Context: Polysaccharide of Taxus chinensis var. mairei Cheng et L.K.Fu (Taxaceae) (PTM) functions in antiapoptosis and antioxidation, but its function on Alzheimer's disease (AD) remains unclear. Objective: To investigate the effect of PTM on AD. Materials and methods: C57BL/6J mice were randomly divided into three groups: control, D-galactose (D-gal), and D-gal þ PTM. AD-like symptom was induced by D-gal for 6 weeks, followed with PTM (0.4 g/kg/d) for 14 days. PTM was added to BV2 cells stimulated with D-gal (1, 10, 20, 50, 100 and 500 lg/mL). Cell viability was evaluated by MTT assay. The expression of NRF2, SOD, cleaved caspase-3, Bax and Bcl-2 were detected with Western blot analysis. Cognitive function was evaluated by Morris water maze test. Results: Decreased cleaved caspase-3 (1.30 ± 0.09) and Bax/Bcl2 ratio (1.32 ± 0.11) were observed in BV2 cells induced by D-gal þ PTM (50 lg/mL). Increased MDA and ROS and decreased SOD were observed in D-gal group. However, decreased MDA (175 ± 9 ng/mL) and ROS level (188 ± 38 ng/mL) were observed after treated with PTM group (p < 0.05). In addition, the expression of NRF2 decreased in D-gal group (0.75 ± 0.09) but increased after treated with PTM (p < 0.05). Furthermore, decreased Ab1-42 was observed and the cognitive function was improved after PTM intervention (p < 0.05). Conclusions: This is the first report that PTM inhibited oxidative stress and apoptosis in AD. The result will further accelerate the applications of Taxus chinensis var. mairei and the treatment for AD.

Background The accumulation of advanced glycation end products (AGEs) occurring in skin tissues can be measured as skin autofluorescence (SAF). Here, we assessed the correlation between SAF values and the complexity and severity of type 2 diabetes mellitus (T2DM) complications. Methods The basic clinical information of 825 patients with T2DM was collected through an electronic system, and SAF was measured by adapting a DM-Scan, a non-invasive optical signal detector. Diabetic complications were diagnosed based on clinical criteria by experienced doctors. Linear regression analysis was used to evaluate the independent determinants of SAF, and multiple logistic regression analysis was performed to assess independent determinants that influence the severity of the complications. Results SAF was significantly associated with the complexity of T2DM complications. Similarly, independent relationships between SAF and age (β = 0.389, P <  0.001), sex (β = − 2.221, P = 0.004), 2-h C-peptide (β = − 0.182, P = 0.017), aminotransferase (ALT, β = − 0.158, P = 0.041), blood creatinine (BCr, β = 0.206, P = 0.009), and fatty liver (β = 0.161, P = 0.026) were observed. With the increasing number of complications, the SAF values increased significantly after adjusting for related risk factors. The SAF values correlated with diabetic retinopathy, diabetic kidney diseases, cardiovascular disease, and diabetic peripheral neuropathy when compared with patients without any T2DM-associated complications. Moreover, the AGE-based diabetic complication risk score for each complication demonstrated a relationship with the presence or absence of certain complications. Conclusion SAF is an independent marker for diabetic retinopathy, diabetic kidney diseases, cardiovascular disease, and diabetic peripheral neuropathy, and it is also a predictor of the complexity of T2DM complications. Moreover, the diabetic complication risk score is capable of predicting the risk of diabetic complications in patients with T2DM.

Objective. We aimed to analyze the correlation between the level of skin advanced glycation end products (AGEs) in type 2 diabetes mellitus (T2DM) patients and the diabetic retinopathy (DR) staging in different traditional Chinese medicine (TCM) syndromes. Methods. 416 T2DM patients were divided into normal group, nonproliferative diabetic retinopathy (NPDR) group (mild, moderate, and severe), and proliferative diabetic retinopathy (PDR) group according to the DR grade. Patients’ height, weight, fasting blood glucose (FBG), hemoglobin A1C (HbA1c), blood lipid, renal function, and skin AGEs were measured. According to TCM syndrome differentiation criteria, 230 patients with T2DM and DR were divided into I. qi and yin deficiency, collateral stasis group; II. liver and kidney deficiency, eye collaterals loss group; and III. yin and yang deficiency, blood stasis, and phlegm coagulation group. Results. The skin AGEs levels of different DR staging groups were statistically significant ( P < 0.05 ), and the skin AGEs levels in the mild and moderate NPDR groups were significantly higher ( P < 0.05 ) than those of the normal group. It was significantly higher ( P < 0.05 ) in the severe NPDR group than in the normal group, mild and moderate NPDR groups. The skin AGEs levels of the PDR group were significantly higher ( P < 0.05 ) than the normal group, mild and moderate NPDR groups. It was positively correlated with DR stage, HbA1c, total cholesterol (TC), low-density lipoprotein (LDL), and urine metal analysis (UMA) (r = 0.467, 0.411, 0.413, 0.503, 0.424, P < 0.05 ). The skin AGEs levels of the qi and yin deficiency and collaterals stasis syndrome group were significantly higher ( P < 0.05 ) than in the liver and kidney deficiency and eye collaterals loss groups. It was also significantly higher ( P < 0.05 ) in yin and yang deficiency, blood stasis, and phlegm coagulation syndrome groups than in qi and yin deficiency and collaterals stasis syndrome groups. Conclusion. There is a positive correlation between skin AGEs and DR staging in T2DM patients. Skin AGEs level is predictive for the risk of DR complications in T2DM patients and is vital in assessing DR degree per TCM syndrome type.

The paper has a discussion of forward problem and inverse problem for beams in strength of materials. Given loading condition can certainly determine its shearing force diagram and bending moment diagram, but conversely, there may be a variety of statically determinate or statically indeterminate constraint conditions. Furthermore, the solution from statically indeterminate constraint conditions doesn't agree with the given shearing force diagram and bending moment diagram in a general way.

Federated Learning is a distributed machine learning framework, which can be used in the Internet of Vehicles to train deep learning models without directly accessing the original data of mobile edge vehicle nodes. ECS can access massive data, but it has the characteristics of high latency and high communication overhead. However, mobile edge computing (MEC) platform can directly and efficiently communicate with mobile edge vehicle nodes. Combining the advantages of the two, a three-layer federated learning system of edge car network edge server cloud server is used. This system is supported by the HierFedProx algorithm and aggregates the model output of the edge car to the edge server to improve the model learning efficiency and reduce the global communication frequency. The experimental results show that the system can reduce the training time and improve the accuracy of the model compared with the federated learning without introducing the edge server.