ABSTRACT
Cuscuta chinensis (C. chinensis) presents many pharmacological activities, including antidiabetic effects, and antioxidant, anti-inflammatory, and antitumor properties. However, the wound care properties of this plant have not yet been reported. Therefore, this research aimed to evaluate the antioxidant, anti-inflammatory, and antibacterial activities of ethanol and ethyl acetate C. chinensis extracts. The phytochemical markers in the extracts were analyzed using high-performance liquid chromatography (HPLC). Then, the selected C. chinensis extract was developed into a nanoemulsion-based gel for wound care testing in rats. The results showed that both of the C. chinensis extracts exhibited antioxidant activity when tested using 2,2-Diphenyl-1-picrylhydrazyl (DPPH), ferric reducing antioxidant power (FRAP), and lipid peroxidation inhibition assays. They reduced the expression of IL-1ß, IL-6, and TNF-α in RAW264.7 cells induced with lipopolysaccharide (LPS). The ethyl acetate extract also had antibacterial properties. Kaempferol was found in both extracts, whereas hyperoside was found only in the ethanol extract. These compounds were found to be related to the biological activities of the extracts, confirmed via molecular docking. The C. chinensis extract-loaded nanoemulsions had a small particle size, a narrow polydispersity index (PDI), and good stability. Furthermore, the C. chinensis extract-loaded nanoemulsion-based gel had a positive effect on wound healing, presenting a better percentage wound contraction Fucidin cream. In conclusion, this formulation has the potential for use as an alternative wound treatment and warrants further study in clinical trials.
ABSTRACT
Cosmetics consumers need to be aware of their skin type before purchasing products. Identifying skin types can be challenging, especially when they vary from oily to dry in different areas, with skin specialist providing more accurate results. In recent years, artificial intelligence and machine learning have been utilized across various fields, including medicine, to assist in identifying and predicting situations. This study developed a skin type classification model using a Convolutional Neural Networks (CNN) deep learning algorithms. The dataset consisted of normal, oily, and dry skin images, with 112 images for normal skin, 120 images for oily skin, and 97 images for dry skin. Image quality was enhanced using the Contrast Limited Adaptive Histogram Equalization (CLAHE) technique, with data augmentation by rotation applied to increase dataset variety, resulting in a total of 1,316 images. CNN architectures including MobileNet-V2, EfficientNet-V2, InceptionV2, and ResNet-V1 were optimized and evaluated. Findings showed that the EfficientNet-V2 architecture performed the best, achieving an accuracy of 91.55% with average loss of 22.74%. To further improve the model, hyperparameter tuning was conducted, resulting in an accuracy of 94.57% and a loss of 13.77%. The Model performance was validated using 10-fold cross-validation and tested on unseen data, achieving an accuracy of 89.70% with a loss of 21.68%.
ABSTRACT
Benincasa hispida peel, a type of postconsumer waste, is considered a source of beneficial phytochemicals. Therefore, it was subjected to investigation for biological activities in this study. B. hispida peel was extracted using 95% v/v, 50% v/v ethanol and water. The obtained extracts were B95, B50 and BW. B95 had a high flavonoid content (212.88 ± 4.73 mg QE/g extract) and phenolic content (131.52 ± 0.38 mg GAE/g extract) and possessed high antioxidant activities as confirmed by DPPH, ABTS and lipid peroxidation inhibition assays. Moreover, B95 showed inhibitory effects against collagenase and hyaluronidase with values of 41.68 ± 0.92% and 29.17 ± 0.66%, which related to anti-aging activities. Via the HPLC analysis, one of the potential compounds found in B95 was rutin. Molecular docking has provided an understanding of the molecular mechanisms underlying the interaction of extracts with collagenase and hyaluronidase. All extracts were not toxic to fibroblast cells and did not irritate the hen's egg chorioallantoic membrane, which indicated its safe use. In conclusion, B. hispida peel extracts are promising potential candidates for further use as antioxidant and anti-aging agents in the food and cosmetic industries.
ABSTRACT
Polycyclic aromatic hydrocarbons (PAHs) are the main toxic components of ambient air particulate matter (PM), causing oxidative damage to the skin and ultimately resulting in skin aging. This study was conducted to determine the anti-oxidant, anti-aging properties and protective effects of the extracts of coffee cherry pulp (Coffea arabica L.), which is a by-product of the coffee industry, against the oxidative damage induced by PAH exposure in human epidermal keratinocytes (HaCaT). Three different techniques were used to extract the coffee cherry pulp: maceration, Soxhlet and ultrasonication to obtain CCM, CCS and CCU extract, respectively, which were then compared to investigate the total phenolic content (TPC) and total flavonoid content (TFC). The chemical compositions were identified and quantified using high-performance liquid chromatography (HPLC). The results demonstrated that Soxhlet could extract the highest content of chlorogenic acid, caffeine and theophylline. CCS showed the significantly highest TPC (324.6 ± 1.2 mg GAE/g extract), TFC (296.8 ± 1.2 mg QE/g extract), anti-radical activity against DPPH free radicals (98.2 ± 0.8 µM Trolox/g extract) and lipid peroxidation inhibition (136.6 ± 6.2 µM Trolox/g extract). CCS also showed the strongest anti-aging effects based on collagenase, elastase, hyaluronidase and tyrosinase inhibitory enzymes. In addition, CCS can protect human keratinocyte cells from PAH toxicity by increasing the cellular anti-oxidant capacity. This study suggests that CCS has the potential to be used as a cosmetic material that helps alleviate skin damage caused by air pollution.
