Assisting immobile individuals with regular repositioning to adjust pressure distribution on key prominences such as the back and buttocks is the most effective measure for preventing pressure ulcers. However, compared to active self-repositioning, passive assisted repositioning results in distinct variations in force distribution on different body parts. This incongruity can affect the comfort of repositioning and potentially lead to a risk of secondary injury, for certain trauma or critically ill patients. Therefore, it is of considerable practical importance to study the passive turning comfort and the optimal turning strategy. Initially, in this study, the load-bearing characteristics of various joints during passive repositioning were examined, and a wedge-shaped airbag configuration was proposed. The airbags coupled layout on the mattress was equivalently represented as a spring-damping system, with essential model parameters determined using experimental techniques. Subsequently, different assisted repositioning strategies were devised by adjusting force application positions and sequences. A human-mattress force-coupled simulation model was developed based on rigid human body structure and equivalent flexible springs. This model provided the force distribution across the primary pressure points on the human body. Finally, assisted repositioning experiments were conducted with 15 participants. The passive repositioning effectiveness and pressure redistribution was validated based on the simulation results, experimental data, and questionnaire responses. Furthermore, the mechanical factors influencing comfort during passive assisted repositioning were elucidated, providing a theoretical foundation for subsequent mattress design and optimization of repositioning strategies.
ObjectiveTo observe expressions of E3 ubiquitin ligase—mitsugmin53 (MG53) protein, MG53 mRNA, and insulin receptor substrate 1 (IRS-1) mRNA in skeletal muscle of non-obese type 2 diabetic mellitus (T2DM) rats after gastric bypass operation (GBP), and to investigate possible mechanism of GBP in improving insulin resistance.MethodsTwenty-four healthy male GK rats were randomly divided into diabetic operation group, diabetic sham operation group, and diabetic control group, 8 rats in each group; besides, 8 male Wistar rats were served as normal control group. The expressions of MG53 protein in skeletal muscle tissue were detected by using Western blot method on week8 after operation. The mRNA levels of IRS-1 and MG53 in skeletal muscles tissue were measured by RT-PCR methods on week 8 after operation.Results① The expressions of MG53 protein and MG53 mRNA in the diabetic sham operation group and diabetic control group were significantly higher than those in the diabetic operation group and the normal control group on week 8 after operation (P<0.05), respectively, which had no significant differences between the diabetic operation group and the normal control group (P>0.05), and between the diabetic sham operation group and the diabetic control group (P>0.05) on week 8 after surgery. ② Compared with the normal control group, the expression of IRS-1 mRNA was significantly decreased in the diabetic operation group, the diabetic sham operation group, and the diabetic control group (P<0.05), while there were no significant differences between the diabetic operation group, diabetic sham operation group, and the diabetic control group on week 8 after operation (P>0.05).ConclusionExpression of E3 ubiquitin ligase—MG53 protein in skeletal muscle tissue in T2DM rats following GBP is decreased, thus reduces the IRS-1 ubiquitin-degradation, increase the expression of IRS-1 protein in insulin signaling pathway of skeletal muscle tissue, and improve insulin resistance of skeletal muscle.
ObjectiveTo explore the risk factors of lymph node metastasis (LNM) in patients with early gastric cancer (EGC), and try to establish a risk prediction model for LNM of EGC.MethodsThe clinicopathologic data of EGC patients who underwent radical gastrectomy and lymph node dissection from January 1, 2015 to December 31, 2019 in this hospital were retrospectively analyzed. Univariate analysis and logistic regression analysis were used to determine the risk factors for LNM of EGC, and the risk prediction model for LNM of EGC was established based on the multivariate results.ResultsA total of 311 cases of EGC were included in this study, and 60 (19.3%) cases had LNM. Univariate and multivariate analysis showed that age (younger), depth of tumor invasion (submucosa), vascular invasion, and undifferentiated carcinoma were the risk factors for LNM of EGC (P<0.05). The optimal threshold for predicting LNM of EGC was 0.158 (area under the receiver operating characteristic curve was 0.864), the sensitivity was 80.0%, and the specificity was 79.3%.ConclusionsFrom results of this study, risk factors for LNM of EGC have age, depth of invasion, vascular invasion, and differentiation degree. Risk prediction model for LNM of EGC established on this results has high sensitivity and specificity, which could provide some references for treatment strategy of EGC.