In-depth study of phytochemical composition, antioxidant activity, enzyme inhibitory and antiproliferative properties of Achillea filipendulina: a good candidate for designing biologically-active food products

Searching for Natural Plants with Antimelanogenesis and Antityrosinase Properties for Cosmeceutical or Nutricosmetics Applications: A Systematic Review

Excessive UV radiation (UVR) exposure has been shown in studies to be a major risk factor for most melanomas, causing premature skin aging as well as immune system suppression due to the increased production of hydrogen peroxide (H2O2) and other reactive oxygen species (ROS) during the melanogenesis process. Although several compounds with antioxidant and antityrosinase activities are widely used in the cosmetic industry, like kojic acid, hydroquinone, ascorbic acid, and arbutin, their use has been limited due to their adverse effects on the skin and cytotoxic issues. Recently, attempts have been made to develop new natural skin-lightening products by using plant extracts that are less toxic and exhibit numerous biological properties with great market demand. In this study, information on the depigmentation effects of various natural plant species was gathered from the SCOPUS database according to the PRISMA guidelines. A total of 414 records were retrieved, and finally, 76 articles were included in the qualitative synthesis by fulfilling all the inclusion criteria. In this review, we discuss the extraction methods and biological assays of 75 highly potential plant species, including the olive, yuzu, longan, and lotus. We concluded that the use of natural plants as skin-whitening agents is highly effective as there is a significant correlation between the content of polyphenolic compounds, antimelanogenesis, antityrosinase, and antioxidant activities. However, it is worth noting that the use of extraction methods or types of solvents is very important in determining the biological activities of plants.

Dandelion flower-fabricated Ag nanoparticles versus synthetic ones with characterization and determination of photocatalytic, antioxidant, antibacterial, and α-glucosidase inhibitory activities

In the present work, Silver nanoparticles (AgNPs) were fabricated through the dandelion flower hydroalcoholic extract, and their properties were characterized by FTIR, XRD, UV visible, SEM, and EDX. The results demonstrated that the average diameter of the green fabricated AgNPs is 45-55 nm (G-AgNPs). The antioxidant, antimicrobial, antidiabetic, and photocatalytic properties of G-AgNPs were compared with two commercially available different diameter sizes (20 and 80-100 nm) of AgNPs (C-AgNPs1- and C-AgNPs2, respectively). The sample's capacity for antioxidants was evaluated by DPPH free radical scavenging method. The consequences showed that G-AgNPs have higher radical scavenging activity (47.8%) than C-AgNPs2 (39.49%) and C-AgNPs1 (33.91%). To investigate the photocatalytic property, methylene blue dye was used. The results displayed that G-AgNPs is an effective photo-catalyst compared to C-AgNPs2 and C-AgNPs1, which respectively have an inhibition potential of 75.22, 51.94, and 56.65%. Also, the antimicrobial capacity of nanoparticles was assayed against, the gram-negative Escherichia coli and gram-positive Staphylococcus aureus bacteria. The results indicated that G-AgNPs could effectively inhibit the growth of both bacteria, compared to C-AgNPs1 and C-AgNPs2. Finally, G-AgNPs exhibited a considerable α-glucosidase enzyme inhibitory effect (88.37%) in comparison with C-AgNPs1 (61.7%) and C-AgNPs2 (50.5%).

Deep Learning Target Detection System for Sewage Treatment

Object detection is to identify objects and then find some objects of interest. With the development of computers, target detection has evolved from traditional detection methods to artificial intelligence methods, and the latter are mainly based on some algorithms of deep learning. This paper mainly tests the treated sewage. First, the neural network and convolutional neural network algorithms in deep learning are studied, and then a target detection system is built based on these two algorithms. Finally, the treated sewage is detected and then compared with that of the traditional target detection system. The experimental results show that the target detection system of the convolutional neural network algorithm has a very stable recognition rate for the treated sewage, swinging around 70%, and the amplitude is not large. However, the target detection system of the neural network algorithm is not very stable in the recognition rate of the treated sewage, and the recognition rate is about 60%.

UHPLC-MS Characterization and Biological Insights of Different Solvent Extracts of Two Achillea Species (A. aleppica and A. santolinoides) from Turkey

In the current study, Achillea santolinoides and Achillea aleppica aeral parts and root were extracted with ethyl acetate, methanol, and water. Detailed phytochemical profiles were obtained using UHPLC-MS, yielding the identification of hydroxybenzoic and hydroxycinnamic acids, phenolic acid glycosides and sugar esters, acylquinic acids, O-glycosyl flavones and flavonols, and flavonoid aglycons, among others. The antioxidant properties and enzyme inhibitory activities of the extracts were assayed with in vitro tests. The phenolic content of the water extracts was significantly higher as compared to the ethyl acetate and methanol ones. A. aleppica aerial parts methanol extract possessed highest flavonoid content (49.18 mg rutin equivalent/g). Antioxidant properties assessment revealed that the methanol extract of A. santolinoides roots actively scavenged DPPH (54.11 mg TE/g) and ABTS radicals (112.53 mg TE/g) and possessed highest reducing potential (183.55 and 129.92 mg TE/g, for CUPRAC and FRAP, respectively). The ethyl acetate extracts of aerial parts and roots of both species showed highest inhibition against BuCHE (6.07–6.76 mg GALAE/g). The ethyl acetate extract of A.santolinoides aerial part showed highest inhibition against tyrosinase (73.00 mg KAE/g). These results showed that the tested Achillea species might represent novel phytotherapeutic avenues for the management of Alzheimer’s disease and epidermal hyperpigmentation conditions, which are both associated with oxidative stress. This paper could shed light into future potential industrial applications using the tested Achillea species.