ObjectiveTo construct and evaluate various machine learning models for predicting the risk of chronic obstructive pulmonary disease （COPD） in individuals， thereby providing data support for early screening and intervention. MethodsA total of 823 subjects were selected for this study， comprising 142 individuals in the high-risk group for COPD and 681 individuals in the low-risk group. Data collected included demographic characteristics， smoking history， symptoms （such as cough and shortness of breath）， and scores from the Chronic obstructive pulmonary disease screening questionnaire. Four machine learning algorithms—Logistic regression， random forest， support vector machine， and XGBoost—were utilized to construct risk prediction models. The performance of these models was assessed using 5-fold cross-validation， with evaluation metrics including accuracy， precision， recall， F1-score， area under the receiver operating characteristic curve （AUC）， and average precision （AP）. Furthermore， a feature importance analysis was performed. ResultsThe Logistic Regression model exhibited superior performance， achieving an AUC of 0.982 and an AP of 0.939. This was closely followed by the Random Forest model， which recorded an AUC of 0.975 and an AP of 0.890. Feature importance analysis revealed that smoking history， symptoms of shortness of breath， and body weight were significant predictors. All models demonstrated robust performance in identifying low-risk populations； however， variations were observed in their efficacy in identifying high-risk populations. ConclusionMachine learning models have proven effective in identifying individuals at high risk for COPD. Among these， the Logistic regression model exhibits the best overall performance， efficiently identifying high-risk populations and serving as a valuable clinical auxiliary screening tool. Various models， each with distinct performance characteristics， are suited to different clinical screening scenarios， thereby offering targeted decision-making support for the establishment of a hierarchical and intelligent COPD screening pathway.

Qingzao Jiufeitang is a famous classical formula for treating lung injury caused by warm and dryness， included in the Catalogue of Ancient Famous Classical Formulas（The First Batch）. By systematically organizing ancient and modern literature on this formula， this study analyzed and verified the origin， medicinal composition， original plants and processing， dosage and decoction method， efficacy and application of this formula. According to the research， Qingzao Jiufeitang was first recorded in Yimen Falyu in the Qing dynasty， and its creation was mainly inspired by the Ming dynasty physician MIAO Xiyong's idea of the moisturizing drugs with sweet flavour and cold nature. Based on the 2020 edition of the Pharmacopoeia of the People's Republic of China（hereinafter referred to as the Chinese Pharmacopoeia） and the textual research results of modern scholars on traditional Chinese herbal medicines， the botanical sources and processing methods of the herbs in this formula are basically clarified. Among them， Mori Folium， Gypsum Fibrosum， Ginseng Radix et Rhizoma， Sesami Semen Nigrum， Asini Corii Colla， Ophiopogonis Radix and Eriobotryae Folium are consistent with the 2020 edition of the Chinese Pharmacopoeia. The primary source of Glycyrrhizae Radix et Rhizoma is the dried roots and rhizomes of Glycyrrhiza uralensis， family Leguminosae， while the primary source of Armeniacae Semen Amarum is the dried mature seeds of Prunus armeniaca， family Rosaceae. It is recommended to use Gypsum Ustum， stir-fried Sesami Semen Nigrum， stir-fried Armeniacae Semen Amarum， Asini Corii Colla bead， and honey-fried Eriobotryae Folium， and the rest of the raw products. According to the conversion of ancient and modern doses， the recommended dosages are 11.19 g for Mori Folium， 9.33 g for Gypsum Fibrosum， 3.73 g for Glycyrrhizae Radix et Rhizoma， 2.61 g for Ginseng Radix et Rhizoma， 3.73 g for Sesami Semen Nigrum， 4.48 g for Ophiopogonis Radix， 2.61 g for Armeniacae Semen Amarum， 3.73 g for Eriobotryae Folium. The decoction method is to add 300 mL of water， decoct it down to 180 mL， remove the residue， and then add 2.98 g of Asini Corii Colla into the decoction. Take it warm after meals， two to three times a day. Qingzao Jiufeitang has the effects of clearing dryness and moistening the lungs， nourishing Yin and invigorating Qi. In ancient times， it was mainly used to treat stagnation and depression of various Qi， as well as paralysis， asthma and vomiting. In modern clinical practice， it is mostly used to treat diseases in respiratory system， otolaryngology， skin system and digestive system caused by warm-dry impairing lung， deficiency of both Qi and Yin. The above research results can provide a reference for the later development of Qingzao Jiufeitang.

ObjectiveTo observe the effect of Xiaoke drink on insulin resistance in ob/ob mice and explore the mechanism. MethodEighteen ob/ob mice were randomly assigned into model， Xiaoke drink （17.68 g·kg^-1）， and atorvastatin （0.01 g·kg^-1） groups （n=6）， and six C57BL/6 mice were selected as the normal group. Mice in the normal and model groups were administrated with the same amount of distilled water. Fasting body weight， weekly food intake， and weekly water intake were measured at a fixed time. Fasting plasma glucose （FPG） and 2-hour post-load plasma glucose （2 hPG） were measured before and after 8-week intervention. After intervention， total cholesterol （TC）， triglyceride （TG）， fasting insulin （FINS）， Homeostasis Model Assessment-Insulin Resistance （HOMA-IR）， blood routine， and alkaline phosphatase （ALP） were measured. Western blot was employed to determine the expression levels of ubiquitin-specific protease 20 （USP20） and 3-hydroxy-3-methylglutaryl coenzyme A reductase （HMGCR） in the liver. The pancreas was stained with hematoxylin-eosin for observation. ResultCompared with the model group， the Xiaoke drink group showed decreased body weight of ob/ob mice （P<0.05， P<0.01）， declined growth trend of body weight （P<0.05， P<0.01）， reduced weekly average water intake， lowered levels of FPG， 2 hPG， TC， and HOMA-IR （P<0.05， P<0.01）， and down-regulated expression level of USP20 in the liver （P<0.05）. HMGCR content was positively correlated with USP20 expression. In addition， Xiaoke drink promoted the recovery of islet tissue morphology and function in ob/ob mice. ConclusionXiaoke drink can ameliorate insulin resistance in ob/ob mice by inhibiting USP20/HMGCR expression， reversing cholesterol biosynthesis process， and reducing cholesterol level.

Objective To explore the clinical efficacy of multi-channel functional electrical stimulation cycling ergometer for children with spastic cerebral palsy. Methods A total of 60 children with rehabilitation treatment for spastic cerebral palsy in Outpatient Department were selected and randomly divided into observation group and control group, with 30 cases in each group. The control group received conventional rehabilitation treatments such as exercise therapy, occupational therapy and Chinese medicine massage, while the observation group received multi-channel functional electrical stimulation cycling ergometer training on the basis of the conventional rehabilitation treatments. Before treatment and 12 weeks after treatment, the Gross Motor Function Measure (GMFM-88), Peabody Developmental Measure Scale-Gross Motor (PDMS-GM), Berg Balance Scale (BBS), and Activities of Daily Living (ADL) were used to assess the gross motor function, balance function, and activities of daily living of the children in both groups. Results Before treatment, there were no significant differences in GMFM-88 (D area, E area score, and total score), PDMS-GM (posture score, mobility score, and manipulation score), BBS, and ADL scores between the two groups (P>0.05). After treatment, the GMFM-88 (D area, E area score and total score), PDMS-GM (posture score, mobility score and manipulation score), BBS and ADL scores in both groups improved significantly compared with those before treatment, and all the scores in the observation group were significantly better than those in the control group (P < 0.05). Conclusion Multi-channel functional electrical stimulation cycling ergometer can effectively improve the gross motor function, balance function, and activities of daily living of children with spastic cerebral palsy.

Background/Aims: To evaluate the causal correlation between complement components and non-viral liver diseases and their potential use as druggable targets. Methods: We conducted Mendelian randomization (MR) to assess the causal role of circulating complements in the risk of non-viral liver diseases. A complement-centric protein interaction network was constructed to explore biological functions and identify potential therapeutic options. Results: In the MR analysis, genetically predicted levels of complement C1q C chain (C1QC) were positively associated with the risk of autoimmune hepatitis (odds ratio 1.125, 95% confidence interval 1.018–1.244), while complement factor H-related protein 5 (CFHR5) was positively associated with the risk of primary sclerosing cholangitis (PSC;1.193, 1.048– 1.357). On the other hand, CFHR1 (0.621, 0.497–0.776) and CFHR2 (0.824, 0.703–0.965) were inversely associated with the risk of alcohol-related cirrhosis. There were also significant inverse associations between C8 gamma chain (C8G) and PSC (0.832, 0.707–0.979), as well as the risk of metabolic dysfunction-associated steatotic liver disease (1.167, 1.036–1.314). Additionally, C1S (0.111, 0.018–0.672), C7 (1.631, 1.190–2.236), and CFHR2 (1.279, 1.059–1.546) were significantly associated with the risk of hepatocellular carcinoma. Proteins from the complement regulatory networks and various liver diseaserelated proteins share common biological processes. Furthermore, potential therapeutic drugs for various liver diseases were identified through drug repurposing based on the complement regulatory network. Conclusions Our study suggests that certain complement components, including C1S, C1QC, CFHR1, CFHR2, CFHR5, C7, and C8G, might play a role in non-viral liver diseases and could be potential targets for drug development.