The Pharmacovigilance Guidelines for Clinical Application of Oral Chinese Patent Medicines （hereinafter referred to as the Guidelines） is first specialized in the field of drug safety for oral Chinese patent medicines （OCPMs） in China. Rooted in China's healthcare context， the Guidelines address the unique usage patterns and risk characteristics of OCPMs， filling a regulatory gap in the pharmacovigilance framework specific to this category. To facilitate accurate understanding and effective implementation of the Guidelines， and to promote the standardized development of pharmacovigilance practices for OCPMs， this study offered a systematic interpretation based on its three core components. In the domain of risk monitoring and reporting， the paper analyzed the rationale for multi-source information integration and clarified the criteria for identifying key products and target populations for intensive monitoring. Regarding risk assessment， the Guidelines were examined from three dimensions of formulation components， medication behaviors， and population to address complex safety issues arising from medicinal constituents， irrational use， and individual susceptibility. In the area of risk control， the analysis focused on context-based interventions and dynamic closed-loop management strategies， exploring practical pathways to shift from passive response to proactive risk mitigation. Furthermore， this paper evaluated the applied value of the Guidelines and identified implementation challenges， such as insufficient capacity at the primary-care level and limited digital infrastructure. In response， the study proposed optimization strategies including establishing a dynamic updating mechanism， strengthening training at the grassroots level， and incorporating artificial intelligence to enhance pharmacovigilance capacity. This interpretation aims to provide actionable insights for marketing authorization holders （including manufacturers）， pharmaceutical distributors， healthcare institutions， and research organizations， ultimately supporting the establishment and refinement of a full lifecycle pharmacovigilance system for OCPMs.

ObjectiveTo construct a stable monoclonal human embryonic kidney 293 （HEK293） cell line expressing recombinant human coagulation factor Ⅶ （rhFⅦ） and evaluate the expression level and procoagulant bioactivity of rhFⅦ. MethodsThe plasmid pCDNA3.1-EGFP-FⅦ was transfected into HEK293 cells to verify the effectiveness of the transfection system. The plasmid pCDNA3.1-FⅦ was transfected into HEK293 cells， and monoclonal stable transfected cell lines were selected using geneticin （G418）. The transcription of the FⅦ gene was identified by reverse transcription polymerase chain reaction （RT-PCR）. The expression level of rhFⅦ in the supernatant of the monoclonal stable transfected cell line was detected by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and Western blot. The concentration of rhFⅦ was determined by enzyme-linked immunosorbent assay （ELISA）， and the procoagulant activity of rhFⅦ was measured by human coagulation factor Ⅶ potency assay. ResultsHEK293 cells transfected with pcDNA3.1-EGFP-FⅦ showed green fluorescence， indicating that rhFⅦ was successfully expressed in the supernatant of HEK293 cells after transient transfection with pcDNA3.1-FⅦ. The monoclonal stable transfected cell line was obtained by G418 screening. RT-PCR identified that the FⅦ gene was integrated into the genome of the monoclonal stable transfected cell line. The cell viability was good as detected by Cell Counting Kit-8， and a single band of rhFⅦ was obtained by purification of the cell supernatant. The highest rhFⅦ expression was （1.27±0.09） mg/L， and the highest procoagulant activity was （380.29±13.80）%. ConclusionThe monoclonal HEK293 cell lines which can express rhFⅦ protein efficiently and stably with excellent procoagulant bioactivity is successfully screened.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective:To evaluate the clinical safety of Fufang E'jiao syrup and provide reference for its rational and safe clinical use. Methods:The literature involving Fufang E'jiao syrup in domestic and international databases, as well as the relevant clinical trials on ClinicalTrials.gov and the Chinese Clinical Trial Registry website were searched up to June 1, 2024. Those literature and clinical trials reporting drug adverse events were included, and the basic information about literature/clinical trials (title, publication year, study design, etc.), patients (age, gender, primary diseases, and dosage of Fufang E'jiao syrup), and adverse events (time of occurrence, clinical manifestations, and outcomes) was extracted. The adverse events were standardized and classified using the Medical Dictionary for Regulatory Activities version 25.0, and were also analyzed based on traditional Chinese medicine theory. Results:A total of 19 literature were included in the analysis, including 16 observational/experimental clinical studies, and 3 case reports. The 19 literature reported a total of 430 adverse events involving 398 patients, and the patients were mainly with malignant tumors and anemia. The 430 adverse events involved 11 system organ classes, which mainly included gastrointestinal disorders (260 events, 60.47%, with the most common symptom being dry mouth), respiratory, thoracic, and mediastinal disorders (119 events, 27.67%, with the most common symptom being dry throat), and skin and subcutaneous tissue disorders (16 events, 3.72%, with the most common symptom being mucosal ulcers). Based on traditional Chinese medicine theory, the 430 adverse events were mainly manifested as symptoms of indigestion (nausea, epigastric discomfort, and decreased appetite) and symptoms of "heat" (dry mouth and dry throat).Conclusions:Fufang E'jiao syrup has a relatively good overall safety profile, with the most common adverse events being symptoms of "heat" and gastrointestinal reactions. Patients should not use it blindly, and it should be used with syndrome differentiation in clinical practice.

With the rapid development of the interdisciplinary area of artificial intelligence and medi-cine,large language model(LLM)has been widely used in the fields such as diagnosis and treatment,medi-cine,and healthcare.LLM has unique advantages in the field of traditional Chinese medicine(TCM),such as high consistency with the"Four Diagnostic Methods",perfect combination of natural language and self-super-vised learning in TCM,the ability to adapt to the characteristics TCM formulas,and the assistance in TCM di-agnosis and treatment.At present,various LLM models have been developed,including the"Qihuang Ask Big Model"and the Digital Traditional Chinese Medicine Big Model"GLM-130B",but they still face challenges such as value mismatch and medical abuse,increased demand for interpretability,lack of advanced technolo-gy,and domestic policy access.This article reviews the evolution of LLM,its unique advantages and applica-tions in the field of TCM,the problems and challenges,and the future development trends,in order to provide reference for the further promotion of LLM in traditional medicine.

Objective: To analyze the trend of the incidence of pulmonary tuberculosis in Yecheng County of Xinjiang from 2011 to 2022 and the influence of age, period and birth cohort effect on the incidence of pulmonary tuberculosis, so as to provide a new theoretical reference for the prevention and control of local pulmonary tuberculosis. Methods : Based on the registration data of new pulmonary tuberculosis cases in Yecheng County, Xinjiang from 2011 to 2022, the connection point regression model was used to calculate the crude incidence rate, age-standardized incidence rate, annual percentage change(APC), and average annual percentage change(AAPC) to describe the epidemic trend of pulmonary tuberculosis. The age-period-cohort model was used to explore the influence of age, period and birth cohort effect on the trend of pulmonary tuberculosis incidence. Results : From 2011 to 2022, a total of 17 057 new cases of pulmonary tuberculosis were registered in Yecheng County, Xinjiang. The crude incidence and standardized incidence were 416.07/100 000 and 496.01/100 000, respectively. The incidence of pulmonary tuberculosis increased first and then decreased during the 12 years, with an upward trend from 2011 to 2018. The APC values of the standardized incidence of pulmonary tuberculosis in the total population, males and females were 24.42%(95%CI: 11.55-38.78), 27.24%(95%CI: 12.35-44.10) and 21.79%(95%CI: 9.81-35.09), respectively. From 2018 to 2022, there was a downward trend. The APC values of the standardized incidence of tuberculosis in the total population, males and females were-38.51%(95%CI:-53.27--19.09),-38.18%(95%CI:-54.59--15.85) and-38.73%(95%CI:-52.96--20.19), respectively. With the increase of age, the incidence of pulmonary tuberculosis showed a trend of rising first and then fluctuating steadily. The risk of the population increased first and then decreased over time, and the later the birth, the lower the risk of the cohort. Conclusion The incidence of pulmonary tuberculosis in Yecheng County of Xinjiang showed a trend of increasing first and then decreasing in the past 12 years, and gradually increased with age. The earlier the birth, the higher the risk of the disease. Men and the elderly are the key targets of tuberculosis prevention and control in Yecheng County, Xinjiang. It is recommended to strengthen the screening of key populations.

Objective : To explore the feasibility of machine learning methods in the discrimination of tuberculosis patients. Methods : The data of 15 observation indicators of 860 patients were obtained from a tertiary hospital. Through in-depth mining and analysis of the data, support vector machine, random forest and neural network model methods were used to discriminate the diseases of patients. Results : The accuracies of the TB suspected patient discrimination models based on support vector machine, random forest and neural network were 90%, 91% and 88%, respectively. Conclusion All three machine learning methods can be used for discriminative analysis of suspected tuberculosis patients. In comparison, random forest performs better in discriminating patients with tuberculosis from those with pneumonia.

Objective To investigate the effect of asperuloside(ASP)on the malignant progression and chemotherapy resistance of hepatocellular carcinoma(HCC)cells by regulating the supersonic hedgehog(SHH)/glioma-associated oncogene homolog 1(GLI1)signaling pathway.Methods The expression of SHH and GLI1 protein in human hepatocellular carcinoma cell line(SMMC-7721)/adriamycin(ADM)and SMMC-7721 cell line were detected by Western blot(WB).The HCC drug-resistant cell line SMMC-7721/ADM were divided into Control group,ADM group,L-ASP group(1 mmol/L ASP),M-ASP group(2 mmol/L ASP),H-ASP group(3 mmol/L ASP),ASP+PM group(1 μmol/L SHH/GLI1 signaling pathway activator PM).Ex-cept for Control group,5 μg/mL ADM was added to each group.The effect of ASP on the proliferation of SMMC-7721/ADM cells was detected by cell counting kit-8(CCK8)assay and plate cloning assay.The effect of ASP on the invasion and migration of SMMC-7721/ADM cells were detected by Transwell assay.The effect of ASP on the apoptosis of SMMC-7721/ADM cells was detected by flow cytometry.The expression of SHH,GLI1,proliferating cell nuclear antigen(PCNA),matrix metalloproteinase-9(MMP-9)and B cell lymphoma-2 associated X protein(Bax)in SMMC-7721/ADM cells were detected by WB.Animal experiments verified the effect of ASP on the growth of HCC xenografts and the expression of SHH/GLI1 signaling pathway proteins.Results The expression of SHH and GLI1 in SMMC-7721/ADM cells were higher than those in SMMC-7721 cells(P＜0.05).L-ASP group,M-ASP group and H-ASP group decreased the proliferation,migration and in-vasion of SMMC-7721/ADM cells in a dose-dependent manner,decreased the expression of SHH,GLI1,PCNA and MMP-9,and promoted cell apoptosis and Bax expression(P＜0.05).SHH/GLI1 signaling pathway acti-vator PM could reverse the inhibitory effect of H-ASP treatment on malignant progression and chemotherapy resistance of SMMC-7721/ADM cells(P＜0.05).ASP could inhibit the growth of HCC transplanted tumor and the expression of SHH and GLI1(P＜0.05).Conclusion ASP can inhibit the malignant progression of HCC cells and enhance the sensitivity of chemotherapy,which may be achieved by inhibiting the SHH/GLI1 signaling pathway.

Objective To investigate the population density and seasonal fluctuations of Aedes albopictus in Guangzhou City, Guangdong Province, from 2021 to 2023, so as to provide insights into A. albopictus control and management of dengue fever. Methods The surveillance of A. albopictus density was performed in all surveillance sites assigned across all streets (townships) in Guangzhou City during the period from January to December from 2021 to 2023. The surveillance frequency was twice every half month from May to September, and once every month for the rest of a year. In each surveillance period, A. albopictus mosquito larvae were captured from indoor and outdoor small water containers in residential areas, parks, medical facilities, schools, other government sectors and social organizations, construction sites, special industries and others for mosquito species identification. Adult mosquitoes were captured using electric mosquito suction apparatus for species identification and gender classification. Adult mosquitoes and mosquito eggs were collected with mosquito and egg traps at the breeding and dwelling places of Aedes mosquitoes for identification. The mosquito oviposition index (MOI), Breteau index (BI), adult mosquito density index (ADI) and standard space index (SSI) were calculated. The A. albopictus density was classified into grades 0, 1, 2 and 3 in each surveillance site, with Grade 0 density defined eligible, and the eligible rate of A. albopictus density was calculated at all surveillance sites each year from 2021 to 2023. In addition, the changing trends in MOI, SSI, BI and ADI of A. albopictus were analyzed in Guangzhou City from 2021 to 2023. Results The eligible rates of A. albopictus density were 61.69%, 68.75% and 55.15% in surveillance sites of Guangzhou City from 2021 to 2023 (χ² = 297.712, P < 0.001), and appeared a tendency towards a reduction followed by a rise each year, which gradually reduced since January, maintained at a low level during the period between May and October, and gradually increased from November to December. The MOI, SSI, BI and ADI of A. albopictus all appeared a tendency towards a rise followed by a reduction in Guangzhou City during the period between January and December from 2021 to 2023. The BI of A. albopictus peaked in the first half of June in 2021 (4.03), the first half of July in 2022 (3.89) and the last half of August in 2023 (5.02), and the SSI of A. albopictus peaked in the last half of June in 2021 (0.93), the last half of May in 2022 (0.59), and the last half of June (0.94) and the first half of September in 2023 (1.12). In addition, the MOI of A. albopictus peaked in the first half of May in 2021 (8.64), the first half of June in 2022 (8.96), and the last half of May (10.21) and the last half of June in 2023 (10.89), and the ADI of A. albopictus peaked in the first half of June in 2021 (3.41), the last half of June in 2022 (4.06), and the first half of July in 2023 (3.61). Conclusions The density of A. albopictus is high in Guangzhou City during the period from May to October, and the risk of local outbreak caused by imported dengue fever is high. Persistent intensified surveillance of the density and seasonal fluctuation of A. albopictus is recommended and timely mosquito prevention and control is required according to the fluctuation in the A. albopictus density.

Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*