Chronic liver diseases are a group of diseases in which the liver is subjected to a variety of injuries over a long period of time， resulting in irreversible pathological changes that last longer than 6 months. Emodin （EMO） is a natural anthraquinone derivative derived from Rheum officinale， and its pharmacological effect has been extensively studied， exhibiting a variety of biological properties and involving multiple signaling molecules and pathways. Western medicine or surgical treatment is currently the main treatment regimen for chronic liver diseases， and the advance in treatment is limited by various reasons such as side effects and high costs. Due to its natural origin and efficacy， EMO has unique advantages in the treatment of chronic liver diseases and has now become a research hotspot. This article summarizes the therapeutic effect of EMO on chronic liver diseases and its mechanism， in order to provide a certain scientific basis for the traditional Chinese medicine treatment of chronic liver diseases and the development of drugs in clinical practice.

Objective To investigate the relationship between serum glucagon-like peptide-1(GLP-1),monocyte chemoattractant protein-1(MCP-1),insulin-like growth factor binding protein-3(IGFBP-3)and glycolipid metabolism,bone metabolism and microvascular complications(MC)in children with type 1 diabe-tes mellitus(T1DM).Methods A total of 211 children with T1DM(T1DM group)admitted to Handan Cen-tral Hospital,Xingtai Traditional Chinese Medicine Hospital,Baoding First Central Hospital and Handan Ma-ternal and Child Health Hospital from January 2021 to February 2023 were selected,patients were divided into MC group(63 cases)and non-MC group(148 cases)according to whether MC was complicated within 1 year,and 108 healthy children who underwent physical examination during the same period were selected as control group.The levels of serum GLP-1,MCP-1,IGFBP-3 and glucose and lipid metabolism indexes[fasting plasma glucose(FPG),fasting insulin(FINS),glycosylated hemoglobin(HbA1c),homeostasis model assessment of insulin resistance(HOMA-IR),total cholesterol(TC),triglyceride(TG),high density lipoprotein cholesterol(HDL-C),low density lipoprotein cholesterol(LDL-C)]and bone metabolism indexes[bone specific alkaline phosphatase(BALP),osteocalcin(OST),type I collagen cross-linked C-terminal peptide(CTX)]were detec-ted.The correlation between serum GLP-1,MCP-1,IGFBP-3 and glucose and lipid metabolism,bone metabo-lism in children with T1DM were analyzed by Pearson and Spearman correlation coefficient.Taking MC in children with T1DM as the dependent variable,the influencing factors were determined by multivariate uncon-ditional Logistic regression model,and the predictive value of serum GLP-1,MCP-1 and IGFBP-3 for MC were analyzed by receiver operating characteristic curve.Results The levels of serum GLP-1,FINS,HDL-C,BALP,OST and CTX in the T1DM group were lower than those in the control group,while the levels of MCP-1,IGFBP-3,FPG,HbA1c,HOMA-IR,TG and LDL-C in the T1DM group were higher than those in the control group,the differences were statistically significant(P<0.05).Serum GLP-1 in children with T1DM was negatively correlated with FPG,HbA1c,HOMA-IR,TG and LDL-C,and positively correlated with FINS,HDL-C,BALP,OST and CTX(P<0.05).MCP-1 and IGFBP-3 were positively correlated with FPG,HbA1c,HOMA-IR,TG and LDL-C,and negatively correlated with FINS,HDL-C,BALP,OST and CTX(P<0.05).Follow-up for 1 year,the incidence of MC in 211 children with T1DM was 29.86%(63/211).Elevated HbA1c,HOMA-IR,LDL-C,MCP-1 and IGFBP-3 were independent risk factors for MC in children with T1DM,and elevated GLP-1 was an independent protective factor(P<0.05).The area under the curve of ser-um GLP-1,MCP-1 and IGFBP-3 combined to predict MC in children with T1DM was 0.919,which was grea-ter than 0.781,0.788 and 0.794 predicted by serum GLP-1,MCP-1 and IGFBP-3 alone(P<0.05).Conclu-sion The decrease of serum GLP-1 level and the increase of MCP-1 and IGFBP-3 levels are related to glyco-lipid metabolism,bone metabolism disorder and MC in children with T1DM,the combined application of ser-um GLP-1,MCP-1 and IGFBP-3 has a good predictive value for MC in children with T1DM.

Objective:To explore the intervention effects of the "four-steps tendon resetting and collaterals dredging manipulation" on the symptoms and muscle status of calf muscle group of patients with chronic ankle sprains.Methods:This study was a prospective self-controlled clinical trial. A total of 39 patients with chronic ankle sprains who sought treatment at the basic units from April to September 2023 and Rehabilitation Medicine Center of Characteristic Medical Center of PLA Rocket Force from February to October 2023 were recruited. The "four-steps tendon resetting and collaterals dredging manipulation" was employed for treatment, with two sessions conducted per patient and one session per week. Pain levels were assessed using the Visual Analog Scale (VAS), ankle joint function was evaluated using the Ankle Osteoarthritis Scale and Function Assessment (AOFAS) score, and MyotonPRO digital palpation instrument was used to measure bilateral triceps and peroneal longus muscles and evaluate muscle status.Results:Compared with before treatment, VAS scores decreased ( t values were 5.85, 5.97, respecively, P<0.001) and AOFAS scores increased ( Z values were -4.59, -4.68, respecively, P<0.001). Before the first treatment and after the second treatment, the damping vibration frequency (Freq) of the affected and healthy triceps and peroneal muscles increased ( t values were -3.09,-2.92,-2.97,-2.28, respecively, P<0.05), the muscle stiffness (Stiff) increased ( t values were -3.12, -2.99, -2.88, -2.15, respecively, P<0.05), and the logarithmic attenuation value (Decr) of the damping vibration of the healthy calf triceps muscle decreased ( t=-2.31, P<0.05); Compared before and after the first treatment, the Decr value ( t=-2.51, P<0.05) and Stiff value ( t=-2.05, P<0.05) of the affected fibular longus muscle increased, while the Ferq, Decr, and Stiff values of the healthy calf triceps muscle increased before and after treatment ( t values were -2.92, -2.13, -2.64, respecively, P<0.05); before and after the second treatment, the Freq values of the triceps and peroneal longus muscles on the affected and healthy sides increased ( t values were -4.28, -2.67, -2.69, -2.38, respecively, P<0.05) and Stiff values increased ( t values were -4.24, -3.43, -3.87, -2.33, respecively, P<0.05); there was no statistical significance in Ferq, Decr, and Stiff values between the affected and healthy sides before and after the first and second treatments ( P>0.05). Conclusion:The "four-steps tendon resetting and collaterals dredging manipulation" can improve the symptoms of chronic ankle sprains and significantly change the muscle condition of the affected and healthy sides of the calf. The mechanism may be related to the neuromuscular control mechanism.

New quality productive forces with innovation and efficient utilization of resources as its core,is a new engine driving the innovative development of the national healthcare system.Healthcare big data has become the core motivity of the new quality productive forces,with the rapid development of industrial technologies including data governance and cloud storage,digital intelligence technology,and artificial intelligence,etc.From the perspective of new quality productive forces,it expounds on how to drive the innovative development of health economics and pharmacoeconomics research based on big data,including aspects of developing the innovative instruments for health outcome measurement,building the innovative frameworks of value assessment for innovative medications,and enhancing the precise evidence of healthcare policy evaluation.It describes how to use Healthcare big data as a driver to promote the innovative development of scientific research in related fields,and give full play to the role of economics evidence generation and decision-making support,so as to promote health care decision-making and optimal allocation of resources towards a new stage of improving quality and efficiency.

New quality productive forces with innovation and efficient utilization of resources as its core,is a new engine driving the innovative development of the national healthcare system.Healthcare big data has become the core motivity of the new quality productive forces,with the rapid development of industrial technologies including data governance and cloud storage,digital intelligence technology,and artificial intelligence,etc.From the perspective of new quality productive forces,it expounds on how to drive the innovative development of health economics and pharmacoeconomics research based on big data,including aspects of developing the innovative instruments for health outcome measurement,building the innovative frameworks of value assessment for innovative medications,and enhancing the precise evidence of healthcare policy evaluation.It describes how to use Healthcare big data as a driver to promote the innovative development of scientific research in related fields,and give full play to the role of economics evidence generation and decision-making support,so as to promote health care decision-making and optimal allocation of resources towards a new stage of improving quality and efficiency.

New quality productive forces with innovation and efficient utilization of resources as its core,is a new engine driving the innovative development of the national healthcare system.Healthcare big data has become the core motivity of the new quality productive forces,with the rapid development of industrial technologies including data governance and cloud storage,digital intelligence technology,and artificial intelligence,etc.From the perspective of new quality productive forces,it expounds on how to drive the innovative development of health economics and pharmacoeconomics research based on big data,including aspects of developing the innovative instruments for health outcome measurement,building the innovative frameworks of value assessment for innovative medications,and enhancing the precise evidence of healthcare policy evaluation.It describes how to use Healthcare big data as a driver to promote the innovative development of scientific research in related fields,and give full play to the role of economics evidence generation and decision-making support,so as to promote health care decision-making and optimal allocation of resources towards a new stage of improving quality and efficiency.

New quality productive forces with innovation and efficient utilization of resources as its core,is a new engine driving the innovative development of the national healthcare system.Healthcare big data has become the core motivity of the new quality productive forces,with the rapid development of industrial technologies including data governance and cloud storage,digital intelligence technology,and artificial intelligence,etc.From the perspective of new quality productive forces,it expounds on how to drive the innovative development of health economics and pharmacoeconomics research based on big data,including aspects of developing the innovative instruments for health outcome measurement,building the innovative frameworks of value assessment for innovative medications,and enhancing the precise evidence of healthcare policy evaluation.It describes how to use Healthcare big data as a driver to promote the innovative development of scientific research in related fields,and give full play to the role of economics evidence generation and decision-making support,so as to promote health care decision-making and optimal allocation of resources towards a new stage of improving quality and efficiency.

New quality productive forces with innovation and efficient utilization of resources as its core,is a new engine driving the innovative development of the national healthcare system.Healthcare big data has become the core motivity of the new quality productive forces,with the rapid development of industrial technologies including data governance and cloud storage,digital intelligence technology,and artificial intelligence,etc.From the perspective of new quality productive forces,it expounds on how to drive the innovative development of health economics and pharmacoeconomics research based on big data,including aspects of developing the innovative instruments for health outcome measurement,building the innovative frameworks of value assessment for innovative medications,and enhancing the precise evidence of healthcare policy evaluation.It describes how to use Healthcare big data as a driver to promote the innovative development of scientific research in related fields,and give full play to the role of economics evidence generation and decision-making support,so as to promote health care decision-making and optimal allocation of resources towards a new stage of improving quality and efficiency.

New quality productive forces with innovation and efficient utilization of resources as its core,is a new engine driving the innovative development of the national healthcare system.Healthcare big data has become the core motivity of the new quality productive forces,with the rapid development of industrial technologies including data governance and cloud storage,digital intelligence technology,and artificial intelligence,etc.From the perspective of new quality productive forces,it expounds on how to drive the innovative development of health economics and pharmacoeconomics research based on big data,including aspects of developing the innovative instruments for health outcome measurement,building the innovative frameworks of value assessment for innovative medications,and enhancing the precise evidence of healthcare policy evaluation.It describes how to use Healthcare big data as a driver to promote the innovative development of scientific research in related fields,and give full play to the role of economics evidence generation and decision-making support,so as to promote health care decision-making and optimal allocation of resources towards a new stage of improving quality and efficiency.

New quality productive forces with innovation and efficient utilization of resources as its core,is a new engine driving the innovative development of the national healthcare system.Healthcare big data has become the core motivity of the new quality productive forces,with the rapid development of industrial technologies including data governance and cloud storage,digital intelligence technology,and artificial intelligence,etc.From the perspective of new quality productive forces,it expounds on how to drive the innovative development of health economics and pharmacoeconomics research based on big data,including aspects of developing the innovative instruments for health outcome measurement,building the innovative frameworks of value assessment for innovative medications,and enhancing the precise evidence of healthcare policy evaluation.It describes how to use Healthcare big data as a driver to promote the innovative development of scientific research in related fields,and give full play to the role of economics evidence generation and decision-making support,so as to promote health care decision-making and optimal allocation of resources towards a new stage of improving quality and efficiency.