Optimized production of a high-performance hybrid biomaterial: biomineralized spider silk for bone tissue engineering

Silks have been widely used as biomaterials due to their biocompatibility, biodegradability, and excellent mechanical properties. In the present work, native spider silk was used as organic template for controlled nucleation of hydroxyapatite (HA) nano-coating that can act as biomimetic interface. Different bio-inspired neutralization methods and process parameters were evaluated to optimize the silk functionalization. The morphology and chemical composition were investigated by scanning electron microscopy, energy-dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy, and X-ray diffraction analysis and mechanical properties were studied through tensile tests. Results showed that the optimized protocol enabled a controlled and homogeneous nucleation of apatite nano-crystals while maintaining silk mechanical performances after mineralization. This study reports the optimization of a simple and effective bio-inspired nucleation process for precise nucleation of HA onto spider silk templates, suitable to develop high-performance hybrid interfaces for bone tissue engineering. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48739.     

Tracking Hidden Binding Pockets Along the Molecular Recognition Path of l-Trp to Indoleamine 2,3-Dioxygenase 1

Indoleamine 2,3-dioxygenase 1 (IDO1) catalyzes the oxidative cleavage of l -Tryptophan (l -Trp) to yield N-formyl-kynurenine in the first and rate limiting step of the kynurenine pathway. Bioactive metabolites, involved in the regulation of important immunological responses and neurological processes, are then produced by downstream enzymes along the pathway. Inhibitors of IDO1 are being designed and developed as therapeutic agents for immuno-oncology. In this work, we investigated the molecular recognition path of l -Trp to IDO1, integrating biophysical methods with supervised molecular dynamics (suMD) and mutagenesis experiments. Results allowed disclosing for the first time high and low dissociation constants of l -Trp to IDO1, and the presence of a metastable interaction site located at the upper part of a channel whose borders are defined by the EF-loop and the C-terminal part of the JK-loop. Collectively, our results provide new clues for the design of next-generation IDO1 ligands.     

Microtopography of the eye surface of the crab Carcinus maenas: an atomic force microscope study suggesting a possible antifouling potential

Marine biofouling causes problems for technologies based on the sea, including ships, power plants and marine sensors. Several antifouling techniques have been applied to marine sensors, but most of these methodologies are environmentally unfriendly or ineffective. Bioinspiration, seeking guidance from natural solutions, is a promising approach to antifouling. Here, the eye of the green crab Carcinus maenas was regarded as a marine sensor model and its surface characterized by means of atomic force microscopy. Engineered surface micro- and nanotopography is a new mechanism found to limit biofouling, promising an effective solution with much reduced environmental impact. Besides giving a new insight into the morphology of C. maenas eye and its characterization, our study indicates that the eye surface probably has antifouling/fouling-release potential. Furthermore, the topographical features of the surface may influence the wettability properties of the structure and its interaction with organic molecules. Results indicate that the eye surface micro- and nanotopography may lead to bioinspired solutions to antifouling protection.     

Minimum Hellinger distance based inference for scalar skew-normal and skew-t distributions

The skew-normal is a parametric model that extends the normal family by the addition of a shape parameter to account for skewness. As well, the skew-t distribution is generated by a perturbation of symmetry of the basic Student’s t density. These families share some nice properties. In particular, they allow a continuous variation through different degrees of asymmetry and, in the case of the skew-t, tail thickness, but still retain relevant features of the perturbed symmetric densities. In both models, a problem occurs in the estimation of the skewness parameter: for small and moderate sample sizes, the maximum likelihood method gives rise to an infinite estimate with positive probability, even when the sample skewness is not too large. To get around this phenomenon, we consider the minimum Hellinger distance estimation technique as an alternative to maximum likelihood. The method always leads to a finite estimate of the shape parameter. Furthermore, the procedure is asymptotically efficient under the assumed model and allows for testing hypothesis and setting confidence regions in a standard fashion.     

Home visits by neighborhood Mentor Mothers provide timely recovery from childhood malnutrition in South Africa: results from a randomized controlled trial

Background  

Child and infant malnourishment is a significant and growing problem in the developing world. Malnourished children are at high risk for negative health outcomes over their lifespans. Philani, a paraprofessional home visiting program, was developed to improve childhood nourishment. The objective of this study is to evaluate whether the Philani program can rehabilitate malnourished children in a timely manner.     

On the power of structural decompositions of graph-based representations of constraint problems

The Constraint Satisfaction Problem (CSP) is a central issue of research in Artificial Intelligence. Due to its intractability, many efforts have been made in order to identify tractable classes of CSP instances, and in fact deep and useful results have already been achieved. In particular, this paper focuses on structural decomposition methods, which are essentially meant to look for near-acyclicity properties of the graphs or hypergraphs that encode the structure of the constraints interactions. In general, constraint scopes comprise an arbitrary number of variables, and thus this structure may be naturally encoded via hypergraphs. However, in many practical applications, decomposition methods are applied over suitable graph representations of the (possibly non-binary) CSP instances at hand. Despite the great interest in such binary approaches, a formal analysis of their power, in terms of their ability of identifying islands of tractability, was missing in the literature.The aim of this paper is precisely to fill this gap, by studying the relationships among binary structural methods, and by providing a clear picture of the tractable fragments of CSP that can be specified with respect to each of these decomposition approaches, when they are applied to binary representations of non-binary CSP instances. In particular, various long-standing questions about primal, dual and incidence graph encodings are answered. The picture is then completed by comparing methods on binary encodings with methods specifically conceived for non-binary constraints.     

Selection of a representative value function in robust multiple criteria sorting

We introduce the concept of a representative value function in robust ordinal regression applied to multiple criteria sorting problems. The proposed approach can be seen as an extension of UTADIS^GMS, a new multiple criteria sorting method that aims at assigning actions to p pre-defined and ordered classes. The preference information supplied by the decision maker (DM) is composed of desired assignments of some reference actions to one or several contiguous classes—they are called assignment examples. The robust ordinal regression builds a set of general additive value functions compatible with the assignment examples and results in two assignments: necessary and possible. The necessary assignment specifies the range of classes to which the action can be assigned considering all compatible value functions simultaneously. The possible assignment specifies, in turn, the range of classes to which the action can be assigned considering any compatible value function individually. In this paper, we propose a way of selecting a representative value function among the set of compatible ones. We identify a few targets which build on results of the robust ordinal regression and could be attained by a representative value function. They concern enhancement of differences between possible assignments of two actions. In this way, the selected function highlights the most stable part of the robust sorting, and can be perceived as representative in the sense of robustness preoccupation. We envisage two possible uses of the representative value function in decision support systems. The first one is an explicit exhibition of the function along with the results of the UTADIS^GMS method, in order to help the DM to understand the robust sorting. The other is an autonomous use, in order to supply the DM with sorting obtained by an example-based procedure driven by the chosen function. Three case studies illustrating the use of a representative value function in real-world decision problems are presented. One of those studies is devoted to the comparison of the introduced concept of representativeness with alternative procedures for determining a single value function, which we adapted to sorting problems, because they were originally proposed for ranking problems.