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Publication
Natural Mineral Water–Plant Extract Combinations as Potential Anti-Aging Ingredients: An In Vitro Evaluation
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Advisor(s)
Abstract(s)
Natural mineral waters (NMWs) and plant extracts have long been valued for their therapeutic properties and skin benefits. This study investigated, in vitro, the role of five Portuguese NMWs (A-E), combined with plant extracts from five species (Ficus carica L., Rubus idaeus L., Vaccinium myrtillus, Cistus ladanifer and Thymus x citriodorus) as bioactive ingredients. Antioxidant capacity was assessed using the 2,2-Diphenyl-1-picrylhydrazyl (DPPH) method. Cellular biocompatibility was evaluated in fibroblasts (L929) and macrophages (RAW 264.7). Skin-repairing and anti-senescence properties were evaluated in L929 cells through the scratch-wound method and beta-galactosidase assay. Superoxide dismutase (SOD) was quantified using a commercial kit, and lipopolysaccharide-induced reactive oxygen species (ROS) were quantified using a fluorescent probe (H2DCFDA) in RAW 264.7. The results highlighted the beneficial impact of extracts combined with NMWs. An increase in antioxidant capacity of up to 90% was observed in mixtures comprising Ficus carica L., compared with NMWs alone. In contrast, mixtures with Cistus ladanifer showed promising anti-aging potential, with a 40% decrease in senescent cells and a 33% ROS reduction. Rubus idaeus L. extract produced an increase in cell migration capacity (up to 50%), depending on the NMW. This study highlights the potential synergism of natural ingredients with plant extracts for anti-aging.
Description
Keywords
Anti-aging Agro-industrial residues Hydrolates Natural mineral waters Skincare
Pedagogical Context
Citation
Gomes, Carolina P.; Oliveira, Ana S.; Rolo, Joana; Silveira, Tayse F.F. da; Palmeira de Oliveira, Rita; Alves, Maria José; Plasencia, Paula; Palmeira de Oliveira, Ana (2025). Natural Mineral Water–Plant Extract Combinations as Potential Anti-Aging Ingredients: An In Vitro Evaluation. Cosmetics. ISSN 2079-9284. 12:3, p. 1-19
Publisher
MDPI