Objective To systematically evaluate the efficacy and safety of traditional Chinese medicine (TCM) compound in treating pulmonary nodules, providing evidence-based medical evidence for TCM intervention in pulmonary nodules. Methods Computer search of PubMed, CNKI, Wanfang, VIP, and SinoMed was conducted to select randomized controlled trials (RCTs) of TCM compound intervention in pulmonary nodules, with the retrieval time from the inception to November 29, 2023. The Cochrane bias risk assessment tool was used to evaluate the quality of the included studies, and Review Manager 5.4 was used for Meta-analysis. Results A total of 18 RCTs were included, covering 8 provinces across the country, with a total sample size of 1301 patients. The TCM compounds used in the included studies all incorporated the method of dissolving phlegm and dissipating nodules. There was a high risk of bias uncertainty in the included studies. Meta-analysis results suggested that TCM compound could significantly reduce the diameter of pulmonary nodules [MD=−1.41, 95%CI (−1.70, −1.13), P<0.001], decrease the number of nodules [MD=−0.37, 95%CI (−0.73, −0.01), P=0.05], alleviate clinical symptoms [MD=−4.84, 95%CI (−6.04, −3.64), P<0.001], and improve lung function [forced expiratory volume in one second (FEV1), MD=0.55, 95%CI (0.09, 1.01), P=0.02; FEV1/forced vital capacity, MD=6.12, 95%CI (4.47, 7.78), P<0.001]. However, there was no statistically significant difference in the probability of malignancy between the experimental group and the control group [MD=−0.01, 95%CI (−0.01, 0.00), P=0.09]. Conclusion TCM compound can significantly reduce the diameter of pulmonary nodules, decrease the number of nodules, alleviate clinical symptoms, and improve lung function, but future multicenter, large-sample, high-quality RCTs are still needed to further explore and verify this conclusion.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

AIM To study the chemical constituents from the water fraction of rhizoma of Smilax trinervula Miq.and their biological activities.METHODS Polyamide,silica gel,Sephadex LH-20,ODS and semi-preparative HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antitumor activities were determined by MTT mothod,and the inhibitory activities on α-glucosidase were determined by PNPG method.RESULTS Eleven compounds were isolated and identified as tyrosine(1),uridine(2),2-(2',3',4'-trihydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(3),2-(1',2',3',4'-tetrahydroxybutyl)-6-(2",3",4"-trihydroxybutyl)-pyrazine(4),2-(1',2',3',4'-tetrahydroxybutyl)-5-(2",3",4"-trihydroxybutyl)-pyrazine(5),uracil(6),2-(1',2',3',4'-tetrahydroxybutyl)-5-(1",2",3",4"-tetrahydroxybutyl)-pyrazine(7),dioscin(8),shikimic acid(9),pyrazine(10),3,4-dihydroxyphenyethyl alcohol 8-O-β-D-glycopyranoside(11).The IC50 values of compounds 8 to human breast cancer cell MCF-7 was(2.36±0.26)μg/mL,and the IC50 values of compounds 3-5 and 7 to α-glucosidase were(1.54±0.15)-(10.53±0.38)μg/mL.CONCLUSION Compounds 1-7,10 are isolated from Smilax genus for the first time,and compound 9,11 are first isolated from this plant.Compound 8 has anti-tumor activity,and compounds 3-5,7 have α-glucosidase inhibitory activities.

Objective To analyze the global literature related to functional cure of hepatitis B from 2019 to 2023 by using bibliometric analysis methods,so as to help researchers understand the research hotspots and trends in this field.Methods The literature related to the topic of functional cure of hepatitis B included in the Science Citation Index Expanded(SCI-Expanded)of the Web of Science Core Collection from 2019 to 2023 was searched.By using VOSviewer and CiteSpace visual analysis tools,analyses were conducted from the perspectives of publication trends,international research cooperation networks,and keyword emergence,and were elaborated with the specific contents of the related literature to elucidate research hotspots and trends.Results A total of 600 eligible papers in this field were included.Keyword co-occurrence and thematic clustering suggested that the main research directions of functional cure were:serum biomarkers for prediction and monitoring of functional cure,functional cure and immunity,nucleoside analog discontinuation,interferon therapy,and long-term prognosis of functional cure.The research contents of the ESI highly cited original research papers were similar to the clustering of the above,but showed more attention on the novel agents for functional cure.The content of the keyword emergence map showed that hotspots of interest changed from virologic mechanisms and serum markers,to nucleoside analog discontinuation and interferon therapy,and finally to immunologic mechanisms and new drug.Conclusion The research hotspots and trends of functional cure of hepatitis B were focused on virological mechanism,serum markers,immunological mechanism,nucleoside analog discontinuation,interferon therapy,and long-term prognosis after cure.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To analyze the global literature related to functional cure of hepatitis B from 2019 to 2023 by using bibliometric analysis methods,so as to help researchers understand the research hotspots and trends in this field.Methods The literature related to the topic of functional cure of hepatitis B included in the Science Citation Index Expanded(SCI-Expanded)of the Web of Science Core Collection from 2019 to 2023 was searched.By using VOSviewer and CiteSpace visual analysis tools,analyses were conducted from the perspectives of publication trends,international research cooperation networks,and keyword emergence,and were elaborated with the specific contents of the related literature to elucidate research hotspots and trends.Results A total of 600 eligible papers in this field were included.Keyword co-occurrence and thematic clustering suggested that the main research directions of functional cure were:serum biomarkers for prediction and monitoring of functional cure,functional cure and immunity,nucleoside analog discontinuation,interferon therapy,and long-term prognosis of functional cure.The research contents of the ESI highly cited original research papers were similar to the clustering of the above,but showed more attention on the novel agents for functional cure.The content of the keyword emergence map showed that hotspots of interest changed from virologic mechanisms and serum markers,to nucleoside analog discontinuation and interferon therapy,and finally to immunologic mechanisms and new drug.Conclusion The research hotspots and trends of functional cure of hepatitis B were focused on virological mechanism,serum markers,immunological mechanism,nucleoside analog discontinuation,interferon therapy,and long-term prognosis after cure.

The case teaching mode,as an important practical way of teaching reform in graduate educa-tion,plays a positive role in stimulating learning interest and improving comprehensive ability.As a core course in biology,advanced immunology is characterised by the depth of its theoretical system and the boundaries of its research scope.In this paper,we first analyzed the significance and current situation of case library construction at home and abroad,and pointed out the key issues that need to be further opti-mised in the existing case teaching mode.Based on the construction strategy of"Advanced Immunolo-gy",three typical teaching cases,namely tumour treatment strategy,gene editing technology to overcome organ transplant rejection,and synthetic immunology,are selected for empirical research,focusing on graduate students' innovative ability to raise questions and solve problems.The effectiveness of teaching practice was summarized from the improvement of teachers' ability,the award-winning of students' disci-plinary competitions,and the co-construction between the university and enterprises,which has a signifi-cant effect and guarantees the benign optimization of the teaching reform of immunology,and also has the popularization value and exemplary effect on the high-quality development of immunology-related courses.

P53 is a key tumor suppressor gene,which is regulated in many ways.Zinc finger 148(ZNF148)and SP5,as zinc finger transcription factors(TFs),play important roles in tumor suppression and carcinogenesis.The regulatory relationship between these two TFs and p53 has not been reported.In this paper,Ishikawa and A549 cell lines with different p53 expression levels were used as research mod-els to explore the transcriptional regulation of the P53 gene by ZNF148 and SP5.The data showed that there were differences in the expression of ZNF148 and SP5 in the two cell lines.The mRNA expression of ZNF148 in Ishikawa was 1.9 times higher than that of A549,and the mRNA expression of SP5 in A549 was 802.4 times that of ZNF148.Data showed that in Ishikawa cells,the expression of P53 de-creased(81.8％)after ZNF148 knockdown,and increased(2.6 times)after SP5 overexpression.Transfection of si-SP5 and ZNF148 expression plasmids into A549 cells increased the mRNA expression of P53 by 6.6 times and 14.6 times,respectively.These results indicate that ZNF148 could activate,whereas SP5 could inhibit,P53 expression.The conserved cis-element of ZNF148 and SP5 TFs was found in the region of the P53 promoter by bioinformatics methods.The data from dual luciferase reporter gene assay showed that the luciferase activity of ZNF148 in Ishikawa and A549 cells was increased by 2.1-fold and 4.2-fold compared with the control group(P＜0.05).Compared with the control group,the normalized relative luciferase activity of transfected SP5 decreased by 77.1％and 35.7％(P＜0.05).However,when the cis-element of ZNF148 and SP5 was mutated,the effect disappeared.Further trans-fection of ZNF148 and SP5 with different ratios revealed that SP5 could reverse the transcriptional activa-tion of P53 by ZNF148.Studies have shown that ZNF148 shares a common site with SP5,and the ratio of the two TFs may influence the transcriptional activity of P53.The expression of the Wnt pathway and the cell proliferation rate after knockdown of ZNF148 and SP5 were further studied to explore the role of the two TFs.Our data show that ZNF148 and SP5 could regulate the transcriptional activity of P53,and their expression levels and interaction may be the key factors regulating P53 expression.

The case teaching mode,as an important practical way of teaching reform in graduate educa-tion,plays a positive role in stimulating learning interest and improving comprehensive ability.As a core course in biology,advanced immunology is characterised by the depth of its theoretical system and the boundaries of its research scope.In this paper,we first analyzed the significance and current situation of case library construction at home and abroad,and pointed out the key issues that need to be further opti-mised in the existing case teaching mode.Based on the construction strategy of"Advanced Immunolo-gy",three typical teaching cases,namely tumour treatment strategy,gene editing technology to overcome organ transplant rejection,and synthetic immunology,are selected for empirical research,focusing on graduate students' innovative ability to raise questions and solve problems.The effectiveness of teaching practice was summarized from the improvement of teachers' ability,the award-winning of students' disci-plinary competitions,and the co-construction between the university and enterprises,which has a signifi-cant effect and guarantees the benign optimization of the teaching reform of immunology,and also has the popularization value and exemplary effect on the high-quality development of immunology-related courses.

Objective To compare the differences of endoscopic ultrasound (EUS)-guided non-invasive measurement of portal venous pressure and EUS-guided portal pressure gradient(EUS-PPG) in measurement of portal venous pressure on animals and their correlation. Methods Twenty-four miniature pigs were selected and fed with carbon tetrachloride and phenobarbital sodium combined with high-fat,low-protein and low-choline diet for 16 weeks to establish a liver cirrhotic portal hypertension model. The changes of biochemical indexes of liver function and liver pathology in the experimental pigs were observed to evaluate whether the model was successful. After the model was successfully established,the hemodynamic parameters of the portal venous trunk were measured non-invasively under EUS guidance,including portal venous blood flow and splenic artery pulsatility index,thereby calculating portal venous pressure. Then,taking EUS-PPG,the portal vein,hepatic vein,and inferior vena cava were punctured with an 18G puncture needle under general anesthesia guided by the translinear endoscopic ultrasound,and the PPG was calculated through the central venous pressure monitoring system.The Pearson correlation analysis,Kappa test,ICC intraclass correlation coefficient and Bland-Altman plot were used for consistency analysis. Results All the 24 pigs survived 16 weeks after modeling.The serum levels of alanine transaminase (ALT),aspartate transaminase (AST),albumin (ALB),globulin (GLB),total bilirubin (TBIL) and indirect bilirubin (IBIL)after modeling were higher than those before modeling(P<0.05). HE staining and Sirius red staining showed abnormal liver morphology and increased collagen fibers after modeling,suggesting that the experimental pig model of liver cirrhotic portal hypertension was successfully established. The results of EUS-guided non-invasive measurement of portal venous pressure showed that the mean splenic artery pulsatility index was (2.03±0.68),the mean portal vein flow was (17.27±4.31)cm/s,and the mean portal venous pressure was (15.97±3.65)mmHg. The measurement results of the mean portal venous pressure,hepatic venous pres-sure and PPG of EUS-PPG were (20.68±4.71)mmHg,(4.07±2.14)mmHg and (16.38±4.28)mmHg respectively. Pearson correlation analysis showed that there was a significant positive correlation between the portal venous pressures measured by the two methods (r=0.902,P<0.001);the consistency tests of Kappa test and ICC intraclass correlation coefficient showed that the measurement results of the two methods were highly consistent (Kappa=0.699,P<0.001;ICC=0.945);Bland-Altman plot analysis showed that most of the points fell within 95％ limits of agreement. Conclusion EUS-guided non-invasive measurement of portal venous pressure has a high correlation and consistency with the measurement results by EUS-PPG,which has high success rate,and accurate reflection of portal venous pressure,with low cost and good safety.