Institution
Tongji University
Education•Shanghai, China•
About: Tongji University is a education organization based out in Shanghai, China. It is known for research contribution in the topics: Computer science & Population. The organization has 76116 authors who have published 81176 publications receiving 1248911 citations. The organization is also known as: Tongji & Tóngjì Dàxué.
Topics: Computer science, Population, Finite element method, Cancer, Adsorption
Papers published on a yearly basis
Papers
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TL;DR: The results imply that increased adsorption potentials of the sludge-based MPs to Cd are attributed to changes in the MP physicochemical properties during wastewater treatment process, and should be further concerned.
214 citations
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TL;DR: In this article, a state-of-the-art review was conducted on three types of novel engineered wood composites, namely fiber reinforced polymer (FRP) reinforced glulam, cross-laminated timber (CLT), and wood scrimber, with particular attentions to their manufacturing technologies, modeling approaches, and mechanical properties.
214 citations
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TL;DR: By applying the adaptive approach to the second model, this paper establishes a general adaptive theory for intermittent control, which can be applied not only to networks without time delay, but also to delayed networks, regardless of whether the intermittent control is periodic or aperiodic.
Abstract: In this paper, we investigate the exponential synchronization problem for linearly coupled networks with delay by pinning a simple aperiodically intermittent controller. The network topology can be directed. Different from previous works, the intermittent control can be aperiodic. Two types of delay are considered. The first case is that the delay is time-varying and large, and in this case, there is no restriction imposed on the delay and the control (and/or rest) width. The other one is that the delay is small enough so that it is less than the minimum of control width. Different approaches are provided to investigate these two cases, and some criteria are given to realize exponential synchronization. Furthermore, by applying the adaptive approach to the second model, we establish a general adaptive theory for intermittent control, which can be applied not only to networks without time delay, but also to delayed networks, regardless of whether the intermittent control is periodic or aperiodic. Finally, the numerical simulations are given to verify the validness of the theoretical results.
214 citations
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TL;DR: The aim is to identify the specific microRNA associated with the cancer and to predict the carcinogenetic mechanism of microRNA on the basis of these results.
Abstract: OBJECTIVE: To investigate the difference of microRNA expression profiles between colonic cancer without lymph node metastasis and the para-cancerous control, to identify the specific microRNA associated with the cancer and to predict the carcinogenetic mechanism of microRNA on the basis of these results.
METHODS: The microRNA (miRNA) were extracted and isolated from six specimens, including colonic cancerous and para-cancerous ones, all of which were confirmed to be without lymph node metastasis. Agilent microRNA microarrays consisting of 723 probes were used for screening the expression differences of microRNA. Data were analyzed using feature extraction software. The expression level of differentially expressed microRNA using quantitative real-time polymerase chain reaction (RT-PCR) was validated.
RESULTS: A total of 14 miRNAs were found to be associated with colonic cancer, in which the expression of miR-106b, miR-135b, miR-18a, miR-18b, miR-196b, miR-19a, miR-224, miR-335, miR-424, miR-20a*, miR-301b and miR-374a were up-regulated and the expression of miR-378 and miR-378* were downregulated in colonic cancer tissues, compared with the para-cancerous control. The expression level of miR-18a and miR-135b were validated in accordance with the results of RT-PCR.
CONCLUSION: The miRNAs are differentially expressed between colonic tumor tissues and para-cancerous tissues. Many of these miRNAs are expected to participate in the process of multiple tumorigenesis. These miRNAs could play an important role in the carcinogenesis of colon. These results provide new insights in human colorectal cancer genesis.
214 citations
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TL;DR: It is shown that TIGIT/PVR (poliovirus receptor) engagement disrupts granule polarization leading to loss of killing activity of NK cells, and Tyr225 or Asn227 mutation leads to restoration of TigIT/ PVR-mediated cytotoxicity, and SHIP1 silencing can dramatically abolish TIGit/Pvr-mediated killing inhibition.
Abstract: Activating and inhibitory receptors control natural killer (NK) cell activity. T-cell immunoglobulin and ITIM (immunoreceptor tyrosine-based inhibition motif) domain (TIGIT) was recently identified as a new inhibitory receptor on T and NK cells that suppressed their effector functions. TIGIT harbors the immunoreceptor tail tyrosine (ITT)-like and ITIM motifs in its cytoplasmic tail. However, how its ITT-like motif functions in TIGIT-mediated negative signaling is still unclear. Here, we show that TIGIT/PVR (poliovirus receptor) engagement disrupts granule polarization leading to loss of killing activity of NK cells. The ITT-like motif of TIGIT has a major role in its negative signaling. After TIGIT/PVR ligation, the ITT-like motif is phosphorylated at Tyr225 and binds to cytosolic adapter Grb2, which can recruit SHIP1 to prematurely terminate phosphatidylinositol 3-kinase (PI3K) and MAPK signaling, leading to downregulation of NK cell function. In support of this, Tyr225 or Asn227 mutation leads to restoration of TIGIT/PVR-mediated cytotoxicity, and SHIP1 silencing can dramatically abolish TIGIT/PVR-mediated killing inhibition.
214 citations
Authors
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Name | H-index | Papers | Citations |
---|---|---|---|
Gang Chen | 167 | 3372 | 149819 |
Yang Yang | 164 | 2704 | 144071 |
Georgios B. Giannakis | 137 | 1321 | 73517 |
Jian Li | 133 | 2863 | 87131 |
Jianlin Shi | 127 | 859 | 54862 |
Zhenyu Zhang | 118 | 1167 | 64887 |
Ju Li | 109 | 623 | 46004 |
Peng Wang | 108 | 1672 | 54529 |
Qian Wang | 108 | 2148 | 65557 |
Yan Zhang | 107 | 2410 | 57758 |
Richard B. Kaner | 106 | 557 | 66862 |
Han-Qing Yu | 105 | 718 | 39735 |
Wei Zhang | 104 | 2911 | 64923 |
Fabio Marchesoni | 104 | 607 | 74687 |
Feng Li | 104 | 995 | 60692 |