Oleanolic acid alleviates obesity-induced skeletal muscle atrophy via the PI3K/Akt signaling pathway.

Oleanolic acid (OA) is a pentacyclic triterpene with reported protective effects against various diseases, including diabetes, hepatitis, and different cancers. However, the effects of OA on obesity-induced muscle atrophy remain largely unknown. This study investigated the effects of OA on skeletal muscle production and proliferation of C2C12 cells. We report that OA significantly increased skeletal muscle mass and improved glucose intolerance and insulin resistance. OA inhibited dexamethasone (Dex)-induced muscle atrophy in C2C12 myoblasts by regulating the PI3K/Akt signaling pathway. In addition, it also inhibited expression of MuRF1 and Atrogin1 genes in skeletal muscle of obese mice suffering from muscle atrophy, and increased the activation of PI3K and Akt, thereby promoting protein synthesis, and eventually alleviating muscle atrophy. Taken together, these findings suggest OA may have potential for the prevention and treatment of muscle atrophy.

[Fast determination of melamine content in milk base on Vis/NIR spectroscopy method].

In order to investigate the feasibility of near infrared reflectance spectroscopy (NIRS) method for detecting if milk was adulterated with melamine or not, the present work has done the following research. Through adulterating different content of melamine into pure milk, altogether 160 samples were prepared. Using the Handheld Field Spec spectrometer spectral data of the samples were obtained, followed by different pretreatment methods to carry on processing the spectrum data, then establishing the mathematical model separately through comparison with different calibration models using different pretreatment methods, thus we got smoothing of moving average as the pretreatment method. One hundred twenty samples were taken out ran domly from 160 samples (all) to set model, with the remaining 40 samples as the validation samples. Two discriminant analysis models were developed by using partial least squares (PLS) method and least squares-support vector machine (LS-SVM) metho respectively, and then the other 40 samples were used to test the performance of the models. The coefficients of correlation (r) between the real values and the discriminant analysis models predicted ones were 0.917 4 (PLS) and 0.910 9 (LS-SVM). The root mean standard errors of prediction (RMSEP) were 0.030 4 (PLS) and 0.046 7 (LS-SVM). The results of this study indicated that NIRS method could provide rapid determination for melamine in milk.