Objective:To establish a rapid quantitative model of sodium chloride content in Halitum of traditional Chinese medicine by using X-ray diffraction technology and machine learning algorithm.Methods:The data of X-ray diffraction patterns of 90 batches of Halitum samples were collected,and the rapid prediction models of X-ray diffraction were constructed by using partial least squares(PLS),support vector regression(SVR)long short-term memory(LSTM)according to the reference values determined by the content determination method of Halitum in the Chinese Pharmacopoeia 2020 edition.Results:The data preprocessed by multivariate scatter correction(MSC)and selected by competitive adaptive reweighted sampling(CARS)were better in PLS model and LSTM model.The data pretreated by standard normal transformation(SNV)and selected by CARS feature variable perform well in SVR.Conclusion:The three models show good prediction potential,which shows that the combination of X-ray diffraction technology and machine learning algorithm is feasible for accurate prediction of the content of Halitum in traditional Chinese medicine.

Objective:To establish a rapid quantitative model for the determination of moisture,extractives,and content in Pollen Typhae.Methods:Near-infrared spectra of 91 batches of Pollen Typhae samples were collected.Spectral preprocessing was performed using S-G,MSC,SNV,and CWT methods.Variable selection was conducted using CARS,SPA,and VIP methods,and compared with full-spectrum modeling.Partial least squares(PLS)mod-els were established for the quantitative determination of moisture,total ash,extractives,and content.The model performance was evaluated by calculating the coefficient of determination for the calibration set and validation set(R2 c,R2v),root mean square error of calibration and validation(RMSEc,RMSEv),and residual prediction devia-tion(RPD).Results:The PLS models for moisture,extractives,and content in Pollen Typhae showed R2c and R2v values greater than 0.9,RMSEc and RMSEv values approaching 0,and RPD values greater than 3.Conclusion:In this study,near-infrared spectroscopy was used to construct quantitative prediction models for moisture,extractives,typhaneoside,and isorhamnetin-3-O-neohesperidoside content in Pollen Typhae.This method enables rapid detection of the main quality control indicators of Pollen Typhae,providing strong technical support for its quality supervision.

Objective:To establish a rapid quantitative model of sodium chloride content in Halitum of traditional Chinese medicine by using X-ray diffraction technology and machine learning algorithm.Methods:The data of X-ray diffraction patterns of 90 batches of Halitum samples were collected,and the rapid prediction models of X-ray diffraction were constructed by using partial least squares(PLS),support vector regression(SVR)long short-term memory(LSTM)according to the reference values determined by the content determination method of Halitum in the Chinese Pharmacopoeia 2020 edition.Results:The data preprocessed by multivariate scatter correction(MSC)and selected by competitive adaptive reweighted sampling(CARS)were better in PLS model and LSTM model.The data pretreated by standard normal transformation(SNV)and selected by CARS feature variable perform well in SVR.Conclusion:The three models show good prediction potential,which shows that the combination of X-ray diffraction technology and machine learning algorithm is feasible for accurate prediction of the content of Halitum in traditional Chinese medicine.

Objective:To establish a rapid quantitative model for the determination of moisture,extractives,and content in Pollen Typhae.Methods:Near-infrared spectra of 91 batches of Pollen Typhae samples were collected.Spectral preprocessing was performed using S-G,MSC,SNV,and CWT methods.Variable selection was conducted using CARS,SPA,and VIP methods,and compared with full-spectrum modeling.Partial least squares(PLS)mod-els were established for the quantitative determination of moisture,total ash,extractives,and content.The model performance was evaluated by calculating the coefficient of determination for the calibration set and validation set(R2 c,R2v),root mean square error of calibration and validation(RMSEc,RMSEv),and residual prediction devia-tion(RPD).Results:The PLS models for moisture,extractives,and content in Pollen Typhae showed R2c and R2v values greater than 0.9,RMSEc and RMSEv values approaching 0,and RPD values greater than 3.Conclusion:In this study,near-infrared spectroscopy was used to construct quantitative prediction models for moisture,extractives,typhaneoside,and isorhamnetin-3-O-neohesperidoside content in Pollen Typhae.This method enables rapid detection of the main quality control indicators of Pollen Typhae,providing strong technical support for its quality supervision.

ObjectiveTo investigate the effects of thyme herbal tea （BLX） on the proliferation of human coronavirus OC43 （HCoV-OC43） in vitro and in vivo. MethodThe chemical composition of BLX was analyzed by UPLC-MS. The cytotoxicity of BLX in HRT-18 cells and the effect of BLX treatment on the proliferation of HCoV-OC43 in cells were analyzed. Copies of viral gene were detected by real-time PCR. The effect of BLX treatment on the life cycle of HCoV-OC43 was detected by time-of-addition assay. The maximum tolerated dose of BLX and the influences of BLX on the body weight and survival time of suckling mice infected with HCoV-OC43 were determined. The expression of viral protein in the brain and lung tissue was analyzed by immunohistochemistry. ResultThere were 11 chemical components identified in BLX by UPLC-MS. BLX showed the 50% cytotoxic concentration （CC₅₀） of （13 859.56±319） mg·L^-1， the median inhibitory concentration （IC₅₀） of （1 439.09±200） mg·L^-1， and the selection index of 8.26-11.44 for HCoV-OC43 in HRT-18 cells. Compared with the cells infected with HCoV-OC43， BLX at the concentrations of 1 500， 1 000， 500 mg·L^-1 inhibited the proliferation of this virus （P<0.05， P<0.01）. BLX exhibited antiviral effect in the early stage of virus infection， and the inhibition role in the attachment stage was more significant than that in the entry stage （P<0.05）. In the suckling mice infected with HCoV-OC43， BLX at 1200 and 600 mg·kg^-1·d^-1 alleviated the symptoms， prolonged the survival period， reduced the death rate， and down-regulated the mRNA level of nucleocapsid protein in the mice. Moreover， BLX at 1 200 mg·kg^-1·d^-1 down-regulated the expression of nucleocapsid protein in the brain （P<0.01） and the lung （P<0.01）. ConclusionBLX contained multiple antiviral ingredients. It inhibited the proliferation of HCoV-OC43 both in vitro and in vivo by interference with viral attachment. This study provides theoretical reference for the treatment of acute respiratory tract infection with HCoV-OC43 and for further development and application of BLX.

Objective:To compare and analyze the predictive value of different inflammatory factors and tumor markers in intrahepatic cholangiocarcinoma and to develop a new and effective preoperative prognostic scoring system.Methods:102 and 72 cases with intrahepatic cholangiocarcinoma who underwent radical surgery in Tianjin Medical University Cancer Institute and Hospital and the Affiliated Hospital of Weifang Medical University were selected as the experimental group and the validation group, respectively. Clinicopathological and follow-up data were collected. Cox proportional-hazards model was used to analyze the predictive value of different prognostic markers. The relationship between prognostic markers and clinicopathological data was analyzed by rank sum test, χ2 or Fisher's exact test. Results:Among the direct inflammatory factors, tumor markers and combined inflammatory factors, prognostic inflammatory index (PII), carbohydrate antigen (CA) 19-9 and systemic inflammation score (SIS) were the most significant predictive factors for postoperative survival outcomes in patients with intrahepatic cholangiocarcinoma. The prognostic inflammatory and tumor score (PITS) was proposed as a new prognostic scoring system for intrahepatic cholangiocarcinoma. PII and CA19-9 were included into the scoring criteria for prognostic stratification of patients. PITS was an independent predictor of tumor-free survival and overall survival in patients with intrahepatic cholangiocarcinoma. Patients with high-grade PITS had later tumor grade and higher frequency of vascular invasion.Conclusion:PITS is highly effective prognostic scoring system for patients with intrahepatic cholangiocarcinoma. In addition, PITS is recommended for preoperative prognostic stratification in patients with intrahepatic cholangiocarcinoma.

Objective To investigate the value of different immune and inflammatory indices in predicting the survival outcome of patients with intrahepatic cholangiocarcinoma (ICC) after curative-intent resection. Methods A retrospective analysis was performed for the case data of 122 patients with ICC who underwent curative-intent resection in Affiliated Hospital of Weifang Medical University and Tianjin Medical University Cancer Institute and Hospital from January 2012 to December 2017 to analyze the correlation of neutrophil-lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR), systemic immune-inflammation index (SII), prognostic inflammation index (PII), inflammation score (IS), and systemic inflammation score (SIS) with the disease-free survival (DFS) and overall survival of ICC patients after surgery, and the value of the above indices in predicting prognosis was evaluated. The chi-square test or the Fisher's exact test was used for comparison of categorical data between groups. The Kaplan-Meier method was used to plot survival curves, and the Log-rank test was used for comparison between groups; the Cox regression model was used for univariate and multivariate analyses, and hazard ratio ( HR ) and 95% confidence interval [ CI ] were calculated. Results The univariate survival analysis showed that NLR ( HR =2.212, P =0.004), LMR ( HR =0.403, P =0.012), PII ( HR =3.013, P < 0.001), prognostic nutritional index (PNI) ( HR =0.530, P =0.019), IS ( HR =1.809, P =0.001), SII ( HR =2.107, P =0.002), and SIS ( HR =2.225, P < 0.001) were predictive factors for postoperative DFS of patients with ICC, and NLR ( HR =2.416, P =0.009), LMR ( HR =0.297, P =0.008), PII ( HR =3.288, P < 0.001), PNI ( HR =0.292, P =0.003), IS ( HR =2.048, P =0.002), SII ( HR =1.839, P =0.049), and SIS ( HR =2.335, P < 0.001) were predictive factors for postoperative OS of patients with ICC. The multivariate survival analysis showed that high levels of PII ( HR =2.146, P =0.035) and SIS ( HR =2.511, P < 0.001) were independent influencing factors for postoperative DFS of ICC patients, and high levels of PII ( HR =2.981, P =0.009), PNI ( HR =0.261, P =0.002), and SIS ( HR =2.294, P =0.010) were independent influencing factors for postoperative OS. The patients with a high level of PII tended to have advanced tumor T stage ( χ 2 =8.777, P =0.003) and M stage ( P =0.029), and the patients with high-grade SIS tended to have advanced N stage ( χ 2 =9.985, P =0.030) and M stage ( χ 2 =8.574, P =0.012). Conclusion Among the various inflammation indices, PII and SIS are recommended for preoperative stratification and prediction of the outcome of ICC patients after curative-intent resection.

Objective:To investigate outpatient's medicine knowledge and satisfaction degree and analyze their correlation.Method:150 outpatients,their doctors and pharmacists were investigated with a fieldwork method.Patients' medical knowledge and satisfaction degree were measured with a quantitative scale table,and their correlation was calculat- ed with a linear regression method.Result:Almost all the doctors and pharmacists could provide their patients with their guidance about medicines,which focused on drug dosage and taking ways.Fewer than 20% patients could take medical ad- vice of potential risks and notice of taking medicine.A significant correlation was shown between patient's medical knowl- edge and satisfaction degree(r=0.76).Conclusion:More guidance from doctors and pharmacists should be provided for outpatients.The medical knowledge learned by patients could influence patient's satisfaction degree significantly.

OBJECTIVE: To discuss the way to evaluate outpatient prescription in medical institutions according to Prescription Administrative Policy so as to provide reference for the practice of prescription evaluation system. METHODS: 500 outpatient prescriptions from April 16 to April 20 in 2007 in our hospital were sampled randomly for an evaluation in respect of drug utilization, prescription behavior, pharmaceutical care level etc. RESULTS & CONCLUSIONS: To evalnation from The prescriptions involved use of injections and of antibacterials, prescribed drugs were covered in "national essential drugs" , prescriptions with general name, the knowledge of patients on the administration and dosage were drectively.It is supply reference for the prescription evaluation system.