Background and Purpose:Previous studies have investigated the prognostic significance of skeletal muscle and adipose tissue composition and distribution in colorectal cancer patients,yet most have not differentiated between rectal and colon cancer patient cohorts.This study aimed to explore the relationship between body composition and long-term prognosis,and to develop a postoperative predictive model.Methods:Clinical data of rectal cancer patients who underwent surgical treatment at Qingdao University Affiliated Hospital from January 2018 to December 2021 were retrospectively collected.Inclusion criteria:①Age＞18 years;② Preoperative colonoscopy and pathological diagnosis of colorectal cancer;③ Complete surgical resection;④Abdominal computed tomography(CT)scan 1 month before surgery.Exclusion criteria:① Clinical data is missing;② Multiple metastases of tumors;③ Tumor T stage 0 or carcinoma in situ;④ Severe artifacts lead to poor quality CT imaging,making it difficult to distinguish between fat and muscle;⑤ Inability to obtain follow-up results.This study has been approved by the Medical Ethics Committee of the Affiliated Hospital of Qingdao University(approval number:QYFYWZLL30313),and informed consent has been waived in the ethical approval process.The skeletal muscle index(SMI)and subcutaneous adipose tissue index(SATI)were calculated by dividing the areas of skeletal muscle and subcutaneous fat observed on CT scans by the square of the patient's height.Univariate and multivariate COX regression analyses were conducted to identify risk factors influencing recurrence-free survival(RFS)and overall survival(OS)in rectal cancer patients.Based on the results of the multivariate analysis,a nomogram prediction model was developed,its predictive power and accuracy were assessed using the receiver operating characteristic(ROC)curve,calibration plots and decision curve analysis(DCA),and internal validation was conducted.Results:A total of 696 patients were included in this study,with 96(13.8%)patients experiencing postoperative recurrence and 89(12.8%)patients dying.Multivariate COX regression analysis showed that SMI,SATI,tumor T stage and N stage were independent factors affecting the postoperative RFS and OS of patients.Nomogram prediction models for RFS and OS in rectal cancer patients were constructed based on the above independent predictors.The area under ROC curve(AUC)for 3-,4-and 5-year RFS was 0.862,0.846 and 0.824,respectively;the AUC for 3-,4-and 5-year OS was 0.886,0.898 and 0.875,respectively.The models were evaluated using calibration curves and decision curves,and internal validation was performed,which showed that the prediction accuracy of the models was good.Conclusion:CT body composition is an independent predictor of RFS and OS in rectal cancer patients,and the nomogram model developed based on these factors demonstrates good predictive value for patient prognosis.

Background and Purpose:Previous studies have investigated the prognostic significance of skeletal muscle and adipose tissue composition and distribution in colorectal cancer patients,yet most have not differentiated between rectal and colon cancer patient cohorts.This study aimed to explore the relationship between body composition and long-term prognosis,and to develop a postoperative predictive model.Methods:Clinical data of rectal cancer patients who underwent surgical treatment at Qingdao University Affiliated Hospital from January 2018 to December 2021 were retrospectively collected.Inclusion criteria:①Age＞18 years;② Preoperative colonoscopy and pathological diagnosis of colorectal cancer;③ Complete surgical resection;④Abdominal computed tomography(CT)scan 1 month before surgery.Exclusion criteria:① Clinical data is missing;② Multiple metastases of tumors;③ Tumor T stage 0 or carcinoma in situ;④ Severe artifacts lead to poor quality CT imaging,making it difficult to distinguish between fat and muscle;⑤ Inability to obtain follow-up results.This study has been approved by the Medical Ethics Committee of the Affiliated Hospital of Qingdao University(approval number:QYFYWZLL30313),and informed consent has been waived in the ethical approval process.The skeletal muscle index(SMI)and subcutaneous adipose tissue index(SATI)were calculated by dividing the areas of skeletal muscle and subcutaneous fat observed on CT scans by the square of the patient's height.Univariate and multivariate COX regression analyses were conducted to identify risk factors influencing recurrence-free survival(RFS)and overall survival(OS)in rectal cancer patients.Based on the results of the multivariate analysis,a nomogram prediction model was developed,its predictive power and accuracy were assessed using the receiver operating characteristic(ROC)curve,calibration plots and decision curve analysis(DCA),and internal validation was conducted.Results:A total of 696 patients were included in this study,with 96(13.8%)patients experiencing postoperative recurrence and 89(12.8%)patients dying.Multivariate COX regression analysis showed that SMI,SATI,tumor T stage and N stage were independent factors affecting the postoperative RFS and OS of patients.Nomogram prediction models for RFS and OS in rectal cancer patients were constructed based on the above independent predictors.The area under ROC curve(AUC)for 3-,4-and 5-year RFS was 0.862,0.846 and 0.824,respectively;the AUC for 3-,4-and 5-year OS was 0.886,0.898 and 0.875,respectively.The models were evaluated using calibration curves and decision curves,and internal validation was performed,which showed that the prediction accuracy of the models was good.Conclusion:CT body composition is an independent predictor of RFS and OS in rectal cancer patients,and the nomogram model developed based on these factors demonstrates good predictive value for patient prognosis.

Objective:To explore the robust relationship between insomnia and type 2 diabetes mellitus by two-sample Mendelian randomization analysis to overcome confounding factors and reverse causality in observational studies.Methods:We identified strong,independent single nucleotide polymorphisms(SNPs)of insomnia from the most up to date genome wide association studies(GWAS)within European ancestors and applied them as instrumental variable to GWAS of type 2 diabetes mellitus.After excluding SNPs that were significantly associated with smoking,physical activity,alcohol consumption,educational attainment,obesity,or type 2 diabetes mellitus,we assessed the impact of insomnia on type 2 diabetes mellitus using inverse variance weighting(IVW)method.Weighted median and MR-Egger regression analysis were also conducted to test the robustness of the association.We calculated the F statistic of the selected SNPs to test the applicability of instrumental variable and F statistic over than ten indicated that there was little possibility of bias of weak instrumental variables.We further examined the existence of pleiotropy by testing whether the intercept term in MR-Egger regression was significantly different from ze-ro.In addition,the leave-one-out method was used for sensitivity analysis to verify the stability and relia-bility of the results.Results:We selected 248 SNPs independently associated with insomnia at the genome-wide level(P＜5 ×10-8)as a preliminary candidate set of instrumental variables.After clum-ping based on the reference panel from 1000 Genome Project and removing the potential pleiotropic SNPs,a total of 167 SNPs associated with insomnia were included as final instrumental variables.The F statistic of this study was 39.74,which was in line with the relevance assumption of Mendelian randomi-zation.IVW method showed insomnia was associated with higher risk of type 2 diabetes mellitus that po-pulation with insomnia were 1.14 times more likely to develop type 2 diabetes mellitus than those without insomnia(95％CI:1.09-1.21,P＜0.001).The weighted median estimator(WME)method and MR-Egger regression showed similar causal effect of insomnia on type 2 diabetes mellitus.And MR-Egger re-gression also showed that the effect was less likely to be triggered by pleiotropy.Sensitivity analyses pro-duced directionally similar estimates.Conclusion:Insomnia is a risk factor of type 2 diabetes mellitus,which has positively effects on type 2 diabetes mellitus.Our study provides further rationale for indivi-duals at risk for diabetes to keep healthy lifestyle.

Objective: To understand current situation of school meal program in Hebei Province and the satisfaction among students and their parents. Methods: Multi-stage random cluster sampling was used to select 24 primary and secondary schools in the three cities of Shijiazhuang, Tangshan and Cangzhou in Hebei Province. A total of 2 739 students from grades 2, 5 and 8 were randomly selected, and 2 716 parents were surveyed. Results: There were 958 students who were very satisfied with the school lunch, 717 who were more satisfied, 686 who were generally satisfied, 221 who were less satisfied, and 157 who were very dissatisfied. Among them, the satisfaction of students in Shijiazhuang and Tangshan was higher than that in Cangzhou(Z=51.42, P<0.01), and the satisfaction of students in urban areas was higher than that in suburbs(Z=4.12, P<0.01). The satisfaction of young students was higher than that of high students(Z=151.42, P<0.01). There were statistically significant differences in some aspects which as food hygiene, food appearance, lunch quantity, food tastes, foodpairing and lunch price among parents of students in the three cities(P<0.01). Conclusion Students and parents are generally statisfied with school lunches, but the taste of meals served in schools needs to be improved, and the government needs to invest more in school meals and provide scientific training for cafeteria staff on a regular basis. Parents’ opinions and suggestions on feeding to improve the quality of feeding.

AIM: Tissue engineered periosteum fabricated by porcine small intestinal submucosa (SIS) combined with rabbit bone marrow-derived mesenchymal stem cells (BMSCs), are similar to the natural periosteum in the morphology, structure and function. The study was designed to explore the cell attachment in process of constructing tissue-engineered periosteum by different wetting methods to determine the most effective method of fabricating tissue-engineered periosteum. METHODS: The experiment was carried out in the Institute of Orthopedics, the Second Affiliated Hospital of Lanzhou University from September 2005 to March 2007.①Two New Zealand purebred rabbits, 20 days old, were used in this study.②Bone marrow was obtained from healthy rabbits, and BMSCs were isolated by using density gradient centrifugation for culture in vitro. After induction, BMSCs were seeded to SIS wetted with fetal bovine serum (experimental group) and pretreated with phosphate buffered saline (control group), to construct the tissue-engineered periosteum that was cultured for two weeks in vitro. ③The adhesion rates were calculated, and alkaline phosphatase (ALP) activity was detected after seeding. The growth, dissociation and proliferation of the cells were observed by inverted microscope and scanning electron microscope. RESULTS: ①At 5 hours and 12 hours after seeding, the adhesion rates were higher in the experimental group than in the control group [(57.34?2.23)%, (39.16?5.22)%, P