25 research outputs found

    Original Article Neuroprotective effect of functionalized multi-walled carbon nanotubes on spinal cord injury in rats

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    Abstract: Traumatic injuries to the brain and spinal cord affect a large percentage of the world's population. However, there are currently no effective treatments for these central nervous system (CNS) injuries. In our study, we evaluated the neuroprotective role of functionalized multi-walled carbon nanotubes (MWCNTs) carrying brain derived neurotrophic factor (BNDF), nogo-66 receptor (NgR) and Ras homolog gene family member A (RhoA) in spinal cord injury (SCI). Our results showed that transfection into rat cortical neurons with BDNF-DNA significantly elevated the expression of BDNF both in vitro and in vivo. Meanwhile, transfection with NgR-siRNA and RhoA-siRNA resulted in an obvious down-regulation of NgR and RhoA in neuron cells and in injured spinal cords. In addition, the functionalized MWCNTs carrying BDNF-DNA, NgR-siRNA and RhoA-siRNA exhibited remarkable therapeutic effects on injured spinal cord. Taken together, our study demonstrates that functionalized MWCNTs have a potential therapeutic application on repair and regeneration of the CNS

    Regulation of angiogenesis by a non-canonical Wnt-Flt1 pathway in myeloid cells

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    Myeloid cells are a feature of most tissues. Here we show that during development, retinal myeloid cells (RMCs) produce Wnt ligands to regulate blood vessel branching. In the mouse retina, where angiogenesis occurs postnatally, somatic deletion in RMCs of the Wnt ligand transporter Wntless results in increased angiogenesis in the deeper layers. We also show that mutation of Wnt5a and Wnt11 results in increased angiogenesis and that these ligands elicit RMC responses via a non-canonical Wnt pathway. Using cultured myeloid-like cells and RMC somatic deletion of Flt1, we show that an effector of Wnt-dependent suppression of angiogenesis by RMCs is Flt1, a naturally occurring inhibitor of vascular endothelial growth factor (VEGF). These findings indicate that resident myeloid cells can use a non-canonical, Wnt-Flt1 pathway to suppress angiogenic branching

    CRIM1 Complexes with ß-catenin and Cadherins, Stabilizes Cell-Cell Junctions and Is Critical for Neural Morphogenesis

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    In multicellular organisms, morphogenesis is a highly coordinated process that requires dynamically regulated adhesion between cells. An excellent example of cellular morphogenesis is the formation of the neural tube from the flattened epithelium of the neural plate. Cysteine-rich motor neuron protein 1 (CRIM1) is a single-pass (type 1) transmembrane protein that is expressed in neural structures beginning at the neural plate stage. In the frog Xenopus laevis, loss of function studies using CRIM1 antisense morpholino oligonucleotides resulted in a failure of neural development. The CRIM1 knockdown phenotype was, in some cases, mild and resulted in perturbed neural fold morphogenesis. In severely affected embryos there was a dramatic failure of cell adhesion in the neural plate and complete absence of neural structures subsequently. Investigation of the mechanism of CRIM1 function revealed that it can form complexes with ß-catenin and cadherins, albeit indirectly, via the cytosolic domain. Consistent with this, CRIM1 knockdown resulted in diminished levels of cadherins and ß-catenin in junctional complexes in the neural plate. We conclude that CRIM1 is critical for cell-cell adhesion during neural development because it is required for the function of cadherin-dependent junctions

    A Short-Term Forecast Model of foF2 Based on Elman Neural Network

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    The critical frequency foF2 of the ionosphere F2 layer is one of the most important parameters of the ionosphere. Based on the Elman neural network (ENN), this paper constructs a single station forecasting model to predict foF2 one hour ahead. In order to avoid the network falling into local minimum, the model is optimized by the improved particle swarm optimization (IPSO). The input parameters used in the model include local time, seasonal information, solar cycle information and magnetic activity information. Data of the Wuhan Station from 2008 to 2016 were used to train and test the model. The prediction results of foF2 show that the root mean square error (RMSE) of the Elman neural network model is 4.30% lower than that of the back-propagation neural network (BPNN) model. The RMSE is further reduced by 8.92% after using the IPSO to optimize the model. This indicates that the Elman neural network model optimized by the improved particle swarm optimization is superior to the BP neural network and Elman neural network in the forecast of foF2 one hour ahead at Wuhan station

    Fault Diagnosis Model of Photovoltaic Array Based on Least Squares Support Vector Machine in Bayesian Framework

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    With the rapid development of the photovoltaic industry, fault monitoring is becoming an important issue in maintaining the safe and stable operation of a solar power station. In order to diagnose the fault types of photovoltaic array, a fault diagnosis method that is based on the Least Squares Support Vector Machine (LSSVM) in the Bayesian framework is put forward. First, based on the elaborate analysis of the change rules of the output electrical parameters and the equivalent circuit internal parameters of photovoltaic array in different fault states, the input variables of the photovoltaic array fault diagnosis model are determined. Second, through the LSSVM algorithm in the Bayesian framework, the fault diagnosis model based on the output electrical parameters and the equivalent circuit internal parameters of the photovoltaic array is built, which can effectively detect the photovoltaic array faults of short circuit, open circuit, and abnormal aging. Then, the simulation model is built to verify the validity of the LSSVM algorithm in the Bayesian framework by comparing it with the model of LSSVM and the Support Vector Machine (SVM). Moreover, a 5 × 3 photovoltaic array and a reference photovoltaic string are established and experimentally tested to validate the performance of the proposed method

    Analytical Formulation for Electromagnetic Leakage Field to Transmission Line Coupling through Covered Apertures of Multiple Enclosures

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    An efficient analytical model has been developed for predicting the electromagnetic leakage field coupling with a lossless two-conductor transmission line (TL) through covered apertures of multiple enclosures. The analytical results have been successfully compared with those from the full-wave simulation software CST over a broad frequency range. The analytical model can be employed to analyze the effect of different factors including the position and the direction of the electric dipole, the conductivity of the conductive sheet, the quantity of the aperture, and the direction of the TL on the induced currents. Besides, it can also deal with apertures in multiple sides of the enclosures

    Animating Geometrical Models Mesh morphing using polycube-based cross-parameterization

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    In this paper, we propose a novel mesh morphing approach based on polycubic crossparameterization. We compose parameterizations over the surfaces of the polycubes whose shape is similar to that of the given meshes. Because the polycubes capture the large-scale features, we can easily preserve the shape of the models, mapping legs to legs, head to head, and so on. For the finer features that are not reflected by the shape of the polycubes, we split the polycubes into matching patches and optimize them to get a low-distortion bijection that satisfies user-prescribed constraints. Our approach works well for meshes with arbitrary genus as long as the polycubes capture this feature and transfers texture seamlessly. We can also build maps with singularities between models with different genus. Copyright # 2005 John Wiley & Sons, Ltd. KEY WORDS: mesh morphing; cross-parameterization; polycube maps; texture transfe

    A brief overview of single-port laparoscopic appendectomy as an optimal surgical procedure for patients with acute appendicitis: still a long way to go

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    Single-port laparoscopic appendectomy (SPLA) has become a good alternative to the traditional surgical treatment of acute appendicitis, due to its advantages of small incision, mild postoperative pain, short hospital stay, and good cosmetic effect. However, the further application of SPLA has been restricted by its relatively long operating time, high level of operating difficulty, and increased equipment and technical requirements. Clinical teams worldwide have attempted to improve and optimize SPLA technical protocols and equipment to maintain stable intraoperative pneumoperitoneal pressure, improve the ‘triangle relationship’ of operating angles, and develop new surgical procedures with less trauma and higher cost-effectiveness. Here, new SPLA techniques reported over the past decade are reviewed and compared, with the aim of providing new insights into technical improvements, equipment upgrades and clinical studies in the coming years
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