A natural experiment is a causal inference study design grounded in real-world research. Its core concept is to use quasi-random variation in exposure generated by external factors to evaluate the effects of interventions or exposures on outcomes. It is particularly suitable for research settings in which randomized controlled trials （RCTs） are infeasible or ethically constrained， and it combines causal inference capacity with relatively strong external validity. This article provides an overview of the definition， key features， and current application status of natural experiments， and proposes the application scenarios for applying natural experiment strategies to the evaluation of therapeutic effects in traditional Chinese medicine （TCM）， including policy implementation or policy change evaluation， assessment of variations in clinical practice within hospitals， and evaluation of differences in resource allocation across regions or institutions. The design pathway includes starting from clinical or policy-related TCM questions， systematically collecting relevant data， performing statistical modeling and effect estimation， and interpreting effect estimates in the context of clinical practice. It further analyzes the advantages and challenges of using natural experiments in TCM.

A natural experiment is a causal inference study design grounded in real-world research. Its core concept is to use quasi-random variation in exposure generated by external factors to evaluate the effects of interventions or exposures on outcomes. It is particularly suitable for research settings in which randomized controlled trials （RCTs） are infeasible or ethically constrained， and it combines causal inference capacity with relatively strong external validity. This article provides an overview of the definition， key features， and current application status of natural experiments， and proposes the application scenarios for applying natural experiment strategies to the evaluation of therapeutic effects in traditional Chinese medicine （TCM）， including policy implementation or policy change evaluation， assessment of variations in clinical practice within hospitals， and evaluation of differences in resource allocation across regions or institutions. The design pathway includes starting from clinical or policy-related TCM questions， systematically collecting relevant data， performing statistical modeling and effect estimation， and interpreting effect estimates in the context of clinical practice. It further analyzes the advantages and challenges of using natural experiments in TCM.

Green prescription is a written prescription aimed at improving health by promoting physical activity and improving diet， with advantages such as high cost-effectiveness， strong feasibility， and minimal harm to patients. The theory of traditional Chinese medicine （TCM） green prescription integrates the health philosophy of "following rule of yin and yang， and adjusting ways to cultivating health"， the exercise philosophy of balancing yin-yang and the five elements， and the dietary philosophy of moderation and balance， which embody core TCM concepts such as treating disease before its onset and harmony between humans and nature. It has also developed traditional exercise practices like Tai Chi， Baduanjin， Wuqinxi， Yi-Gin-Ching， and Qigong， as well as dietary adjustments like medicated diet and herbal wines. However， it is believed that the TCM green prescription currently suffers from insufficient evidence-based research， low patient awareness and acceptance， and weak basic research. Based on this， it is proposed that large-sample clinical trials should be conducted in the future to improve the quality of evidence-based medicine， basic research can be carried out with the help of artificial intelligence and other methods in research design， the hospital information system （HIS） can be used for control at the implementation level， and publicity and patient education can be strengthened through the new media， so as to promote the development and application of the TCM green prescriptions in the field of global health treatment.

Traditional Chinese Medicine(TCM)emphasizes syndrome differentiation and treatment,characterized by"maintaining the prescription if effective"and"changing the prescription if ineffective".Traditional randomized controlled trials(RCTs)are inadequate for evaluating the efficacy of dynamic treatment adjustments.The Sequential Multiple Assignment Randomized Trial(SMART)is an emerging adaptive research design that incorporates randomization at multiple stages,allowing for adjustments in subsequent interventions based on treatment responses.This approach is suitable for evaluating dynamic treatment regimens while retaining the low bias risk of traditional RCTs,making it highly promising for clinical research in TCM.This paper summarizes recent methodological advancements in SMART design,including different sample size estimation and statistical analysis methods for primary effect objectives,embedded adaptive intervention objectives,and optimization objectives,along with providing corresponding operational software.Additionally,it offers considerations for applying SMART design in TCM research,such as the selection of disease types,interventions,decision points,tailoring variables,sample size calculation,statistical methods,the importance of pilot trials,ethical considerations,and limitations.The aim is to promote the exploration and practice of this method in the field of TCM,thereby contributing to the generation of high-quality evidence-based evidence for TCM.

Traditional Chinese Medicine(TCM)emphasizes syndrome differentiation and treatment,characterized by"maintaining the prescription if effective"and"changing the prescription if ineffective".Traditional randomized controlled trials(RCTs)are inadequate for evaluating the efficacy of dynamic treatment adjustments.The Sequential Multiple Assignment Randomized Trial(SMART)is an emerging adaptive research design that incorporates randomization at multiple stages,allowing for adjustments in subsequent interventions based on treatment responses.This approach is suitable for evaluating dynamic treatment regimens while retaining the low bias risk of traditional RCTs,making it highly promising for clinical research in TCM.This paper summarizes recent methodological advancements in SMART design,including different sample size estimation and statistical analysis methods for primary effect objectives,embedded adaptive intervention objectives,and optimization objectives,along with providing corresponding operational software.Additionally,it offers considerations for applying SMART design in TCM research,such as the selection of disease types,interventions,decision points,tailoring variables,sample size calculation,statistical methods,the importance of pilot trials,ethical considerations,and limitations.The aim is to promote the exploration and practice of this method in the field of TCM,thereby contributing to the generation of high-quality evidence-based evidence for TCM.

Objective:To investigate the effects of Wumei-Fangfeng drug on Treg/Th17 immune balance in allergic rhinitis(AR)mice via regulating MMP9 derived from mast cell exosomes.Methods:Potential targets of Wumei and Fangfeng were screened,and the intersection was taken from the targets and AR risk genes,subsequently GO analysis and protein-protein interaction analysis were performed to screen therapeutic targets.AR mice model were constructed,mast cells and exosomes were separate from femurs of mice.Wumei-Fangfeng drug and exosomes were used to treat mice.The behavioral scores of mice in each group were evaluated,mRNA expressions of Foxp3,RORγt were detected in nasal mucosa of mice.After knocking down of MMP9 in exosomes,the behavioral score,Foxp3 and RORγt mRNA expressions were observed in AR mice.Results:Bioinformatics results showed that Wumei-Fangfeng drug may act on AR by mast cell exosomes derived IL-1β and MMP9.Compared with normal mice,mRNA expression of Foxp3 in AR mice was decreased,while RORγt mRNA expression was increased,and MMP9 expression was increased(all P<0.05).Expression of Foxp3 mRNA was increased,and expressions of RORγt and MMP9 were decreased in AR mice treated with Wumei-Fangfeng drug,however,mast cell exosomes could further counteract the effects of Wumei-Fangfeng drug,and the effects of mast cell exosomes was weakened after MMP9 knockdown.Conclusion:Wumei-Fangfeng drug regulates the imbalance of Treg/Th17 in AR mice by inhibiting the exosomal MMP9 of bone marrow-derived mast cells.

The quality evaluation of the blind method is to evaluate the clinical blind data obtained from clinical trials adopting the blind method and judge the effectiveness of the blind method by investigating the blind effect of different blind objects. A successful blind method can avoid the influence of subjective factors on the test results of subjects and researchers to a certain extent. The quality evaluation of the blind method can reflect not only the effectiveness of the blind method but also the accuracy and credibility of clinical trial results. In recent years， randomized controlled trials have been widely used in the evaluation of the clinical efficacy of traditional Chinese medicine （TCM）， but the quality of the implementation of blind methods is uneven， and the evaluation criteria have not yet been formed. In this paper， the data collection methods， calculation principles， advantages， and disadvantages of two quantitative quality evaluation methods of blind methods， namely James Blinding Index （JBI） and Bang Blinding Index （BBI）， were introduced. The two indexes were analyzed in a randomized controlled trial of acupuncture and moxibustion to relieve postoperative oral pain. The calculation process of the results was demonstrated by R software and visualized by forest map. At the same time， a tool table was designed to facilitate the collection of evaluation data of blind methods in TCM clinical trials at different stages. Finally， the necessity and feasibility of quality evaluation of blind method in TCM research were discussed to provide a basis for evaluating and improving the quality of blind method implementation in TCM clinical trials.

ObjectiveThis study aims to understand the recognition of practitioners in traditional Chinese medicine （TCM） hospitals on hospital-based health technology assessment （HB-HTA）， assessment needs， challenges， and suggestions， so as to provide references for the future work. MethodThe convenient sampling method was adopted to survey the relevant practitioners in TCM hospitals. The questionnaire included 39 questions in 4 dimensions and was distributed through the online platform Weijuanxing. ResultA total of 244 questionnaires were recovered， and the obtained data were analyzed in SPSS. The results showed that 137 practitioners were very familiar with HB-HTA and there was no significant difference in the recognition of practitioners in different occupations （F=0.251； P=0.778）. The practitioners in Hong Kong， Macao， and Taiwan had lower recognition than those in other regions. In terms of the assessment needs， 127 practitioners believed that it was very necessary to carry out HB-HTA in TCM hospitals in the future. Chinese patent medicines/Chinese herbal medicine decoction pieces （5.91） and TCM appropriate technology （5.57） had higher assessment priority scores. The assessment needs were high for the effectiveness （235 practitioners） and safety （224 practitioners） of health technology. The lack of specialized organization and standardized evaluation process system and the shortage of talents were considered to be the major challenges for the future development in this field. ConclusionThe stakeholders carrying out the health technology assessment in TCM hospitals had certain awareness of HB-HTA. Most practitioners believed that it was necessary to carry out HB-HTA in TCM hospitals in the future， while the work might face challenges such as the lack of organizations and system and the shortage of talents， which requires policy support.

Objective:To compare the differences in the prevalence of mild micro-hepatic encephalopathy (MHE) among patients with cirrhosis by using the psychometric hepatic encephalopathy score (PHES) and the Stroop smartphone application (Encephal App) test.Methods:This prospective, multi-center, real-world study was initiated by the National Clinical Medical Research Center for Infectious Diseases and the Portal Hypertension Alliance and registered with International ClinicalTrials.gov (NCT05140837). 354 cases of cirrhosis were enrolled in 19 hospitals across the country. PHES (including digital connection tests A and B, digital symbol tests, trajectory drawing tests, and serial management tests) and the Stroop test were conducted in all of them. PHES was differentiated using standard diagnostic criteria established by the two studies in China and South Korea. The Stroop test was evaluated based on the criteria of the research and development team. The impact of different diagnostic standards or methods on the incidence of MHE in patients with cirrhosis was analyzed. Data between groups were differentiated using the t-test, Mann-Whitney U test, and χ2 test. A kappa test was used to compare the consistency between groups. Results:After PHES, the prevalence of MHE among 354 cases of cirrhosis was 78.53% and 15.25%, respectively, based on Chinese research standards and Korean research normal value standards. However, the prevalence of MHE was 56.78% based on the Stroop test, and the differences in pairwise comparisons among the three groups were statistically significant (kappa = -0.064, P < 0.001). Stratified analysis revealed that the MHE prevalence in three groups of patients with Child-Pugh classes A, B, and C was 74.14%, 83.33%, and 88.24%, respectively, according to the normal value standards of Chinese researchers, while the MHE prevalence rates in three groups of patients with Child-Pugh classes A, B, and C were 8.29%, 23.53%, and 38.24%, respectively, according to the normal value standards of Korean researchers. Furthermore, the prevalence rates of MHE in the three groups of patients with Child-Pugh grades A, B, and C were 52.68%, 58.82%, and 73.53%, respectively, according to the Stroop test standard. However, among the results of each diagnostic standard, the prevalence of MHE showed an increasing trend with an increasing Child-Pugh grade. Further comparison demonstrated that the scores obtained by the number connection test A and the number symbol test were consistent according to the normal value standards of the two studies in China and South Korea ( Z = -0.982, -1.702; P = 0.326, 0.089), while the other three sub-tests had significant differences ( P < 0.001). Conclusion:The prevalence rate of MHE in the cirrhotic population is high, but the prevalence of MHE obtained by using different diagnostic criteria or methods varies greatly. Therefore, in line with the current changes in demographics and disease spectrum, it is necessary to enroll a larger sample size of a healthy population as a control. Moreover, the establishment of more reliable diagnostic scoring criteria will serve as a basis for obtaining accurate MHE incidence and formulating diagnosis and treatment strategies in cirrhotic populations.

Objective:To investigate the diagnostic accuracy of serological indicators and evaluate the diagnostic value of a new established combined serological model on identifying the minimal hepatic encephalopathy (MHE) in patients with compensated cirrhosis.Methods:This prospective multicenter study enrolled 263 compensated cirrhotic patients from 23 hospitals in 15 provinces, autonomous regions and municipalities of China between October 2021 and August 2022. Clinical data and laboratory test results were collected, and the model for end-stage liver disease (MELD) score was calculated. Ammonia level was corrected to the upper limit of normal (AMM-ULN) by the baseline blood ammonia measurements/upper limit of the normal reference value. MHE was diagnosed by combined abnormal number connection test-A and abnormal digit symbol test as suggested by Guidelines on the management of hepatic encephalopathy in cirrhosis. The patients were randomly divided (7∶3) into training set ( n=185) and validation set ( n=78) based on caret package of R language. Logistic regression was used to establish a combined model of MHE diagnosis. The diagnostic performance was evaluated by the area under the curve (AUC) of receiver operating characteristic curve, Hosmer-Lemeshow test and calibration curve. The internal verification was carried out by the Bootstrap method ( n=200). AUC comparisons were achieved using the Delong test. Results:In the training set, prevalence of MHE was 37.8% (70/185). There were statistically significant differences in AMM-ULN, albumin, platelet, alkaline phosphatase, international normalized ratio, MELD score and education between non-MHE group and MHE group (all P<0.05). Multivariate Logistic regression analysis showed that AMM-ULN [odds ratio ( OR)=1.78, 95% confidence interval ( CI) 1.05-3.14, P=0.038] and MELD score ( OR=1.11, 95% CI 1.04-1.20, P=0.002) were independent risk factors for MHE, and the AUC for predicting MHE were 0.663, 0.625, respectively. Compared with the use of blood AMM-ULN and MELD score alone, the AUC of the combined model of AMM-ULN, MELD score and education exhibited better predictive performance in determining the presence of MHE was 0.755, the specificity and sensitivity was 85.2% and 55.7%, respectively. Hosmer-Lemeshow test and calibration curve showed that the model had good calibration ( P=0.733). The AUC for internal validation of the combined model for diagnosing MHE was 0.752. In the validation set, the AUC of the combined model for diagnosing MHE was 0.794, and Hosmer-Lemeshow test showed good calibration ( P=0.841). Conclusion:Use of the combined model including AMM-ULN, MELD score and education could improve the predictive efficiency of MHE among patients with compensated cirrhosis.