Objective: To establish a prediction model for high-risk cardiovascular disease (CVD) among residents aged 35 to 75 years, so as to provide the basis for improving CVD prevention and control measures. Methods: Permanent residents aged 35 to 75 years were selected from Dongcheng District, Beijing Municipality using the stratified random sampling method from 2018 to 2023. Demographic information, lifestyle, waist circumference and blood biochemical indicators were collected through questionnaire surveys, physical examinations and laboratory tests. Influencing factors for high-risk CVD among residents aged 35 to 75 years were identified using a multivariable logistic regression model, and a prediction model for high-risk CVD was established. The predictive effect was evaluated using the receiver operating characteristic (ROC) curve. Results: A total of 6 968 individuals were surveyed, including 2 821 males (40.49%) and 4 147 females (59.51%), and had a mean age of (59.92±9.33) years. There were 1 155 high-risk CVD population, with a detection rate of 16.58%. Multivariable logistic regression analysis showed that gender, age, smoking, central obesity, systolic blood pressure, fasting blood glucose, triglyceride and low-density lipoprotein cholesterol were influencing factors for high-risk CVD among residents aged 35 to 75 years (all P<0.05). The area under the ROC curve of the established prediction model was 0.849 (95%CI: 0.834-0.863), with a sensitivity of 0.693 and a specificity of 0.863, indicating good discrimination. Conclusion The model constructed by eight factors including demographic characteristics, lifestyle and blood biochemical indicators has good predictive value for high-risk CVD among residents aged 35 to 75 years.

Objective To understand the current situation of nutrition literacy of primary and secondary school students in Shijingshan District of Beijing, and analyze its influencing factors, and to put forward targeted suggestions for improving the students’ nutrition literacy and promoting their healthy growth. Methods A multi-stage stratified cluster sampling method was used to select 2480 primary and secondary school students and their parents from 5 primary schools, 3 middle schools and 1 high school in Shijingshan District. The multivariate logistic regression model was used to analyze the factors influencing the attainment rate of nutrition literacy. Results The median score of nutrition literacy of 2480 primary and secondary school students from grades 1 to 12 was 77.86 (in hundred-mark system), the quartile range (IQR) was 16.96, and the attainment rate of nutrition literacy was 42.46%. The cognitive level (45.12%) was higher than the skill level (41.20%) among students from grades 3 to 12. In terms of skills, the attainment rate of food preparation was the lowest, at 30.38%. The scores of nutrition literacy of girls were higher than those of boys, and the scores of primary school students were higher than those of secondary school students. Students with different levels of caregiver’s education, family income, and family food environment had different scores of nutrition literacy, and the differences were statistically significant (P<0.05). Multivariate logistic regression analysis showed that the attainment rate of nutrition literacy was closely related to student’s gender and study stage, caregiver’s education level, and family food environment. Conclusion The nutrition literacy of primary and secondary school students in Shijingshan District still needs to be improved, especially in the aspect of skills. Targeted nutrition education should be carried out.

AIM: To explore the effects of preoperative anterior segment parameters on the rotational stability of Toric intraocular lens(Toric IOL).METHODS:Prospective study. A total of 41 cataract patients(54 eyes)with combined corneal regular astigmatism from March to December 2023 were included and treated with cataract phacoemulsification combined with plate loop Toric IOL implantation in the Department of Ophthalmology of the First Affiliated Hospital of Zhengzhou University. The rotation degree of Toric IOL and uncorrected distance visual acuity(UCDVA)were evaluated at 1 d, 2 wk, and 1 mo postoperatively, the corrected distance visual acuity(CDVA)was evaluated at 2 wk and 1 mo after surgery, and the decentration and tilt of the Toric IOL were assessed at 2 wk postoperatively.RESULTS:A total of 33 patients(40 eyes)were included in this study. The UCDVA(LogMAR)of 1 d, 2 wk and 1 mo postoperatively were 0.10(0.10, 0.30), 0.05(0, 0.10)and 0(0, 0.10), respectively, which was improved compared with the preoperative levels of [0.80(0.49, 1.00)](P<0.001). The CDVA(LogMAR)of 2 wk and 1 mo postoperatively were 0.05(0, 0.15)and 0(0, 0.138), respectively, which was improved compared with preoperative levels of [0.52(0.40, 0.80)](P<0.001). The residual astigmatism of 2 wk and 1 mo postoperatively were 0.625(0.25, 0.75)D and 0.50(0.25, 0.75)D, respectively, which was significantly reduced compared with preoperative astigmatism of [1.82(1.31, 2.59)D](P<0.001). The preoperative anterior segment length(ASL), and lens thickness(LT)were positively correlated with Toric IOL rotation degree at 1 d(rs=0.463, P=0.003; rs=0.340, P=0.032)and 2 wk(rs=0.520, P=0.001; rs=0.409, P=0.009)postoperatively. At 1 mo postoperatively, only ASL was positively correlated with Toric IOL rotation degree(rs=0.463, P=0.003). The results of linear regression analysis showed that preoperative ASL was a predictor of rotation degree at 1 d, 2 wk and 1 mo after surgery(F1 d=10.098, P1 d=0.003; F2 wk=16.915, P2 wk<0.001; F1 mo=10.957, P1 mo=0.002). The rotation degree of Toric IOL was positively correlated with lens decentration(rs=0.360, P=0.043).CONCLUSION:The early postoperative rotation of Toric IOL is positively correlated with ASL, and the rotation is also positively correlated with lens decentration.

ObjectiveTo analyze the impact of maternal postpartum depression (PPD) at 2 months postpartum on caregiving for infants aged2 to 24 months, and to provide a scientific basis for future maternal and infant healthcare services. MethodsBased on the Shanghai Maternal-Child Pairs Cohort, 1 060 mother-child pairs were selected from those fully participating in follow-up visits at 2, 6, 12, and 24 months postpartum. Pregnancy and childbirth-related information was collected using standardized questionnaire surveys and hospital obstetric and maternity records. The Edinburgh postpartum depression scale was used to assess the maternal postpartum depressive symptoms at 2 months postpartum. At 2, 6, 12, and 24 months postpartum, questionnaire survey was used to evaluate the maternal responsiveness in caregiving and the provision of early learning opportunities for infants. Scores for responsive caregiving and early learning opportunities at 2, 6, 12, and 24 months were grouped based on the 25th percentile (P₂₅) of total scores. The mixed-effects model was used to analyze the longitudinal impact of maternal postpartum depression at 2 months on the caregiving of 2 to 24-month-old infants. ResultsThe longitudinal results from the mixed-effects model did not show an impact of maternal PPD on infant responsive caregiving within 12 months and early learning opportunities within24 months. However, cross-sectional analysis revealed that, compared to the non-PPD group, the risk of low responsive caregiving at 2 months in the PPD group was 93% higher (OR=1.931, 95%CI: 1.113‒3.364, P=0.019). The risks for low provision of early learning opportunities at2 months and 24 months increased by 59% (OR=1.589, 95%CI: 1.082‒2.324, P=0.017) and 60% (OR=1.598, 95%CI:1.120‒2.279, P=0.010), respectively. ConclusionMaternal postpartum depression increases the risk of low responsive caregiving at 2 months, but its long-term effects warrant further research.

OBJECTIVE: To propose a machine learning-based method for predicting the trajectories during manual acupuncture manipulation (MAM), aiming to improve the precision and consistency of acupuncture practitioner' operation and provide the real-time suggestions on MAM error correction. METHODS: Computer vision technology was used to analyze the hand micromotion when holding needle during acupuncture, and provide a three-dimensional coordinate description method of the index finger joints of the holding hand. Focusing on the 4 typical motions of MAM, a machine learning-based MAM trajectory predictive model was designed. By integrating the changes of phalangeal joint angle and hand skeletal information of acupuncture practitioner, the motion trajectory of the index finger joint was predicted accurately. Besides, the roles of machine learning-based MAM trajectory predictive model in the skill transmission of acupuncture manipulation were verified by stratified randomized controlled trial. RESULTS: The performance of MAM trajectory predictive model, based on the long short-term memory network (LSTM), obtained the highest stability and precision, up to 98%. The learning effect was improved when the model applied to the skill transmission of acupuncture manipulation. CONCLUSION The machine learning-based MAM predictive model provides acupuncture practitioner with precise action prediction and feedback. It is valuable and significant for the inheritance and error correction of manual operation of acupuncture.
Humans ; Acupuncture Therapy/instrumentation* ; Machine Learning ; Adult ; Male ; Female

OBJECTIVE: To investigate the effect of manual acupuncture manipulations (MAMs) on subcutaneous muscle tissue, by developing quantitative models of "lifting and thrusting" and "twisting and rotating", based on machine learning techniques. METHODS: A depth camera was used to capture the acupuncture operator's hand movements during "lifting and thrusting" and "twisting and rotating" of needle. Simultaneously, the ultrasound imaging was employed to record the muscle tissue responses of the participants. Amplitude and angular features were extracted from the movement data of operators, and muscle fascicle slope features were derived from the data of ultrasound images. The dynamic time warping barycenter averaging algorithm was adopted to align the dual-source data. Various machine learning techniques were applied to build quantitative models, and the performance of each model was compared. The most optimal model was further analyzed for its interpretability. RESULTS: Among the quantitative models built for the two types of MAMs, the random forest model demonstrated the best performance. For the quantitative model of the "lifting and thrusting" technique, the coefficient of determination (R²) was 0.825. For the "twisting and rotating" technique, R² reached 0.872. CONCLUSION Machine learning can be used to effectively develop the models and quantify the effects of MAMs on subcutaneous muscle tissue. It provides a new perspective to understand the mechanism of acupuncture therapy and lays a foundation for optimizing acupuncture technology and designing personalized treatment regimen in the future.
Humans ; Acupuncture Therapy/methods* ; Machine Learning ; Male ; Adult ; Female ; Subcutaneous Tissue/diagnostic imaging* ; Young Adult

Traditional Chinese medicine(TCM) capable of clearing heat and removing toxin is most commonly used in clinical practice and has the effect of removing fire-heat and toxin. Studies have shown that most of the Ilex plants have the effect of clearing heat and removing toxin, among which the varieties of I. cornuta, I. pubescens, I. rotunda, I. latifolia, and I. chinensis are most widely used. These plants generally contain triterpenoids and their glycosides, alkaloids, flavonoids, phenylpropanoids, and other chemical components, especially pentacyclic triterpenoids. According to their skeletons, pentacyclic triterpenoids can be divided into the oleanane type, the ursane type, the lupinane type, etc. Among them, ursane-type components are the most abundant, and 136 species have been found so far. These components have been proved to have pharmacological effects such as anti-inflammatory, anti-tumor, hypolipidemic, anti-thrombosis, cardiomyocyte-protective, antibacterial, and hepatoprotective effects. Therefore, this paper systematically reviews the domestic and foreign literature on Ilex plants with a focus on the research progress on pentacyclic triterpenoids and their pharmacological activities, aiming to provide reference for the development of TCM resources with the effect of clearing heat and removing toxin.
Ilex/chemistry* ; Plants, Medicinal/chemistry* ; Pentacyclic Triterpenes/pharmacology* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology* ; Humans ; Animals

To elucidate the mechanism by which steaming affects the quality of Curcuma kwangsiensis root tubers, methods such as LSCM, RVA, dual-wavelength spectrophotometry, LF-NMR, and LC-MS were employed to qualitatively and quantitatively detect changes in starch gelatinization characteristics, water distribution, and material composition of C. kwangsiensis root tubers under different steaming durations. Based on multivariate statistical analysis, the correlation between differences in gelatinization parameters, water distribution, and terpenoid material composition was investigated. The results indicate that steaming affects both starch gelatinization and water distribution in C. kwangsiensis. During the steaming process, transformations occur between amylose and amylopectin, as well as between semi-bound water and free water. After 60 min of steaming, starch gelatinization and water distribution reached an equilibrium state. The content of amylopectin, the amylose-to-amylopectin ratio, and parameters such as gelatinization temperature, viscosity, breakdown value, and setback value were significantly correlated(P≤0.05). Additionally, the amylose-to-amylopectin ratio was significantly correlated with total free water and total water content(P≤0.05). Steaming induced differences in the material composition of C. kwangsiensis root tubers. Clustering of primary metabolites in the OPLS-DA model was distinct, while secondary metabolites were classified into 9 clusters using the K-means clustering algorithm. Differential terpenoid metabolites such as(-)-α-curcumene were significantly correlated with zerumbone, retinal, and all-trans-retinoic acid(P<0.05). Curcumenol was significantly correlated with isoalantolactone and ursolic acid(P<0.05), while all-trans-retinoic acid was significantly correlated with both zerumbone and retinal(P<0.05). Alpha-tocotrienol exhibited a significant correlation with retinal and all-trans-retinoic acid(P<0.05). Amylose was extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and α-tocotrienol(P<0.05). Amylopectin was significantly correlated with zerumbone(P<0.05) and extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and 9-cis-retinoic acid(P<0.01). The results provide scientific evidence for elucidating the mechanism of quality formation of steamed C. kwangsiensis root tubers as a medicinal material.
Curcuma/chemistry* ; Starch/chemistry* ; Multivariate Analysis ; Water/chemistry* ; Terpenes/analysis* ; Plant Roots/chemistry* ; Plant Tubers/chemistry* ; Drugs, Chinese Herbal/chemistry*

As a new type of production factor that can empower the development of new quality productivity, the data element is an important engine to promote the high quality development of the industry. Traditional Chinese medicine(TCM) dispensing is the most basic work of TCM clinical pharmacy, and its quality directly affects the clinical efficacy of TCM. The integration of data elements and TCM dispensing can stimulate the innovation and vitality of the TCM dispensing industry and promote the high-quality and sustainable development of the industry. A large-scale, detailed, and systematic study on TCM dispensing was conducted. The innovative practice path of data fusion construction in the whole process of TCM dispensing was investigated by integrating the digital resources "nine full activities" of TCM dispensing, creating the digital dictionary of "TCM clinical information data elements", and exploring innovative applications of TCM dispensing driven by data and technology, so as to promote the standardized, digital, and intelligent development of TCM dispensing in medical health services. The research content of this project was successfully selected as the second batch of "Data element×" typical cases of National Data Administration in 2024, which is the only selected case in the field of TCM.
Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal ; Humans

The differences in chemical quality characteristics between Xinjiang Rehmannia glutinosa and R. glutinosa were analyzed to provide a theoretical basis for the introduction and quality control of R. glutinosa. In this study, the high performance liquid chromatography(HPLC) fingerprints of 6 batches of Xinjiang R. glutinosa and 10 batches of R. glutinosa samples were established. The content of iridoid glycosides, phenylethanoid glycosides, monosaccharides, oligosaccharides, and polysaccharides in Xinjiang R. glutinosa and R. glutinosa was determined by high performance liquid chromatography-diode array detection(HPLC-DAD), high performance liquid chromatography-evaporative light scattering detection(HPLC-ELSD), and ultraviolet-visible spectroscopy(UV-Vis). The determination results were analyzed with by chemical pattern recognition and entropy weight TOPSIS method. The results showed that there were 19 common peaks in the HPLC fingerprints of the 16 batches of R. glutinosa, and catalpol, aucubin, rehmannioside D, rehmannioside A, hydroxytyrosol, leonuride, salidroside, cistanoside A, and verbascoside were identified. Hierarchical cluster analysis(HCA) and principal component analysis(PCA) showed that Qinyang R. glutinosa, Mengzhou R. glutinosa, and Xinjiang R. glutinosa were grouped into three different categories, and eight common components causing the chemical quality difference between Xinjiang R. glutinosa and R. glutinosa in Mengzhou and Qinyang of Henan province were screened out by orthogonal partial least squares discriminant analysis(OPLS-DA). The results of content determination showed that there were glucose, sucrose, raffinose, stachyose, polysaccharides, and nine glycosides in Xinjiang R. glutinosa and R. glutinosa samples, and the content of catalpol, rehmannioside A, leonuride, cistanoside A, verbascoside, sucrose, and glucose was significantly different between Xinjiang R. glutinosa and R. glutinosa. The analysis with entropy weight TOPSIS method showed that the comprehensive quality of R. glutinosa in Mengzhou and Qinyang of Henan province was better than that of Xinjiang R. glutinosa. In conclusion, the types of main chemical components of R. glutinosa and Xinjiang R. glutinosa were the same, but their content was different. The chemical quality of R. glutinosa was better than Xinjiang R. glutinosa, and other components in R. glutinosa from two producing areas and their effects need further study.
Rehmannia/classification* ; Drugs, Chinese Herbal/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Quality Control