Mi Jang

Extraction Optimization for Obtaining Artemisia capillaris Extract with High Anti-Inflammatory Activity in RAW 264.7 Macrophage Cells

Plant extracts have been used as herbal medicines to treat a wide variety of human diseases. We used response surface methodology (RSM) to optimize the Artemisia capillaris Thunb. extraction parameters (extraction temperature, extraction time, and ethanol concentration) for obtaining an extract with high anti-inflammatory activity at the cellular level. The optimum ranges for the extraction parameters were predicted by superimposing 4-dimensional response surface plots of the lipopolysaccharide- (LPS-) induced PGE2 and NO production and by cytotoxicity of A. capillaris Thunb. extracts. The ranges of extraction conditions used for determining the optimal conditions were extraction temperatures of 57–65°C, ethanol concentrations of 45–57%, and extraction times of 5.5–6.8 h. On the basis of the results, a model with a central composite design was considered to be accurate and reliable for predicting the anti-inflammation activity of extracts at the cellular level. These approaches can provide a logical starting point for developing novel anti-inflammatory substances from natural products and will be helpful for the full utilization of A. capillaris Thunb. The crude extract obtained can be used in some A. capillaris Thunb.-related health care products.

Predictive modeling of Staphylococcus aureus growth on Gwamegi (semidry Pacific saury) as a function of temperature

Gwamegi (semidry Pacific saury [Cololabis saira]) is a Korean food made by a traditional method of repeated freezing and de-freezing during winter. The present study aimed at developing predictive modeling of S. aureus growth on Gwamegi as a function of temperature (10–35°C). Modified Gompertz, Baranyi, and logistic primary models were fitted to experimental values. Polynomial quadratic, nonlinear Arrhenius and square root models were selected as secondary models and analyzed using specific growth rate (μmax) and lag time (λ) values obtained from the primary models. Based on the optimized models derived from the Baranyi and square root equations for μmax, its r2 and mean square error (MSE) were 0.991 and 0.00058, and bias factor (Bf) and accuracy factor (Af) were 1.0087 and 1.0801, respectively. The logistic and polynomial quadratic equations for λ, its r2 and MSE were 0.989 and 0.22834, Bf and Af were 0.9742 and 1.0271, respectively. These predictive models can provide basic information for quantitative microbial risk assessment of Gwamegi and other processed semidried seafood.

Anti-inflammatory effects of 4 medicinal plant extracts in lipopolysaccharide-induced RAW 264.7 cells

The anti-inflammatory activity of 4 plant extracts [guava (Psidium guajava) leaf, capillary wormwood (Artemisia capillaris Thunb.), Chinese goldthread (Coptis chinensis), and dandelion (Taraxacum platycarpum)] was investigated in lipopolysaccharide (LPS)-stimulated RAW 264.7 cells. Six phenolic compounds (gallic acid, caffeic acid, chlorogenic acid, catechin, quercetin, and baicalin) were analyzed using LC-MS/MS. Guava leaf extracts showed the highest inhibitory effects on LPS-induced nitric oxide (NO, 52.58%) and prostaglandin E2 (PGE2, 43.45%) production. The total phenolic contents (TPC) in guava leaf, capillary wormwood, Chinese goldthread, and dandelion were 426.84, 154.42, 41.73, and 122.04 mg of gallic acid equivalent (GAE)/g of extract, respectively. TPC was positively correlated with the NO-inhibitory effect (r= 0.963, p<0.05) and the PGE2-inhibitory effect (r=0.971, p<0.05) at 30 μg/mL of treatment. The guava leaf extracts contained the highest levels of gallic acid and catechin, while the capillary wormwood extracts contained the highest levels of chlorogenic acid and quercetin.