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Bin-Zhi Qian

Researcher at University of Edinburgh

Publications -  43
Citations -  11251

Bin-Zhi Qian is an academic researcher from University of Edinburgh. The author has contributed to research in topics: Metastasis & Cancer. The author has an hindex of 22, co-authored 35 publications receiving 8834 citations. Previous affiliations of Bin-Zhi Qian include Guangzhou Medical University & Albert Einstein College of Medicine.

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Real-Time Imaging Reveals Local, Transient Vascular Permeability, and Tumor Cell Intravasation Stimulated by TIE2hi Macrophage-Derived VEGFA

TL;DR: Show that VEGFA signaling from TIE2(hi) TMEM macrophages results in local, transient vascular permeability and tumor cell intravasation, providing evidence for the mechanism underlying the association of TMEM with distant metastatic recurrence, offering a rationale for therapies targeting TMEM.
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Insight into hepatocellular carcinogenesis at transcriptome level by comparing gene expression profiles of hepatocellular carcinoma with those of corresponding noncancerous liver.

TL;DR: In this paper, a comprehensive characterization of gene expression profiles of hepatitis B virus-positive HCC through the generation of a large set of 5′-read expressed sequence tag (EST) clusters (11,065 in total) from HCC and non-cancerous liver samples, which then were applied to a cDNA microarray system containing 12,393 genes/ESTs and to comparison with a public database.
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Perivascular M2 Macrophages Stimulate Tumor Relapse after Chemotherapy

TL;DR: This work reports that an alternatively activated (M2) subpopulation of TAMs accumulate around blood vessels in tumors after chemotherapy, where they promote tumor revascularization and relapse, in part, via VEGF-A release and rationalizes a strategy to leverage chemotherapeutic efficacy by selectively targeting this perivascular, relapse-promoting M2-related TAM cell population.
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Mouse models of metastasis: progress and prospects.

TL;DR: The currently available mouse models of metastasis are described, focusing on the mechanistic and therapeutic insights that have been gained by their application, strengths and weaknesses of different models and key technological advances that are generating more refined models.