From perfect strangers to research partners: a study of relationships, resource sharing and perceived benefits within R&D cooperation networks

Doctoral thesis in Marketing and Strategy.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Polysaccharide-based freestanding multilayered membranes exhibiting reversible switchable properties

The design of self-standing multilayered structures based on biopolymers has been attracting increasing interest due to their potential in the biomedical field. However, their use has been limited due to their gel-like properties. Herein, we report the combination of covalent and ionic cross-linking, using natural and non-cytotoxic cross-linkers, such as genipin and calcium chloride (CaCl2). Combining both cross-linking types the mechanical properties of the multilayers increased and the water uptake ability decreased. The ionic cross-linking of multilayered chitosan (CHI)â alginate (ALG) films led to freestanding membranes with multiple interesting properties, such as: improved mechanical strength, calcium-induced adhesion and shape memory ability. The use of CaCl2 also offered the possibility of reversibly switching all of these properties by simple immersion in a chelate solution. We attribute the switch-ability of the mechanical properties, shape memory ability and the propensity for induced-adhesion to the ionic cross-linking of the multilayers. These findings suggested the potential of the developed polysaccharide freestanding membranes in a plethora of research fields, including in biomedical and biotechnological fields.