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Daam1 regulates fascin for actin assembly in mouse oocyte meiosis
Lu, Yujie,Zhang, Yu,Pan, Meng-Hao,Kim, Nam-Hyung,Sun, Shao-Chen,Cui, Xiang-Shun Landes Bioscience 2017 Cell Cycle Vol.16 No.14
<P>As a formin protein, Daam1 (Dishevelled-associated activator of morphogenesis 1) is reported to regulate series of cell processes like endocytosis, cell morphology and migration via its effects on actin assembly in mitosis. However, whether Daam1 plays roles in female meiosis remains uncertain. In this study, we investigated the expression and functions of Daam1 during mouse oocyte meiosis. Our results indicated that Daam1 localized at the cortex of oocytes, which was similar with actin filaments. After Daam1 morpholino (MO) microinjection, the expression of Daam1 significantly decreased, which resulted in the failure of oocyte polar body extrusion. These results might be due to the defects of actin assembly, since the decreased fluorescence intensity of actin filaments in oocyte cortex and cytoplasm were observed. However, Daam1 knockdown seemed not to affect the meiotic spindle movement. In addition, we found that fascin might be the down effector of Daam1, since the protein expression of fascin decreased after Daam1 knockdown. Thus, our data suggested that Daam1 affected actin assembly during oocyte meiotic division via the regulation of fascin expression.</P>
Zhang, Lu,Feng, Qiang,Wang, Jiuling,Zhang, Shuai,Ding, Baoquan,Wei, Yujie,Dong, Mingdong,Ryu, Ji-Young,Yoon, Tae-Young,Shi, Xinghua,Sun, Jiashu,Jiang, Xingyu American Chemical Society 2015 ACS NANO Vol.9 No.10
<P>The functionalized lipid shell of hybrid nanoparticles plays an important role for improving their biocompatibility and <I>in vivo</I> stability. Yet few efforts have been made to critically examine the shell structure of nanoparticles and its effect on cell–particle interaction. Here we develop a microfluidic chip allowing for the synthesis of structurally well-defined lipid-polymer nanoparticles of the same sizes, but covered with either lipid-monolayer-shell (MPs, monolayer nanoparticles) or lipid-bilayer-shell (BPs, bilayer nanoparticles). Atomic force microscope and atomistic simulations reveal that MPs have a lower flexibility than BPs, resulting in a more efficient cellular uptake and thus anticancer effect than BPs do. This flexibility-regulated cell–particle interaction may have important implications for designing drug nanocarriers.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/ancac3/2015/ancac3.2015.9.issue-10/acsnano.5b05792/production/images/medium/nn-2015-05792e_0007.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/nn5b05792'>ACS Electronic Supporting Info</A></P>
( Xibin Jia ),( Yujie Xiao ),( Dawei Yang ),( Zhenghan Yang ),( Chen Lu ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.10
To explore an effective non-invasion medical imaging diagnostics approach for hepatocellular carcinoma (HCC), we propose a method based on adopting the multiple technologies with the multi-parametric data fusion, transfer learning, and multi-scale deep feature extraction. Firstly, to make full use of complementary and enhancing the contribution of different modalities viz. multi-parametric MRI images in the lesion diagnosis, we propose a data-level fusion strategy. Secondly, based on the fusion data as the input, the multi-scale residual neural network with SPP (Spatial Pyramid Pooling) is utilized for the discriminative feature representation learning. Thirdly, to mitigate the impact of the lack of training samples, we do the pre-training of the proposed multi-scale residual neural network model on the natural image dataset and the fine-tuning with the chosen multi-parametric MRI images as complementary data. The comparative experiment results on the dataset from the clinical cases show that our proposed approach by employing the multiple strategies achieves the highest accuracy of 0.847±0.023 in the classification problem on the HCC differentiation. In the problem of discriminating the HCC lesion from the non-tumor area, we achieve a good performance with accuracy, sensitivity, specificity and AUC (area under the ROC curve) being 0.981±0.002, 0.981±0.002, 0.991±0.007 and 0.999±0.0008, respectively.
Detection of Grasping Position from Video Images Based on SSD
Taichi Kitayama,Huimin Lu,Yujie Li,Hyoungseop Kim 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10
Recently, consistent container transportation of roads and ships is mainstream of international freight transport. Because of various factors, automation of cargo handling work is required at the container terminal. Various causes are decrement of future labor force population by an increasing trend of container moving amount and declining birthrate and aging population. Therefore, this study presents the relative position of hanger and container measurement technology using Single Shot Multibox Detector (SSD) for the purpose of improvement of cargo handling work efficiency and unmanned container terminal. In the case of undetected by SSD, it will be detected using AKAZE feature. The proposed method is applied to 368 images of container gripping taken by a camera installed in a container crane. As a result, Interaction of Union (IoU) targeted for container gripping is 87.79%, and a detection rate is 94.57%.
Wide Residual Networks for Semantic Segmentation
Yoshiki NAKAYAMA,Huimin LU,Yujie LI,Hyoungseop KIM 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10
In the task of object recognition, convolutional neural networks (CNNs) have achieved high performance. In addition, these CNNs are also applied to the field of semantic image segmentation. However, applying the classification models to semantic segmentation tasks has a problem, lack of global context and reduction in resolution. In this work, we propose global context module and high resolution path in order to solve above problems. By simply combining them with an existing classification model (wide residual networks), our methods yield high-accuracy segmentation models. Our proposed approaches produce competitive results, the mean intersection over union (IoU) 67.6% and global accuracy 91.1%, on CamVid test set.
Superhydrophobic and smart MgAl-LDH anti-corrosion coating on AZ31 Mg surface
Manyi Huang,Guangming Lu,Jibin Pu,Yujie Qiang 한국공업화학회 2021 Journal of Industrial and Engineering Chemistry Vol.103 No.-
Layered double hydroxides (LDHs) have been widely used as ‘‘smart” containers in the field of metal corrosionprotection, and have broad industrial prospects. It is environmentally friendly and feasible to usealiphatic carboxylates and corresponding acids as substitutes for harmful corrosion inhibitors. However,previous studies rarely involved comparing the anti-corrosion mechanisms of different aliphatic acidsmodified on the LDH surface, and the durability of the prepared coatings also needs to be improved. Inthis work, MgAl-LDH laminates were grown in situ on AZ31 substrates by a hydrothermal method,and then modified by sodium laurate (SL) and sodium dodecylbenzene sulfonate (SDBS). Due to the physicalbarrier effect of the LDH layers, the spatial repulsion effect of the air film and the ion exchange reactionsin the interlayer galleries, the functional coatings prepared exhibit smart and superior anticorrosionperformance on the magnesium substrates in 3.5 wt.% NaCl solution. Compared with LDHSDBS-8 coating, the obtained superhydrophobic LDH-SL-8 coating shows more excellent long-term corrosionprotection owing to the stronger intercalation capacity.
Li Jiang,Junaid Ali Syed,Guoli Zhang,Yujie Ma,Jun Ma,Hongbin Lu,Xiangkang Meng 한국공업화학회 2019 Journal of Industrial and Engineering Chemistry Vol.80 No.-
The enhanced corrosion resistance with sustained conductivity are the prerequisites of stainless steelbipolar plates for practical application in proton exchange membrane fuel cell. Herein, we prepare aconductive polypyrrole-graphene oxide/polypyrrole-camphorsulfonic acid bilayer composite coating(PPY-GO/PPY-CSA) on 304 stainless steel bipolar plate by electrodeposition method. The electrochemicaltests are conducted in the simulated bipolar plates working environment, the potentiostatic polarizationresults imply that the PPY-GO/PPY-CSA composite coating offers stable corrosion resistance with lowpotentiostatic corrosion current density in comparison with the PPY-GO coating. The correspondingelectrochemical impedance spectroscopy measurements reveal that the PPY-GO/PPY-CSA compositecoating exhibits satisfactory conductivity and displays sustained anodic protection effect with superioranticorrosion performance during the 696 h of immersion. The excellent corrosion protection ability ofthe PPY-GO/PPY-CSA composite coating owing to its good adhesion strength, compact structure,satisfactory conductivity as well as the synergetic interaction between the two layers of the coating.
Recognition of Surrounding Environment for Electric Wheelchair Based on WideSeg
Yuki SAKAI,Yoshiki NAKAYAMA,Huimin LU,Yujie LI,Hyoungseop KIM 제어로봇시스템학회 2019 제어로봇시스템학회 국제학술대회 논문집 Vol.2019 No.10
At present, the aging population is growing in Japan. Along with that, the expectation for the utilization of welfare equipment is increasing. Electric wheelchair, a convenient transportation tool, is popularized rapidly. On the other hand, accidents have occurred, and the dangers for driving are pointed out. Therefore, it needs to improve accident factors, reduce accidents and improve the convenience of electric wheelchair by automation. Environmental recognition is necessary for the development of autonomous electric wheelchair. Environmental recognition includes self-position estimation, recognition of sidewalks, crosswalks and traffic lights, moving object prediction, etc. In order to solve these various problems, this paper examines the segmentation of sidewalks, crosswalks and traffic lights. We develop the WideSeg that is one of semantic segmentation algorithms applying convolutional neural networks (CNN).