OBJECTIVE To screen and quantitatively analyze the quality marker （Q-Marker） associated with anti-renal fibrosis in Shenqi shenshuai mixture （SQSS）， so as to provide references for the analysis of pharmacodynamic substances and new drug transformation of SQSS. METHODS The chemical components of SQSS were characterized by untargeted metabolomics. Combined with network pharmacology， gene expression omnibus （GEO） and connectivity map （CMAP） databases， the anti-renal fibrosis Q-Markers of SQSS were screened. HPLC-MS/MS was applied to determine the contents of Q-Markers in 10 batches of SQSS. RESULTS A total of 1 319 compounds were identified from SQSS via untargeted metabolomics，and 84 active ingredients with anti-renal fibrosis activity were further screened out， such as formononetin. Nine anti-renal fibrosis Q-Markers were obtained by network pharmacology and GEO database， including berberine， quercetin， honokiol， nicotinamide， daidzein， coumarin， kaempferol， formononetin and amygdalin. The quantitative results showed that the average contents of the above components （excluding amygdalin） in 10 batches of SQSS were 2.523， 1.942， 26.848， 1.415， 0.692， 0.171， 0.374， 7.401 μg/mL， respectively. CONCLUSIONS Nine anti-renal fibrosis Q-Markers of SQSS were screened in this study， and the contents of eight among them were determined. The results can provide a basis for elucidating the pharmacodynamic material basis and promoting the new drug transformation of SQSS.

OBJECTIVE To screen and quantitatively analyze the quality marker （Q-Marker） associated with anti-renal fibrosis in Shenqi shenshuai mixture （SQSS）， so as to provide references for the analysis of pharmacodynamic substances and new drug transformation of SQSS. METHODS The chemical components of SQSS were characterized by untargeted metabolomics. Combined with network pharmacology， gene expression omnibus （GEO） and connectivity map （CMAP） databases， the anti-renal fibrosis Q-Markers of SQSS were screened. HPLC-MS/MS was applied to determine the contents of Q-Markers in 10 batches of SQSS. RESULTS A total of 1 319 compounds were identified from SQSS via untargeted metabolomics，and 84 active ingredients with anti-renal fibrosis activity were further screened out， such as formononetin. Nine anti-renal fibrosis Q-Markers were obtained by network pharmacology and GEO database， including berberine， quercetin， honokiol， nicotinamide， daidzein， coumarin， kaempferol， formononetin and amygdalin. The quantitative results showed that the average contents of the above components （excluding amygdalin） in 10 batches of SQSS were 2.523， 1.942， 26.848， 1.415， 0.692， 0.171， 0.374， 7.401 μg/mL， respectively. CONCLUSIONS Nine anti-renal fibrosis Q-Markers of SQSS were screened in this study， and the contents of eight among them were determined. The results can provide a basis for elucidating the pharmacodynamic material basis and promoting the new drug transformation of SQSS.

Objective To investigate occupational exposure levels of lead, arsenic and cadmium in the lead smelting plant of Hunan Shui Kou Shan Nonferrous Metals Group Co. Ltd., analyze their effects on health of employees, and compare the applicability of different occupational health risk assessment methods, and to provide a basis for prevention and control of occupational exposure risks in enterprises. Methods According to systematic sampling method, 380 employees with lead, arsenic and cadmium exposure (exposure group) and 100 non-exposure employees (non-exposure group) were selected from 2022 to 2024 for on-site investigation of occupational health [concentration time-weighted average (C_TWA)] and physical examination. The risk was evaluated by qualitative assessment method, the U.S. Environmental Protection Agency (EPA) inhalation risk assessment method, and the Singapore Ministry of Manpower (MOM) semi-quantitative method. The consistency was analyzed by the Kappa test. Results C_TWA values of lead, arsenic, and cadmium in all positions were lower than the occupational exposure limit (OEL). The levels of blood lead, urine arsenic, and urine cadmium, as well as the prevalence of multiple systems in the exposure group were significantly higher than those in the non-exposure group (P<0.05). The proportions of chronic lead, arsenic, and cadmium poisoning were increasing year by year in the exposure group (P<0.05). The qualitative assessment method mainly indicated low and medium risk, while the EPA and MOM methods mainly indicated medium and high risk, with good agreement between the two methods (Kappa=0.676, P<0.05). Conclusion Although the enterprise meets the C_TWA standards, there are still occupational health risks of lead, arsenic, and cadmium. The EPA inhalation risk assessment method is more applicable.

ObjectiveTo analyze the comorbidity patterns of chronic metabolic diseases and their influencing factors among residents aged 35‒75 years old in Nantong City of Jiangsu Province, and to provide theoretical support for the prevention and control of comorbidities. MethodsThe permanent residents aged 35‒75 years from the Comprehensive Prevention and Control Project of Cardiovascular and Cerebrovascular Diseases in Nantong City from 2021 to 2024 were selected as the research subjects. Clustering analysis and association rule were used to investigate the comorbidity patterns of chronic metabolic diseases, and their influencing factors were identified through logistic regression analyses. ResultsThe prevalence of comorbidity of chronic metabolic diseases among residents aged 35‒75 years in Nantong City was 47.40%. Among comorbidity patterns based on disease counts, the prevalence of hypertension+dyslipidemia was highest in binary comorbidity patterns (6.25%), while that of hypertension+dyslipidemia+obesity was highest in ternary comorbidity patterns (4.01%). Association rules showed that in both binary and ternary comorbidity patterns, the confidence level was highest for obesity+hypertension (72.70%) and obesity+dyslipidemia+hypertension (74.54%). Renal insufficiency formed an independent cluster in cluster analyses. Logistic regression analyses revealed that, compared with the non-comorbidity group, males (OR=2.22, 95%CI: 1.69‒2.91), advanced age (45‒54 years, OR=1.38, 95%CI: 1.02‒1.88; 55‒64 years, OR=1.59, 95%CI: 1.14‒2.23; 65‒75 years, OR=2.34, 95%CI: 1.58‒3.47), and low physical activity (OR=1.26, 95%CI: 1.10‒1.65) were influencing factors for metabolic disease comorbidity. ConclusionIn the comorbidity patterns of chronic metabolic diseases among residents aged 35‒75 years in Nantong City, hypertension, diabetes mellitus, and dyslipidemia interact with each other. Individuals with obesity are more prone to diseases such as hypertension and dyslipidemia. Prevention and control of chronic metabolic diseases should be strengthened for males, individuals with low physical activity and advanced age.

Objective To systematically evaluate the risk prediction models for postoperative pulmonary infection in patients with esophageal cancer, providing an objective basis for clinical selection and optimization of models. Methods A systematic search was conducted in Chinese and English databases such as VIP, Wanfang, CNKI, CBM, PubMed, Cochrane Library, Embase, and Web of Science for studies related to the risk prediction models of postoperative pulmonary infection in patients with esophageal cancer from the inception to September 30, 2024. The PROBAST tool was used to assess the quality of prognostic model research, and the RevMan 5.4 software was used for meta-analysis of predictive factors. Results A total of 17 articles were included, containing 26 pulmonary infection risk prediction models. The area under the receiver operating characteristic curve (AUC) ranged from 0.627 to 0.942, among which 21 models had good predictive performance (AUC>0.7). Quality assessment through the PROBAST tool revealed that all 17 articles had a high risk of bias. Meta-analysis results showed that common predictive factors for postoperative pulmonary infection in esophageal cancer included smoking history (OR=1.97), smoking index ≥200 (cigarettes-years) (OR=4.38), smoking index ≥400 (cigarettes-years) (OR=2.00), age (OR=1.27), comorbid diabetes (OR=2.13), comorbid emphysema or chronic obstructive pulmonary disease (OR=1.55), low plasma albumin levels (OR=1.17), prognostic nutritional index (OR=4.45), history of related lung diseases (OR=2.10), tumor location (OR=2.32), surgical approach (OR=2.21), operation time (OR=1.73), preoperative serum procalcitonin levels (OR=3.06), anastomotic leakage (OR=3.39), reduced forced expiratory volume in the first second/forced vital capacity ratio (OR=0.86), and hoarseness (OR=2.23). Conclusion At present, the risk prediction models for postoperative pulmonary infection in esophageal cancer are still in the stage of continuous development and optimization, and their research quality needs to be further improved. Future research can refer to the predictive factors summarized in this study based on meta-analysis, combined with clinical practice, to select appropriate methods to construct and validate the risk prediction models for postoperative pulmonary infection in esophageal cancer, thus providing early targeted preventive strategies for high-risk patients.

ObjectiveTo investigate the distribution of traditional Chinese medicine （TCM） syndrome patterns among postmenopausal women with dyslipidemia， and to examine the correlations of lipid parameters with bone mineral density （BMD） and bone metabolism markers across common TCM syndrome patterns， thereby providing a clinical reference for individualized integrative traditional Chinese and western medicine interventions stratified according to TCM syndrome patterns. MethodsA multi-center cross-sectional study was conducted among postmenopausal women aged 45-64 years with dyslipidemia. TCM syndromes were determined using a scale-based scoring method. BMD measurements were collected， and fasting venous blood samples were assayed for lipid parameters including total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein cholesterol （HDL-C）， and low-density lipoprotein cholesterol （LDL-C）， and bone metabolism biomarkers including osteocalcin （OST）， total procollagen type Ⅰ N-terminal propeptide （P1NP）， alkaline phosphatase （ALP）， bone-specific alkaline phosphatase （BALP）， β-isomerized C-terminal telopeptide of type Ⅰ collagen （β-CTX）， 25-hydroxyvitamin D ［25（OH）D］， and thyroid-stimulating hormone （TSH）. Chi-square tests were used to compare the distribution of dyslipidemia across different TCM syndromes. Spearman's rank correlation analysis was performed to evaluate the correlations between TCM syndrome patterns and dyslipidemia， as well as the correlations of lipid parameters with BMD and bone metabolism markers within each syndrome pattern. ResultsA total of 506 postmenopausal women with dyslipidemia were included， comprising 172 cases of spleen-kidney yang deficiency syndrome （33.99%）， 163 cases of phlegm-turbidity obstruction syndrome （32.21%）， 118 cases of liver-kidney yin deficiency syndrome （23.32%）， 33 cases of qi stagnation and blood stasis syndrome （6.52%）， and 20 cases of yin deficiency and yang hyperactivity syndrome （3.95%）. Phlegm-turbidity obstruction syndrome was negatively correlated with TC abnormality （r=-0.120， P=0.007） and positively correlated with TG abnormality （r=0.246， P＜0.001）. Spleen-kidney yang deficiency syndrome and liver-kidney yin deficiency syndrome were both negatively correlated with TG abnormality （r=-0.101， P=0.023； r=-0.116， P=0.009， respectively）. Further correlation analysis confirmed that phlegm-turbidity obstruction syndrome was negatively correlated with TC abnormality （r=-0.120） and significantly positively correlated with TG abnormality （r=0.246）. Both the spleen-kidney yang deficiency syndrome and liver-kidney yin deficiency syndrome were negatively correlated with TG abnormality （r=-0.101 and r=-0.116， respectively）. In patients with phlegm-turbidity obstruction syndrome， HDL-C was negatively correlated with BMD at the left femoral neck （r=-0.178， P=0.023） and at left total hip （r=-0.190， P=0.015）. In patients with liver-kidney yin deficiency syndrome， TG was positively correlated with BMD at the lumbar spine （L1-L4） and left total hip （r=0.214， P=0.020； r=0.221， P=0.016， respectively）. More significant correlations were observed in patients with spleen-kidney yang deficiency syndrome， TG was positively correlated with ALP （r=0.210， P=0.006）； TC was positively correlated with TSH and 25（OH）D （r=0.153， P=0.045； r= 0.231， P=0.002， respectively）； HDL-C was positively correlated with OST and 25（OH）D （r=0.156， P=0.040； r=0.228， P=0.003， respectively）； and LDL-C was positively correlated with TSH and 25（OH）D （r=0.156， P= 0.041； r=0.182， P=0.017， respectively）. In patients with liver-kidney yin deficiency syndrome， HDL-C was negatively correlated with TSH （r=-0.204， P=0.027）. ConclusionThe association between dyslipidemia and skeletal health in postmenopausal women varies across TCM syndromes. Lipid abnormalities in women with phlegm-turbidity obstruction syndrome or liver-kidney yin deficiency syndrome are accompanied primarily by site-specific alterations in BMD， whereas those in women with spleen-kidney yang deficiency syndrome are reflected mainly in changes in bone metabolism markers. These findings suggest that targeted intervention strategies should be developed according to TCM syndrome characteristics for postmenopausal women with dyslipidemia.

ObjectiveTo investigate the distribution of traditional Chinese medicine （TCM） syndrome patterns among postmenopausal women with dyslipidemia， and to examine the correlations of lipid parameters with bone mineral density （BMD） and bone metabolism markers across common TCM syndrome patterns， thereby providing a clinical reference for individualized integrative traditional Chinese and western medicine interventions stratified according to TCM syndrome patterns. MethodsA multi-center cross-sectional study was conducted among postmenopausal women aged 45-64 years with dyslipidemia. TCM syndromes were determined using a scale-based scoring method. BMD measurements were collected， and fasting venous blood samples were assayed for lipid parameters including total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein cholesterol （HDL-C）， and low-density lipoprotein cholesterol （LDL-C）， and bone metabolism biomarkers including osteocalcin （OST）， total procollagen type Ⅰ N-terminal propeptide （P1NP）， alkaline phosphatase （ALP）， bone-specific alkaline phosphatase （BALP）， β-isomerized C-terminal telopeptide of type Ⅰ collagen （β-CTX）， 25-hydroxyvitamin D ［25（OH）D］， and thyroid-stimulating hormone （TSH）. Chi-square tests were used to compare the distribution of dyslipidemia across different TCM syndromes. Spearman's rank correlation analysis was performed to evaluate the correlations between TCM syndrome patterns and dyslipidemia， as well as the correlations of lipid parameters with BMD and bone metabolism markers within each syndrome pattern. ResultsA total of 506 postmenopausal women with dyslipidemia were included， comprising 172 cases of spleen-kidney yang deficiency syndrome （33.99%）， 163 cases of phlegm-turbidity obstruction syndrome （32.21%）， 118 cases of liver-kidney yin deficiency syndrome （23.32%）， 33 cases of qi stagnation and blood stasis syndrome （6.52%）， and 20 cases of yin deficiency and yang hyperactivity syndrome （3.95%）. Phlegm-turbidity obstruction syndrome was negatively correlated with TC abnormality （r=-0.120， P=0.007） and positively correlated with TG abnormality （r=0.246， P＜0.001）. Spleen-kidney yang deficiency syndrome and liver-kidney yin deficiency syndrome were both negatively correlated with TG abnormality （r=-0.101， P=0.023； r=-0.116， P=0.009， respectively）. Further correlation analysis confirmed that phlegm-turbidity obstruction syndrome was negatively correlated with TC abnormality （r=-0.120） and significantly positively correlated with TG abnormality （r=0.246）. Both the spleen-kidney yang deficiency syndrome and liver-kidney yin deficiency syndrome were negatively correlated with TG abnormality （r=-0.101 and r=-0.116， respectively）. In patients with phlegm-turbidity obstruction syndrome， HDL-C was negatively correlated with BMD at the left femoral neck （r=-0.178， P=0.023） and at left total hip （r=-0.190， P=0.015）. In patients with liver-kidney yin deficiency syndrome， TG was positively correlated with BMD at the lumbar spine （L1-L4） and left total hip （r=0.214， P=0.020； r=0.221， P=0.016， respectively）. More significant correlations were observed in patients with spleen-kidney yang deficiency syndrome， TG was positively correlated with ALP （r=0.210， P=0.006）； TC was positively correlated with TSH and 25（OH）D （r=0.153， P=0.045； r= 0.231， P=0.002， respectively）； HDL-C was positively correlated with OST and 25（OH）D （r=0.156， P=0.040； r=0.228， P=0.003， respectively）； and LDL-C was positively correlated with TSH and 25（OH）D （r=0.156， P= 0.041； r=0.182， P=0.017， respectively）. In patients with liver-kidney yin deficiency syndrome， HDL-C was negatively correlated with TSH （r=-0.204， P=0.027）. ConclusionThe association between dyslipidemia and skeletal health in postmenopausal women varies across TCM syndromes. Lipid abnormalities in women with phlegm-turbidity obstruction syndrome or liver-kidney yin deficiency syndrome are accompanied primarily by site-specific alterations in BMD， whereas those in women with spleen-kidney yang deficiency syndrome are reflected mainly in changes in bone metabolism markers. These findings suggest that targeted intervention strategies should be developed according to TCM syndrome characteristics for postmenopausal women with dyslipidemia.

Objective To observe the value of machine learning model based on MR T2WI and diffusion weighted imaging(DWI)radiomics for predicting perineural invasion(PNI)of rectal cancer.Methods Totally 343 patients with rectal cancer were retrospectively collected and divided into training set(n=275,92 PNI[+]and 183 PNI[-])and test set(n=68,23 PNI[+]and 45 PNI[-])at the ratio of 8∶2.Univariate and multivariate logistic regression(LR)were used to analyze clinical data and screen the independent predictors of PNI in rectal cancer,so as to construct a clinical model.The best radiomics features were extracted and screened based on preoperative T2WI and DWI.Then extremely randomized trees,multilayer perceptron,light gradient boosting machine,extreme gradient boosting,support vector machine(SVM),LR,K-nearest neighbor and random forest algorithms were used to construct ML models,respectively,and the optimal ML model was selected to establish a clinical-radiomics ML model combined with clinical relevant independent predictors.The predictive efficacy and clinical value of each model were evaluated.Results Patients' age was the independent predictor of PNI of rectal cancer(OR=0.988,P＜0.001),and the area under the curve(AUC)of the clinical model constructed based on it was 0.435 and 0.458 in training and test sets,respectively.SVM model was the best one among 8 ML models,with AUC in training and test set of 0.887 and 0.854,respectively.The AUC of clinical-radiomics ML model in training and test sets was 0.887 and 0.860,respectively,not different with AUC of SVM model(both P＞0.05).Decision curve analysis showed that when the threshold value was 0.20-0.45,clinical net benefit of SVM model was higher than that of other models.Conclusion SVM model based on T2WI and DWI radiomics could effectively predict PNI of rectal cancer.

This paper designed a pressure swing adsorption(PSA)oxygen production equipment in mobile cabin of container,and a dual-tower type of oxygen producer was adopted.The inside of container included some major components,such as air compressor,filters,adsorption dryer,purifier,air buffer tank,oxygen generator,process tank,oxygen compressor,and an oxygen tank,and it adopted a unique circular structure with compact layout,which can optimize the work parameters of oxygen production equipment in mobile cabin of container,and provide convenience for installation and maintenance in the inside of the container,and provide continuously and stably qualified oxygen.At the same time,the DYSP intelligent control system was adopted,which can realize remote control,data acquisition,and parameter settings,and other operations.Compared with infrastructure installation of oxygen production equipment,the PSA oxygen production equipment in mobile cabin of container has a series of advantages,such as convenient displacement,small footprint and fast use.It can enhance control efficiency of oxygen production equipment,and reduce labor costs.It has wide applicability to hospitals,mobile cabin hospitals,factories that need oxygen,which are temperately established and need be emergently used.

Objective:To compare the value of different imaging modalities in evaluating early efficacy of 90Y-selective internal radiation therapy (SIRT) for liver malignant tumors. Methods:From September 2021 to December 2023, a retrospective analysis was conducted on 43 patients (32 males, 11 females; age (55.8±14.7) years) with liver malignant tumors who received 90Y-SIRT at Hainan Cancer Hospital and Boao Super Hospital. The injection dosage of 90Y was 1.5(1.2, 2.4)GBq. Clinical and imaging data of patients before and after treatment for multimodal evaluation were collected, including MRI plain and enhanced scans, as well as diffusion weighted imaging (DWI). Plain scan images were evaluated for the treatment efficacy by response evaluation criteria in solid tumors (RECIST) 1.1 version, while enhanced MRI was scored into 1-5 based on changes in the target area, including increased low-density range, necrotic features, and decreased enhancement. The minimum apparent diffusion coefficient (ADC min) of DWI increased by 20% compared to baseline was determined to be responsive. Wilcoxon signed rank test was used to analyze data, and ROC curve analysis was used to analyze the diagnostic efficacy of different imaging modalities (Delong test). Results:All patients had baseline MRI data, 39 underwent MRI at 1-month after treatment, and 22 underwent MRI at 3-month after treatment. Based on MRI plain scan images, the target lesions showed partial remission (PR) in 10.26%(4/39) of patients, progressive disease (PD) in 5.13%(2/39) of patients, and stable disease (SD) in 84.61%(33/39) of patients at 1-month after treatment; while there were 40.91%(9/22) PR, 9.09%(2/22) PD and 50.00%(11/22) SD at 3-month after treatment. Based on DWI images, 35.90%(14/39) and 68.18%(15/22) of patients were considered responsive at 1-month and 3-month after treatment, respectively. Compared with baseline, the differences of tumor sizes, enhancement degree of target lesions and ADC min at 1-month and 3-month after treatment were statistically significant ( Z values: from -3.88 to -2.39, all P<0.05). Compared with the tumor size and enhancement degree, the AUCs of ADC min were the highest at 1-month (0.701) and 3-month (0.953) after treatment ( Z values: 0.40-2.29, all P<0.05). Conclusions:MRI plain scan, MRI enhancement and DWI are effective in the evaluation the efficacy of 90Y-SIRT for liver malignant tumors at 1-month and 3-month after treatment. ADC min is superior to tumor size and enhancement degree in diagnostic efficacy.