A simple and general route for monofunctionalization of fluorescent and magnetic nanoparticles using peptides

Nanoparticles are now utilized in many diverse biological and medical applications. Despite this, it remains challenging to tailor their surface for specific molecular targeting while maintaining high biocompatibility. To address this problem, we evaluate a phytochelatin-related peptide surface coating to produce functional and biocompatible nanoparticles (NPs) based on fluorescent InP/ZnS and CdSe/ZnS or superparamagnetic FePt and Fe(3)O(4). Using a combination of transmission electron microscopy, size-exclusion chromatography and gel electrophoresis (GE), we demonstrate the excellent colloidal properties of the peptide-coated NPs (pNPs) and the compact nature of the coating (～4?nm thickness). We develop a simple protocol for the monofunctionalization of the pNPs with targeting biomolecules, by combining covalent conjugation with GE purification. We then employ functionalized InP/ZnS pNPs in a live-cell, single-molecule imaging application to specifically target and detect individual proteins in the cell membrane. These findings showcase the versatility of the peptides for preparing compact NPs of various compositions and sizes, which are easily functionalized, and suitable for a broad range of biomedical applications.     

Numerical and experimental studies of the riveting process

As one of important mechanical joining methods, rivet joints are widely used in buildings, bridges, aircrafts and automotives and in many other fields. Many variables have influences on the response of the rivet joints, such as the geometry of the joints, the material parameters of the parts, the clearance of the assembly, etc. In this paper, a finite element numerical model is developed for the analysis and optimization of the riveting process. Our approach is three-dimensional in order to be able to model non axisymmetric situations of riveting and testing of the joint strength. Four different sizes of solid rivets are considered for simulation and experimental study of the process. The comparison of the results between the numerical simulations and the experiments allows us to validate our approach.     

Mechanical Properties of Highly Porous Super Liquid‐Repellent Surfaces

Surfaces with self‐cleaning properties are desirable for many applications. Conceptually, super liquid‐repellent surfaces are required to be highly porous on the nano‐ or micrometer scale, which inherently makes them mechanically weak. Optimizing the balance of mechanical strength and liquid repellency is a core aspect toward applications. However, quantitative mechanical testing of porous, super liquid‐repellent surfaces is challenging due to their high surface roughness at different length scales and low stress tolerance. For this reason, mechanical testing is often performed qualitatively. Here, the mechanical responses of soot‐templated super liquid‐repellent surfaces are studied qualitatively by pencil and finger scratching and quantitatively by atomic force microscopy, colloidal probe force measurements, and nanoindentation. In particular, colloidal probe force measurements cover the relevant force and length scales. The effective elastic modulus, the plastic work W_plastic and the effective adhesive work W_adhesive are quantified. By combining quantitative information from force measurements with measurements of surface wetting properties, it is shown that mechanical strength can be balanced against low wettability by tuning the reaction parameters.     

Electric Field Assisted Microfluidic Platform for Generation of Tailorable Porous Microbeads as Cell Carriers for Tissue Engineering

Injection of cell‐laden scaffolds in the form of mesoscopic particles directly to the site of treatment is one of the most promising approaches to tissue regeneration. Here, a novel and highly efficient method is presented for preparation of porous microbeads of tailorable dimensions (in the range ≈300–1500 mm) and with a uniform and fully interconnected internal porous texture. The method starts with generation of a monodisperse oil‐in‐water emulsion inside a flow‐focusing microfluidic device. This emulsion is later broken‐up, with the use of electric field, into mesoscopic double droplets, that in turn serve as a template for the porous microbeads. By tuning the amplitude and frequency of the electric pulses, the template droplets and the resulting porous bead scaffolds are precisely produced. Furthermore, a model of pulsed electrodripping is proposed that predicts the size of the template droplets as a function of the applied voltage. To prove the potential of the porous microbeads as cell carries, they are tested with human mesenchymal stem cells and hepatic cells, with their viability and degree of microbead colonization being monitored. Finally, the presented porous microbeads are benchmarked against conventional microparticles with nonhomogenous internal texture, revealing their superior performance.     

Attenuated total reflection infrared spectroscopy: an efficient technique to quantitatively determine the orientation and conformation of proteins in single silk fibers

Polarized attenuated total reflection (ATR) infrared spectroscopy is an efficient technique to determine the orientation and conformation of a large variety of samples, but it is more difficult to apply to very small specimens such as silk fibers. The Golden Gate single-reflection ATR accessory that uses diamond as an ATR element and a focalized beam turns out to be highly efficient to study quantitatively the orientation and conformation of a single silk fibroin filament of the silkworm Bombyx mori that is about 10 mum in diameter. For orientation measurements, rotating the sample instead of the electric field greatly simplifies the theoretical analysis and keeps the penetration depth of the infrared radiation constant. A sample holder that can be fitted on the ATR accessory has thus been developed to allow accurate rotation of the sample and to obtain spectra with a low, non-damaging, and reproducible pressure on the fiber. To validate the method, spectra have been recorded as a function of the angle theta between the fiber axis and the polarization of the incident radiation. The data have been fitted following the cosine square dependency of the absorbance with respect to the angle theta. The procedure has been applied to the spectral components of the amide I bands, as determined from spectral decomposition. Multiple angle measurements turn out to be quite useful to correct systematic angle errors and validate the accuracy of the curve-fitting parameters of the band decomposition. By using the calculated dichroic ratio, a parameter of -0.46 +/- 0.01 has been calculated for the antiparallel beta-sheets and -0.04 +/- 0.02 for the remaining structures. From the orientation-insensitive spectrum A(0), the amount of beta-sheets has been estimated to 49 +/- 3%. The results obtained from only two measurements with the electric field of the incident radiation parallel and perpendicular to the fiber axis has demonstrated that ATR spectroscopy can be used routinely in quantitative studies of the molecular orientation and conformation of macromolecules.     

A texture discretization technique adapted to polycrystalline aggregates with non-uniform grain size

This paper presents a new procedure for the sampling of crystallographic textures into discrete lattice orientations. The method is, for example, useful in order to assign initial grain orientations in crystal-plasticity-based finite element simulation of forming processes. The discretization technique ensures that the orientation sampling is statistically representative of a known orientation distribution function (ODF). Contrary to previous discretization techniques, the new method is valid also when the model microstructure consists of grains with non-uniform size. The accuracy of the texture representation is assessed in the case of cold rolled IF steel. Crystal plasticity theory coupled to finite element modeling is used to predict mechanical planar anisotropy of the sheet. Comparison is made between model predictions assuming, respectively, a uniform or a heterogeneous grain-size distribution.     

The Shortening of MWNT‐SPION Hybrids by Steam Treatment Improves Their Magnetic Resonance Imaging Properties In Vitro and In Vivo

Carbon nanotubes (CNTs) have been advocated as promising nanocarriers in the biomedical field. Their high surface area and needle‐like shape make these systems especially attractive for diagnostic and therapeutic applications. Biocompatibility, cell internalization, biodistribution, and pharmacokinetic profile have all been reported to be length dependent. In this study, further insights are gotten on the role that the length of CNTs plays when developing novel contrast agents for magnetic resonance imaging (MRI). Two samples of CNTs with different length distribution have been decorated with radio‐labeled iron oxide nanoparticles. Despite characterization of the prepared hybrids reveals a similar degree of loading and size of the nanoparticles for both samples, the use of short CNTs is found to enhance the MRI properties of the developed contrast agents both in vitro and in vivo compared to their long counterparts.     

Manifold surface reconstruction of an environment from sparse Structure-from-Motion data

The majority of methods for the automatic surface reconstruction of an environment from an image sequence have two steps: Structure-from-Motion and dense stereo. From the computational standpoint, it would be interesting to avoid dense stereo and to generate a surface directly from the sparse cloud of 3D points and their visibility information provided by Structure-from-Motion. The previous attempts to solve this problem are currently very limited: the surface is non-manifold or has zero genus, the experiments are done on small scenes or objects using a few dozens of images. Our solution does not have these limitations. Furthermore, we experiment with hand-held or helmet-held catadioptric cameras moving in a city and generate 3D models such that the camera trajectory can be longer than one kilometer.     

Fair multi-agent task allocation for large datasets analysis

MapReduce is a design pattern for processing large datasets distributed on a cluster. Its performances are linked to the data structure and the runtime environment. Indeed, data skew can yield an unfair task allocation, but even when the initial allocation produced by the partition function is well balanced, an unfair allocation can occur during the reduce phase due to the heterogeneous performance of nodes. For these reasons, we propose an adaptive multi-agent system. In our approach, the reducer agents interact during the job and the task reallocation is based on negotiation in order to decrease the workload of the most loaded reducer and so the runtime. In this paper, we propose and evaluate two negotiation strategies. Finally, we experiment our multi-agent system with real-world datasets over heterogeneous runtime environment.     

CHOOSE: Towards a metamodel for enterprise architecture in small and medium-sized enterprises

Enterprise architecture (EA) is a coherent whole of principles, methods, and models that are used in the design and realization of an enterprise’s organizational structure, business processes, information systems, and IT infrastructure. Recent research indicates the need for EA in small and medium-sized enterprises (SMEs), important drivers of the economy, as they struggle with problems related to a lack of structure and overview of their business. However, existing EA frameworks are perceived as too complex and, to date, none of the EA approaches are sufficiently adapted to the SME context. Therefore, this paper presents the CHOOSE metamodel for EA in SMEs that was developed and evaluated through action research in an SME and further refined and validated through case study research in five other SMEs. This metamodel is based on the essential dimensions of EA frameworks and is kept simple so that it may be applied in an SME context. The final CHOOSE metamodel includes only four essential concepts (i.e. goal, actor, operation, object), one for each most frequently used EA focus. As an example, an extract is included from the specific model that was created for the SME used in our action research. Finally, the CHOOSE metamodel is evaluated according to the dimensions essential in EA and the requirements for EA in an SME context.