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Bladder urothelial carcinoma (BLCA) is a common malignant tumor of the human urinary system, and a large proportion of BLCA patients have a poor prognosis. Therefore, there is an urgent need to find more efficient and sensitive biomarkers for the prognosis of BLCA patients in clinical practice. RNA sequencing (RNA‐seq) data and clinical information were obtained from The Cancer Genome Atlas, and 584 energy metabolism‐related genes (EMRGs) were obtained from the Reactome pathway database. Cox regression analysis and least absolute shrinkage and selection operator analysis were applied to assess prognostic genes and build a risk score model. The estimate and cibersort algorithms were used to explore the immune microenvironment, immune infiltration, and checkpoints in BLCA patients. Furthermore, we used the Human Protein Atlas database and our single‐cell RNA‐seq datasets of BLCA patients to verify the expression of 13 EMRGs at the protein and single‐cell levels. We constructed a risk score model; the area under the curve of the model at 5 years was 0.792. The risk score was significantly correlated with the immune markers M0 macrophages, M2 macrophages, CD8 T cells, follicular helper T cells, regulatory T cells, and dendritic activating cells. Furthermore, eight immune checkpoint genes were significantly upregulated in the high‐risk group. The risk score model can accurately predict the prognosis of BLCA patients and has clinical application value. In addition, according to the differences in immune infiltration and checkpoints, BLCA patients with the most significant benefit can be selected for immune checkpoint inhibitor therapy.

Background: Bladder urothelial carcinoma (BLCA) is one of the most common malignant tumors with high morbidity and recurrence rate. The study aims to establish a prediction model to elaborate the relation between inflammatory response and prognosis of BLCA and thus to evaluate the potential prognostic value of inflammatory response–related genes (IRGs) in therapeutic choices.Methods: The study utilized the gene expression profiles from the The Cancer Genome Atlas and Gene Expression Omnibus (GSE32894) datasets. Differentially expressed IRGs between normal and tumor tissues were identified, and 10 of them were correlated with overall survival (OS) (p < 0.05). Then, the LASSO–Cox regression analysis was applied to optimize the signature. RNA sequencing data of patients with BLCA from GSE32894 were applied as a validation set. Cox regression analyses of the seven-gene signature were performed to examine the efficiency of signature in predicting prognosis. Receiver operating characteristic curve analysis was applied to measure the predictive performance of the risk score for OS. Analysis of independent prognostic factors, downstream functional enrichment, drug sensitivity, and immune features were included in this study.Results: The IRG signature (LDLR, ROS1, MMP14, TNFAIP6, MYC, PTGER4, and RIPK2) was used to divide patients into high- and low-risk groups. Cox regression analyses revealed that the risk score was an independent predictive factor. Functional enrichment analysis revealed that genes were enriched in prognosis-related molecular functions and immune-related biological processes. Drug sensitivity and tumor microenvironment correlation analysis indicated that the signature was related to immunotherapy effect.Conclusion: The study defined a new prognostic signature consisting of seven IRGs, which could effectively predict the prognosis of patients with BLCA and reveal relationship of immune features in BLCA with different risk scores. The study also provided a possible indicator for targeted therapy.

Autogenous healing of osteoporotic fractures is challenging, as the regenerative capacity of bone tissues is impaired by estrogen reduction and existed pro-inflammatory cytokines. In this study, a biofunctional ginsenoside Rg1 and strontium-containing mineral (SrHPO4, SrP)-incorporated biodegradable silk fibroin-gelatin (SG) scaffold (Rg1/SrP/SG) was developed to stimulate the osteoporotic bone repair. The incorporation of 15 wt% SrP significantly enhanced the mechanical strength, stimulated the osteogenic differentiation of mouse bone marrow mesenchymal stem cells, and suppressed the osteoclastogenesis of RAW264.7 in a concentration-related manner. The loading of Rg1 in SG and 15SrP/SG scaffolds obviously promoted the angiogenesis of human umbilical vein endothelial cells via activating the expression of vascular endothelial growth factor and basic fibroblast growth factor genes and proteins. The bioactive strontium ions (Sr2+) and Rg1 released from the scaffolds together mediated lipopolysaccharide-treated macrophages polarizing into M2 type. They downregulated the expression of inflammatory-related genes (interleukin (IL)-1β, tumor necrosis factor α, and IL-6) and stimulated the expression of genes related to anti-inflammation (Arginase and IL-10) as well as bone repair (BMP-2 and PDGF-BB) in the macrophages. The in vivo results also displayed that SrP and Rg1 significantly promoted the bone repair effect of SG scaffolds in osteoporotic critical-sized calvarial defects. Besides, the degradation rate of the scaffolds was close to the bone regeneration rate. Therefore, the simultaneous addition of SrP and Rg1 is a promising way for facilitating the osteoporotic bone repair activity of SG scaffolds via promoting the osteogenesis and angiogenesis, as well as inhibiting the osteoclastogenesis and inflammation.

As the final flow channel of the liquid rocket engine, the manufacturing of impinging atomization nozzles has become a critical link in the manufacture of impinging atomization components. At present, the high-precision machining of millimeter nozzles in large-scale production is quite difficult, which inevitably leads to the diversity of internal flow field and atomization field parameters. In this investigation, the influence of the diameter deviation of impinging nozzles on the atomization field is analyzed by experiment. The transparent nozzle is installed in a typical colliding atomizer. The ultra-precision measurement is carried out by the optical fiber measurement system and the flow field in the nozzle is visualized. The information of atomized droplets in the atomization field is assembled by the laser interferometric particle imaging technology (IPI). The experimental results indicate that the micro-deviations of the collision aperture have a profound influence on the cavitation state of the flow field in the nozzles and the atomization characteristics (droplet diameter and atomization cone angle) of the atomization field.

For the assembly of a multi-stage rotor, such as an aero-engine or gas turbine, the parts need to be assembled optimally to avoid excessive unbalance. We propose a method to optimize the unbalance of a multi-stage rotor during assembly. First, we developed an assembly error propagation model for a multi-stage rotor. The alignment process and distribution of the screw holes of the adjacent rotors was considered for the first time. Secondly, we propose a new assembly datum for unbalance optimization to ensure consistency with the actual conditions of a dynamic balance test. Finally, the unbalance optimization of a multi-stage rotor was achieved using a genetic algorithm, and the corresponding optimal assembly orientations of rotors at different stages were also identified. The results of the simulations showed that the assembly error propagation model had high accuracy and that the genetic optimization process had good convergence. The effect of unbalance optimization was also proven with experiments.