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Fluid-structural coupling occurs when microcantilever sensors vibrate in a fluid. Due to the complexity of the mechanical characteristics of microcantilevers and lack of high-precision microscopic mechanical testing instruments, effective methods for studying the fluid-structural coupling of microcantilevers are lacking, especially for non-rectangular microcantilevers. Here, we report fluid-structure interactions (FSI) of the cable-membrane structure via a macroscopic study. The simplified aeroelastic model was introduced into the microscopic field to establish a fluid-structure coupling vibration model for microcantilever sensors. We used the finite element method to solve the coupled FSI system. Based on the simplified aeroelastic model, simulation analysis of the effects of the air environment on the vibration of the commonly used rectangular microcantilever was also performed. The obtained results are consistent with the literature. The proposed model can also be applied to the auxiliary design of rectangular and non-rectangular sensors used in fluid environments.  相似文献   
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ObjectiveWe investigated whether glutamate, NMDA receptors, and eukaryote elongation factor-2 kinase (eEF-2K)/eEF-2 regulate P-glycoprotein expression, and the effects of the eEF-2K inhibitor NH125 on the expression of P-glycoprotein in rat brain microvessel endothelial cells (RBMECs).MethodsCortex was obtained from newborn Wistar rat brains. After surface vessels and meninges were removed, the pellet containing microvessels was resuspended and incubated at 37°C in culture medium. Cell viability was assessed by the MTT assay. RBMECs were identified by immunohistochemistry with anti-vWF. P-glycoprotein, phospho-eEF-2, and eEF-2 expression were determined by western blot analysis. Mdr1a gene expression was analyzed by RT-PCR.ResultsMdr1a mRNA, P-glycoprotein and phospho-eEF-2 expression increased in L-glutamate stimulated RBMECs. P-glycoprotein and phospho-eEF-2 expression were down-regulated after NH125 treatment in L-glutamate stimulated RBMECs.ConclusionseEF-2K/eEF-2 should have played an important role in the regulation of P-glycoprotein expression in RBMECs. eEF-2K inhibitor NH125 could serve as an efficacious anti-multidrug resistant agent.  相似文献   
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Weilan Ye 《The EMBO journal》2014,33(8):786-787
Since metastatic lesions of solid tumors are the major cause of mortality in cancer patients, understanding the molecular mechanisms of metastasis is of paramount importance. Although extensive knowledge has been accumulated regarding the early steps in metastasis—starting with the departure of cancer cells from their primary sites, to their transit through the hematogenous and/or lymphatic systems, and ending with their entrance into the parenchyma of distant organs—it is difficult if not impossible to translate such knowledge into medicine due to the challenge of identifying patients with only primary tumors but otherwise pristine organs. In other words, autopsy studies indicate that a large proportion of patients already harbor dormant, undetectable micrometastases at the time of cancer diagnosis (Hensel et al, 2013 ). Accordingly, stopping tumor cell dissemination is too late for these patients. Therefore, understanding the survival and outgrowth of micrometastases may hold greater promise to combat metastatic disease.  相似文献   
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World Journal of Microbiology and Biotechnology - Antibiotic and arsenic (As) contaminations are worldwide public health problems. Previously, the bacterial ABC-type efflux protein MacAB reportedly...  相似文献   
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Applied Microbiology and Biotechnology - Avibacterium paragallinarum is a Gram-negative bacterium that causes infectious coryza in chicken. It was reported that the capsule polysaccharides...  相似文献   
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In this paper, the panel count data analysis for recurrent events is considered. Such analysis is useful for studying tumor or infection recurrences in both clinical trial and observational studies. A bivariate Gaussian Cox process model is proposed to jointly model the observation process and the recurrent event process. Bayesian nonparametric inference is proposed for simultaneously estimating regression parameters, bivariate frailty effects, and baseline intensity functions. Inference is done through Markov chain Monte Carlo, with fully developed computational techniques. Predictive inference is also discussed under the Bayesian setting. The proposed method is shown to be efficient via simulation studies. A clinical trial dataset on skin cancer patients is analyzed to illustrate the proposed approach.  相似文献   
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