Effect of Xin Mai Jia on atherosclerosis in rats

A cynomolgus monkey model of carotid atherosclerosis induced by puncturing and scratching of the carotid artery combined with a high-fat diet

Cardio-cerebrovascular disease is one of the three major causes of mortality in humans and constitutes a major socioeconomic burden. Carotid atherosclerosis (CAS) is a very common lesion of the arterial walls, which leads to narrowing of the arteries, in some cases occluding them entirely, increasing the risk of cardiovascular events. The aim of the present study was to evaluate a cynomolgus monkey model of carotid atherosclerosis (CAS) induced by puncturing and scratching combined with a high-fat diet. A total of 12 cynomolgus monkeys were randomly divided into four groups: A, puncturing and scratching carotid artery intimas + high-fat diet (n=3); B, puncturing and scratching carotid artery intimas + regular diet (n=3); C, high-fat diet only (n=3); and D, regular diet only (n=3). Blood was harvested at weeks 4, 6 and 8 and plasma lipid levels were assessed. At week 8, monkeys were sacrificed and carotid arteries were harvested for hematoxylin and eosin (H&E) staining to observe pathological changes. The results revealed that a high-fat diet led to increased plasma lipid levels and accelerated plaque formation. Carotid color Doppler ultrasonography was performed and, along with H&E staining, revealed plaque formation in group A. In summary, the results of the present study suggest that a cynomolgus monkey model of CAS model may be successfully constructed by puncturing and scratching of the carotid artery intimas in combination with a high-fat diet.

Rapid Determination of Puerarin by Near-infrared Spectroscopy During Percolation and Concentration Process of Puerariae Lobatae Radix

BACKGROUND

Gegen (Puerariae Labatae Radix) is one of the important medicines in Traditional Chinese Medicine. The studies showed that Gegen and its preparation had effective actions for atherosclerosis.

OBJECTIVE

Near-infrared (NIR) was used to develop a method for rapid determination of puerarin during percolation and concentration process of Gegen.

MATERIALS AND METHODS

About ten batches of samples were collected with high-performance liquid chromatography analysis values as reference, calibration models are generated by partial least-squares (PLS) regression as linear regression, and artificial neural networks (ANN) as nonlinear regression.

RESULTS

The root mean square error of prediction for the PLS and ANN model was 0.0396 and 0.0365 and correlation coefficients (r (2)) was 97.79% and 98.47%, respectively.

CONCLUSIONS

The NIR model for the rapid analysis of puerarin can be used for on-line quality control in the percolation and concentration process.

SUMMARY

Near-infrared was used to develop a method for on-line quality control in the percolation and concentration process of GegenCalibration models are generated by partial least-squares (PLS) regression as linear regression and artificial neural networks (ANN) as non-linear regressionThe root mean square error of prediction for the PLS and ANN model was 0.0396 and 0.0365 and correlation coefficients (r (2)) was 97.79% and 98.47%, respectively. Abbreviations used: NIR: Near-Infrared Spectroscopy; Gegen: Puerariae Loabatae Radix; TCM: Traditional Chinese Medicine; PLS: Partial least-squares; ANN: Artificial neural networks; RMSEP: Root mean square error of validation; R2: Correlation coefficients; PAT: Process analytical technology; FDA: The Food and Drug Administration; Rcal: Calibration set; RMSECV: Root mean square errors of cross-validation; RPD: Residual predictive deviation; SLS: Straight Line Subtraction; MLP: Multi-Layer Perceptron; MSE: Mean square error.