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您的检索式：作者名="Wanwan Peng"
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| 1 | Glycolipid iGb3 feedback amplifies innate immune responses via CD1d reverse signaling显示文摘The cross-talk between cellular lipid metabolism and the innate immune responses remains obscure. In addition to presenting lipid antigens to Natural Killer T-cells (NKT cells), the Cluster of Differentiation 1D Glycoprotein (CD1d) might mediate reverse signaling in antigen-presenting cells (APCs). Here we found CD1d deficiency attenuated Toll-like receptor (TLR)-triggered inflammatory innate responses in macrophages and dendritic cells, protecting mice from endotoxin shock. TLR activation in macrophages induced metabolic changes of glycosphingolipids (GSLs), among which glycolipid isoglobotrihexosylceramide (iGb3) was rapidly produced. The endogenously generated iGb3 bound CD1d in endosomal compartments and then synergized with the initially activated TLR signal to induce Tyr332 phosphorylation of CD1d intracellular domain. This led to the recruitment and activation of proline-rich tyrosine kinase 2 (Pyk2). Pyk2 interacted with IκB kinase β (IKKβ) and TANK-binding kinase 1 (TBK1), and enhanced tyrosine phosphorylation of Tyr188/199 of IKKβ and Tyr179 of TBK1 and thus, their activation to promote full activation of TLR signaling. Thus, intracellular CD1d reverse signaling, triggered by endogenous iGb3, amplifies inflammatory innate responses in APCs. Our findings identify a non-canonical function of CD1d reverse signaling activated by lipid metabolite in the innate immune response. | Xingguang Liu Peng Zhang Yunkai Zhang Zheng Wang Sheng Xu Yingke Li Wanwan Huai Qingqing Zhou Xiang Chen Xi Chen Nan Li Peng Wang Yunsen Li Xuetao Cao | 2019 | Cell Research2019，29，1： | 1 |
| 2 | Hollow carbon microbox from acetylacetone as anode material for sodium-ion batteries显示文摘Carbon-based materials have attracted much interest as one of the promising anodes for sodium-ion batteries. However, low utilization of electrolyte and slow ion-transfer rate during electrochemical process hinder the further application of traditional bulk carbon. In order to enhance the diffusion kinetics and maintain the reversibility, hierarchical hollow carbon microbox was successfully prepared through a tunable bottom-up self-template routine for sodium-ion batteries. During annealing process, the morphology construction and activation happened synchronously. Based on that, a range of cross-linked porous nanosheet and hollow microbox were attained by manipulating reactant condition. The generation of texture and physical property are analyzed and are established linkages related to the electrochemical behavior. As results depicted in kinetic exploration and simulation based on cyclic voltammetry, the surfacecontrolled electrochemical behavior gradually turns to be the diffusion-controlled behavior as the hollow microbox evolves to porous nanosheet. The probable reason is that the rational microstructure/texture design leads to the accelerated diffusion kinetic procedure and the reduced concentration difference polarization. Sodium storage mechanism was deduced as reversible binding of Na-ions with local defects,including vacancies on sp2 graphitic layers, at the edges of flakes and other structural defects instead of intercalation. Bestowed by the morphology design, the broad pore width distribution, abundant defects/active sites and surface functionality, hollow microbox electrode delivers great electrochemical performances. This work is expected to propose a novel and effective strategy to prepare tunable hierarchical hollow carbon microbox and induce the fast kinetic of carbon anode material. | Tianyun Qiu Wanwan Hong Lin Li Yu Zhang Peng Cai Cheng Liu Jiayang Li Guoqiang Zou Hongshuai Hou Xiaobo Ji | 2020 | Journal of Energy Chemistry2020，29，12： | 1 |
| 3 | Deeper Attention-Based Network for Structured Data显示文摘Deep learning methods are applied into structured data and in typical methods,low-order features are discarded after combining with high-order featuresfor prediction tasks.However,in structured data,ignorance of low-order features may cause the low prediction rate.To address this issue,in this paper,deeper attention-based network(DAN)is proposed.With DAN method,to keep both low-and high-order features,attention average pooling layer was utilized to aggregate features of each order.Furthermore,by shortcut connections from each layer to attention average pooling layer,DAN can be built extremely deep to obtain enough capacity.Experimental results show DAN has good performance and works effectively. | Xiaohua Wu Youping Fan Wanwan Peng Hong Pang Yu Luo | 2020 | 国际计算机前沿大会会议论文集2020，，1： | 0 |
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