Construction of the lactate-sensing fibremats by confining sensor fluorescent protein of lactate inside nanofibers of the poly(HPMA/DAMA)/ADH-nylon 6 core-shell fibremat.

The development of a new materials platform capable of sustaining the functionality of proteinous sensor molecules over an extended period without being affected by biological contaminants in living systems, such as proteases, is highly demanded. In this study, our primary focus was on fabricating new core-shell fibremats using unique polymer materials, capable of functionalizing encapsulated sensor proteins while resisting the effects of proteases. The core-fibre parts of core-shell fibremats were made using a newly developed post-crosslinkable water-soluble copolymer, poly(2-hydroxypropyl methacrylamide)--poly(diacetone methacrylamide), and the bifunctional crosslinking agent, adipic dihydrazide, while the shell layer of the nanofibers was made of nylon 6.

Influence of Molecular Structures of Organic Foulants on the Antifouling Properties of Poly(2-methoxyethyl acrylate) and Its Analogs: A Molecular Dynamics Study.

Elucidating the fouling phenomena of polymer surfaces will facilitate the molecular design of high-performance biomedical devices. Here, we investigated the remarkable antifouling properties of two acrylate materials, poly(2-methoxyethyl acrylate) (PMEA) and poly(3-methoxypropionic acid vinyl ester) (PMePVE), which have a terminal methoxy group on the side chain, via molecular dynamics simulations of binary mixtures of acrylate/methacrylate trimers with -pentane or 2,2-dimethylpropane (neopentane), that serve as the nonpolar organic probe (organic foulants). The second virial coefficient () was determined to assess the aggregation/dispersion properties in the binary mixtures.

Interactions between Acrylate/Methacrylate Biomaterials and Organic Foulants Evaluated by Molecular Dynamics Simulations of Simplified Binary Mixtures.

Improving hydrophilicity is a key factor for enhancing the biocompatibility of polymer surfaces. Nevertheless, previous studies have reported that poly(2-methoxyethyl acrylate) (PMEA) surfaces demonstrate markedly better biocompatibility than more hydrophilic poly(2-hydroxyethyl methacrylate) (PHEMA) surfaces. In this work, the origins of the excellent biocompatibility of the PMEA surface are investigated using molecular dynamics (MD) simulations of simplified binary mixtures of acrylate/methacrylate trimers and organic solvents, with -nonane, 1,5-pentanediol, or 1-octanol serving as the probe organic foulants.

Measurement of dynamic surface tension by mechanically vibrated sessile droplets.

We developed a novel method for measuring the dynamic surface tension of liquids using mechanically vibrated sessile droplets. Under continuous mechanical vibration, the shape of the deformed droplet was fitted by numerical analysis, taking into account the force balance at the drop surface and the momentum equation. The surface tension was determined by optimizing four parameters: the surface tension, the droplet's height, the radius of the droplet-substrate contact area, and the horizontal symmetrical position of the droplet.

Information-theoretic approach for the discovery of design rules for crystal chemistry.

In this work, it is shown that for the first time that, using information-entropy-based methods, one can quantitatively explore the relative impact of a wide multidimensional array of electronic and chemical bonding parameters on the structural stability of intermetallic compounds. Using an inorganic AB2 compound database as a template data platform, the evolution of design rules for crystal chemistry based on an information-theoretic partitioning classifier for a high-dimensional manifold of crystal chemistry descriptors is monitored. An application of this data-mining approach to establish chemical and structural design rules for crystal chemistry is demonstrated by showing that, when coupled with first-principles calculations, statistical inference methods can serve as a tool for significantly accelerating the prediction of unknown crystal structures.

Bimodal colloidal mixtures: from fast to slow aggregation regions.

A Brownian dynamics simulation has been used to investigate the aggregation kinetics of bimodal colloidal mixtures with similar surface chemistries but different sizes, driven by the DLVO interaction potential. The time evolution of structural formation is examined by the mean number of neighbors under fast and slow aggregation regions. It was found that the electrolyte ionic strength affects the kinetic pattern of colloidal aggregation.

Reducing false positives in molecular pattern recognition.

In the search for new cancer subtypes by gene expression profiling, it is essential to avoid misclassifying samples of unknown subtypes as known ones. In this paper, we evaluated the false positive error rates of several classification algorithms through a 'null test' by presenting classifiers a large collection of independent samples that do not belong to any of the tumor types in the training dataset. The benchmark dataset is available at www2.

Learning the parts of objects by auto-association.

Recognition-by-components is one of the possible strategies proposed for object recognition by the brain, but little is known about the low-level mechanism by which the parts of objects can be learned without a priori knowledge. Recent work by Lee and Seung (Nature 401 (1999) 788) shows the importance of non-negativity constraints in the building of such models. Here we propose a simple feedforward neural network that is able to learn the parts of objects by the auto-association of sensory stimuli.