Objective: To understand the hydration status and related factors of rural boarding primary school students, so as to provide a scientific basis for drinking water health intervention for primary school students. Methods: In November 2023, a convenience sampling approach was employed to conduct a hydration status survey among 144 boarding students in grades 5 and 6 of a rural primary school in Guangxi. The Duplicate meal method and weighing method were utilized to measure the food derived water intake over three consecutive days. Urine osmolarity of students was measured on site for three days, and a simple physical examination was also carried out. A self administered questionnaire was used to investigate students drinking water literacy, daily water intake, and physical activity levels. Meanwhile, a drinking water literacy survey was conducted among 21 substitute teachers and 144 parents of the boarding students in grades 5 and 6. Logistic regression was used to identify factors associated with students hydration status. Results: The median daily total water intake of students was 2 043.55 mL, and 54.86% of the students did not reach the recommended Adequate Intake (AI). The median food derived water intake was 1 149.24 mL, accounting for 53.94% of the total water intake. Univariate analysis revealed that the daily drinking frequency, daily water intake, and food derived water intake of students were related factors of hydration status ( β =-1.60, -1.01, -0.00, all P <0.05). Multivariate Logistic regression analysis showed that primary school students with a daily drinking frequency of ≥7 times were more likely to maintain an adequate hydration status ( OR =0.28, 95% CI =0.09-0.93, P ＜0.05). Conclusions The water intake from food is the main source of water in the body for boarding primary school students in a certain rural school in Guangxi. Primary school students should increase their water intake frequency appropriately to maintain an adequate hydration status.

Objective: To investigate the current status of knowledge, attitudes and practices regarding drinking water among primary school students in rural areas of China, so as to provide scientific basis for implementing health interventions related to drinking water. Methods: From November to December 2023, a stratified cluster random sampling method was employed to select 6 354 fourth to sixth grade primary school students in Shanxi, Zhejiang, Jiangxi, Guangxi and Gansu for a questionnaire survey. A uniformly designed questionnaire (including basic information, drinking water-related knowledge, attitudes and practices indicators) was distributed and completed by the students themselves. The χ 2 test was used to analyze the differences in drinking water-related indicators among students of different gender and boarder, and Logistic regression was used to analyze the influencing factors of drinking water practices among students. Results: Among the indicators of drinking water knowledge, the awareness rate of appropriate daily water intake for respective student age groups was the lowest (27.90%). The awareness rate among nonresident students was significantly higher than that among boarding students (31.29%, 15.49%, χ 2=132.75, P <0.01). Regarding attitudes toward drinking water, 13.33% of the students believed that well water or tap water could be drunk directly, and 9.58% believed that going to the toilet at school was troublesome. Regarding practices, the self-reported water intake among students was 1 000 (600, 1 200) mL. The results of multifactorial Logistic regression showed that higher grades ( OR=1.60, 95%CI =1.34-1.92), nonresident students ( OR=1.32, 95%CI = 1.15 -1.52), northern region ( OR=1.43, 95%CI =1.27-1.61), knowledge of appropriate daily water intake ( OR=1.41, 95%CI =1.24-1.60), drinking temperature ( OR=1.43, 95%CI =1.28-1.60), scientific hydration methods ( OR=1.25, 95%CI =1.08- 1.44 ), and adopting scientific hydration methods regularly ( OR=1.75, 95%CI =1.50-2.04) were the independent influences on daily water intake attainment ( P <0.05). Conclusions Rural primary school students lack knowledge about healthy drinking water, have cognitive biases about safe drinking water and exhibit unhealthy drinking behavior. It is suggested that health education be carried out in combination with the characteristics of students to enhance their drinking water literacy.

Objective To investigate the value of multimodal model integrating digital mammography(MG)and MRI radiomics features for preoperative prediction of lymphovascular invasion(LVI)status in breast cancer.Methods The clinical and imaging data from 336 patients with pathologically confirmed invasive breast cancer were retrospectively analyzed and randomly divided into a training group(235 cases)and a test group(101 cases)according to the ratio of 7∶3.Feature dimensionality reduction was carried out by Pearson correlation analysis followed by least absolute shrinkage and selection operator(LASSO)regression.Radiomics models were constructed based on MG craniocaudal(CC),dynamic contrast enhancement(DCE),T2 WI,and integrated MRI sequences;a multimodal model was further developed by incorporating clinical high-risk factors.The predictive efficiency of each model was evaluated by plotting receiver operating characteristic(ROC)curve.Results The ROC curve analysis showed that the multimodal model performed the best predictive efficiency,with area under the curve(AUC)of 0.989 and 0.861,accuracy of 0.949 and 0.782,sensitivity of 0.923 and 0.828,and specificity of 0.962 and 0.764 in the training group and test group respectively.Conclusion The multimodal model,integrating MG and MRI radiomics features,show optimal performance and can be served as a preoperative prediction of LVI status in breast cancer.

Objective To investigate the value of multimodal model integrating digital mammography(MG)and MRI radiomics features for preoperative prediction of lymphovascular invasion(LVI)status in breast cancer.Methods The clinical and imaging data from 336 patients with pathologically confirmed invasive breast cancer were retrospectively analyzed and randomly divided into a training group(235 cases)and a test group(101 cases)according to the ratio of 7∶3.Feature dimensionality reduction was carried out by Pearson correlation analysis followed by least absolute shrinkage and selection operator(LASSO)regression.Radiomics models were constructed based on MG craniocaudal(CC),dynamic contrast enhancement(DCE),T2 WI,and integrated MRI sequences;a multimodal model was further developed by incorporating clinical high-risk factors.The predictive efficiency of each model was evaluated by plotting receiver operating characteristic(ROC)curve.Results The ROC curve analysis showed that the multimodal model performed the best predictive efficiency,with area under the curve(AUC)of 0.989 and 0.861,accuracy of 0.949 and 0.782,sensitivity of 0.923 and 0.828,and specificity of 0.962 and 0.764 in the training group and test group respectively.Conclusion The multimodal model,integrating MG and MRI radiomics features,show optimal performance and can be served as a preoperative prediction of LVI status in breast cancer.

Objective To construct the theoretical framework of rehabilitation big data based on International Classification of Func-tioning,Disability and Health(ICF). Methods Drawing upon international rehabilitation policy documents,such as the World Health Organization's Rehabili-tation in health systems;Rehabilitation in health systems:guide for action;Rehabilitation indicator menu:a tool accompanying the Framework for Rehabilitation Monitoring and Evaluation(FRAME);Template for Rehabilita-tion Information Collection(TRIC):a tool accompanying the Systematic Assessment of Rehabilitation Situation(STARS);and Framework and Standards for Country Health Information Systems;this study examined the com-position and function of rehabilitation big data.The content structure of the rehabilitation big data domain was an-alyzed using the World Health Organization Family of International Classifications(WHO-FICs).Furthermore,the generation patterns of rehabilitation big data was constructed drawing on the Health Metrics Network and big data hierarchical classification. Results Within the six primary elements of the health service system,the information system element was particularly significant,encompassing a substantial branch known as rehabilitation big data.There were three components of rehabilitation big data:health condition,health-related factors and health services.The content framework for this data was derived from the WHO-FICs framework,which covered three dimensions:health and function,dis-ease and function,and disease,function and intervention.A comprehensive model for generating and applying re-habilitation big data in rehabilitation services was developed in line with the requirements for constructing big da-ta architectures.The sources of this data included population censuses,social registration information,population surveys,resources,services and personal records.The result chain of rehabilitation big data encompassed five major processes:input,process,output,outcome and impact.The processing and utilization of this data involved collection,storage,management,analysis and application. Conclusion A theoretical framework for rehabilitation big data has been constructed based on the ICF theory.

Objective To explore and organize the standards of rehabilitation big data. Methods The connotation and extension of rehabilitation big data were discussed based on International Classification of Functioning,Disability and Health(ICF)framework.Referring to the documents of Guidance on the analysis and use of routine health information systems rehabilitation module,Rehabilitation in health systems:guide for action,Rehabilitation indicator menu:a tool accompanying the Framework for Rehabilitation Monitoring and Evaluation(FRAME),and Data quality assurance.Module 1.Framework and metrics,the sources,patterns,clas-sification systems and coding standards were discussed under the ICF theory,and the metadata standards were ex-plored.The application and management of rehabilitation big data standards were discussed according to Nation-al Health Medical Big Data Standards,Security and Service Management Measures(Trial). Results The rehabilitation big data included rehabilitation service data and personal health data,coming from population-based and institution-based data,covering macro,meso and micro levels.The pattern of rehabilitation data flow corresponded to the interaction and source of the entire process of rehabilitation service,to organize and manage rehabilitation big data.The classification system included object classes,object feature classes,participant role classes,relationship classes,and activity and event classes,each of which was further subdivided into subcatego-ries to cover the entities,features,roles,relationships and activities involved in the rehabilitation process.The metadata standards included three levels:core,general and specialized metadata,ensuring standardized manage-ment,sharing and interoperability of rehabilitation data. Conclusion This study delves into the standardization of rehabilitation big data based on the ICF framework,encompass-ing multiple dimensions such as the connotation and extension of rehabilitation big data,data sources,data mod-els,classification systems,coding standards,and metadata standards.The construction of a rehabilitation big data standard system involves standardization efforts in various aspects,including data content,data structure,data coding,and metadata.These standards not only adhere to the norms of data flow,but also take into account the complexity of data composition.This system aligns with health big data standards,ensuring data consistency,ac-curacy,and interoperability,thus providing a foundation for effective exchange and comparison between different data sources.The establishment of a rehabilitation big data standard system not only ensures the standardized pro-cessing of rehabilitation big data,but also lays a solid foundation for effective exchange between rehabilitation big data and other health data,as well as for the widespread application of rehabilitation big data.This provides crucial support for improving the quality and efficiency of rehabilitation services,ensuring that patients receive appropriate care,rehabilitation and support.It holds significant theoretical and practical implications for promot-ing the development of the rehabilitation field.

ObjectiveTo explore the efficacy and mechanism of Danshen Zexie decoction in treating the rats with metabolic-associated fatty liver disease （MAFLD）. MethodSixty male SD rats were randomized into control group， model group， essentiale （polyene phosphatidylcholine capsules， 0.144 g·kg^-1） group， and low-， medium-， and high-dose Danshen Zexie decoction （1.16， 2.32， and 4.64 g·kg^-1， respectively） groups. The rat model of MAFLD was established with high fat diet， and 8-week therapy started at the induction of MAFLD. The serum levels of total cholesterol （TC）， triglyceride （TG）， alanine aminotransferase （ALT）， and aspartate aminotransferase （AST）， as well as the liver levels of TC， TG， free fatty acid （FFA）， superoxide dismutase （SOD）， glutathione （GSH）， and malondialdehyde （MDA）， were measured. The pathological changes of liver were observed by hematoxylin-eosin （HE） staining and oil red O staining， and the steatosis score and oil red O staining area were calculated. The level of reactive oxygen species （ROS） in the liver was detected by immunofluorescence. The protein levels of adenosine monophosphate-activated protein kinase （AMPK）， p-AMPK， nuclear factor E₂-related factor 2 （Nrf2）， glutamate-cysteine ligase catalytic subunit （GCLC）， glutamate-cysteine ligase modifier subunit （GCLM）， and nicotinamide adenine dinucleotide phosphate： quinine oxidoreductase （NQO1） in the liver were determined by Western blot. ResultCompared with control group， the modeling of MAFLD elevated the levels of TC， TG， ALT， and AST in the serum and TC， TG， FFA， MDA， and ROS in the liver （P<0.01）， lowered the levels of SOD and GSH and down-regulated the protein levels of phosphorylation（p）-AMPK， Nrf2， GCLC， GCLM， and NQO1 in the liver （P<0.05， P<0.01）. Further， a large number of lipid droplet vacuoles and balloon-like lesions appeared in the hepatocytes， and the steatosis score and oil red O staining area increased in the model group （P<0.01）. Compared with model group， Danshen Zexie decoction lowered the levels of TC， TG， ALT， and AST in the serum and TC， TG， FFA， MDA， and ROS in the liver （P<0.01）， increased the levels of SOD and GSH and up-regulated the protein levels of p-AMPK， Nrf2， GCLC， GCLM， and NQO1 in the liver （P<0.05， P<0.01）. Moreover， the decoction alleviated the degree of liver steatosis （P<0.05， P<0.01）. ConclusionDanshen Zexie decoction protects against MAFLD by activating AMPK/Nrf2 signaling pathway and suppressing oxidative stress.

Tumor chemoprevention and treatment are two approaches aimed at improving the survival of patients with cancers. An ideal anti-tumor drug is that which not only kills tumor cells but also alleviates tumor-causing risk factors, such as precancerous lesions, and prevents tumor recurrence. Chinese herbal monomers are considered to be ideal treatment agents due to their multi-target effects. Astragaloside has been shown to possess tumor chemoprevention, direct anti-tumor, and chemotherapeutic drug sensitization effects. In this paper, we review the effects of astragaloside on tumor prevention and treatment and provide directions for further research.
Humans ; Chemoprevention ; Antineoplastic Agents ; Neoplasms/prevention & control* ; Saponins/pharmacology* ; Triterpenes/pharmacology*

OBJECTIVE To study the chemical constituents in S henfu injection and the anti-inflammatory activities of its polyacetylene compounds. METHODS Shenfu injection was separated and purified by macroporous adsorption resin ，medium pressure liquid chromatography ，preparative thin layer chromatography and reversed-phase semi-preparative high-performance liquid chromatography，and the compound structure was identified according to the physicochemical properties and spectral data. RAW 264.7 cell inflammation model was used to evaluate the anti-inflammatory activities of polyacetylene compounds . The effects of active polyacetylene compounds on the expressions of cyclooxygenase- 2（COX-2）protein were evaluated by Western blot assay. RESULTS Twelves compounds were isolated and identified from Shenfu injection ，including 8 ginsenoside compounds ，i.e. ginsenoside Rg 1（1），ginsenoside Re （2），ginsenoside Rb 1（3），ginsenoside Rk 1（4），20（R）-ginsenoside Rh 1（5），20（S）-ginsenoside Rg3 （6），notoginsenoside R 1（7），panaxatriol（8）；4 polyacetylene compounds ，i.e.（3R，9R，10R）-panaxytriol（9），panaxydol（10）， heptadeca-1，8-dien-4，6-diyne-3，10-diol（11）and panaxynol （12）. Among 4 polyacetylene compounds ，only compound 10 had anti-inflammatory activity. Compound 10 was not toxic to normal RAW 264.7 cells；when the concentration of compound 10 ranged 12.5-50.0 μmol/L，it could significantly reverse the lipopolysaccharide-induced NO content increase in cell supernatant （P＜0.05 or P＜0.01）；when the concentration of co mpound 10 was 50.0 μmol/L，it could significantly reverse the lipopolysaccharide-induced protein expression increase of COX- 2 in cells （P＜0.05）. CONCLUSIONS Compounds 4，7，10-12 are identified and reported in Shenfu injection for the first time ，and panaxydol possesses a certain anti-inflammatory effect.

OBJECTIVE：To establish an HPLC fing erprint of Ginsen g Radix et Rhizoma Rubra ，and to optimize its processing technology. METHODS ：HPLC method was adopted. The determination was performed on Waters SymmetryShield TM RP18 column with mobile phase consisted of acetonitrile-water （gradient elution ）at the flow rate of 1.0 mL/min. The column temperature was set at 30 ℃，and the detection wavelength was 203 nm. The sample size was 10 μL. Using ginsenoside Rb1 as reference peak ，HPLC fingerprints of 10 batches of Ginseng Radix et Rhizoma Rubra was established. The similarity of them was evaluated by using Similarity Evaluation System of TCM Chromatogram Fingerprint （2012 A edition ） to confirm common peak. With steaming temperature，time and drying method as factors ，using the content of ginsenoside and fingerprint similarity as index ，the processing technology was optimized with L 16（43）orthogonal test design and verified. Cluster analysis was conducted with SPSS 19.0 statistical software of 10 batches of Ginseng Radix et Rhizoma Rubra and 3 batches of optimal processed sample. RESULTS ：There were a total of 13 common peaks in the fingerprints of 10 batches of Ginseng Radix et Rhizoma Rubra. The similarity was more than 0.920；3 common peaks were identified ，such as ginsenoside Rg 1，ginsenoside Re ，ginsenoside Rb 1. The optimal processing technology included that steamed at 100 ℃ for 150 min，dried at 60 ℃. The results of validation test show that the contents of ginsenoside Rg 1，Re and Rb 1 were 0.26％-0.29％，0.17％-0.20％，0.47％-0.54％，and the similarity between 3 batches of Ginseng Radix et Rhizome Rubra optimal processed sample and the control fingerprints was more than 0.970. The results of cluster analysis showed that 10 batches of Gimseng Radix et Rhizoma Rubra and 3 batches of optimal processed sample could be clustered into two categories；HS3-HS10 could be clustered into one category ，and 3 batches of optimal processed sample ，HS1 and HS 2 be clustered into one category. CONCLUSIONS ：Established fingerprint can be used for the optimization of processing technology of Gimseng Radix et Rhizoma Rubra ，and characterize the correlation between f luctuation of technology parameter and quality of medicinal material；the optimal processing technology is reasonable an d