Protein delivery based on uncoated and chitosan-coated mesoporous silicon microparticles

Mesoporous silicon is a biocompatible, biodegradable material that is receiving increased attention for pharmaceutical applications due to its extensive specific surface. This feature enables to load a variety of drugs in mesoporous silicon devices by simple adsorption-based procedures. In this work, we have addressed the fabrication and characterization of two new mesoporous silicon devices prepared by electrochemistry and intended for protein delivery, namely: (i) mesoporous silicon microparticles and (ii) chitosan-coated mesoporous silicon microparticles. Both carriers were investigated for their capacity to load a therapeutic protein (insulin) and a model antigen (bovine serum albumin) by adsorption. Our results show that mesoporous silicon microparticles prepared by electrochemical methods present moderate affinity for insulin and high affinity for albumin. However, mesoporous silicon presents an extensive capacity to load both proteins, leading to systems were protein could represent the major mass fraction of the formulation. The possibility to form a chitosan coating on the microparticles surface was confirmed both qualitatively by atomic force microscopy and quantitatively by a colorimetric method. Mesoporous silicon microparticles with mean pore size of 35 nm released the loaded insulin quickly, but not instantaneously. This profile could be slowed to a certain extent by the chitosan coating modification. With their high protein loading, their capacity to provide a controlled release of insulin over a period of 60-90 min, and the potential mucoadhesive effect of the chitosan coating, these composite devices comprise several features that render them interesting candidates as transmucosal protein delivery systems.     

Decomposing profit inefficiency in DEA through the weighted additive model

An issue that has received little attention in the Data Envelopment Analysis literature is the decomposition of profit inefficiency by means of measures that account all sources of technical inefficiency. In this paper we introduce a new way to measure and decompose profit inefficiency through weighted additive models. All our results are derived from a new Fenchel-Mahler inequality using duality theory.     

Exploring the thermochromism of sulfite-embedded polyoxometalate capsules

The Dawson-type polyanion [α-Mo(18)O(54)(SO(3))(2)](4-), with two SO(3)(2-) templates embedded inside a polyoxomolybdate(vi) cage, exhibits thermochromism over an exceptionally wide temperature range (～500 K). The temperature dependence of the cluster structure, established from X-ray crystallography, IR and Raman spectroscopy and DFT calculations, is related to a decreasing HOMO-LUMO gap in the near UV with increasing temperature. We postulate this is due to geometrical changes that affect both the occupied and unoccupied frontier molecular orbitals of this cluster anion.     

Multilevel Monte Carlo in approximate Bayesian computation

In the following article, we consider approximate Bayesian computation (ABC) inference. We introduce a method for numerically approximating ABC posteriors using the multilevel Monte Carlo (MLMC). A sequential Monte Carlo version of the approach is developed and it is shown under some assumptions that for a given level of mean square error, this method for ABC has a lower cost than i.i.d. sampling from the most accurate ABC approximation. Several numerical examples are given.     

Design and Tuning of Photoswitches for Solar Energy Storage

Current energy demand makes it compulsory to explore alternative energy sources beyond fossil fuels. Molecular solar thermal (MOST) systems have been proposed as a suitable technology for the use and storage of solar energy. Compounds used for this application need to fulfil a long series of requirements, being the absorption of sunlight and the energy stored some of the most critical. In this paper, we study different families of well-known molecular photoswitches from the point of view of their potential use as MOST. Starting from basic structures, we use density functional theory (DFT) computational modelling to propose two different strategies to increase the energy difference between isomers and to tune the absorption spectrum. The inclusion of a mechanical lock in the structure, via an alkyl chain and the presence of a hydrogen bonding are shown to directly influence the energy difference and the absorption spectra. Results shown here prove that these two approaches could be relevant for the design of new compounds with improved performance for MOST applications.     

A novel analog fuzzy controller for intelligent sensors

A new analog fuzzy logic controller implemented in CMOS technology is described. The chosen membership function generator keeps the needed area for the inference engine very small while giving a big flexibility in the configuration of the membership function. The proposed solution for defuzzification gives an additional area reduction over earlier implementations. High speed, low power fuzzy controller hardware make the chip appropriate for intelligent sensor application. Simulation results as well as test measurements are presented and discussed to illustrate the properties and robustness of the proposed circuit.     

Chapter 3 Translation invariance in data envelopment analysis: A generalization

In this paper, we undertake a revision and a generalization of the results contained in the only paper so far published on the matter of translation invariance by allowing inputs and outputs to take not only zero but negative values. This broadens the field of application of the DEA methodology.