Search

Scientific investigation on essential oils composition and the related biological profile are continuously growing. Nevertheless, only a few studies have been performed on the relationships between chemical composition and biological data. Herein, the investigation of 61 assayed essential oils is reported focusing on their inhibition activity against Microsporum spp. including development of machine learning models with the aim of highlining the possible chemical components mainly related to the inhibitory potency. The application of machine learning and deep learning techniques for predictive and descriptive purposes have been applied successfully to many fields. Quantitative composition-activity relationships machine learning-based models were developed for the 61 essential oils tested as Microsporum spp. growth modulators. The models were built with in-house python scripts implementing data augmentation with the purpose of having a smoother flow between essential oils' chemical compositions and biological data. High statistical coefficient values (Accuracy, Matthews correlation coefficient and F 1 score) were obtained and model inspection permitted to detect possible specific roles related to some components of essential oils' constituents. Robust machine learning models are far more useful tools to reveal data augmentation in comparison with raw data derived models. To the best of the authors knowledge this is the first report using data augmentation to highlight the role of complex mixture components, in particular a first application of these data will be for the development of ingredients in the dermo-cosmetic field investigating microbial species considering the urge for the use of natural preserving and acting antimicrobial agents.

In this work, we evaluated the antidermatophytic activities of three resorcinol derivatives that have a history of use in dermo-cosmetic applications to discover molecules with multiple dermatological activities (i.e., multi-target drugs), thereby reducing the cost and time necessary for new drug development. The antidermatophytic activities of the three skin lighteners were evaluated relative to the known antifungal drug fluconazole on nine dermatophytes responsible for the most common dermatomycoses: Microsporum gypseum , Microsporum canis , Trichophyton violaceum , Arthroderma cajetani , Trichophyton mentagrophytes , Epidermophyton floccosum , Nannizzia gypsea , Trichophyton rubrum and Trichophyton tonsurans . Among the three tested resorcinols, only two showed promising properties, with the ability to inhibit the growth of all tested dermatophytes; additionally, the IC 50 values of these two resorcinols against the nine dermatophytes confirmed their good antifungal activity, particularly for phenylethyl resorcinol against M. gypseum . Ultrastructural alterations exhibited by the fungus were observed using scanning electron microscopy and transmission electron microscopy and reflected a dose-dependent response to treatment with the activation of defence and self-preservation strategies.

Multi-target strategies are directed toward targets that are unrelated (or distantly related) and can create opportunities to address different pathologies. The antidermatophytic activities of nine natural skin lighteners: α-bisabolol, kojic acid, β-arbutin, azelaic acid, hydroquinone, nicotinamide, glycine, glutathione and ascorbyl tetraisopalmitate, were evaluated, in comparison with the known antifungal drug fluconazole, on nine dermatophytes responsible for the most common dermatomycoses: Microsporum gypseum, Microsporum canis, Trichophyton violaceum, Nannizzia cajetani, Trichophyton mentagrophytes, Epidermophyton floccosum, Arthroderma gypseum, Trichophyton rubrum and Trichophyton tonsurans. α-Bisabolol showed the best antifungal activity against all fungi and in particular; against M. gypseum. Further investigations were conducted on this fungus to evaluate the inhibition of spore germination and morphological changes induced by α-bisabolol by TEM.

The phenolic compound phloridzin (phloretin 2′-O-glucoside, variously named phlorizin, phlorrhizin, phlorhizin or phlorizoside) is a prominent member of the chemical class of dihydrochalcones, which are phenylpropanoids. Phloridzin is specifically found in apple and apple juice and known for its biological properties. In particular we were attracted by potential dermo-cosmetic applications. Here we report the synthesis, stability studies and antimicrobial activity of compound F2, a new semi-synthetic derivative of phloridzin. The new derivative was also included in finished formulations to evaluate its stability with a view to a potential topical use. Stability studies were performed by HPLC; PCL assay and ORAC tests were used to determine the antioxidant activity. F2 presented an antioxidant activity very close to that of the parent phloridzin, but, unlike the latter, was more stable in formulations. To further explore potential health claims, antifungal activity of phloridzin and its derivative F2 were determined; the results, however, were rather low; the highest value was 31,6% of inhibition reached by F2 on Microsporum canis at the highest dose.