Traditional Chinese medicine （TCM） clinical trials face challenges such as low participant compliance， insufficient geographical coverage， and cost-effectiveness imbalances. Decentralized clinical trials （DCT）， enabled by digital technology for remote data collection and monitoring， offer a new direction for TCM clinical trial research. This article systematically reviews three novel clinical trial design models. Combining the holistic concept and indivi-dualized treatment characteristics of TCM， it analyzes the challenges currently faced in TCM DCT practice， including the digitization and standardization of TCM theory， data security， privacy protection and patient engagement difficu-lties， insufficient ethical review and regulatory system adaptation， inadequate personnel training， and a shortage of interdisciplinary talent. Addressing these challenges， the article proposes methodological recommendations for DCT implementation that align with the principles of TCM diagnosis and treatment. These recommendations include promoting the intelligentization and standardization of TCM practices， constructing a full-chain data security and privacy protection system， improving the ethical framework and clarifying regulatory responsibilities， and cultivating and building interdisciplinary talent and capabilities， which provide theoretical and technical references for establishing standardized DCT practices in TCM.

Traditional Chinese medicine （TCM） clinical trials face challenges such as low participant compliance， insufficient geographical coverage， and cost-effectiveness imbalances. Decentralized clinical trials （DCT）， enabled by digital technology for remote data collection and monitoring， offer a new direction for TCM clinical trial research. This article systematically reviews three novel clinical trial design models. Combining the holistic concept and indivi-dualized treatment characteristics of TCM， it analyzes the challenges currently faced in TCM DCT practice， including the digitization and standardization of TCM theory， data security， privacy protection and patient engagement difficu-lties， insufficient ethical review and regulatory system adaptation， inadequate personnel training， and a shortage of interdisciplinary talent. Addressing these challenges， the article proposes methodological recommendations for DCT implementation that align with the principles of TCM diagnosis and treatment. These recommendations include promoting the intelligentization and standardization of TCM practices， constructing a full-chain data security and privacy protection system， improving the ethical framework and clarifying regulatory responsibilities， and cultivating and building interdisciplinary talent and capabilities， which provide theoretical and technical references for establishing standardized DCT practices in TCM.

Implementation science (IS) aims to systematically analyze and address the real-world gaps from evidence to practice and the influencing factors of the context. It is necessary to carry out qualitative research to gather relevant implementation outcomes. Nevertheless, traditional qualitative analysis has issues such as consuming a great deal of time and energy, and it is unable to promptly provide the crucial data required for implementation science research. The Rapid Qualitative Analysis (RQA) method, through semi-structured interviews and the adoption of techniques such as immediate data condensation and matrix analysis, can effectively shorten the cycle of qualitative data collection and data processing. RQA can promptly identify social determinants of health such as structural barriers, facilitators, and the behavioral characteristics of target groups. It provides a real-time basis for public health decision-making, the interpretation of complex social phenomena, and the process and effectiveness evaluation of research projects. Although RQA is difficult to conduct in-depth theoretical analysis based on grounded theory, its efficiency and flexibility make it the preferred tool for large-scale and time-sensitive research. Thus, it has been widely applied in implementation science research. This paper sorts out the core concepts and commonly used technical methods of RQA, as well as the differences between RQA and traditional qualitative analysis. It also explores the applications of RQA in intervention optimization, process evaluation, and implementation outcome evaluation. By integrating specific cases, this paper clarifies its application value in the field of implementation science. In the future, it is advisable to explore the integration of RQA with technologies such as artificial intelligence and big data, in order to bridge the gap between the transformation of scientific research achievements into practice. Under circumstances of limited resources or tight time constraints, RQA can be used to efficiently conduct implementation science research, providing convenient and scientific methodological and technical support for accelerating evidence-based practice.

Objective To identify factors affecting and key environmental factors of the Oncomelania hupensis snail density in the Yangtze River Delta region using machine learning methods. Methods Administrative village-level O. hupensis snail survey data in the Yangtze River Delta (including Shanghai Municipality, Jiangsu Province, Zhejiang Province and Anhui Province) from 2011 to 2021 were retrieved from the Information Management System for Parasitic Disease Control of Chinese Center for Disease Control and Prevention. Environmental factor data were captured from the Google Earth Engine platform, including elevation, slope, terrain, normalized difference vegetation index (NDVI), vegetation type, soil type, total petroleum hydrocarbon (TPH), ammonium nitrogen, inorganic nitrogen, dissolved oxygen, pH of water, chemical oxygen demand (COD) and inorganic phosphorus, and climatic factor data in the study region were retrieved from the Copernicus Climate Data Store, including annual precipitation, aridity index and annual mean temperature (AMT). O. hupensis snail survey data in the Yangtze River Delta region from 2011 to 2021 were randomly divided into a training set (70%) and a test set (30%), and five machine learning models were selected for machine learning model construction and comparative analysis of the O. hupensis snail density using the software R 4.3.0, including random forest (RF), eXtreme gradient boosting (XGBoost), support vector machine (SVM), gradient boosting machine (GBM) and neural network (NN). The XGBoost model was employed to construct a predictive model for the O. hupensis snail density, and the impact of each environmental factor on O. hupensis snail distribution was quantified. The SHapley Additive exPlanations (SHAPs) values were calculated to estimate the average contribution of each variable to the model prediction, and the core environmental factors affecting the O. hupensis snail population density were screened. Results Among the five machine learning models, the XGBoost model exhibited the optimal comprehensive performance, with the coefficient of determination (R²) of 0.855, mean squared error (MSE) of 0.188, root mean squared error (RMSE) of 0.434 and mean absolute error (MAE) of 0.155, respectively. Analysis of factors affecting the O. hupensis snail density with the XGBoost model showed that among the 16 environmental factors, the top four high-impact factors ranked by SHAPs values included annual precipitation, elevation, aridity index and NDVI, with cumulative SHAPs contributions of 75%, which was higher than that of other environmental factors. If NDVI was higher than 0.6, the O. hupensis snail density increased with NDVI and peaked if NDVI was 0.8 (1.60 snails/0.1 m²). The O. hupensis snail density increased with elevation if the elevation ranged from 14 to 40 m, and slowly rose if the annual precipitation ranged from 900 to 1 300 mm, and then increased rapidly to the peak (1.52 snails/0.1 m²) if the annual precipitation ranged from 1 300 to 1 500 mm. In addition, the O. hupensis snail density increased rapidly to the maximum (1.60 snails/0.1 m²) if the aridity index ranged from 0.8 to 1.1, and decreased gradually if the aridity index exceeded 1.1. Conclusions The XGBoost model shows excellent performance in prediction of the O. hupensis snail density and identification of key environmental factors in the Yangtze River Delta region. Annual precipitation, elevation, aridity index and NDVI are key environmental factors affecting the distribution and density of O. hupensis snails in the Yangtze River Delta region.

To understand the progress of, summarize experiences from, and analyze problems in the national schistosomiasis elimination programme, this article presented the national schistosomiasis epidemiology and surveillance in the People’s Republic of China in 2025. By the end of 2025, Shanghai Municipality, Zhejiang Province, Fujian Province, Guangdong Province and Guangxi Zhuang Autonomous Region maintained the achievement of schistosomiasis elimination, and 7 provinces of Jiangsu, Sichuan, Yunnan, Hubei, Hunan, Anhui and Jiangxi remained at the criteria of schistosomiasis transmission interruption. In 2025, there were 450 counties (cities, districts), 3 203 townships and 26 029 villages endemic for schistosomiasis in China, with a total population of 73.598 million in endemic villages. Among the 450 endemic counties (cities, districts), 421 (93.56%) achieved the criteria of schistosomiasis elimination and 29 (6.44%) reached the criteria of transmission interruption. In 2025, a total of 3 630 874 residents received immunological tests for schistosomiasis across endemic areas in China, with 31 588 seropositives identified (seroprevalence, 0.87%), and a total of 154 293 individuals received parasitological examinations, with 5 egg-positives detected. A total of 26 688 advanced schistosomiasis cases were recorded in China by the end of 2025. Of 529 683 bovines raised in schistosomiasis-endemic villages in China in 2025, 101 637 bovines received immunological tests for schistosomiasis, with 183 seropositives detected (seroprevalence, 0.18%), and 165 654 bovines received parasitological examinations, with no egg-positives identified. In 2025, Oncomelania hupensis snail survey was performed covering an area of 667 524.82 hm² in China, and 176 378.64 hm² O. hupensis snail habitats were identified, including 123.77 hm² emerging O. hupensis snail habitats and 953.71 hm² re-emerging O. hupensis snail habitats. A total of 19 283 schistosomiasis cases received chemotherapy with praziquantel in China in 2025, and 477 450 person-times and 304 279 herd-times received expanded chemotherapy, respectively. In addition, O. hupensis snail control with chemical treatment covered 116 475.10 hm² snail habitats across China in 2025, with an actual area with chemical control covering 68 510.93 hm² and an area with environmental improvements covering 1 101.84 hm². The national schistosomiasis surveillance results indicated that the mean prevalence of Schistosoma japonicum infections was both 0 among humans and bovines in 2025, and no S. japonicum infection was detected in O. hupensis snails. These data showed that the prevalence of schistosomiasis remained low in China in 2025; however, the area of O. hupensis snail habitats stayed high, with an increase in emerging and reemerging O. hupensis snail habitats. It is recommended to improve the surveillance and forecast mechanism for schistosomiasis and precisely implement the O. hupensis snail control programme in high-risk areas.

Allergic conjunctivitis is a common ocular inflammatory disease, with intense itching being the most typical and distressing symptom for patients. In recent years, with the in-depth study of the interaction between the nervous and immune systems, significant progress has been made in understanding the mechanism of itching in allergic conjunctivitis. This review elaborates on the neurobiological basis of itching in allergic conjunctivitis, with a focus on the complex dialogue between immune cells and sensory neurons, particularly the core role of the IL-33-ST2-CGRP signaling axis in mediating itching. Additionally, this article introduces new findings in genetic susceptibility research, including the identification of susceptibility genes for allergic conjunctivitis through transcriptome-wide association studies. The sensory nervous system not only transmits itch signals but also actively participates in the formation of antigen channels related to conjunctival goblet cells, thereby regulating the local uptake of allergens and the initiation of the immune response. Moreover, targeted novel therapeutic strategies offer hope for patients with refractory allergic conjunctivitis. Exploring the molecular and cellular mechanisms of itching in allergic conjunctivitis will provide a theoretical basis for the development of more effective treatment methods.

Objective: To investigate the health literacy level and its influencing factors among the elderly in Shunyi District, Beijing Municipality, so as to provide the evidence for developing health literacy intervention measures and improving the elderly's health literacy level. Methods: From September to November 2024, permanent residents aged ≥60 years in Shunyi District were selected by a multi-stage random sampling method combined with probability proportionate to size sampling method. The Chinese Elderly Health Literacy Questionnaire was used to conduct face-to-face surveys on basic information, health status, and health literacy. The health literacy level of the elderly was analyzed. Multivariable logistic regression model and decision tree model were used to analyze the influencing factors for health literacy level of the elderly. Results: There were 285 males (47.50%) and 315 females (52.50%). The mean age was (68.91±7.38) years. The health literacy level of the elderly was 14.33%. The literacy levels of basic concepts, basic knowledge, and basic skills were 43.33%, 5.33%, and 50.83%, respectively. The literacy levels of scientific aging concept, intrinsic capacity and geriatric syndromes, healthy lifestyle, information acquisition and self-care, health service utilization and chronic disease management, and safety and first aid were 52.33%, 7.17%, 51.83%, 58.83%, 72.00%, and 4.33%, respectively. Multivariable logistic regression analysis showed that educational level (high school/technical secondary school/technical school and above, OR=2.376, 95%CI: 1.020-5.532), monthly household income per capita (1 000-<3 500 yuan, OR=2.973, 95%CI: 1.349-6.555), residence (urban, OR=3.836, 95%CI: 2.071-7.105), and health attention (relatively concerned, OR=4.164, 95%CI: 1.779-9.742) were influencing factors for health literacy level of the elderly. Decision tree model results showed that educational level, monthly household income per capita, residence, and health attention were influencing factors for health literacy level of the elderly, with residence being the main influencing factor. Elderly people living in urban areas, relatively concerned about health, and with high school/technical secondary school/technical school and above educational level had higher health literacy level (40.00%). Conclusions The health literacy level of the elderly in Shunyi District is mainly affected by educational level, monthly household income per capita, residence, and health attention. It is recommended to focus on rural elderly with lower educational level, monthly household income per capita, and health attention.

Objective:To investigate the trends in insulin resistance, as represented by the triglyceride-glucose index (TyG index), among Chinese adult residents from 2010 to 2018 and to explore influencing factors.Methods:China Chronic Disease and Risk Factor Surveillance was conducted in 2010, 2013, and 2018, using a multi-stage stratified cluster random sampling method across all 31 provinces (autonomous regions and municipalities) in China. This study sampled 98 712 adults in 2010, 176 534 adults in 2013, and 184 876 adults in 2018, all aged ≥18 years, totaling 406 933 participants. Individuals with a TyG index > P75 were classified as having insulin resistance. The mean TyG index and the prevalence of insulin resistance were calculated for different years, sexes, age groups, provinces (autonomous regions and municipalities), and subgroups for 2018. Linear and logistic regression models were used to test trends in means and rates over time, and multivariate logistic regression models were conducted to analyze potential factors associated with insulin resistance. All analyses were adjusted for complex sampling weights based on the study design. Results:From 2010 to 2018, the mean TyG index among Chinese adults increased from 8.44±0.63 to 8.70±0.64, with significant upward trends observed across different age groups, sexes, and urban-rural residencies (all P<0.001). The mean TyG index was higher among males, urban residents, and those aged 45-59. There were significant differences in the mean TyG indices and prevalence of insulin resistance across provinces (autonomous regions and municipalities) (all P<0.05). Higher insulin resistance prevalence was independently associated with being male, aged ≥45 years, living in urban areas, excessive alcohol consumption, and insufficient physical activity (all P<0.05). Conclusions:From 2010 to 2018, the level of insulin resistance, as indicated by the TyG index, showed an increasing trend among Chinese adults. Males, individuals aged ≥45 years, urban residents, and individuals with unhealthy lifestyles such as excessive alcohol consumption or insufficient physical activity should be the focus of efforts to prevent and control metabolic diseases related to insulin resistance.

Objective:To understand the prevalence and related factors of three common chronic diseases, hyperlipidemia, hypertension and diabetes in HIV-infected persons.Methods:As of December 2023, HIV-infected persons >15 years old who are receiving antiviral therapy (ART) and follow-up in Henan Province were selected as the study objects. Questionnaires, physical examinations, and blood samples were collected to collect demographic information, ART, body weight, blood lipids, blood pressure, and blood sugar of HIV-infected persons. The logistic regression model was used to analyze the related factors of hyperlipidemia, hypertension and diabetes.Results:Among 4 023 HIV-infected patients, the prevalence rates of hyperlipidemia, hypertension, and diabetes were 64.47% (2 594/4 023), 16.80% (676/4 023), and 10.54% (424/4 023), respectively. Multivariate analysis showed that hyperlipidemia was positively associated with ≥40 years of age, overweight and obesity, two nucleoside reverse transcriptase inhibitors (NRTIs) + proteasome inhibitors (PIs) regimen and two NRTIs+ integrase inhibitor regimen, and negatively associated with low body weight. Hypertension was positively correlated with the age group ≥40 years old, family history of cardiovascular and cerebrovascular diseases, overweight and obesity, ART time ≥0.5 years, and negatively correlated with low body weight. Diabetes was positively associated with age group ≥40 years, family history of cardiovascular and cerebrovascular disease, overweight and obesity, and negatively associated with the use of two NRTIs+PIs treatment regimens.Conclusions:In 2023, the prevalence of hyperlipidemia, hypertension, and diabetes among HIV-infected people in Henan Province was relatively high, and the risk of common chronic diseases among those ≥40 years old, overweight and obese, and those with a family history of cardiovascular and cerebrovascular diseases was also relatively high. It is recommended to strengthen the prevention and management of common chronic diseases among HIV-infected people.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.