Objectives::Approximately 20%-25% of the global adult population is affected by metabolic syndrome (MetS), highlighting its status as a major public health concern. This study aims to investigate the predictive value of cardiorenal biomarkers on mortality among patients with MetS, thus optimizing treatment strategies.Methods::Utilizing data from the National Health and Nutrition Examination Survey (NHANES) cycles between 1999 and 2004, we conducted a prospective cohort study involving 2369 participants diagnosed with MetS. We evaluated the association of cardiac and renal biomarkers with all-cause and cardiovascular disease (CVD) mortality, employing weighted Cox proportional hazards models. Furthermore, machine learning models were used to predict mortality outcomes based on these biomarkers.Results::Among 2369 participants in the study cohort, over a median follow-up period of 17.1 years, 774 (32.67%) participants died, including 260 (10.98%) from CVD. The highest quartiles of cardiac biomarkers (N-terminal pro-B-type natriuretic peptide [NT-proBNP]) and renal biomarkers (beta-2 microglobulin, [β2M]) were significantly associated with increased risks of all-cause mortality (hazard ratios [HRs] ranging from 1.94 to 2.06) and CVD mortality (HRs up to 2.86), after adjusting for confounders. Additionally, a U-shaped association was observed between high-sensitivity cardiac troponin T (Hs-cTnT), creatinine (Cr), and all-cause mortality in patients with MetS. Machine learning analyses identified Hs-cTnT, NT-proBNP, and β2M as important predictors of mortality, with the CatBoost model showing superior performance (area under the curve [AUC] = 0.904).Conclusion::Cardiac and renal biomarkers are significant predictors of mortality in MetS patients, with Hs-cTnT, NT-proBNP, and β2M emerging as crucial indicators. Further research is needed to explore intervention strategies targeting these biomarkers to improve clinical outcomes.

Objectives::Approximately 20%-25% of the global adult population is affected by metabolic syndrome (MetS), highlighting its status as a major public health concern. This study aims to investigate the predictive value of cardiorenal biomarkers on mortality among patients with MetS, thus optimizing treatment strategies.Methods::Utilizing data from the National Health and Nutrition Examination Survey (NHANES) cycles between 1999 and 2004, we conducted a prospective cohort study involving 2369 participants diagnosed with MetS. We evaluated the association of cardiac and renal biomarkers with all-cause and cardiovascular disease (CVD) mortality, employing weighted Cox proportional hazards models. Furthermore, machine learning models were used to predict mortality outcomes based on these biomarkers.Results::Among 2369 participants in the study cohort, over a median follow-up period of 17.1 years, 774 (32.67%) participants died, including 260 (10.98%) from CVD. The highest quartiles of cardiac biomarkers (N-terminal pro-B-type natriuretic peptide [NT-proBNP]) and renal biomarkers (beta-2 microglobulin, [β2M]) were significantly associated with increased risks of all-cause mortality (hazard ratios [HRs] ranging from 1.94 to 2.06) and CVD mortality (HRs up to 2.86), after adjusting for confounders. Additionally, a U-shaped association was observed between high-sensitivity cardiac troponin T (Hs-cTnT), creatinine (Cr), and all-cause mortality in patients with MetS. Machine learning analyses identified Hs-cTnT, NT-proBNP, and β2M as important predictors of mortality, with the CatBoost model showing superior performance (area under the curve [AUC] = 0.904).Conclusion::Cardiac and renal biomarkers are significant predictors of mortality in MetS patients, with Hs-cTnT, NT-proBNP, and β2M emerging as crucial indicators. Further research is needed to explore intervention strategies targeting these biomarkers to improve clinical outcomes.

Objective To investigate the dosimetric effect of truncated regions in computed tomography (CT) images on the targets and organs at risk in volumetric modulated arc therapy (VMAT) for middle thoracic esophageal cancer. Methods CT images of 15 patients with middle thoracic esophageal cancer were selected. Circle masks were used to make the volume of the truncated region account for 10%, 20%, 30%, and 40% of the arm volume, and the corresponding truncated CT images were obtained. The real CT was denoted as CT0. Two radiotherapy plans were made on CT0. One plan was VMAT_1F with full arcs, and the other one was VMAT_3F with arm avoidance. The plans were transplanted to four truncated CT, respectively, and the dosimetric differences between different plans were compared using Wilcoxon signed-rank test. Results Compared with VMAT_1F in CT0, D_mean and V₅ of the lung decreased in VMAT_3F, but D_max of the spinal cord, D_mean of the heart, and V₂₀ of the lung increased. In VMAT_3F, there was no statistically significant difference between the dosimetric parameters in the four truncated CT and those in CT0 (all P > 0.05). In VMAT_1F, except for homogeneity index and D_max of the spinal cord, the dosimetric parameters in four truncated CT were significantly different from those in CT0 (P < 0.05). The dosimetric difference increased with the increase in truncated region-to-volume ratio. Conclusion Complete CT data should be collected in clinical practice, and the radiation field avoiding the truncated regionshould be set if necessary to reduce the influence of the truncated region on dosimetry.

Objective:To explore the effect of salt restriction strategy based on salt taste on salt taste preference (STP) and sodium intake in patients with chronic heart failure.Methods:From April to September 2020, convenience sampling was used to select 166 patients with chronic heart failure in the Cardiology Department of a Class Ⅲ Grade A hospital in Nanjing City, Jiangsu Province as the research object. The patients were randomly divided into the experimental group (83 cases) and the control group (83 cases) . Both groups of patients were given standardized chronic heart failure treatment methods and health education. On this basis, the experimental group was given a low-salt nutrient meal of 5.0g, 6.0g, and 7.5 g per day according to the different STP of the patients.The 24-hour urine sodium, STP, and Dietary Sodium Restriction Questionnaire (DSRQ) were used to evaluate the intervention effect.Results:After the intervention, there was a statistically significant difference in STP between the two groups of patients ( P<0.05) . The 24-hour urine sodium of the experimental group after intervention was lower than that of the control group, and the difference was statistically significant ( P<0.01) . After the intervention, the DSRQ score of the experimental group was higher than that of the control group, and the difference was statistically significant ( P<0.01) . Conclusions:The salt restriction strategy based on salt taste can reduce the STP and urine sodium of patients with chronic heart failure, and improve the current status of the implementation of sodium restriction diet.

Medical images can provide clinicans with accurate and comprehensive patients’ information. Morphological or functional abnormalities caused by various diseases can be manifested in many aspects. Although MR images and CT images can highlight the medical image data of different tissue structures of patients, single MR images or CT images cannot fully reflect the complexity of diseases. Using MR image to predict CT image is one of the cross-modal prediction of medical images. In this paper, the methods of MR image prediction for CTmage are classified into four categoriesincluding registration based on atlas, based on image segmentationmethod, based on learning method and based on deep learning method. In our research, we concluded that the method based on deep learning should bemore promoted in the future by compering the existing problems and future development of MR image predicting CT image method.

Objective: To evaluate the possible mediation effect of DNA methylation in the associations between birth weight and adulthood obesity in women in China. Methods: A cross-sectional survey was conducted in 1 602 women with genetic relationship in urban area of Shanghai during March-December 2016. Information about their birth weight, birth length, current lifestyle and disease history were collected and body measurement was conducted at the interview. DNA methylation at specific sites of GNASAS, IGF2, IGF2-R, IL10 and LEP were measured using bisulphite pyrosequencing. Generalized estimating equations models with restricted cubic spline functions were used to estimate the associations of birth weight with BMI, waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-hip ratio (WHtR) in adulthood, and their associations with DNA methylation were evaluated using multilevel linear models. Multilevel structural equation models were used to evaluate the mediation effect of DNA methylation. Results: A significant non-linear association was observed between birth weight and WC as well as WHtR (P<0.05). Lower birth weight was associated with higher level of methylation at IGF2-DMR (CpG1, 2), IGF2-R (CpG8, 10, 13, 16 and 17), with β coefficients and 95%CI being -4.35 (-7.30- -1.39), -4.50 (-7.59- -1.41), -2.33 (-4.60- -0.05), -1.78 (-3.88- -0.33), -2.58 (-4.82- -0.34), -2.03 (-4.00- -0.06) and -1.87 (-3.73- -0.01), respectively, but related with a lower level of methylation at LEP CpG16 (β=4.19, 95%CI: 0.37- 8.00). Lower level of methylation at IGF2-DMR (CpG7), IGF2-R (CpG3, 5, 8, 9, 10, 14, 17, 19) and LEP (CpG3, 8, 10) was associated with larger WC, with β coefficients ranging from -0.016 to -0.040 (all P<0.05). Methylation at IGF2-R CpG8 was observed to mediate the association of birth weight and WC, and could explain 3.3% of the association. Conclusion Our results suggested that DNA methylation might mediate the effect of nutrition in uteri on adulthood central obesity in women in China.