biomarkers through proteomics of plaque and other matrices relevant to the progression of atherosclerosis.     

Post-buckling dynamic behavior of self-assembled 3D microstructures

The paper presents the snap-through phenomenon in the case of micro fabricated clamped-clamped buckled beam. This dynamic post-buckling behavior is likely to occur in 3D microstructures when they are subjected to large vibration amplitudes. The main difference between this work and previous studies is the MEMS specific beam dimension, especially the large initial deflection of the buckled beam that involves the inversion of the two first resonance frequencies. The mathematical development allows showing how the vibration amplitude of the supporting base affects the post-buckling dynamic behavior of the beam. For each frequency, the limit between the stable behavior and the snap-through behavior is evaluated. Moreover, the effect of environment is taken into account from the damping point of view. Samples are fabricated and the experiment is described. Measurements are compared to the theoretical approach and the results are in good agreement with the proposed model.     

System-on-chip design by proof-based refinement

Systems-on-chip (SoCs) and SoC architectures provide a collection of challenging problems related to specification, modelling techniques, security issues and structuring questions. We describe a design methodology integrating the event B method and characterized by the incremental and proof-controlled construction of SoC models. The essence of the methodology is the refinement of models, starting from system requirements and producing event B models for characterizing the system under development. The refinement is a unifying concept that ensures the consistency of the different models produced and our contribution is an illustration through a case study, namely a system for measuring the parameters of audio/video quality in the digital video broadcasting (DVB) set of digital TV standards. The first part is the derivation of an architecture of parameters from the document ETSI TR 101 290 and the validation of the architecture using invariants of B models. The second part is the proposal of B models of the SystemC scheduler and an instantiation of these abstract models of the simulation semantics by parameters of the SystemC codes automatically translated from the B models of the DVB system. Finally, the third part relies upon a proof-based methodology for deriving an operational semantics of a given system that is expressed by an event B model including invariant properties.     

Chemical sensor based on a novel capacitive microwave flexible transducer with polymer nanocomposite-carbon nanotube sensitive film

Microsystem Technologies - This study presents the results on the feasibility of a resonant planar chemical capacitive sensor in the microwave frequency range suitable for gas detection and...     

Interest of molecular functionalization for electrochemical storage

Despite great interests in electrochemical energy storage systems for numerous applications, considerable challenges remain to be overcome. Among the various approaches to improving the stability, safety, performance, and cost of these systems, molecular functionalization has recently been proved an attractive method that allows the tuning of material surface reactivity while retaining the properties of the bulk material. For this purpose, the reduction of aryldiazonium salt, which is a versatile method, is considered suitable; it forms robust covalent bonds with the material surface, however, with the formation of multilayer structures and sp³ defects (for carbon substrate) that can be detrimental to the electronic conductivity. Alternatively, non-covalent molecular functionalization based on π–π interactions using aromatic ring units has been proposed. In this review, the various advances in molecular functionalization concerning the current limitations in lithium-ion batteries and electrochemical capacitors are discussed. According to the targeted applications and required properties, both covalent and non-covalent functionalization methods have proved to be very efficient and versatile. Fundamental aspects to achieve a better understanding of the functionalization reactions as well as molecular layer properties and their effects on the electrochemical performance are also discussed. Finally, perspectives are proposed for future implementation of molecular functionalization in the field of electrochemical storage.

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The undirected capacitated arc routing problem with profits

A profit and a demand are associated with each edge of a set of profitable edges of a given graph. A travel time is associated with each edge of the graph. A fleet of capacitated vehicles is given to serve the profitable edges. A maximum duration of the route of each vehicle is also given. The profit of an edge can be collected by one vehicle only that also serves the demand of the edge. The objective of this problem, which is called the undirected capacitated arc routing problem with profits (UCARPP), is to find a set of routes that satisfy the constraints on the duration of the route and on the capacity of the vehicle and maximize the total collected profit. We propose a branch-and-price algorithm and several heuristics. We can solve exactly instances with up to 97 profitable edges. The best heuristics find the optimal solution on most of instances where it is available.     

Modular architecture of the microfactories for automatic micro-assembly

The construction of a new generation of MEMS which includes micro-assembly steps in the current microfabrication process is a big challenge. It is necessary to develop new production means named micromanufacturing systems in order to perform these new assembly steps. The classical approach called “top-down” which consists in a functional analysis and a definition of the tasks sequences is insufficient for micromanufacturing systems. Indeed, the technical and physical constraints of the microworld (e.g. the adhesion phenomenon) must be taken into account in order to design reliable micromanufacturing systems. A new method of designing micromanufacturing systems is presented in this paper. Our approach combines the general “top-down” approach with a “bottom-up” approach which takes into account technical constraints. The method enables to build a modular architecture for micromanufacturing systems. In order to obtain this modular architecture, we have devised an original identification technique of modules and an association technique of modules. This work has been used to design the controller of an experimental robotic micro-assembly station.     

The use of fuzzy logic and neural networks models for sensory properties prediction from process and structure parameters of knitted fabrics

In a competitive business environment, the textile industrialists intend to propose diversified products according to consumers preference. For this purpose, the integration of sensory attributes in the process parameters choice seems to be a useful alternative. This paper provides fuzzy and neural models for the prediction of sensory properties from production parameters of knitted fabrics. The prediction accuracy of these models was evaluated using both the root mean square error (RMSE) and mean relative percent error (MRPE). The results revealed the models ability to predict tactile sensory attributes based on the production parameters. The comparison of the prediction performances showed that the neural models are slightly powerful than the fuzzy models.