Salvianolic Acid B Prevents Bone Loss in Prednisone-Treated Rats through Stimulation of Osteogenesis and Bone Marrow Angiogenesis

Glucocorticoid (GC) induced osteoporosis (GIO) is caused by the long-term use of GC for treatment of autoimmune and inflammatory diseases. The GC related disruption of bone marrow microcirculation and increased adipogenesis contribute to GIO development. However, neither currently available anti-osteoporosis agent is completely addressed to microcirculation and bone marrow adipogenesis. Salvianolic acid B (Sal B) is a polyphenolic compound from a Chinese herbal medicine, Salvia miltiorrhiza Bunge. The aim of this study was to determine the effects of Sal B on osteoblast bone formation, angiogenesis and adipogenesis-associated GIO by performing marrow adipogenesis and microcirculation dilation and bone histomorphometry analyses. (1) In vivo study: Bone loss in GC treated rats was confirmed by significantly decreased BMD, bone strength, cancellous bone mass and architecture, osteoblast distribution, bone formation, marrow microvessel density and diameter along with down-regulation of marrow BMPs expression and increased adipogenesis. Daily treatment with Sal B (40 mg/kg/d) for 12 weeks in GC male rats prevented GC-induced cancellous bone loss and increased adipogenesis while increasing cancellous bone formation rate with improved local microcirculation by capillary dilation. Treatment with Sal B at a higher dose (80 mg/kg/d) not only prevented GC-induced osteopenia, but also increased cancellous bone mass and thickness, associated with increase of marrow BMPs expression, inhibited adipogenesis and further increased microvessel diameters. (2) In vitro study: In concentration from 10−6 mol/L to 10−7 mol/L, Sal B stimulated bone marrow stromal cell (MSC) differentiation to osteoblast and increased osteoblast activities, decreased GC associated adipogenic differentiation by down-regulation of PPARγ mRNA expression, increased Runx2 mRNA expression without osteoblast inducement, and, furthermore, Sal B decreased Dickkopf-1 and increased β-catenin mRNA expression with or without adipocyte inducement in MSC. We conclude that Sal B prevented bone loss in GC-treated rats through stimulation of osteogenesis, bone marrow angiogenesis and inhibition of adipogenesis

Effect of Austenitization Temperature on Microstructure and Mechanical Properties of B1500HS Boron Steel in the Hot Stamping

In the paper, a typical part of B1500HS boron steel was formed using the hot stamping tools, and the effect of austenitization temperature on the microstructure and mechanical properties of B1500HS boron steel was studied. The results show that, the temperature of steel plate has a significant effect on the temperature of hot stamping tools, and the temperature of punch rises at a faster speed than that of die in the hot stamping process. The austenitization temperature has a significant effects on the size of martensite. The cooling rate of steel plate has a significant effect on the tensile strength when the austenitization temperature is 870 °C. The fracture of sample austenitized at 870 °C or 900 °C is the dimple, the fracture of sample austenitized at 930 °C or 960 °C is the mixture of quasicleavage and dimple

Research on hot stamping for a typical part of B1500HS boron steel using experiment and numerical simulation methods

In the paper, a typical part of B1500HS boron steel was formed using the hot stamping tools, and the effect of austenitization temperature on the microstructure and mechanical properties of B1500HS steel was studied by the experiment and finite element methods. The results show that, the temperature of steel plate has a significant effect on the temperature of hot stamping tools, and the temperature of punch rises at a faster speed than that of die in the hot stamping process. The austenitization temperature and time both have significant effects on the size of martensite, but have not obvious effects on the hardness. The cooling rate of steel plate has a significant effect on the tensile strength when the austenitization temperature is 870 °C. The fracture of sample austenitized at 870 °C or 900 °C is the dimple, the fracture of sample austenitized at 930 °C or 960 °C is the mixture of quasicleavage and dimple

Research on hot stamping for a typical part of B1500HS boron steel using experiment and numerical simulation methods

In the paper, a typical part of B1500HS boron steel was formed using the hot stamping tools, and the effect of austenitization temperature on the microstructure and mechanical properties of B1500HS steel was studied by the experiment and finite element methods. The results show that, the temperature of steel plate has a significant effect on the temperature of hot stamping tools, and the temperature of punch rises at a faster speed than that of die in the hot stamping process. The austenitization temperature and time both have significant effects on the size of martensite, but have not obvious effects on the hardness. The cooling rate of steel plate has a significant effect on the tensile strength when the austenitization temperature is 870 °C. The fracture of sample austenitized at 870 °C or 900 °C is the dimple, the fracture of sample austenitized at 930 °C or 960 °C is the mixture of quasicleavage and dimple

Avionics Module Fault Diagnosis Algorithm Based on Hybrid Attention Adaptive Multi-Scale Temporal Convolution Network

Since the reliability of the avionics module is crucial for aircraft safety, the fault diagnosis and health management of this module are particularly significant. While deep learning-based prognostics and health management (PHM) methods exhibit highly accurate fault diagnosis, they have disadvantages such as inefficient data feature extraction and insufficient generalization capability, as well as a lack of avionics module fault data. Consequently, this study first employs fault injection to simulate various fault types of the avionics module and performs data enhancement to construct the P2020 communications processor fault dataset. Subsequently, a multichannel fault diagnosis method, the Hybrid Attention Adaptive Multi-scale Temporal Convolution Network (HAAMTCN) for the integrated functional circuit module of the avionics module, is proposed, which adaptively constructs the optimal size of the convolutional kernel to efficiently extract features of avionics module fault signals with large information entropy. Further, the combined use of the Interaction Channel Attention (ICA) module and the Hierarchical Block Temporal Attention (HBTA) module results in the HAAMTCN to pay more attention to the critical information in the channel dimension and time step dimension. The experimental results show that the HAAMTCN achieves an accuracy of 99.64% in the avionics module fault classification task which proves our method achieves better performance in comparison with existing methods

A CT-based integrated model for preoperative prediction of occult lymph node metastasis in early tongue cancer

Background Occult lymph node metastasis (OLNM) is an essential prognostic factor for early-stage tongue cancer (cT1-2N0M0) and a determinant of treatment decisions. Therefore, accurate prediction of OLNM can significantly impact the clinical management and outcomes of patients with tongue cancer. The aim of this study was to develop and validate a multiomics-based model to predict OLNM in patients with early-stage tongue cancer. Methods The data of 125 patients diagnosed with early-stage tongue cancer (cT1-2N0M0) who underwent primary surgical treatment and elective neck dissection were retrospectively analyzed. A total of 100 patients were randomly assigned to the training set and 25 to the test set. The preoperative contrast-enhanced computed tomography (CT) and clinical data on these patients were collected. Radiomics features were extracted from the primary tumor as the region of interest (ROI) on CT images, and correlation analysis and the least absolute shrinkage and selection operator (LASSO) method were used to identify the most relevant features. A support vector machine (SVM) classifier was constructed and compared with other machine learning algorithms. With the same method, a clinical model was built and the peri-tumoral and intra-tumoral images were selected as the input for the deep learning model. The stacking ensemble technique was used to combine the multiple models. The predictive performance of the integrated model was evaluated for accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC-ROC), and compared with expert assessment. Internal validation was performed using a stratified five-fold cross-validation approach. Results Of the 125 patients, 41 (32.8%) showed OLNM on postoperative pathological examination. The integrated model achieved higher predictive performance compared with the individual models, with an accuracy of 84%, a sensitivity of 100%, a specificity of 76.5%, and an AUC-ROC of 0.949 (95% CI [0.870–1.000]). In addition, the performance of the integrated model surpassed that of younger doctors and was comparable to the evaluation of experienced doctors. Conclusions The multiomics-based model can accurately predict OLNM in patients with early-stage tongue cancer, and may serve as a valuable decision-making tool to determine the appropriate treatment and avoid unnecessary neck surgery in patients without OLNM

Changes and significance of vascular endothelial injury markers in patients with diabetes mellitus and pulmonary thromboembolism

Abstract Background To investigate the changes and clinical significance of vascular endothelial injury markers in type 2 diabetes mellitus (T2DM) complicated with pulmonary embolism (PE). Methods This prospective study enrolled patients with T2DM hospitalized in one hospital from January 2021 to June 2022. Soluble thrombomodulin (sTM) (ELISA), von Willebrand factor (vWF) (ELISA), and circulating endothelial cells (CECs) (flow cytometry) were measured. PE was diagnosed by computed tomography pulmonary angiography (CTPA). Results Thirty participants were enrolled in each group. The plasma levels of sTM (151.22 ± 120.57 vs. 532.93 ± 243.82 vs. 1016.51 ± 218.00 pg/mL, P  676.68 pg/mL for the diagnosis of T2DM + PE achieved an AUC of 0.973, while vWF > 13.75 ng/mL achieved an AUC of 0.954. The combination of sTM and vWF above their cutoff points achieved an AUC of 0.993, with 100% sensitivity and 96.7% specificity. Conclusions Patients with T2DM show endothelial injury and dysfunction, which were worse in patients with T2DM and PE. High sTM and vWF levels have certain clinical predictive values for screening T2DM accompanied by PE