Flow field calculation and dynamic characteristic analysis of spherical hybrid gas bearings based on passive grid

In order to research the spherical spiral groove hybrid gas bearings, the Realizable k − ε turbulence model of gas film was established based on FLUENT. The simulation calculation method of 6-degrees of freedom passive grid was used, which can simulate the lubrication characteristics of the gas film transient flow field accurately. And the gas film pressure distribution and dynamic characteristic coefficients are numerically calculated. The dynamic and static pressure coupling effects of the gas flow field were analyzed, and the axis motion trajectory was simulated. The effect of rotation speed, gas supply pressure and tangential angle on the dynamic characteristic coefficients during bearing operation was analyzed. And the stability of the gas bearing was studied. The conclusion from the analysis shows that different rotation speed and gas supply pressure will change the pressure distribution of the gas bearing during the operation. The dynamic characteristics of the gas film can be changed by reasonably optimizing the operation parameters, which can change the whirl characteristics of the gas film and improve the stability. Through calculation and analysis, the tangential angle is selected between 55° and 60°, to ensure that the gas film has a high stiffness, while it also can obtain the larger damping. The simulation results and the experimental results are compared and analyzed to verify the correctness and effectiveness of the simulation method. At the same time, the research of this paper provided a theoretical basis for optimizing the bearing structure and operating parameters, improving the dynamic characteristics of gas bearings and improving the operation stability

Genomic Analyses Reveal Mutational Signatures and Frequently Altered Genes in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers worldwide and the fourth most lethal cancer in China. However, although genomic studies have identified some mutations associated with ESCC, we know little of the mutational processes responsible. To identify genome-wide mutational signatures, we performed either whole-genome sequencing (WGS) or whole-exome sequencing (WES) on 104 ESCC individuals and combined our data with those of 88 previously reported samples. An APOBEC-mediated mutational signature in 47% of 192 tumors suggests that APOBEC-catalyzed deamination provides a source of DNA damage in ESCC. Moreover, PIK3CA hotspot mutations (c.1624G>A [p.Glu542Lys] and c.1633G>A [p.Glu545Lys]) were enriched in APOBEC-signature tumors, and no smoking-associated signature was observed in ESCC. In the samples analyzed by WGS, we identified focal (<100 kb) amplifications of CBX4 and CBX8. In our combined cohort, we identified frequent inactivating mutations in AJUBA, ZNF750, and PTCH1 and the chromatin-remodeling genes CREBBP and BAP1, in addition to known mutations. Functional analyses suggest roles for several genes (CBX4, CBX8, AJUBA, and ZNF750) in ESCC. Notably, high activity of hedgehog signaling and the PI3K pathway in approximately 60% of 104 ESCC tumors indicates that therapies targeting these pathways might be particularly promising strategies for ESCC. Collectively, our data provide comprehensive insights into the mutational signatures of ESCC and identify markers for early diagnosis and potential therapeutic targets

Quantitative evaluation of the immunodeficiency of a mouse strain by tumor engraftments

© 2015 Ye et al. Background: The mouse is an organism that is widely used as a mammalian model for studying human physiology or disease, and the development of immunodeficient mice has provided a valuable tool for basic and applied human disease research. Following the development of large-scale mouse knockout programs and genome-editing tools, it has become increasingly efficient to generate genetically modified mouse strains with immunodeficiency. However, due to the lack of a standardized system for evaluating the immuno-capacity that prevents tumor progression in mice, an objective choice of the appropriate immunodeficient mouse strains to be used for tumor engrafting experiments is difficult. Methods: In this study, we developed a tumor engraftment index (TEI) to quantify the immunodeficiency response to hematologic malignant cells and solid tumor cells of six immunodeficient mouse strains and C57BL/6 wild-type mouse (WT). Results: Mice with a more severely impaired immune system attained a higher TEI score. We then validated that the NOD-scid-IL2Rg-/- (NSI) mice, which had the highest TEI score, were more suitable for xenograft and allograft experiments using multiple functional assays. Conclusions: The TEI score was effectively able to reflect the immunodeficiency of a mouse strain.Link_to_subscribed_fulltex

A Modified Back Propagation Artificial Neural Network Model Based on Genetic Algorithm to Predict the Flow Behavior of 5754 Aluminum Alloy

In order to predict flow behavior and find the optimum hot working processing parameters for 5754 aluminum alloy, the experimental flow stress data obtained from the isothermal hot compression tests on a Gleeble-3500 thermo-simulation apparatus, with different strain rates (0.1&ndash;10 s&ndash;1) and temperatures (300&ndash;500 &deg;C), were used to construct the constitutive models of the strain-compensation Arrhenius (SA) and back propagation (BP) artificial neural network (ANN). In addition, an optimized BP&ndash;ANN model based on the genetic algorithm (GA) was established. Furthermore, the predictability of the three models was evaluated by the statistical indicators, including the correlation coefficient (R) and average absolute relative error (AARE). The results showed that the R of the SA model, BP&ndash;ANN model, and ANN&ndash;GA model were 0.9918, 0.9929, and 0.9999, respectively, while the AARE of these models was found to be 3.2499&ndash;5.6774%, 0.0567&ndash;5.4436% and 0.0232&ndash;1.0485%, respectively. The prediction error of the SA model was high at 400 &deg;C. It was more accurate to use the BP&ndash;ANN model to determine the flow behavior compared to the SA model. However, the BP&ndash;ANN model had more instability at 300 &deg;C and a true strain in the range of 0.4&ndash;0.6. When compared with the SA model and BP&ndash;ANN model, the ANN&ndash;GA model had a more efficient and more accurate prediction ability during the whole deformation process. Furthermore, the dynamic softening characteristic was analyzed by the flow curves. All curves showed that 5754 aluminum alloy showed the typical rheological characteristics. The flow stress rose rapidly with increasing strain until it reached a peak. After this, the flow stress remained constant, which demonstrates a steady flow softening phenomenon. Besides, the flow stress and the required variables to reach the steady state deformation increased with increasing strain rate and decreasing temperature

Research on dynamic characteristics of gas film of spherical hybrid gas bearings based on computational fluid dynamics

A realizable k–ε turbulence model for spherical spiral groove hybrid gas bearing films was established based on computational fluid dynamics (CFD). A six degrees of freedom passive grid was used to calculate the gas film pressure distribution, bearing capacity, and dynamic characteristic coefficients numerically. The gas flow field dynamic and static pressure coupling mechanism was studied. The effects of the rotation speed, gas film thickness eccentricity ratio, and gas supply pressure on the dynamic and static pressure bearing capacity, and dynamic characteristic coefficients during operation were analyzed as a method of research into the mechanical mechanisms of gas bearing stability. The CFD calculation analysis can simulate the complex gas flow in the transient flow field of the gas film and determine reasonable operation parameters to optimize the dynamic and static pressure coupling effects, which can improve the gas film bearing capacity, dynamic characteristics, and operational stability of gas bearings

Numerical and analytical flow models in ecological channels with interaction of vegetation and freshwater

Aquatic vegetation interferes with river hydrodynamics, thus affecting the mass transport and energy transfer in an ecosystem. The flow over submerged vegetation is characterized by a complex velocity profile and multiple turbulence structures, which have been usually simulated using cylinders or strips in previous studies. Because the simplified vegetation configuration may hide or amplify some physical processes found in natural conditions, we investigate the velocity distribution and turbulence structure in foliaged vegetation flows using both analytical and numerical approaches. The main innovations and findings can be summarized as follows: 1) numerical and analytical models adopted in this paper accurately simulate the flow velocity profile in vegetated channel; 2) the Karman constant is found to be unsuitable for complex vegetation morphologies, so we proposed adjusted coefficient; 3) an image processing method is adopted to quantify the vegetation morphology accurately; 4) the existing mixing-layer thickness formula is found to be unsuitable for vegetation with leaves, an improved formula is proposed showing high correlation coefficient (0.9562) between measured and predicted data; 5) to ensure applicability to larger-scale hydrodynamic simulations, an analytical expression of Manning’s coefficient is proposed based on an analytical multi-layer flow velocity model. These research findings can provide theoretical support for the design of vegetated river and ecological restoration

Apatinib exhibits anti-leukemia activity in preclinical models of acute lymphoblastic leukemia

Abstract Background Acute lymphoblastic leukemia (ALL) is a clonal malignant disorder characterized by an uncontrolled proliferation of immature B or T lymphocytes. Extensive studies have suggested an involvement of angiogenesis signaling in ALL progression and resistance to treatment. Thus, targeting angiogenesis with anti-angiogenic drugs may be a promising approach for ALL treatment. In this study, we investigated the effectiveness of Apatinib, a novel receptor tyrosine kinase inhibitor selectively targeting VEGFR-2 in ALL cells. Method ALL cell lines were treated with different concentration of Apatinib and then CCK8 assay, flow cytometry were used to determine the IC50 value and cell apoptosis, respectively. The effect of Apatinib against primary ALL cells from 11 adult patients and normal counterparts were also analyzed by apoptosis with flow cytometry. Next, we used western bolting and mass cytometry (CyTOF) assay to explore the underlying mechanism of the cytotoxicity of Apatinib. Finally, the anti-leukemia activity was further evaluated in an in vivo xenograft model of ALL. Results Our results showed that Apatinib significantly inhibited cell growth and promoted apoptosis in both B and T lineage ALL cell lines in a dose- and time-dependent manner. The IC50 values of Apatinib against Nalm6, Reh, Jurkat and Molt4 for 48 h were 55.76 ± 13.19, 51.53 ± 10.74, 32.43 ± 5.58, 39.91 ± 9.88 μmol/L, and for 72 h were 30.34 ± 2.65, 31.96 ± 3.92, 17.62 ± 5.90, and 17.65 ± 2.17 μmol/L respectively. Similarly, Apatinib shows cytotoxic activity against primary adult ALL cells while sparing their normal counterparts in vitro. Moreover, Apatinib suppressed ALL growth and progression in an in vivo xenograft model. Mechanistically, Apatinib-induced cytotoxicity was closely associated with inhibition of VEGFR2 and its downstream signaling cascades, including the PI3 K, MAPK and STAT3 pathways. Conclusion Our study indicates that Apatinib exerts its anti-leukemia effect by inducing apoptosis through suppressing the VEGFR2 signaling pathway, supporting a potential role for Apatinib in the treatment of ALL