Novel etheroatom containing aliphatic polyesters for biomedical and environmental applications

Biodegradable polymers for short time applications have attracted much interest all over the world. The reason behind this growing interest is the incompatibility of the polymeric wastes with the environment where they are disposed after usage. Synthetic aliphatic polyesters represent one of the most economically competitive biodegradable polymers. In addition, they gained considerable attention as they combine biodegradability and biocompatibility with interesting physical and chemical properties. In this framework, the present research work focused on the modification by reactive blending and polycondensation of two different aliphatic polyesters, namely poly(butylene succinate) (PBS) and poly(butylene 1,4-cyclohexanedicarboxylate) (PBCE). Both are characterized by good thermal properties, but their mechanical characteristics do not fit the requirements for applications in which high flexibility is requested and, moreover, both show slow biodegradation rate. With the aim of developing new materials with improved characteristics with respect to the parent homopolymers, novel etheroatom containing PBS and PBCE-based fully aliphatic polyesters and copolyesters have been therefore synthesized and carefully characterized. The introduction of oxygen or sulphur atoms along the polymer chains, by acting on chemical composition or molecular architecture, tailored solid-state properties and biodegradation rate: type and amount of comonomeric units and sequence distribution deeply affected the material final properties owing, among all, to the hydrophobic/hydrophilic ratio and to the different ability of the polymer to crystallize. The versatility of the synthesized copolymers has been well proved: as a matter of fact these polymers can be exploited both for biomedical and ecological applications. Feasibility of 3D electrospun scaffolds has been investigated, biocompatibility studies and controlled release of a model molecule showed good responses. As regards ecological applications, barrier properties and eco-toxicological assessments have been conducted with outstanding results. Finally, the ability of the novel polyesters to undergo both hydrolytic and enzymatic degradation has been demonstrated under physiological and environmental conditions.

Differential expression analysis for sequence count data via mixtures of negative binomials

The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.