Designing Temperature-Responsive Biocompatible Copolymers and Hydrogels Based on 2-Hydroxyethyl(meth)acrylates

Free-radical copolymerization of 2-hydroxyethyl methacrylate with 2-hydroxyethyl acrylate can be successively utilized for the synthesis of water-soluble polymers and hydrogels with excellent physicochemical properties, thus showing promise for pharmaceutical and biomedical applications. In the work presented it has been demonstrated that water-soluble copolymers based on 2-hydroxyethyl methacrylate and 2-hydroxyethyl acrylate exhibit lower critical solution temperature in aqueous solutions, whereas the corresponding high molecular weight homopolymers do not have this unique property. The temperature-induced transitions observed upon heating the aqueous solutions of these copolymers proceed via liquid−liquid phase separation. The hydrogels were also synthesized by copolymerizing 2-hydroxyethyl methacrylate and 2-hydroxyethyl acrylate in the absence of a bifunctional cross-linker. The cross-linking of these copolymers during copolymerization is believed to be due to the presence of bifunctional admixtures or transesterification reactions. Transparency, swelling behavior, mechanical properties, and porosity of the hydrogels are dependent upon the monomer ratio in the copolymers. Hydrogel samples containing more 2-hydroxyethyl methacrylate are less transparent, have lower swelling capacity, higher elastic moduli, and pores of smaller size. The assessment of the biocompatibility of the copolymers using the slug mucosal irritation test revealed that they are also less irritant than poly(acrylic acid).

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC.

Detection of pressed hazelnut oil in virgin olive oil by analysis of polar components: improvement and validation of the method

An improved method for the detection of pressed hazelnut oil in admixtures with virgin olive oil by analysis of polar components is described. The method. which is based on the SPE-based isolation of the polar fraction followed by RP-HPLC analysis with UV detection. is able to detect virgin olive oil adulterated with pressed hazelnut oil at levels as low as 5% with accuracy (90.0 +/- 4.2% recovery of internal standard), good reproducibility (4.7% RSD) and linearity (R-2: 0.9982 over the 5-40% adulteration range). An international ring-test of the developed method highlighted its capability as 80% of the samples were, on average, correctly identified despite the fact that no training samples were provided to the participating laboratories. However, the large variability in marker components among the pressed hazelnut oils examined prevents the use of the method for quantification of the level of adulteration. (C) 2003 Elsevier Ltd. All rights reserved.