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| 1 | Toxicity of graphene oxide and multi-walled carbon nanotubes against human cells and zebrafish显示文摘Graphene possesses unique physical and chemical properties, which have inspired a wide range of potential biomedical applications. However, little is known about the adverse effects of graphene on the human body and ecological environment. The purpose of our work is to make assessment on the toxicity of graphene oxide (GO) against human cell line (human bone marrow neuroblastoma cell line and human epithelial carcinoma cell line) and zebrafish (Danio rerio) by comparing the toxic effects of GO with its sister, multi-walled carbon nanotubes (MWNTs). The results show that GO has a moderate toxicity to organisms since it can induce minor (about 20%) cell growth inhibition and slight hatching delay of zebrafish embryos at a dosage of 50 mg/L, but did not result in significant increase of apoptosis in embryo, while MWNTs exhibit acute toxicity leading to a strong inhibition of cell proliferation and serious morphological defects in developing embryos even at relatively low concentration of 25 mg/L. The distinctive toxicity of GO and MWNTs should be ascribed to the different models of interaction between nanomaterials and organisms, which arises from the different geometric structures of nanomaterials. Collectively, our work suggests that GO does actual toxicity to organisms posing potential environmental risks and the result is also shedding light on the geometrical structure-dependent toxicity of graphitic nanomaterials. | CHEN LiQiang HU PingPing ZHANG Li HUANG SiZhou LUO LingFei HUANG ChengZhi | 2012 | Science China Chemistry2012，55，10： | 12 |
| 2 | Single-cell transcriptomic landscape of human blood cells显示文摘High throughput single-cell RNA-seq has been successfully implemented to dissect the cellular and molecular features underlying hematopoiesis.However,an elaborate and comprehensive transcriptome reference of the whole blood system is lacking.Here,we profiled the transcriptomes of 7551 human blood cells representing 32 immunophenotypic cell types,including hematopoietic stem cells,progenitors and mature blood cells derived from 21 healthy donors.With high sequencing depth and coverage,we constructed a single-cell transcriptional atlas of blood cells(ABC) on the basis of both protein-coding genes and long noncoding RNAs(lncRNAs),and showed a high consistence between them.Notably,putative lncRNAs and transcription factors regulating hematopoietic cell differentiation were identified.While common transcription factor regulatory networks were activated in neutrophils and monocytes,lymphoid cells dramatically changed their regulatory networks during differentiation.Furthermore,we showed a subset of nucleated erythrocytes actively expressing immune signals,suggesting the existence of erythroid precursors with immune functions.Finally,a web portal offering transcriptome browsing and blood cell type prediction has been established.Thus,our work provides a transcriptional map of human blood cells at single-cell resolution,thereby offering a comprehensive reference for the exploration of physiological and pathological hematopoiesis. | Xiaowei Xie Mengyao Liu Yawen Zhang Bingrui Wang Caiying Zhu Chenchen Wang Qing Li Yingying Huo Jiaojiao Guo Changlu Xu Linping Hu Aiming Pang Shihui Ma Una Wang Wenbin Cao Shulian Chen Qiuling Li Sudong Zhang Xueying Zhao Wen Zhou Hongbo Luo Guoguang Zheng Erlie Jiang Sizhou Feng Lixiang Chen Lihong Shi Hui Cheng Sha Hao Ping Zhu Tao Cheng | 2021 | National Science Review2021，8，3： | 3 |
| 3 | Nondestructive monitoring of annealing and chemical-mechanical planarization behavior using ellipsometry and deep learning显示文摘The Cu-flling process in through-silicon via(TSV-Cu)is a key technology for chip stacking and three-dimensional vertical packaging.During this process,defects resulting from chemical-mechanical planarization(CMP)and annealing severely affect the reliability of the chips.Traditional methods of defect characterization are destructive and cumbersome.In this study,a new defect inspection method was developed using Mueller matrix spectroscopic ellipsometry.TSV-Cu with a 3-μm-diameter and 8-μm-deep Cu filling showed three typical types of characteristics:overdishing(defect-OD),protrusion(defect-P),and defect-free.The process dimension for each defect was 13 nm.First,the three typical defects caused by CMP and annealing were investigated.With single-channel deep learning and a Mueller matrix element(MME),the TSV-Cu defect types could be distinguished with an accuracy rate of 99.94%.Next,seven effective MMEs were used as independent channels in the artificial neural network to quantify the height variation in the Cu flling in the z-direction.The accuracy rate was 98.92%after training,and the recognition accuracy reached 1 nm.The proposed approach rapidly and nondestructively evaluates the annealing bonding performance of CMP processes,which can improve the reliability of high-density integration. | Qimeng Sun Dekun Yang Tianjian Liu Jianhong Liu Shizhao Wang Sizhou Hu Sheng Liu Yi Song | 2023 | Microsystems & Nanoengineering2023，9，2： | 0 |
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