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.

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*

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 observe the effects of remote home monitoring Baduanjin exercises on exercise capacity,lower limb muscle strength,quality of life and clinical symptoms in stable moderate-to-severe chronic obstructive pul-monary disease(COPD)patients. Method:Seventy-six patients with moderate to severe chronic obstructive pulmonary disease in the stable stage were selected and randomly divided into a treatment group(n=38)and a control group(n=38).The con-trol group was given routine medication and health education,while the treatment group was given baduanjin training under remote monitoring via APP and equipment for 12 weeks on the basis of the control group.Func-tional outcomes were assessed before and 12 weeks after the intervention in both groups,including:exercise capacity(6 minutes walking distance,6MWD),lower limb muscle strength(time of Isometric squatting test),quality of life(the MOS 36-item Short Form Health Survey,SF36)and clinical symptoms scores(St.George's Respiratory Questionnaire,SGRQ). Result:After 12-week intervention,the difference of 6WMD between pre-treatment and post-treatment was sig-nificantly better in the treatment group than that in the control group(P=0.001);the time spent squatting against the wall was significantly better(P=0.019)and statistically significant(P=0.034)compared to the con-trol group.In terms of SF-36,the items of role physical,(RP)(P＜0.001),vitality,(VT)(P=0.001),mental health,(MH)(P=0.008)and general health,(GH)(P=0.001)were significantly improved in the treatment group after treatment when compared with the pre-treatment period,and all of them were significantly better than the control group.On the SGRQ,there was a significant improvement in the treatment group compared to the control group for Symptoms(P=0.011),Activity(P=0.047),Impacts(P=0.002),and Total score(P=0.001). Conclusion:Remote home monitoring Baduanjin exercises significantly improved the COPD patients'exercise capacity,lower limb muscle strength,quality of life and clinical symptoms.

Objective:To investigate the detection status and genotypes distribution characteristics of norovirus(NoV)in environmental sewage from three monitoring points in Fujian province, and to explore the significance of its application to NoV monitoring.Methods:Sewage samples were collected monthly at 5 sampling sites in representative monitoring cities, enriched and concentrated. Partial gene fragments of norovirus VP1 were amplified by reverse transcription-semi nested polymerase chain reaction (RT-snPCR), TA cloned and sequenced. Genotypes were identified based on the sequencing.Results:A total of 56 sewage samples were collected from July 2022 to June 2023. The detection rates of GⅠ and GⅡ were 89.29% (50/56) and 94.64% (53/56), respectively. A total of 7 NoV GⅠ genotypes and 13 GⅡgenotypes were identified. GⅠ.1, GⅠ.4, GⅡ.4 and GⅡ.17 were the dominant genotypes. NoV genotypes detected in different sampling sites were not exactly the same. The detection rate of NoV was low from August to November 2022, and the prevalence of the dominant genotypes was different in different seasons. GⅠ.1 and GⅡ.4 were highly prevalent from August to November 2022, but were replaced by GⅠ.4 and GⅡ.17 from December 2022 to June 2023, respectively. More NoV genotypes were detected in January-June 2023, comparing to the July-December 2022. The dominant genotype GII.17, has multiple clades and new variants have been discovered that are different from the 2014/2015 circulating strains.Conclusions:The detection rates of NoV in environmental sewage were very high, and genotypes were diverse. Environmental sewage surveillance could be an important complementary method for NoV cases surveillance.

Periodontitis is a critical risk factor for the occurrence and development of diabetes.Porphyromonas gingivalis may participate in insulin resistance(IR)caused by periodontal inflammation,but the functional role and specific mechanisms of P.gingivalis in IR remain unclear.In the present study,clinical samples were analysed to determine the statistical correlation between P.gingivalis and IR occurrence.Through culturing of hepatocytes,myocytes,and adipocytes,and feeding mice P.gingivalis orally,the functional correlation between P.gingivalis and IR occurrence was further studied both in vitro and in vivo.Clinical data suggested that the amount of P.gingivalis isolated was correlated with the Homeostatic Model Assessment for IR score.In vitro studies suggested that coculture with P.gingivalis decreased glucose uptake and insulin receptor(INSR)protein expression in hepatocytes,myocytes,and adipocytes.Mice fed P.gingivalis tended to undergo IR.P.gingivalis was detectable in the liver,skeletal muscle,and adipose tissue of experimental mice.The distribution sites of gingipain coincided with the downregulation of INSR.Gingipain proteolysed the functional insulin-binding region of INSR.Coculture with P.gingivalis significantly decreased the INSR-insulin binding ability.Knocking out gingipain from P.gingivalis alleviated the negative effects of P.gingivalis on IR in vivo.Taken together,these findings indicate that distantly migrated P.gingivalis may directly proteolytically degrade INSR through gingipain,thereby leading to IR.The results provide a new strategy for preventing diabetes by targeting periodontal pathogens and provide new ideas for exploring novel mechanisms by which periodontal inflammation affects the systemic metabolic state.

With the rapid development of the interdisciplinary area of artificial intelligence and medicine, large language model (LLM) has been widely used in the fields such as diagnosis and treatment, medicine, 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-supervised learning in TCM, the ability to adapt to the characteristics TCM formulas, and the assistance in TCM diagnosis 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 technology, and domestic policy access. This article reviews the evolution of LLM, its unique advantages and applications in the field of TCM, the problems and challenges, and the future development trends, in order to providereference for the further promotion of LLM in traditional medicine.

"Target trial emulation" (TTE), as a new framework in real-world research, has been formally established in recent years. It can be used to guide the evaluation of the effectiveness and safety of medical interventions based on real-world data for observational causal inference. The core idea of this framework is to follow the principles of randomized controlled trial (RCT), emulate a corresponding RCT using real-world data, and then draw conclusions about the causal relationship between interventions and outcomes. The main implementation tips of TTE can be summarized as "3-7-2": 3 implementation steps including formulating the causal question, designing the emulation plan, and emulating the target study; 7 design elements including eligibility criteria, treatment strategies, intervention allocation, follow-up period, outcome, causal contrast of interest, and analysis plan; and control of 2 critical biases including immortal time bias and prevalent user bias. In this article, we present an overview of the development, current status, implementation steps, classic examples, advantages and limitations of TTE, and its application prospects in traditional Chinese medicine (TCM). It is hoped that this article can assist researchers in TCM to utilize this method for real-world research and contribute to the construction of a clinical evaluation system with distinctive features of TCM.