The repair of bone defects is heavily influenced by the dynamic osteogenic microenvironment. Static scaffolds constructed by traditional 3D printing technology cannot simulate the dynamic nature of the microenvironment during bone defect repair due to the fixed structure, uncontrollable release of active factors, and difficult regeneration of blood vessels, among other factors. Breaking through the limitations of these static scaffolds and realizing the intelligent and dynamic regulation of the osteogenic microenvironment is a key scientific issue in the field of bone tissue engineering. 4D printing technology combines the dynamic responsiveness of bone restoration materials with the concept of intelligent design to regulate the micro and macro structure of scaffolds. This technology provides a new method for bone tissue engineering by responding to endogenous and exogenous stimuli and creating a better osteogenic microenvironment through functionalized design, including drug delivery and antibacterial function. However, this technology currently suffers from challenges related to dynamic response material design, insufficient precision of printing technology, and mismatches between multi-stimulus response systems, metabolic rhythms of bone tissue, and functionalized composite scaffolds. Future research should focus on the development of smart response materials with excellent dynamic responses and bioactivity, the creation of new printing technologies, and the design of personalized and precise bone repair solutions. The aim of this paper is to review the current research status of 4D printing for bone tissue engineering in terms of material types, response mechanisms, and applications to provide a theoretical basis for the development and clinical application of functional bone repair materials in the future.

ObjectiveTo evaluate the public health governance capacity in Jiangsu Province and provide an optimized pathway for the construction of a “strong, rich, beautiful, and high-quality” new Jiangsu. MethodsA total of 806 policy documents, 658 public information reports, and 148 research literatures related to public health governance capacity in Jiangsu Province from January 1995 to December 2023 were collected. The status of current public health goverance was assessed based on the evaluation criteria suitable for public health systems, and the strengths and the weaknesses of the system were identified. ResultsThe public health governance capability of Jiangsu Province was scored at 738.3 points, ranking 3rd nationally. Maternal health care and emergency response capacities achieved leading positions nationwide, both ranking 2nd. Jiangsu had exhibited a standardized guidance in the strategic level, a well-established management mechanism, an extensive coverage in information collection, and a scientifically established health targets setting. However, bottlenecks remained, including an unclear division of responsibilities across organizational departments, an insufficient public-health workforce, the absence of a stable growth mechanism for government funding investment, and difficulties in promptly identifying public needs. ConclusionJiangsu’s public-health system demonstrates leading nationally, yet several components remain underdeveloped. Future efforts should consolidate advantages while addressing weaknesses, further diversify content and forms, establish a stable funding increase mechanism, and clarify departmental functions, thereby providing solid health support for realizing the developmental goals of a “strong, rich, beautiful and high-quality” new Jiangsu.

The digitization of traditional Chinese medicine (TCM) has generated vast amounts of data. However, these data are characterized by significant heterogeneity and complex semantic structures, posing substantial challenges for systematic integration and intelligent analysis, and limiting its potential for modern clinical and computational research. To address the challenges posed by the high heterogeneity and complex structure in TCM data, we designed and developed the TCM Data Hub platform, which is powered by the YiYuan large language models (LLMs). This platform aims to enhance intelligent data processing capabilities and unlock the potential for clinical application of TCM data through systematic integration and efficient utilization, thereby bridging the gap between traditional knowledge and modern computational research. This study first analyzed the heterogeneity and complexity of TCM information with respect to data types, structures, and semantics. A standardized data framework was constructed to enhance data integration and interoperability. Based on the TCM Intelligent Computing Platform of the China Academy of Chinese Medical Sciences, we trained the YiYuan LLMs to acquire domain-specific semantic understanding of TCM, thereby improving the platform’s comprehension of specialized terminology and knowledge systems. Leveraging the natural language processing capabilities of the LLMs, we developed a human-in-the-loop data processing system to enable efficient extraction, cleansing, and structured organization of TCM data. In addition, utilizing Vue and Java technologies, we developed multiple LLM-powered intelligent agents and systems, including a human-in-the-loop data processing system, as well as automated prescription mining and network pharmacology analysis agents. Task-specific agents tailored to TCM data processing were developed to enhance the model’s effectiveness in clinical knowledge discovery. System functionality and platform infrastructure were implemented using Java and Vue technologies.The TCM Data Hub platform has completed system construction and core functionality implementation. It supported integrated management and efficient access to 8 key types of TCM data: prescriptions, materia medica, ingredients, targets, diseases (Western medicine), diseases (TCM), syndromes, and therapeutic methods. The human-in-the-loop data processing system achieved an accuracy of 95.34% in structuring TCM data and supported annotation for data requiring manual labeling. The intelligent agent-driven big-data analytics module enabled 1-click, end-to-end workflows for TCM prescription mining, herb-syndrome association analysis, network pharmacology, and molecular biology research, completing a full data mining task in approximately 30 minutes. Users can interact with and manipulate data through a visual front-end interface. The system demonstrated stable performance, strong scalability, and a user-friendly experience. Empowered by the YiYuan LLMs, the TCM Data Hub platform significantly improves the accessibility, usability, and intelligence of TCM data. It effectively bridges traditional TCM knowledge with modern intelligent technologies, providing robust data support and intelligent tools for TCM research and clinical applications.

AIM: To analyze the relationship between obesity-related indicators, blood lipid levels and primary open angle glaucoma(POAG)and explore its risk factors. METHODS:Patients with POAG treated in the hospital from March 2022 to March 2024 were selected as the POAG group, and healthy people in the same period were selected as the non-POAG group. The obesity related indicators [body mass index(BMI), waist circumference, waist-to-hip ratio], blood lipid levels [serum total cholesterol(TC), triglyceride(TG), high-density lipoprotein(HDL-C), low-density lipoprotein(LDL-C)] and general clinical data of the two groups were compared. The binary Logistic regression analysis was used to analyze the risk factors affecting the occurrence of POAG, and the ROC curve was established to analyze the efficiency of various variables in predicting the occurrence of POAG.RESULTS:A total of 54 POAG patients and 54 non-POAG subjects were included. The POAG group had a mean age of 50.30±5.73 y(29 males, 25 females), and the non-POAG group had a mean age of 50.28±5.72 y(28 males, 26 females).The BMI, intraocular pressure, waist circumference, waist-to-hip ratio, and TG levels in the POAG group were higher than those in the non-POAG group, while the HDL-C level was lower than that in the non-POAG group(all P<0.001). High BMI, high waist circumference, high waist-to-hip ratio, and high TG were identified as risk factors for POAG(all P<0.05), whereas high HDL-C was a protective factor(P<0.05).The AUCs for BMI, waist circumference, waist-to-hip ratio, TG, HDL-C, and the combined prediction were 0.885, 0.873, 0.707, 0.777, 0.664, and 0.974, respectively; the sensitivities were 0.815, 0.833, 0.730, 0.637, 0.663, and 0.944, respectively; and the specificities were 0.852, 0.759, 0.711, 0.789, 0.752, and 0.889, respectively. These results indicate that the combined multi-index prediction had the best performance, with good sensitivity and specificity.CONCLUSION:Obesity-related indicators such as high BMI, high waist circumference, high waist-to-hip ratio, and dyslipidemia(high TG, low HDL-C)are associated risk factors for POAG. The combined multi-index prediction model including BMI, waist circumference, waist-to-hip ratio, TG, and HDL-C demonstrates the best performance in POAG risk assessment, with both high sensitivity and specificity, providing a scientific basis for early clinical screening and intervention.

Objective:To observe the pregnancy outcomes of patients with unexplained recurrent spontaneous abortion (URSA) after interventional treatment or expectant treatment.Methods:This prospective study followed up 398 patients with recurrent spontaneous abortion from March 2017 to September 2022 in seven hospitals. Among them, 267 patients were diagnosed with URSA, including 124 patients who were initially diagnosed in the interventional treatment hospital and 143 patients who were initially diagnosed in the expectant treatment hospital. All URSA patients were followed up for 33 months. Ongoing pregnancy rates were observed as main outcome indicators.Results:A total of 127 patients became pregnant, and 107 of them had sustained pregnancies, the ongoing pregnancy rate was 84.25% (107/127). The ongoing pregnancy rate was 86.11% (31/36) in the interventional treatment group and 83.52% (76/91) in the expectant treatment group, with no significant difference ( P>0.05). During the follow-up, the ongoing pregnancy rates in the interventional treatment hospital and the expectant treatment hospital were 75.71% (53/70) and 94.74% (54/57), respectively, with a significant difference ( P<0.05). The ongoing pregnancy rate after interventional treatment in the interventional treatment hospital was 82.76% (24/29), which was similar to the 94.00% (47/50) after expectant treatment in the expectant treatment hospital ( P>0.05). Conclusion:The ongoing pregnancy rate of interventional treatment for URSA patients has not been significantly improved, suggesting that it may not be necessary to carry out this treatment.

Objective:To observe the clinical efficacy of Chinese materia medica soaking therapy combined with cervical rotation-traction manipulation in the treatment of cervical spondylotic radiculopathy (CSR).Methods:A randomized controlled trial was conducted. Totally 84 CSR patients from the Orthopedics Department of Shunyi Hospital, Beijing Traditional Chinese Medicine Hospital from April 2023 to May 2024 were selected as the observation subjects. They were divided into two groups using a random number table method, with 42 patients in each group. The treatment for both groups lasted for 14 d. VAS scale was used to assess pain levels before and after treatment, OASTCSR was used to evaluate cervical function, and NDI was used to assess cervical functional status; adverse reactions during treatment were observed and recorded, and clinical efficacy was evaluated.Results:The total effective rate was 95.24% (40/42) in the treatment group and 80.95% (34/42) in the control group, with statistical significance ( χ2=4.36, P=0.029). After treatment, the VAS score (1.60±1.21 vs. 2.91±1.12, t=-1.89), the OASTCSR score (5.17±2.14 vs. 9.31±3.82, t=-11.57), and the NDI score (9.17±2.13 vs. 13.36±3.45, t=-10.82) in the treatment group were lower than those in the control group ( P<0.001 or P<0.05). During the treatment period, neither group experienced any adverse reactions. Conclusion:The combination of Chinese materia medica soaking therapy and cervical rotation-traction manipulation can significantly improve the clinical symptoms and quality of life of patients with CSR, and its efficacy is superior to the use of cervical rotation-traction manipulation alone.

Objective To analyze the research hotspots,frontiers,and trends in clinical randomized controlled trials(RCTs)on acupuncture-moxibustion for post-stroke shoulder-hand syndrome(SHS)over the past decade using bibliometric and knowledge mapping methods.Methods The clinical RCTs on acupuncture-moxibustion for post-stroke SHS from five Chinese and English databases were retrieved,including CNKI,Wanfang,VIP,PubMed,and Web of Science(WOS).CiteSpace and VOSviewer were employed for analysis,and visualized knowledge maps were generated.Results A total of 1 226 Chinese and 20 English articles were included,with both reaching publication peaks in 2021.The top three institutions in terms of output were Huguosi Traditional Chinese Medicine Hospital Affiliated to Beijing University of Chinese Medicine,The Second Affiliated Hospital of Heilongjiang University of Chinese Medicine,and Heilongjiang University of Chinese Medicine.The most prolific author was Song Fengjun,while Pei Jian had the highest centrality.The five most frequently used keywords were shoulder-hand syndrome,stroke,acupuncture-moxibustion,rehabilitation training,and joint mobility.Emerging research topics included activities of daily living,limb function,and range of motion.Conclusion Clinical research on acupuncture-moxibustion for post-stroke SHS holds significant developmental potential.Strengthening international collaboration to explore therapeutic mechanisms is recommended,and researchers should continue optimizing treatment protocols to enhance the quality of clinical evidence.

Cerebral small vessel disease represents a group of common vascular disorders involving pathological changes in arterioles,capillaries and venules,with microvascular investigation remaining a key challenge in stroke.With high signal-to-noise ratio and high contrast enabled by enhanced field strength,7T MRI can surpass the resolution limits of 3T MRI,revealing structural and functional abnormalities in cerebral small vessels below 400 μm,as well as detecting subtle lesions in brain tissue.This paper reviews the research progress of multimodal high-resolution imaging techniques based on 7T MRI,such as time-of-flight angiography,phase contrast imaging and susceptibility imaging,in the study of cerebral small vessel disease.Utilizing these technologies,7T MRI can clearly display the structure of cerebral small vessels,such as the lenticulostriate arteries and deep medullary veins,and measure functional parameters like flow velocity and susceptibility.Additionally,it can sensitively detect cerebral microbleeds and cortical cerebral microinfarct.These imaging data provide valuable information for detecting early features of cerebral small vessel disease and assessing its progression,offering new insights into its pathogenesis.Combined with artificial intelligence-based image analysis methods,7T MRI holds great promise for early diagnosis and progression evaluation in cerebral small vessel disease.

Objective:To observe the pregnancy outcomes of patients with unexplained recurrent spontaneous abortion (URSA) after interventional treatment or expectant treatment.Methods:This prospective study followed up 398 patients with recurrent spontaneous abortion from March 2017 to September 2022 in seven hospitals. Among them, 267 patients were diagnosed with URSA, including 124 patients who were initially diagnosed in the interventional treatment hospital and 143 patients who were initially diagnosed in the expectant treatment hospital. All URSA patients were followed up for 33 months. Ongoing pregnancy rates were observed as main outcome indicators.Results:A total of 127 patients became pregnant, and 107 of them had sustained pregnancies, the ongoing pregnancy rate was 84.25% (107/127). The ongoing pregnancy rate was 86.11% (31/36) in the interventional treatment group and 83.52% (76/91) in the expectant treatment group, with no significant difference ( P>0.05). During the follow-up, the ongoing pregnancy rates in the interventional treatment hospital and the expectant treatment hospital were 75.71% (53/70) and 94.74% (54/57), respectively, with a significant difference ( P<0.05). The ongoing pregnancy rate after interventional treatment in the interventional treatment hospital was 82.76% (24/29), which was similar to the 94.00% (47/50) after expectant treatment in the expectant treatment hospital ( P>0.05). Conclusion:The ongoing pregnancy rate of interventional treatment for URSA patients has not been significantly improved, suggesting that it may not be necessary to carry out this treatment.

Cerebral small vessel disease represents a group of common vascular disorders involving pathological changes in arterioles,capillaries and venules,with microvascular investigation remaining a key challenge in stroke.With high signal-to-noise ratio and high contrast enabled by enhanced field strength,7T MRI can surpass the resolution limits of 3T MRI,revealing structural and functional abnormalities in cerebral small vessels below 400 μm,as well as detecting subtle lesions in brain tissue.This paper reviews the research progress of multimodal high-resolution imaging techniques based on 7T MRI,such as time-of-flight angiography,phase contrast imaging and susceptibility imaging,in the study of cerebral small vessel disease.Utilizing these technologies,7T MRI can clearly display the structure of cerebral small vessels,such as the lenticulostriate arteries and deep medullary veins,and measure functional parameters like flow velocity and susceptibility.Additionally,it can sensitively detect cerebral microbleeds and cortical cerebral microinfarct.These imaging data provide valuable information for detecting early features of cerebral small vessel disease and assessing its progression,offering new insights into its pathogenesis.Combined with artificial intelligence-based image analysis methods,7T MRI holds great promise for early diagnosis and progression evaluation in cerebral small vessel disease.