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Inhibition of melanogenesis by quercetin and vitamin E is extensively reported in the literature, independently, with limitations in antioxidant potential owing to less permeation, solubility, decreased bioavailability, and reduced stability. Thus, the aim of the present study was to synthesize a novel complex of metal ions (copper and zinc) with quercetin to enhance antioxidant properties which were confirmed by docking studies. Polycaprolactone-based nanoparticles of the synthesized complex (PCL-NPs, Q-PCL-NPs, Zn-Q-PCL-NPs, Cu-Q-PCL-NPs) were made later loaded with vitamin E which made the study more interesting in enhancing antioxidant profile. Nanoparticles were characterized for zeta size, charge, and polydispersity index, while physiochemical analysis of nanoparticles was strengthened by FTIR. Cu-Q-PCL-NPs-E showed maximum in vitro release of vitamin E, i.e., 80 ± 0.54%. Non-cellular antioxidant effect by 2,2-diphenyl-1-picrylhydrazyl was observed at 93 ± 0.23% in Cu-Q-PCL-NPs-E which was twofold as compared to Zn-Q-PCL-NPs-E. Michigan Cancer Foundation-7 (MCF-7) cancer cell lines were used to investigate the anticancer and cellular antioxidant profile of loaded and unloaded nanoparticles. Results revealed reactive oxygen species activity of 90 ± 0.32% with the addition of 89 ± 0.64% of its anticancer behavior shown by Cu-Q-PCL-NPs-E after 6 and 24h. Similarly, 80 ± 0.53% inhibition of melanocyte cells and 95 ± 0.54% increase of keratinocyte cells were also shown by Cu-Q-PCL-NPs-E that confirmed the tyrosinase enzyme inhibitory effect. Conclusively, the use of zinc and copper complex in unloaded and vitamin E–loaded nanoparticles can provide enhanced antioxidant properties with inhibition of melanin, which can be used for treating diseases of melanogenesis. [ABSTRACT FROM AUTHOR]

Flavonoids are present naturally in many fruits and vegetables including onions, apples, tea, cabbage, cauliflower, berries and nuts which provide us with quercetin, a powerful natural antioxidant and cytotoxic compound. Due to antioxidant property, many nutraceuticals and cosmeceuticals products contain quercetin as a major ingredient nowadays. Current review enlightened sources and quercetin's role as an antioxidant, antimicrobial, antidiabetic, anticancerous and anti-inflammatory agent in medical field during last 5 to 6 years. Literature search was systematically done using scientific for the published articles of quercetin. A total of 345 articles were reviewed, and it was observed that more than 40% of articles were about quercetin's use as an antioxidant agent, more than 25% of studies were about its use as an anticancer agent, and articles on antimicrobial activity were more than 15%. 10% of the articles showed anti-inflamamatory effects of quercetin. Literature search also revealed that quercetin alone and its complexes with chitosan, metal ions and polymers possessed good antidiabetic properties. Thus, the review focuses on new therapeutic interventions and drug delivery system of quercetin in medical field for the benefit of mankind. [ABSTRACT FROM AUTHOR]

Particulate matter has a detrimental consequence on the health of living organisms throughout the world and predicting their concentration is very imperative to assess their impact on human health. Faridabad is the most populated and largest city of Haryana, India, and the current study was designed to foresee the PM2.5 content by different modeling techniques: (1) support vector machine (SVM), (ii) random forest (RF), (iii) artificial neural network (ANN), (iv) M5P model, and (v) Gaussian process regression (GP). Collected data (659 observations) from May 2015 to May 2018 were used to develop the models. Parameters such as temperature (T), ground-level ozone (O3), sulfur dioxide (SO2), nitrogen dioxide (NO2), nitric oxide (NO), NOx, wind speed (WS), wind direction (WD), relative humidity (RH), bar pressure (BP), and solar radiation (SR) are used as input parameters for prediction of PM2.5. The results of all the models suggested that RF model with testing correlation coefficient (CC) 0.8312, mean absolute error (MAE) 30.7757, R2 (correlation of determination) 0.6909, and root mean square error (RMSE) 44.6947 is the best estimator for appraisal of PM2.5 followed by SVM, GP, M5P, and ANN models. The sensitivity analysis results indicated that wind speed is the utmost influencing parameter for the estimation of PM2.5. Abilities of different models were compared and RF was established as the best technique based on assessment criteria. We recommend more studies employing RF and other techniques as hybrids that lead to better models. [ABSTRACT FROM AUTHOR]