Antioxidant potential of two Apiaceae plant extracts: a comparative study focused on the phenolic composition

The present study aimed to characterize the extracts prepared from Pimpinella anisum L. (anise) and Coriandrum sativum L. (coriander) (Apiaceae plants) seeds in terms of phenolic composition, and to correlate the obtained profiles with the antioxidant activity. Anise gave the highest abundance in phenolic compounds (42.09± 0.11 mg/g extract), mainly flavonoids (28.08±0.17 mg/g extract) and phenolic acids (14.01±0.06 mg/g extract), and also the highest antioxidant potential, accessed for the ability to inhibit lipid peroxidation and -carotene bleaching, reducing power and free radical scavenger activity. Apigenin and luteolin derivatives, as also caffeoylquinic acid derivatives appear to be directly related with the higher in vitro antioxidant potential of the anise extract.. In contrast, the weak antioxidant potential of coriander seems to be due to their lower abundance in phenolic compounds (2.24±0.01 mg/g extract). Further studies are necessary to evaluate the in vivo antioxidant potential of the tested extracts, but the performed in vitro experiments highlight them as potential health promoters.

Pharmacological evaluation of plant extracts from Chapada Diamantina (Bahia, Brazil): Focus on antioxidant and cytotoxic properties

Tese de Doutoramento em Biologia de Plantas MAP - Bioplant

Nanotechnological approaches using curcumin and Withania somnifera: neuroprotection and antimicrobial activities

Tese de Doutoramento em Biologia de Plantas

Impact of an educational hands-on project on the antimicrobial, antitumor and anti-inflammatory properties of plants on Portuguese students' awareness, knowledge, and competences

Promoting environmental and health education is crucial to allow students to make conscious decisions based on scientific criteria. The study is based on the outcomes of an Educational Project implemented with Portuguese students and consisted of several activities, exploring pre-existent Scientific Gardens at the School, aiming to investigate the antibacterial, antitumor and anti-inflammatory properties of plant extracts, with posterior incorporation in soaps and creams. A logo and a webpage were also created. The effectiveness of the project was assessed via the application of a questionnaire (pre- and post-test) and observations of the participants in terms of engagement and interaction with all individuals involved in the project. This project increased the knowledge about autochthonous plants and the potential medical properties of the corresponding plant extracts and increased the awareness about the correct design of scientific experiments and the importance of the use of experimental models of disease. The students regarded their experiences as exciting and valuable and believed that the project helped to improve their understanding and increase their interest in these subjects and in science in general. This study emphasizes the importance of raising students’ awareness on the valorization of autochthonous plants and exploitation of their medicinal properties.

Evolution of the gene regulatory network controlling flower dorsoventral asymmetry

Tese de Doutoramento em Biologia de Plantas.

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.