Superswelling Microneedle Arrays for Dermal Interstitial Fluid (Prote)Omics

The noninvasive sampling of dermal interstitial fluid (ISF) for the monitoring of clinical biomarkers is a greatly appealing area of research. The identification of molecular biomarkers in biological fluids has been accelerated with -omics analyses but remains limited in ISF because of its time-consuming and complex extraction process. Here, the generation of microneedle (MN) patches made of superabsorbent acrylate-based hydrogels for the rapid sampling of dermal ISF is described to explore its proteome. In depth, iterative optimization allows the identification of novel acrylate-based compositions with the required chemical, mechanical, and biocompatibility properties allowing proteomic analysis of the extracted ISF for the first time after sampling with swelling MNs. The generated MN arrays show no cytotoxic effect, successfully cross the stratum corneum, and can collect up to 6 µL of dermal ISF in 10 min in vivo. Proteomics lead to the detection of 176 clinically relevant biomarkers in the collected samples validating the use of ISF as a relevant bodily fluid for disease monitoring and diagnostic. Importantly, it is discovered that extraction fingerprint is strongly dependent on the MNs chemistry, and thus specific biomarkers could be selectively extracted by tuning the composition of the patch, making the system versatile and specific.     

Geopolymer assembly by emulsion templating: Emulsion stability and hardening mechanisms

This work investigates emulsion templating to synthesize hexadecane oil/geopolymer composites. In a system with hexadecane as the internal (dispersed) phase and an alkali activated continuous phase without added surfactant, adding aluminosilicate clay particles does not increase resistance against creaming or coalescence, while adding a surfactant (L35 or CTAB) stabilizes the solid-liquid interface. Infrared studies and rheological studies of the associated geopolymerization determined that the presence of the organic phase or surfactant has no significant effect on the geopolymerization kinetics, as determined by the change in time of the Si-O-T IR stretching frequency and the rheological moduli involved during the process. The stabilization of the organic template is reminiscent of Pickering emulsion even though we employ a much greater amount of inorganic material for geopolymer formation. Although the addition of surfactant has a significant effect on the behavior of the paste, the percolation of the network remains unmodified, highlighting the fact that the phenomenon is not dependent on viscosity. Finally, rheological measurements were used to obtain the mass fractal dimension of the as-made gel network, which is able to differentiate the interfacial effect between surfactant molecules with a slightly denser interphase when a cationic surfactant is used.     

Microscale and mesoscale discrete models for dynamic fracture of structures built of brittle material

In this work we present the discrete models for dynamic fracture of structures built of brittle materials. The models construction is based on Voronoi cell representation of the heterogeneous structure, with the beam lattice network used to model the cohesive and compressive forces between the neighboring cells. Each lattice component is a geometrically exact shear deformable beam which can describe large rigid body motion and the most salient fracture mechanisms. The latter can be represented through the corresponding form of the beam constitutive equations, which are derived either at microscale with random distribution of material properties or at a mesoscale with average deterministic values. The proposed models are also placed within the framework of dynamics, where special attention is paid to constructing the lattice network mass matrix as well as the corresponding time-stepping schemes. Numerical simulations of compression and bending tests is given to illustrate the models performance.     

FDTD simulation of 30 /spl mu/m diameter polymer micro-ring

Numerical results on polymer surrounded by an air micro-ring coupled to waveguides are presented. The FDTD method predicts a filter width of 1.4 nm and an extraction efficiency of almost 80% for a gap of 0.15 /spl mu/m.     

Potential science-technology spillovers in regions: An insight on geographic co-location of knowledge activities in the EU

This article depicts some features of the geography of science and technology outputs in the EU, with a particular attention to regional “co-location” of these two pillars of the “knowledge-based society”. Economists have, for a decade, paid great attention to local “spillovers” stating that industrial firms often draw advantages from the presence of nearby academic centres. The presence in the same areas of strong academic and technological resources is both a condition and a result of science-technology interactions. Concentrating on publications and patents as proxies of the science and technology level in regions, we built a typology of regions according to their commitment to the two knowledge-base activities and then analysed the co-locations of science and technology from several points of view. A fine-grain lattice, mainly based on standard Nuts3 level, was used. Co-location, at the EU level, is not a general rule. A strong potential for spillover/ interaction does exist in the top-class regions which concentrate a high proportion of European S and T output. But for regions with a small/medium level of S&T activity, a divergence of orientations appears between a science-oriented family and a technology-oriented family, indicating an imbalance between local S and T resources. If we look at the S-oriented regions, whilst controlling for underlying factors, such as population and regional economic product, a significant geographic linkage between T and S appears. This suggests a trajectory of science-based technological development. A careful examination of S&T thematic alignments and specialisation is necessary to develop the hypothesis that fostering academic resources could increase the technological power along a growth path. This revised version was published online in August 2006 with corrections to the Cover Date.     

Linearly bounded infinite graphs

Linearly bounded Turing machines have been mainly studied as acceptors for context-sensitive languages. We define a natural class of infinite automata representing their observable computational behavior, called linearly bounded graphs. These automata naturally accept the same languages as the linearly bounded machines defining them. We present some of their structural properties as well as alternative characterizations in terms of rewriting systems and context-sensitive transductions. Finally, we compare these graphs to rational graphs, which are another class of automata accepting the context-sensitive languages, and prove that in the bounded-degree case, rational graphs are a strict sub-class of linearly bounded graphs.A preliminary version of this article appeared in MFCS 2005.     

A multiparameter wearable physiologic monitoring system for space and terrestrial applications.

A novel, unobtrusive and wearable, multiparameter ambulatory physiologic monitoring system for space and terrestrial applications, termed LifeGuard, is presented. The core element is a wearable monitor, the crew physiologic observation device (CPOD), that provides the capability to continuously record two standard electrocardiogram leads, respiration rate via impedance plethysmography, heart rate, hemoglobin oxygen saturation, ambient or body temperature, three axes of acceleration, and blood pressure. These parameters can be digitally recorded with high fidelity over a 9-h period with precise time stamps and user-defined event markers. Data can be continuously streamed to a base station using a built-in Bluetooth RF link or stored in 32 MB of on-board flash memory and downloaded to a personal computer using a serial port. The device is powered by two AAA batteries. The design, laboratory, and field testing of the wearable monitors are described.     

Learning hierarchical probabilistic logic programs

Machine Learning - Probabilistic logic programming (PLP) combines logic programs and probabilities. Due to its expressiveness and simplicity, it has been considered as a powerful tool for learning...