Effects of selenium-cadmium co-enriched Cardamine hupingshanensis on bone damage in mice.

Selenium (Se) and cadmium (Cd) usually co-existed in soils, especially in areas with Se-rich soils in China. The potential health consequences for the local populations consuming foods rich in Se and Cd are unknown. Cardamine hupingshanensis (HUP) is Se and Cd hyperaccumulator plant that could be an ideal natural product to assess the protective effects of endogenous Se against endogenous Cd-caused bone damage. Male C57BL/6 mice were fed 5.22 mg/kg cadmium chloride (CdCl2) (Cd 3.2 mg/kg body weight (BW)), or HUP solutions containing Cd 3.2 mg/kg BW and Se 0.15, 0.29 or 0.50 mg/kg BW (corresponding to the HUP0, HUP1 and HUP2 groups) interventions. Se-enriched HUP1 and HUP2 significantly decreased Cd-induced femur microstructure damage and regulated serum bone osteoclastic marker levels and osteogenesis-related genes. In addition, endogenous Se significantly decreased kidney fibroblast growth factor 23 (FGF23) protein expression and serum parathyroid hormone (PTH) levels, and raised serum calcitriol (1,25(OH)2D3). Furthermore, Se also regulated gut microbiota involved in skeletal metabolism disorder. In conclusion, endogenous Se, especially with higher doses (the HUP2 group), positively affects bone formation and resorption by mitigating the damaging effects of endogenous Cd via the modulation of renal FGF23 expression, circulating 1,25(OH)2D3 and PTH and gut microbiota composition.

Effect of pretreatments of camellia seeds on the quality, phenolic profile, and antioxidant capacity of camellia oil.

Camellia oil is one of the four major woody oils in the world and has high nutritional value due to its richness in monounsaturated fatty acids (MUFAs) and bioactive substances. In order to compare the effects of pretreatments of camellia seeds on the quality, phenolic profile, and antioxidant capacity of camellia oil, three different pretreatment methods, i.e., hot air (HA), steam (ST) and puffing (PU), were used to treat the seed powder in the present study. All three pretreatments changed the internal structure of the camellia seeds. The oil yield was increased after all three pretreatments, with the highest oil yield increased by PU pretreatment (Based on the oil yield, we screened out the best conditions of the three pretreatments, HA pretreatment is 60°C for 40 min, ST pretreatment is 100°C for 15 min, PU pretreatment is 800 rpm). The fatty acids (FAs) of the oil were relatively stable, with no significant changes after three pretreatments. However, all three pretreatments had a significant effect on the acid value (AV), peroxide value (PV), and benzo(a)pyrene (Ba P) of the camellia oil. The PU and HA pretreatments could increase the tocopherol content and the total sterols content in the camellia oil. The ST and PU pretreatments significantly increased the free phenolics (FP) content, all three pretreatments reduced the contents of conjugated phenolics (CP) and insoluble-bound phenolics (IBP) in the camellia oil. The IBP made the most significant contribution to the antioxidant capacities of camellia oil. ST and PU prtreatments increased the antioxidant capacities of the total phenolics in the camellia oil. Eight phenolics in FP, CP, and IBP were significantly correlated with the antioxidant capacities of camellia oil. The results of the present study could provide some theoretical guidance for the pretreatment of camellia seeds for higher oil yield, phenolic content and enhanced antioxidant capacities of camellia oil.

Sensing the quality parameters of Chinese traditional Yao-meat by using a colorimetric sensor combined with genetic algorithm partial least squares regression.

Yao-meat is a traditional Chinese salted meat. Total volatile basic nitrogen content (TVB-N), total viable bacterial count (TVC), and residual nitrite (RN) level are important indexes of freshness for Yao-meat. This paper attempted the feasibility to determine TVB-N content, TVC and RN level in Yao-meat by a colorimetric sensor array chip. A color change profile for each sample was obtained by differentiating the image of sensor array before and after exposure to Yao-meat's volatile organic compounds. Genetic algorithm partial least squares regression (GA-PLS) was proposed to build the relationship between the TVB-N content, TVC, RN and the color change profiles of sensor array, and to select informative chemically responsive dyes for the three quality parameters. The GA-PLS models were achieved with RTVB-N=0.812, RTVC=0.856, RRN=0.855, in prediction set. This study demonstrated that colorimetric sensory array with GA-PLS algorithm could be used successfully to analyze the quality of Chinese traditional Yao-meat.