Objective To establish a specific HPLC method and a standard fingerprint for quality control ofZiziphi Spinosae Folium.Methods The samples were separated on a Kinetex C18 column (100 mm × 2.1 mm,2.6 μm) by gradient elution at the flow rate of 300 μL/min using acetonitrile and 0.1％ aqueous formic acid as the mobile phase.The column temperature was 30℃.The detection wavelength was 225 nm and the sample size was 10 μL.The fingerprint evaluation software (2012 edition) for Chinese materia medica (CMM) was used to evaluate the similarity of the 12 batches of samples.Results There were 13 characteristic peaks identified in the characteristic spectra ofZiziphi Spinosae Folium samples.Peak 6 was Rutin.The similarities of 13 batches ofZiziphi Spinosae Folium samples were proved to behigher than 0.850.Conclusion The method is available with a good reproducibility and accuraty which can control the quality standards effectively.

Objective To establish and compare HPLC fingerprint chromatograms of Dipsaci Radix decoction pieces, aqueous decoction and formula granules.Methods The HPLC analysis was carried out in Wondasil C18 column (4.6 mm × 250 mm, 5 μm) with a mobile phase of acetonitrile-0.1% phosphoric acid by gradient elution. The flow rate was 1.0 mL/min; the detection wavelength was set at 212 nm; the column temperature was kept at 30℃. Results The fingerprint chromatograms from 12 batches of Dipsaci Radix decoction pieces, aqueous decoction and formula granules were established respectively. 14 common peaks in the fingerprint chromatogram in the formula granules could be tracked in the aqueous decoction, and 13 common peaks in the fingerprint chromatogram could be tracked in the decoction pieces. 2 chemical compounds were identified, such as asperosaponinⅥ and chlorogenic acid.ConclusionThe method of HPLC fingerprint chromatograms is stable and with good repeatability. Dipsaci Radix decoction pieces, aqueous decoction and formula granules are basically the same chemical composition.

Objective:To investigate the correlation between neutrophil/lymphocyte ratio (NLR) combined with low-density lipoprotein cholesterol/high-density lipoprotein cholesterol ratio (LDL-C/HDL-C) and severity of coronary lesions in patients with acute coronary syndrome (ACS).Methods:Patients who were diagnosed with ACS due to chest pain and received emergency coronary angiography in the First Affiliated Hospital of University of Science and Technology of China and the Affiliated Hospital of Anhui Medical University from January 2017 to June 2020 were enrolled in the final analysis. The data of gender, age, body mass index (BMI), past history, emergency blood routine indicators [neutrophil (NEU), lymphocyte (LYM), monocyte (MON), eosinophil (EOS), basophil (BAS), red blood cell (RBC), mean corpuscular volume (MCV), blood red cell distribution width (RDW), mean platelet volume (MPV), platelet volume distribution width (PDW)], blood lipid index [triglyceride (TG), total cholesterol (TC), HDL-C, LDL-C, very low-density lipoprotein cholesterol (VLDL-C)], and coronary angiography were collected. The results of coronary angiography were evaluated by the Gensini score. According to the Gensini score, the patients were divided into the control group (Gensini score = 0, 55 cases) and the study group (Gensini score > 0, 889 cases), and then the patients in the study group were divided into the low-Gensini-score group (Gensini score < 66, 419 cases) and the high-Gensini-score group (Gensini score ≥ 66, 470 cases). The differences in the general baseline data of the four groups were compared, and the correlation between the statistically significant data and the Gensini score was linearly analyzed, and then the combined diagnostic factors (NLR combined with LDL-C/HDL-C ratio) were obtained by Logistic regression analysis. The receiver operator characteristic curve (ROC curve) was used to evaluate the predictive value of NLR combined with LDL-C/HDL-C ratio in predicting the severity of coronary artery lesions in patients with ACS. Finally, multivariate linear regression analysis was used to establish the predictive model between NLR combined with LDL-C/HDL-C ratio and Gensini score.Results:A total of 944 patients were finally included. The differences in gender, age, BMI, hypertension, diabetes, smoking history, NEU, LYM, MON, EOS, RDW, TC, HDL-C, LDL-C, NLR, LDL-C/HDL-C ratio between the control group and the study group were statistically significant. The differences in BMI, hypertension, diabetes, smoking history, NEU, LYM, MON, EOS, TG, TC, HDL-C, LDL-C, NLR and LDL-C/HDL-C ratio between the low-Gensini-score group and the high-Gensini-score group were statistically significant. Linear regression analysis showed that compared with other indicators, the correlation between NLR, LDL-C/HDL-C ratio and Gensini score was stronger in the study group ( r values were 0.634 and 0.663, respectively, both P < 0.05). Binary Logistic regression analysis of the indicators related to Gensini score showed that NEU, LYM, HDL-C and LDL-C were independent risk factors for coronary stenosis in patients with ACS [odds ratio ( OR) were 0.189, 10.309, 13.993, 0.251, 95% confidence intervals (95% CI) were 0.114-0.313, 4.679-22.714, 3.402-57.559, 0.121-0.519, respectively, all P < 0.05]. ROC curve analysis showed that NLR combined with LDL-C/HDL-C ratio had higher predictive value in predicting the severity of coronary lesions in ACS patients [area under the ROC curve (AUC) was 0.952, 95% CI was 0.93-0.969], when the cutoff value was -3.152, the sensitivity was 98.20%, and the specificity was 81.60%. According to the results of multivariate linear regression analysis, the prediction model between NLR, LDL-C/HDL-C ratio and Gensini score was established, and the formula was Gensini score = -7.772+15.675×LDL-C/HDL-C ratio+8.288×NLR ( R2 = 0.862). Conclusion:There is a significant correlation between emergency NLR combined with LDL-C/HDL-C ratio and Gensini score in patients with ACS at admission, which has a certain predictive value for the severity of coronary artery stenosis in patients with ACS, and can be used as a predictor for evaluating the severity of coronary artery disease.

Objective: To explore the genetic cause for abnormal pregnancies through detecting chromosomal copy number variations (CNVs) in abortic tissues by next generation sequencing (NGS). Methods: NGS technique was used to detect CNVs in abortion tissues. Parental chromosomal karyotypes were predicted based on the results. The aberrant chromosomal segments of the parents were accurately mapped by G-banding karyotyping analysis and fluorescence in situ hybridization (FISH). Results: In addition to numerical chromosomal aberrations, 12 microdeletion/microduplications were detected by NGS. For 8 families where both parents accepted chromosomal karyotyping, 4 carriers of chromosomal abnormalities were identified. One marker chromosome was missed by karyotyping analysis, and a mother was confirmed to carry a cryptic balanced translocation by FISH. Conclusion NGS can facilitate detection of cryptic chromosomal translocations in couples with repeated pregnancy failure and is of great value for detecting abnormal CNVs for its high sensitivity.