Objective To develop a RP-HPLC method for the determination of piperine in the root of Piper nigrum L.Methods RP-HPLC was carried out on Luna C18 column(250 mm? 4.60 mm,5 ? m) with the column temperature of 35 ℃.The mobile phase consisted of a mixture of methanol-water(77 :23) at a flow rate of 1.0 mL? min-1.The determination wavelength was at 343 nm.Results The calibration curve was linear within the concentration range of 0.164 ? g～ 0.984 ? g,r=0.9996,and the average recovery was 98.09 %,RSD=2.67 %(n=9).The average content of piperine in three batches of pepper roots was in the range of 6.67～6.77mg?g-1.Conclusion Pepper root contains piperine,and this method is suitable for the quality control of the root of Piper nigrum L.

Objective To investigate the predictive value of preoperative fibrinogen/albumin ratio (FAR) and systemic immune inflammation index (SII) on the postoperative prognosis of patients with pancreatic ductal adenocarcinoma. Methods An ROC curve was used in determining the best cutoff values of FAR and SII and then grouped. The Cox proportional hazards model was used in analyzing the prognostic factors of radical pancreatic cancer surgery, and then a Nomogram prognostic model was established. C-index, AUC, and calibration curve were used in evaluating the discrimination and calibration ability of the Nomogram. DCA curves were used in assessing the clinical validity of the Nomograms. Results The optimal cutoff values for preoperative FAR and SII were 0.095 and 532.945, respectively. FAR≥ 0.095, SII≥ 532.945, CA199≥ 450.9 U/ml, maximum tumor diameter≥ 4 cm, and the absence of postoperative chemotherapy were independent risk factors for the poor prognosis of pancreatic cancer (P<0.05). The discrimination ability, calibration ability, and clinical effectiveness of Nomogram prognostic model were better than those of the TNM staging system. Conclusion The constructed Nomogram prognostic model has higher accuracy and level of discrimination and more clinical benefits than the TNM staging prognostic model.

Objective:To investigate the predictive value of preoperative lymphocyte-to-monocyte ratio (LMR) combined with platelet-to-lymphocyte ratio (PLR) (LMR-PLR) scoring model for prognosis of pancreatic ductal adenocarcinoma (PDAC) after radical resection.Methods:The retrospective cohort study was conducted. The clinicopathological data of 116 patients with PDAC who were admitted to the Second Hospital of Lanzhou University from January 2015 to December 2019 were collected. There were 73 males and 43 females, aged 61.5(range, 29.0-75.0)years. All patients underwent radical resection for PDAC. Observation indicators: (1) optimal cut-off value of LMR and PLR; (2) clinicopathological features of patients with different scores of preoperative LMR-PLR scoring model; (3) follow-up and survival; (4) influencing factors for prognosis of PDAC patients; (5) construction and verification of nomogram prediction model. Measurement data with skewed distribution were represented as M(range). Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test. Comparison of ordinal data was conducted using the Mann-Whitney U test. The Graphpad prism 8 was used to draw survival curve, the Kaplan-Meier method was used to calculate survival rate, and the Log-Rank test was used for survival analysis. The COX proportional hazard regression model was used for univariate and multivariate analyses. The X-tile software was used to determine the optimal cut-off values of LMR and PLR. The nomogram prediction model was conducted based on the results of multivariate analysis, and the receiver operating characteristic (ROC) curve was drawn. The area under curve (AUC) was used to evaluate the discrimination of nomogram prediction model. The calibration curve was used to evaluate the consistency of nomogram prediction model and the decision curve was used to evaluate the clinical benefits. Results:(1) Optimal cut-off value of LMR and PLR. The optimal cut-off values of LMR and PLR were 1.9 and 156.3. (2) Clinicopathological features of patients with different scores of preoperative LMR-PLR scoring model. Cases with LMR-PLR scoring as 0, 1, 2 were 11, 42, 63. Cases with CA125 <12.4 U/mL, cases postoperative with vascular invasion, cases with postoperative chemotherapy in patients with 0, 1, 2 of LMR-PLR scoring were 1, 8, 24, 9, 27, 27, 3, 26, 43, showing significant differences among them ( χ2=6.73, 8.37, 6.68, P<0.05). (3) Follow-up and survival. All 116 patients were followed up for 39(range, 2-86)months. The 1-, 2-, 3-year survival rate of 116 PDAC patients was 50.9%, 37.9%, 19.3%, respectively, with a survival time of 13(range, 1-85)months. The survival time of patients with LMR-PLR scoring as 0, 1, 2 was 3(range, 1-9)months, 7(range, 2-56)months, 26(range, 2-85)months, respectively, showing a significant difference among them ( χ2=48.78, P<0.05). (4) Influencing factors for prognosis of PDAC patients. Results of multivariate analysis showed that carcinoembryonic antigen (CEA), CA19-9, LMR-PLR score, tumor diameter were independent factors affecting prognosis of patients ( hazard ratio=1.61, 1.88, 0.27, 1.87, 95% confidence interval as 1.02-2.54, 1.18-3.00, 0.19-0.39, 1.13-3.09, P<0.05). (5) Construction and verification of nomogram prediction model. The nomogram prediction model was constructed based on CEA, CA19-9, LMR-PLR score and tumor diameter. The AUC of ROC curve in predicting 1-, 2-, 3-year survival rate of patients was 0.86 (95% confidence interval as 0.79-0.93, P<0.05), 0.86 (95% confidence interval as 0.79-0.92, P<0.05), 0.87 (95% confidence interval as 0.78-0.95, P<0.05), respectively. Results of calibration curve showed that the predicted survival rate of nomogram prediction model was consistent with the actual survival rate, with the consistency index as 0.74. Results of decision curve showed that the predictive performance of nomogram prediction model was superior to that of a single factor at a risk threshold of 0.12-0.85. Conclusions:CEA, CA19-9, LMR-PLR score, tumor diameter are independent factors affecting prognosis of patients undergoing radical resection for PDAC, and the nomogram prediction model can predict postoperative survival rate. The predicted survival rate of nomogram prediction model is consistent with the actual survival rate, and the predictive performance of nomogram prediction model is superior to that of a single factor at a risk threshold of 0.12-0.85.