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RISS 인기검색어
- 검색키워드
- 저자 : Xiaolian Liu (검색결과 4 건)
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Deep forest based intelligent fault diagnosis of hydraulic turbine
Xiaolian Liu,Yu Tian,Xiaohui Lei,Mei Liu,Xin Wen,Haocheng Huang,Hao Wang 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.5
Deep neural networks (DNNs) for intelligent machinery fault diagnosis require a large amount of training data, powerful computational facilities and have many hyper-parameters that have to be carefully tuned to ensure maximum performance. Deep forest, as a novel alternative to the deep learning framework, has the potential to overcome these shortcomings. In this study, a deep forest-based end-toend intelligent fault diagnosis method is proposed for hydraulic turbine, in which multi-grained scanning is first used to transform fault feature representations from raw data and enhance fault feature learning ability, and then cascade structure is constructed with different types of random forests to learn fault features level by level and classify faults. The effectiveness of the proposed method is validated using the experimental dataset under twelve conditions, and its practicability is validated using a simulated dataset generated by adding white Gaussian noise to raw experimental signals. The results show that the proposed method is able to adaptively mine available fault features from measured signals, and its diagnosis accuracy is better than that obtained by existing methods. More importantly, the proposed method has better robustness to noise and is less limited to the number of training data.
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Huang, Xinglu,Zhang, Fan,Wang, Yu,Sun, Xiaolian,Choi, Ki Young,Liu, Dingbin,Choi, Jin-sil,Shin, Tae-Hyun,Cheon, Jinwoo,Niu, Gang,Chen, Xiaoyuan American Chemical Society 2014 ACS NANO Vol.8 No.5
<P/><P>Stem-cell-based therapies have attracted considerable interest in regenerative medicine and oncological research. However, a major limitation of systemic delivery of stem cells is the low homing efficiency to the target site. Here, we report a serendipitous finding that various iron-based magnetic nanoparticles (MNPs) actively augment chemokine receptor CXCR4 expression of bone-marrow-derived mesenchymal stem cells (MSCs). On the basis of this observation, we designed an iron-based nanocluster that can effectively label MSCs, improve cell homing efficiency, and track the fate of the cells <I>in vivo</I>. Using this nanocluster, the labeled MSCs were accurately monitored by magnetic resonance imaging and improved the homing to both traumatic brain injury and glioblastoma models as compared to unlabeled MSCs. Our findings provide a simple and safe method for imaging and targeted delivery of stem cells and extend the potential applications of iron-based MNPs in regenerative medicine and oncology.</P>
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Hu, Xi,Sun, Jihong,Li, Fangyuan,Li, Ruiqing,Wu, Jiahe,He, Jie,Wang, Nan,Liu, Jianan,Wang, Shuaifei,Zhou, Fei,Sun, Xiaolian,Kim, Dokyoon,Hyeon, Taeghwan,Ling, Daishun American Chemical Society 2018 Nano letters Vol.18 No.2
<P>Although metallic nanomaterials with high X-ray attenuation coefficients have been widely used as X-ray computed tomography (CT) contrast agents, their intrinsically poor biodegradability requires them to be cleared from the body to avoid any potential toxicity. On the other hand, extremely small-sized nanomaterials with outstanding renal clearance properties are not much effective for tumor targeting because of their too rapid clearance in vivo. To overcome this dilemma, here we report on the hollow bismuth subcarbonate nanotubes (BNTs) assembled from renal-clearable ultrasmall bismuth subcarbonate nanoclusters for tumor-targeted imaging and chemoradiotherapy. The BNTs could be targeted to tumors with high efficiency and exhibit a high CT contrast effect. Moreover, simultaneous radio- and chemotherapy using drug-loaded BNTs could significantly suppress tumor volumes, highlighting their potential application in CT imaging-guided therapy. Importantly, the elongated nanotubes could be disassembled into isolated small nanoclusters in the acidic tumor microenvironment, accelerating the payload release and kidney excretion. Such body clearable CT contrast agent with high imaging performance and multiple therapeutic functions shall have a substantial potential for biomedical applications.</P>
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CDH17 nanobodies facilitate rapid imaging of gastric cancer and efficient delivery of immunotoxin
Jingbo Ma,Xiaolong Xu,Chunjin Fu,Peng Xia,Ming Tian,Liuhai Zheng,Kun Chen,Xiaolian Liu,Yilei Li,Le Yu,Qinchang Zhu,Yangyang Yu,Rongrong Fan,Haibo Jiang,Zhifen Li,Chuanbin Yang,Chengchao Xu,Ying Long,J 한국생체재료학회 2022 생체재료학회지 Vol.26 No.4
Background: It is highly desirable to develop new therapeutic strategies for gastric cancer given the low survival rate despite improvement in the past decades. Cadherin 17 (CDH17) is a membrane protein highly expressed in cancers of digestive system. Nanobody represents a novel antibody format for cancer targeted imaging and drug delivery. Nanobody targeting CHD17 as an imaging probe and a delivery vehicle of toxin remains to be explored for its theragnostic potential in gastric cancer. Methods: Naïve nanobody phage library was screened against CDH17 Domain 1-3 and identified nanobodies were extensively characterized with various assays. Nanobodies labeled with imaging probe were tested in vitro and in vivo for gastric cancer detection. A CDH17 Nanobody fused with toxin PE38 was evaluated for gastric cancer inhibition in vitro and in vivo. Results: Two nanobodies (A1 and E8) against human CDH17 with high affinity and high specificity were successfully obtained. These nanobodies could specifically bind to CDH17 protein and CDH17-positive gastric cancer cells. E8 nanobody as a lead was extensively determined for tumor imaging and drug delivery. It could efficiently co-localize with CDH17-positive gastric cancer cells in zebrafish embryos and rapidly visualize the tumor mass in mice within 3 h when conjugated with imaging dyes. E8 nanobody fused with toxin PE38 showed excellent anti-tumor effect and remarkably improved the mice survival in cell-derived (CDX) and patient-derived xenograft (PDX) models. The immunotoxin also enhanced the anti-tumor effect of clinical drug 5-Fluorouracil. Conclusions: The study presents a novel imaging and drug delivery strategy by targeting CDH17. CDH17 nanobodybased immunotoxin is potentially a promising therapeutic modality for clinical translation against gastric cancer.
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