In this work, the biological and chemical fingerprints of three extracts (ethyl acetate, methanol and water) from two Potentilla species (P. reptans and P. speciosa) were investigated. Antioxidant, enzyme inhibitory, and cytotoxic activities were performed for the biological fingerprint. For the chemical characterization, total bioactive components and individual phenolic components were determined using photometric and HPLC methods, respectively. The main identified phenolic compounds in these extracts were rutin and catechin. Methanol and water extracts contained the highest total phenolic and flavonoid content. The results of antioxidant assays showed that methanol and water extracts displayed higher antioxidant activity compared to the ethyl acetate extract. Generally, methanol and water extracts exhibited higher biological activities correlated with higher levels the bioactive components. For P. speciosa, the methanol extract exhibited the highest enzyme inhibitory activity (except BChE inhibitory activity). P. reptans exhibited also high antiproliferative activity against MCF-7 cells whilst P. speciosa had weak to moderate activity against both of A549 and MCF-7 cell lines. The results suggest that Potentilla species could be potential candidates for developing new phyto-pharmaceuticals and functional ingredients.

Fully ripe fruits and mature leaves of Elaeagnus angustifolia were harvested and analyzed by means of analytical and biological tests to better comprehend the chemical composition and therapeutic/nutraceutical potential of this plant. Fruits and leaves were dried and the obtained powders were analyzed to study their color character and (via headspace gas chromatography) describe the chemical profile. Subsequently, they were submitted to a chloroform–methanol extraction, to a hydroalcoholic extraction procedure assisted or not by microwaves, and to an extraction with supercritical CO₂, assisted or not by ethanol as the co-solvent, to detect the polyphenolic and the volatile content. The resulting extracts were evaluated in terms of chlorophyll and carotenoid content, polyphenolic content, volatile fraction, total phenolic content, total flavonoid content, antioxidant activity, radical scavenging activity, and enzymatic inhibition activity. The results confirmed the correlation between the chemical composition and the high antioxidant potential of leaf extracts compared to the fruit extracts in terms of the phenolic and pigment content. A promising effect against tyrosinase emerged for all the extracts, suggesting a therapeutic/nutraceutical use for this plant. Conversely, the volatile content from both natural matrices was similar.

The main goals of this research were the chemical and biological characterization of the bitter melon (Momordica charantia) isolate obtained by traditional (maceration) extraction, as well as optimization of this process using response surface methodology (RSM) and artificial neural networks (ANNs). Experiments were performed using Box–Behnken experimental design on three levels and three variables: extraction temperature (20 °C, 40 °C, and 60 °C), solvent concentration (30%, 50%, and 70%) and extraction time (30, 60, and 90 min). The measurements consisted of 15 randomized runs with 3 replicates in a central point. The antioxidant activity of obtained extracts was determined by the 1,1-diphenyl-2-picrylhydrazyl (DPPH), cupric ion reducing antioxidant capacity (CUPRAC) and ferric reducing antioxidant power (FRAP) assays while chemical characterization was done in terms of the total phenolic content (TPC). The methodology shows positive influence of solvent concentration on all four observed outputs, while temperature showed a negative impact. RSM showed that the optimal extraction conditions were 20 °C, 70% methanol, and an extraction time of 52.2 min. Under these conditions, the TPCs were 20.66 milligrams of gallic acid equivalents (mg GAE/g extract), DPPH 30.22 milligrams of trolox equivalents (mg TE/g extract), CUPRAC 67.78 milligrams of trolox equivalents (mg TE/g extract), and FRAP 45.48 milligrams of trolox equivalents (mg TE/g extract). The neural network coupled with genetic algorithms (ANN-GA) was also used to optimize the conditions for each of the outputs separately. It is anticipated that results reported herein will establish baseline data and also demonstrate that that the present model can be applied in the food and pharmaceutical industries.