The general models for intermediates quality analysis in the production process of Yaobitong capsule were established by near infrared spectroscopy (NIRS) combined with chemometrics, realizing the rapid determination of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, ginsenoside Rd and moisture. The spray-dried fine powder and total mixed granule were selected as research objects. The contents of five saponins were determined by high performance liquid chromatography and the moisture content was determined by drying method. The measured contents were used as reference values. Meanwhile, NIR spectra were collected. After removing abnormal samples by Monte Carlo cross validation (MCCV), Monte Carlo uninformative variables elimination (MC-UVE) and competitive adaptive reweighted sampling (CARS) were used to select feature variables respectively. Based on the feature variables, quantitative models were established by partial least squares regression (PLSR), extreme learning machine (ELM) and ant lion optimization least squares support vector machine (ALO-LSSVM). The results showed that CARS-ALO-LSSVM model had the optimum effect. The correlation coefficients of the six index components were greater than 0.93, and the relative standard errors were controlled within 6%. ALO-LSSVM was more suitable for a large number of samples with rich information, and the prediction effect and stability of the model were significantly improved. The general models with good predicting effect can be used for the rapid quality determination of Yaobitong capsule intermediates.

Objective To compare the effects of 20 mg qd and 10 mg bidadministration of iprrazole enteric-coated tablets on the control of gastric acid in healthy subjects.Methods A randomized,single-center,parallel controlled trial was designed to include 8 healthy subjects.Randomly divided into 2 groups,20 mg qd administration group:20 mg enteric-coated tablets of iprrazole in the morning;10 mg bid administration group:10 mg enteric-coated tablets of iprrazole in the morning and 10 mg in the evening.The pH values in the stomach of the subjects before and 24 h after administration were monitored by pH meter.The plasma concentration of iprazole after administration was determined by HPLC-MS/MS.The main pharmacokinetic parameters were calculated by Phoenix WinNonlin(V8.0)software.Results The PK parameters of iprrazole enteric-coated tablets and reference preparations in fasting group were as follows:The Cmax of 20 mg qd group and 10 mg bid group were(595.75±131.15)and(283.50±96.98)ng·mL-1;AUC0-t were(5 531.94±784.35)and(4 686.67±898.23)h·ng·mL-1;AUC0-∞ were(6 003.19±538.59)and(7 361.48±1 816.77)h·ng·mL-1,respectively.The mean time percentage of gastric pH＞3 after 20 mg qd and 10 mg bid were 82.64％and 61.92％,and the median gastric pH within 24 h were 6.25±1.49 and 3.53±2.05,respectively.The mean gastric pH values within 24 h were 5.71±1.36 and 4.23±1.45,respectively.The correlation analysis of pharmacokinetic/pharmacodynamics showed that there was no significant correlation between the peak concentration of drug in plasma and the inhibitory effect of acid.Conclusion Compared with the 20 mg qd group and the 10 mg bid group,the acid inhibition effect is better,the administration times are less,and the safety of the two administration regimes is good.

Objective To evaluate the bioequivalence of oral sidenafil citrate tablets manufactured(100 mg)test preparations and reference preparations in healthy subjects under fasting and fed conditions.Methods Using a single-dose,randomized,open-lable,two-period,two-way crossover design,36 healthy subjects respectively for fasting and fed study were enrolled,and randomized into two groups to receive a single dose of test 100 mg with 7-day washout period.Plasma concentration of sidenafil and N-demethylsildenafil was determined by liquid chromatography-tandem mass spectrometry(LC-MS/MS)method.The pharmacokinetic parameters were calculated by Analyst 1.6.3(AB Scie)using non-compartmental model,and bioequivalence evaluation was performed for the two preparations.Relevant safety evaluations were performed during the trial.Results The main pharmacokinetic parameters of sidenafil after a single oral dose of sidenafil citrate tablets under fasting condition for test and reference were as follows:Cmax were(494.69±230.94)and(558.78±289.83)ng·mL-1,AUC0-t were(1 336.21±509.78)and(1 410.82±625.99)h·ng·mL-1,AUC0-were(1 366.49±512.16)and(1 441.84±628.04)h·ng·mL-1,respectively.The main pharmacokinetic parameters of sidenafil under fed condition for T and R were as follows:Cmax were(381.89±126.53)and(432.47±175.91)ng·mL-1,AUC0-t were(1 366.34±366.99)and(1 412.76±420.37)h·ng·mL-1,AUC0-were(1 403.28±375.32)and(1 454.13±429.87)h·ng·mL-1,respectively.The results demonstrated the bioequivalence of sidenafil citrate tablets between T and R.The incidence of adverse events in fasting and fed tests were 33.33％and 25.00％,respectively.No serious adverse event was reported.Conclusion The test and reference formulation of sidenafil citrate tablets were equivalent and was safe.

Objective To explore the protective mechanism of honey-processed Hedysari Radix in regulating intestinal mucosal injury in rats with spleen qi deficiency.Methods The three-factor composite modeling method of bitter cold diarrhea,overwork and hunger and satiety disorder was used to construct a spleen qi deficiency model rats.After the model was successfully made,they were randomly divided into model group,honey-processed Hedysari Radix group and probiotic group,with 15 animals in each group.Another 15 normal rats were taken as the blank group.The honey-processed Hedysari Radix group was given 12.6 g·kg-1 water decoction of honey-processed Hedysari Radix by gavage,the probiotics group was given Bifidobacterium Lactobacillus triple viable tablets suspension at a dose of 0.625 g·kg-1,and the blank group and the model group were given the same dose of distilled water.The rats in the four groups were administered once a day for 15 days.Enzyme-linked immunosorbent assay was used to detect diamine oxidase(DAO)in serum,D-lactic acid(D-LA),secretory immunoglobulin A factor,and Western blotting was used to detect the expression levels of AMP-activated protein kinase(AMPK),zonula occludens-1(ZO-1)and occludin in colon tissues.Results The serum levels of DAO in the blank group,model group,honey-processed Hedysari Radix group and probiotic group were(138.93±9.78),(187.95±12.90),(147.21±6.92)and(166.47±3.37)pg·mL-1;the contents of D-LA were(892.23±49.17),(1 099.84±137.64),(956.56±86.04)and(989.61±51.75)μg·L-1;the contents of SIgA in colon tissues were(14.04±1.42),(11.47±2.39),(11.84±1.49)and(12.93±1.65)μg·mL-1;the relative expression levels of ZO-1 protein in colon tissues were 1.18±0.11,0.42±0.04,0.77±0.05 and 0.95±0.07;the relative expression levels of occludin protein were 1.35±0.31,0.61±0.17,1.19±0.19 and 0.88±0.13;the relative expression levels of AMPK protein were 0.91±0.02,0.35±0.09,0.74±0.08 and 0.59±0.11.Compared with the model group,there were significant differences in the serum content of DAO and D-LA,SIgA content in colon,and the content of ZO-1,occludin and AMPK protein in the honey-processed Hedysari Radix group(P＜0.01,P＜0.05).Conclusion Honey-processed Hedysari Radix can enhance the protective effect on the intestinal mucosa of rats with spleen qi deficiency by regulating the expression of related inflammatory cytokines,intestinal mucosal upper cell enzymes and tight junction proteins in rats with spleen qi deficiency.

Abstract Vitamin D, as an important nutrient, has been widely recognized for its significant role in the growth and development of children and adolescents, but its association with mental health is still under exploration. The article reviews and summarizes the related researches on vitamin D and common mental health problems of children and adolescents, including depression symptoms, anxiety symptoms, and suicidal ideation and behaviors, and possible biological mechanisms of vitamin D influencing mental health, to provide scientific evidence and ideas for improving the mental health of children and adolescents in China, as well as insights for future studies.

ObjectiveTo investigate the effect of mucin 1 (MUC1) on the proliferation and apoptosis of nasopharyngeal carcinoma (NPC) and its regulatory mechanism. MethodsThe 60 NPC and paired para-cancer normal tissues were collected from October 2020 to July 2021 in Quanzhou First Hospital. The expression of MUC1 was measured by real-time quantitative PCR (qPCR) in the patients with PNC. The 5-8F and HNE1 cells were transfected with siRNA control (si-control) or siRNA targeting MUC1 (si-MUC1). Cell proliferation was analyzed by cell counting kit-8 and colony formation assay, and apoptosis was analyzed by flow cytometry analysis in the 5-8F and HNE1 cells. The qPCR and ELISA were executed to analyze the levels of TNF-α and IL-6. Western blot was performed to measure the expression of MUC1, NF-кB and apoptosis-related proteins (Bax and Bcl-2). ResultsThe expression of MUC1 was up-regulated in the NPC tissues, and NPC patients with the high MUC1 expression were inclined to EBV infection, growth and metastasis of NPC. Loss of MUC1 restrained malignant features, including the proliferation and apoptosis, downregulated the expression of p-IкB、p-P65 and Bcl-2 and upregulated the expression of Bax in the NPC cells. ConclusionDownregulation of MUC1 restrained biological characteristics of malignancy, including cell proliferation and apoptosis, by inactivating NF-κB signaling pathway in NPC.

Exploring the action targets (groups) of traditional Chinese medicine (TCM) is an important proposition to promote the innovation and development of TCM, but it has attracted a lot of attention as to whether it is related to the efficacy or the disease. Our team found that the metabolomic signature molecules in the development of diabetes mellitus (DM) were significantly associated with the clinical efficacy of Yuquan Pill through a large clinical sample study. Taking this as a clue, our team intends to expand the information on the omics features of DM development, and discover the key targets (groups) and their lead compounds for the hypoglycemic effect of Yuquan Pill. The project includes: ① Based on the retrospective clinical trials, using omics technology integrated with generative artificial intelligence, mining the characteristic information of proteome and microbiome, forming driving factors together with metabolome characteristic molecules, and characterizing the molecular trajectories of diabetes evolution and their interference by Yuquan Pill; ② Taking the evolving molecular trajectories as a link and pointer, using anthropomorphic modeling and molecular biology techniques such as chemical proteomics to discover the key targets (groups) of Yuquan Pill's hypoglycemic effect, with the prospective clinical samples for validation; ③ Evaluate the overall response of key targets (groups) using graph neural network technology, and search for drug-derived/endogenous lead compounds with proven clinical pathologies and clear mechanisms of action, so as to provide a new paradigm and technology for the discovery of complex active ingredient targets (groups) of TCM that are related to their clinical efficacy, as well as for the discovery of innovative medicines.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.