Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Contributos para a elucidação do modo de ação de própolis português: o caso do própolis do Pereiro

Dissertação de mestrado em Genética Molecular

Caso de demonstração de uma framework para automatização do teste de APIs de aplicações SaaS

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Dissolution enhancement of active pharmaceutical ingredients by therapeutic deep eutectic systems

A therapeutic deep eutectic system (THEDES) is here defined as a deep eutectic solvent (DES) having an active pharmaceutical ingredient (API) as one of the components. In this work, THEDESs are proposed as enhanced transporters and delivery vehicles for bioactive molecules. THEDESs based on choline chloride (ChCl) or menthol conjugated with three different APIs, namely acetylsalicylic acid (AA), benzoic acid (BA) and phenylacetic acid (PA), were synthesized and characterized for thermal behaviour, structural features, dissolution rate and antibacterial activity. Differential scanning calorimetry and polarized optical microscopy showed that ChCl:PA (1:1), ChCl:AA (1:1), menthol:AA (3:1), menthol:BA (3:1), menthol:PA (2:1) and menthol:PA (3:1) were liquid at room temperature. Dissolution studies in PBS led to increased dissolution rates for the APIs when in the form of THEDES, compared to the API alone. The increase in dissolution rate was particularly noticeable for menthol-based THEDES. Antibacterial activity was assessed using both Gram-positive and Gram-negative model organisms. The results show that all the THEDESs retain the antibacterial activity of the API. Overall, our results highlight the great potential of THEDES as dissolution enhancers in the development of novel and more effective drug delivery systems.