Natural products and extracts from plants as natural UV filters for sunscreens:A review

Although solar exposure is necessary for human health,phototoxicology induced by excessive UVB and UVA radiation,which involves sunburns,skin aging and even tu-morigenesis,has been widely researched.Sunscreen is one of the most important ways to protect skin from UV phototoxic damage.As well as inorganic and organic UV filters,some natural products or plant extracts with aromatic rings in their structures,such as flavonoids or polyphenols,can absorb UV to reduce sunburn,acting as a natu-ral UV filter;they also show antioxidant or/and anti-inflammatory activity.This could explain why,although there are no officially approval natural commercial sun-filters,more and more commercial sunscreen products containing plant extracts are avail-able on the market.Here we summarize articles focusing on natural UV filters from plant published in the last 6 years,selecting the most significant data in order to better understand the photoprotective activity of natural products and extracts from plants,including their major constituents and main biological effects,methods for evaluating UV radiation resistance,anti-UV radiation experimental models and anti-UV radiation mechanisms.

A Comparative Study on Chemical Composition of Supercritical CO_2 Extraction Products in Peels of Trichosanthes kirilowii Maxim. from Changqing District

[Objective] This study aimed to investigate the differences in chemical composition of supercritical CO2 extraction products in peels of Trichosanthes kirilowii Maxim. from Changqing district. [Method] Supercritical fluidextraction （SFE） and GCMS method were applied to determine and analyze the chemical components of the extracts in peels of three strains of Trichosanthes kirilowii Maxim. [Result] The chemical components of supercritical CO2 extraction products in peels of three strains of Trichosanthes kirilowii Maxim. varied., and the number of chemical components with normalized percentage content higher than 1% was 5, 7 and 8, respectively. There are 14 kinds of common components, and the relative content of hexadecanoic acid was the highest. [Conclusion] Supercritical CO2 extracts in peels of different strains of Trichosanthes kirilowii Maxim. contain different chemical components, providing scientific basis for breeding excellent varieties and the development and utilization of Trichosanthes kirilowii Maxim.

Mechanism and Clinical Observation of Effect of Growgx Yeast Fermentation Product Extract on Photo-aged HFF-1 Cells

[Objectives]To explore the effect of the extract of Growgx yeast fermentation product on ultraviolet A(UVA)-induced photo-aging of human skin fibroblasts(HFF-1)and its specific mechanisms from the level of cell biology,and discussed the application of the Growgx yeast fermentation product extract for skin aging.[Methods]A photo-aging model of HFF-1 cells was induced by UVA radiation meter,and it was given different concentrations of Growgx for intervention.The proliferation activity of the HFF-1 cells was detected with MTT method,and their migration and invasion ability was measured by scratch test.The SOD,HYP and MDA levels were detected with corresponding kits.After oxygen infusion apparatus assisted facial skin administration,the repair of the skin was observed through the VISIA skin tester.[Results]The survival rate of HFF-1 cells was reduced significantly by UVA with an irradiation dose of 10.8 J/cm2(P<0.05),while Growgx significantly increased their survival rate(P<0.001)and sped up the repair of damaged cells.Growgx promoted the production of SOD(P<0.05),reduced the level of MDA(P<0.05),and increased the level of HYP(P<0.05).Growgx effectively inhibited UVA-induced photo-aging of HFF-1 cells.The mechanism may be related to accelerating cell damage repair,up-regulating SOD and HYP expression levels,and reducing MDA expression level.The clinical observation showed that Growgx effectively improved skin spots and pores,making the skin smoother and more delicate.[Conclusions]Growgx can effectively fight against photo-aging caused by ultraviolet rays,and can significantly improve skin wrinkles.

Feature extraction of search product based on multi-feature fusion-oriented to Chinese online reviews

The increasing Chinese online reviews contain rich product demand information,especially for search products.This study suggests a product feature extraction model from online reviews based on multi-feature fusion named PFEMF(products features extraction based on multi-feature fusion)model.Combining sentence and word characteristics of Chinese online reviews,the model explores the lexical features,frequency features,span features,and semantic similarity features of words.And then,they are fused to identify the features that customers are concerned about most by sequential relationship analysis.The identified product feature provides direction for product innovation and facilitates the product selection for customers.Finally,the study takes iPad Air as an example to prove this model.The results show that the extraction performance of the PFEMF model is superior to the traditional term frequency-inverse document frequency(tf-idf)algorithm,word span algorithm,and semantic similarity algorithm.

Mining Intention-Related Products on Online Q＆A Community

User generated content on social media has attracted much attention from service/product providers, as it contains plenty of potential commercial opportunities. However, previous work mainly focuses on user consumption intention （CI） identification, and little effort has been spent to mine intention-related products. In this paper, focusing on the Baby ＆Child Care domain, we propose a novel approach to mine intention-related products on online question and answer （Q＆A） community. Making use of the question-answering pairs as data source, we first automatically extract candidate products based on dependency parser. And then by means of the collocation extraction model, we identify the real intention-related products from the candidate set. The experimental results on our carefully constructed evaluation dataset show that our approach achieves better performance than two natural baseline methods.