Time filter

Source Type

Shanghai, China

Tongji University , colloquially known as Tongji , located in Shanghai, has more than 50,000 students and 8,000 staff members . It offers degree programs at both undergraduate and postgraduate levels. Established in 1907 by the German government together with German physicians in Shanghai, Tongji is one of the oldest and most prestigious universities in China. Among its various departments it is especially highly ranked in engineering, among which its architecture, urban planning and civil engineering departments have consistently ranked first in China for decades, and its automotive engineering, oceanography, environmental science, software engineering, German language departments are also ones of the best domestically. Wikipedia.

Yan B.,Tongji University
RSC Advances | Year: 2012

This critical review mainly focuses on recent research progress in photofunctional lanthanide hybrid materials. The review covers hybrids with complexes of organically modified silanes as precursors for sol-gel processing, hybrids with lanthanide complex units grafted onto the interior of mesoporous hosts, hybrids with lanthanide complex units on polymer chains, and other non-silica or composite-based lanthanide hybrids. The photophysical properties of lanthanide hybrids are also discussed. Finally, future challenges and opportunities in this field are discussed. © The Royal Society of Chemistry. 2012.

Tang D.G.,University of Texas M. D. Anderson Cancer Center | Tang D.G.,Tongji University
Cell Research | Year: 2012

Heterogeneity is an omnipresent feature of mammalian cells in vitro and in vivo. It has been recently realized that even mouse and human embryonic stem cells under the best culture conditions are heterogeneous containing pluripotent as well as partially committed cells. Somatic stem cells in adult organs are also heterogeneous, containing many subpopulations of self-renewing cells with distinct regenerative capacity. The differentiated progeny of adult stem cells also retain significant developmental plasticity that can be induced by a wide variety of experimental approaches. Like normal stem cells, recent data suggest that cancer stem cells (CSCs) similarly display significant phenotypic and functional heterogeneity, and that the CSC progeny can manifest diverse plasticity. Here, I discuss CSC heterogeneity and plasticity in the context of tumor development and progression, and by comparing with normal stem cell development. Appreciation of cancer cell plasticity entails a revision to the earlier concept that only the tumorigenic subset in the tumor needs to be targeted. By understanding the interrelationship between CSCs and their differentiated progeny, we can hope to develop better therapeutic regimens that can prevent the emergence of tumor cell variants that are able to found a new tumor and distant metastases. © 2012 IBCB, SIBS, CAS All rights reserved.

Detecting the borders between coding and non-coding regions is an essential step in the genome annotation. And information entropy measures are useful for describing the signals in genome sequence. However, the accuracies of previous methods of finding borders based on entropy segmentation method still need to be improved. In this study, we first applied a new recursive entropic segmentation method on DNA sequences to get preliminary significant cuts. A 22-symbol alphabet is used to capture the differential composition of nucleotide doublets and stop codon patterns along three phases in both DNA strands. This process requires no prior training datasets. Comparing with the previous segmentation methods, the experimental results on three bacteria genomes, Rickettsia prowazekii, Borrelia burgdorferi and E.coli, show that our approach improves the accuracy for finding the borders between coding and non-coding regions in DNA sequences. This paper presents a new segmentation method in prokaryotes based on Jensen-Rényi divergence with a 22-symbol alphabet. For three bacteria genomes, comparing to A12_JR method, our method raised the accuracy of finding the borders between protein coding and non-coding regions in DNA sequences.

Du J.,Tongji University | O'Reilly R.K.,University of Warwick
Chemical Society Reviews | Year: 2011

Anisotropic particles, such as patchy, multicompartment and Janus particles, have attracted significant attention in recent years due to their novel morphologies and diverse potential applications. The non-centrosymmetric features of these particles make them a unique class of nano- or micro-colloidal materials. Patchy particles usually have different compositional patches in the corona, whereas multicompartment particles have a multi-phasic anisotropic architecture in the core domain. In contrast, Janus particles, named after the double-faced Roman god, have a strictly biphasic geometry of distinct compositions and properties in the core and/or corona. The term Janus particles, multicompartment particles and patchy particles frequently appears in the literature, however, they are sometimes misused due to their structural similarity. Therefore, in this critical review we classify the key features of these different anisotropic colloidal particles and compare structural properties as well as discuss their preparation and application. This review brings together and highlights the significant advances in the last 2 to 3 years in the fabrication and application of these novel patchy, multicompartment and Janus particles (98 references). © 2011 The Royal Society of Chemistry.

Knowledge of subcellular localizations (SCLs) of plant proteins relates to their functions and aids in understanding the regulation of biological processes at the cellular level. We present PlantLoc, a highly accurate and fast webserver for predicting the multi-label SCLs of plant proteins. The PlantLoc server has two innovative characters: building localization motif libraries by a recursive method without alignment and Gene Ontology information; and establishing simple architecture for rapidly and accurately identifying plant protein SCLs without a machine learning algorithm. PlantLoc provides predicted SCLs results, confidence estimates and which is the substantiality motif and where it is located on the sequence. PlantLoc achieved the highest accuracy (overall accuracy of 80.8%) of identification of plant protein SCLs as benchmarked by using a new test dataset compared other plant SCL prediction webservers. The ability of PlantLoc to predict multiple sites was also significantly higher than for any other webserver. The predicted substantiality motifs of queries also have great potential for analysis of relationships with protein functional regions. The PlantLoc server is available at http://cal.tongji.edu.cn/PlantLoc/.

Discover hidden collaborations