Shanghai Jiao Tong University

About: Shanghai Jiao Tong University is a education organization based out in Shanghai, Shanghai, China. It is known for research contribution in the topics: Population & Cancer. The organization has 157524 authors who have published 184620 publications receiving 3451038 citations. The organization is also known as: Shanghai Communications University & Shanghai Jiaotong University.

Recruitment of mesenchymal stem cells into prostate tumours promotes metastasis

Abstract: Tumours recruit mesenchymal stem cells to facilitate healing, which induces their conversion into cancer-associated fibroblasts that facilitate metastasis. However, this process is poorly understood on the molecular level. Here we show that CXCL16, a ligand for CXCR6, facilitates mesenchymal stem cell or very small embryonic-like cells recruitment into prostate tumours. CXCR6 signalling stimulates the conversion of mesenchymal stem cells into cancer-associated fibroblasts, which secrete stromal-derived factor-1, also known as CXCL12. CXCL12 expressed by cancer-associated fibroblasts then binds to CXCR4 on tumour cells and induces an epithelial-to-mesenchymal transition, which ultimately promotes metastasis to secondary tumour sites. Our results provide the molecular basis for mesenchymal stem cell recruitment into tumours and how this process leads to tumour metastasis.

Highly Reversible and Rechargeable Safe Zn Batteries Based on a Triethyl Phosphate Electrolyte

Abstract: Zinc metal is an attractive anode material for next-generation batteries. However, dendrite growth and limited Coulombic efficiency (CE) during cycling are the major roadblocks towards the widespread commercialization of batteries employing Zn anodes. In this work we report the novel adoption of triethyl phosphate (TEP) as a solvent and co-solvent with aqueous electrolytes to obtain a highly stable and dendrite-free Zn anode. Stable Zn plating/stripping for over 3000 h was obtained, accompanied by a CE of 99.68 %. SEM images of the Zn anodes revealed highly porous interconnected dendrite-free Zn deposits. The electrolyte displayed good compatibility with both Zn anodes and potassium copper hexacyanoferrate (KCuHCf) cathodes for Zn ion batteries (ZIBs). The full cell showed a long cycling stability and high rate capability. The present work is a contribution towards cost-effective and safe battery systems.

Nanoparticles Coated with Neutrophil Membranes Can Effectively Treat Cancer Metastasis.

Abstract: The dissemination, seeding, and colonization of circulating tumor cells (CTCs) serve as the root of distant metastasis. As a key step in the early stage of metastasis formation, colonization of CTCs in the (pre-)metastatic niche appears to be a valuable target. Evidence showed that inflammatory neutrophils possess both a CTC- and niche-targeting property by the intrinsic cell adhesion molecules on neutrophils. Inspired by this mechanism, we developed a nanosize neutrophil-mimicking drug delivery system (NM-NP) by coating neutrophils membranes on the surface of poly(latic-co-glycolic acid) nanoparticles (NPs). The membrane-associated protein cocktails on neutrophils membrane were mostly translocated to the surface of NM-NP via a nondisruptive approach, and the biobinding activity of neutrophils was highly preserved. Compared with uncoated NP, NM-NP exhibited enhanced cellular association in 4T1 cell models under shear flow in vitro, much higher CTC-capture efficiency in vivo, and improved homing to the pre...

Target-Aware Deep Tracking

Abstract: Existing deep trackers mainly use convolutional neural networks pre-trained for the generic object recognition task for representations. Despite demonstrated successes for numerous vision tasks, the contributions of using pre-trained deep features for visual tracking are not as significant as that for object recognition. The key issue is that in visual tracking the targets of interest can be arbitrary object class with arbitrary forms. As such, pre-trained deep features are less effective in modeling these targets of arbitrary forms for distinguishing them from the background. In this paper, we propose a novel scheme to learn target-aware features, which can better recognize the targets undergoing significant appearance variations than pre-trained deep features. To this end, we develop a regression loss and a ranking loss to guide the generation of target-active and scale-sensitive features. We identify the importance of each convolutional filter according to the back-propagated gradients and select the target-aware features based on activations for representing the targets. The target-aware features are integrated with a Siamese matching network for visual tracking. Extensive experimental results show that the proposed algorithm performs favorably against the state-of-the-art methods in terms of accuracy and speed.

Do State Renewable Portfolio Standards Promote In-State Renewable Generation?

Abstract: Several US states have passed renewable portfolio standard (RPS) policies in order to encourage investment in renewable energy technologies. Existing research on their effectiveness has either employed a cross-sectional approach or has ignored heterogeneity among RPS policies. In this paper, we introduce a new measure for the stringency of an RPS that explicitly accounts for some RPS design features that may have a significant impact on the strength of an RPS. We also investigate the impacts of renewable portfolio standards on in-state renewable electricity development using panel data and our new measure of RPS stringency, and compare the results with those when alternative measures are used. Using our new measure, the results suggest that RPS policies have had a significant and positive effect on in-state renewable energy development, a finding which is masked when design differences among RPS policies are ignored. We also find that another important design feature – allowing "free trade" of REC’s – can significantly weaken the impact of an RPS. These results should prove instructive to policy makers, whether considering the development of a federal-level RPS or the development or redesign of a state-level RPS.