AIM To establish an LC-MS/MS method for the simultaneous content determination of paeoniflorin,albiflorin,neochlorogenic acid,chlororogenic acid,catechin,epicatechin,ethyl gallate,danshensu,ferulic acid,caffeic acid,gallic acid,protocatechuic acid,protocatechualdehyde and rosmarinic acid in Yangxue Qingnao Granules (Angelicae sinensis Radix,Chuanxiong Rhizoma,Paeoniae Radix Alba,etc.).METHODS The analysis of methanol extract of this drug was performed on a 20 ℃ thermostatic Waters Symmetry Shield RP C18 column (3.9 mm × 150 mm,5 μm),with the mobile phase comprising of acetonitrile-water (containing 0.1％ formic acid) flowing at 0.4 mL/min in a gradient elution manner.RESULTS Fourteen constituents showed good linear relationships within their own ranges,whose average recoveries were 85.5％-107.0％ with the RSDs of 2.0％-5.0％.CONCLUSION This simple,sensitive,accurate and reproducible method can be used for the quality control of Yangxue Qingnao Granules.

Objective:To evaluate the feasibility of using two-dimensional shear wave elastography (2D-SWE) based liver and spleen elastic hardness (L/S-SWE) in patients with liver cirrhosis, and to determine the exclusion and diagnostic thresholds for early identification of liver cirrhosis.Methods:A total of 574 patients with chronic hepatitis B (hepatitis B for short) were included in this study. The clinical characteristics, L-SWE and S-SWE of the patients were collected, and the differences between cirrhosis group ( n=311) and non cirrhosis group ( n=263) were analyzed. The success rate and stability of liver and spleen elastic surgery were evaluated in two groups. The receiver operating characteristic (ROC) curve was used to analyze the efficacy of L-SWE, S-SWE, aspartate aminotransferase to platelet ratio index (APRI) alone and in combination in diagnosing liver cirrhosis. By analyzing the ROC curve, the double threshold for excluding and diagnosing liver cirrhosis was determined. Results:There was a statistically significant difference in platelet count and APRI between the cirrhosis group and the non cirrhosis group (all P<0.05). In the feasibility assessment of 2D-SWE technology, the success rate and stability of liver and spleen elastic operation were relatively high (success rate: 97.2% vs 81.3%; stability: 0.92 vs 0.84), and the success rate and stability of L-SWE operation were slightly better than S-SWE. The success rate of S-SWE operation in the cirrhosis group was higher than that in the non cirrhosis group ( P<0.05). The correlation analysis results showed that L-SWE, S-SWE, APRI were positively correlated with liver tissue pathological grading ( r=0.677, 0.528, 0.149, all P<0.05). The areas under the ROC curve for identifying liver cirrhosis using L-SWE, S-SWE, and APRI were 0.959, 0.896, and 0.706, respectively. When L-SWE and S-SWE were combined, the area under the ROC curve was 0.987, the sensitivity was 92.6%, and the specificity was 96.0%. The Delong test showed that the combined diagnosis of L-SWE and S-SWE had the same diagnostic efficacy as using L-SWE alone for liver cirrhosis ( P>0.05). Further analysis of the ROC curve showed that the likelihood of liver cirrhosis was low when L-SWE was less than 9.4 kPa, and high when L-SWE was greater than 12.0 kPa. Patients between 9.4 and 12.0 kPa can undergo further S-SWE testing; If the S-SWE was between 17.5 and 29.3 kPa, it was classified as 2D-SWE, which was difficult to determine whether there was liver cirrhosis, and further liver puncture and other examinations were needed. Conclusions:2D-SWE technology has high operational feasibility in the diagnosis of liver cirrhosis, and combined with S-SWE, it helps to improve the diagnostic efficiency of early non-invasive identification of liver cirrhosis, enabling more patients to avoid unnecessary liver puncture examinations.

Along with the develoipment of high-throughput sequencing technologies, both sample size and SNP number are increasing rapidly in genome-wide association studies (GWAS), and the associated computation is more challenging than ever. Here, we present a memory-efficient, visualization-enhanced, and parallel-accelerated R package called"rMVP"to address the need for improved GWAS computation. rMVP can 1) effectively process large GWAS data, 2) rapidly evaluate population structure, 3) efficiently estimate variance components by Efficient Mixed-Model Association eX-pedited (EMMAX), Factored Spectrally Transformed Linear Mixed Models (FaST-LMM), and Haseman-Elston (HE) regression algorithms, 4) implement parallel-accelerated association tests of markers using general linear model (GLM), mixed linear model (MLM), and fixed and random model circulating probability unification (FarmCPU) methods, 5) compute fast with a globally efficient design in the GWAS processes, and 6) generate various visualizations of GWAS-related information. Accelerated by block matrix multiplication strategy and multiple threads, the association test methods embedded in rMVP are significantly faster than PLINK, GEMMA, and FarmCPU_pkg. rMVP is freely available at https://github.com/xiaolei-lab/rMVP.