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| 1 | In vitro culture and differentiation of rat embryonic midbrain-derived neural stem cells显示文摘BACKGROUND:Midbrain-derived neural stem cells (mNSCs) can differentiate into functional mature dopaminergic neurons. The mNSCs are considered the ideal choice for cell therapy of Parkinson’s disease. OBJECTIVE: To isolate rat embryonic mNSCs and to observe the differentiation characteristics of mNSCs induced by cell growth-promoting factors. DESIGN,TIME AND SETTING: An in vitro cell culture study based on the molecular biology of nerve cells was carried out at the Institute of Clinical Medicine,China-Japan Friendship Hospital (China) from March to November 2007. MATERIALS: Sprague Dawley rats at embryonic day 14 were used in this study. Nestin antibody,β-Ⅲ tubulin antibody,glial fibrillary acidic protein (GFAP) antibody and cyclic nucleotide 3’-phosphohydrolase (CNPase) antibody were provided by Abcam; DMEM/F12 medium and N2 supplement were provided by In-vitrogen; epidermal growth factor (EGF) and fibroblast growth factor-2 (FGF2) were provided by R&D Sys-tems. METHODS: The ventral mesencephalon was dissected from embryonic day 14 rat embryos. By trypsin di-gestion and mechanical separation,the brain tissue was triturated into a fine single-cell suspension. The cells were cultured in 5 mL serum-free medium containing DMEM/F12,1% N2 supplement,20 ng/mL EGF and FGF2. The mNSCs at the third generation were coated with 10 μg/mL polylysine and induced to differenti-ate in the DMEM/F12 supplemented with 1% fetal bovine serum and 1% N2. MAIN OUTCOME MEASURES: The neural spheres of the third passage were identified by nestin im-munofluorescence; at the same time,the cells were induced to differentiate,and the types of differentiated cell were identified by immunofluorescence for βⅢ tubulin,GFAP and CNPase. RESULTS: Seven days after primary culture,a great many neurospheres could be obtained by successive pasage. Immunofluorescence assays showed that the neurospheres were nestin positive,and after differentia-tion,the cells expressed GFAP,CNPase and β-Ⅲ-tubulin. CONCLUSION: Embryonic day 14 rat mNSCs can differentiate into neuron-like cells and glial cells fol-lowing induction by EGF,FGF2 and N2 additive. | Xingli Deng Ruen Liu Zhongtang Feng Jing Guo Wu Wang Deqiang Lei Hongyan Li Zhihua Chen | 2008 | Neural Regeneration Research2008，3，11： | 19 |
| 2 | Risk factors for the incidence of apoplexy in pituitary adenoma: a single-center study from southwestern China显示文摘Background:Although the incidence and clinical manifestations of pituitary apoplexy were reported by a few researches,the results are not consistent.This study aimed to explore the risk factors associated with an incidence of apoplexy in pituitary adenomas.Methods:The clinical information of 843 patients with pituitary adenoma from the Department of Neurological Surgery,1st Affiliated Hospital of Kunming Medical University,was reviewed.The incidence,clinical manifestation,and potential risk factors for pituitary apoplexy were analyzed by a case-control study.Results:In total,121 patients(14.4%)with macroadenoma were suffered from pituitary apoplexy.Headache,vomiting,and visual impairment are the top 3 symptoms for the pituitary apoplexy.Logistic regression results showed that the hypertension(hypertension vs non-hypertension OR=2.765,95%CI:1.41~5.416),tumor type(negative staining vs.positive staining,OR=1.501,95%CI:1.248~5.235),and tumor size(diameter>2 cm vs.diameter≤2 cm,OR=3.952,95%CI:2.211~7.053)are independent factors associated with pituitary apoplexy.Conclusion:Our results indicate that the risk factors for the incidence of pituitary apoplexy depend mainly on properties of the tumor itself(tumor size and pathologic type)and the blood pressure of patients. | Yao Li Yuan Qian Yisheng Qiao Xiaoxiang Chen Jiaotian Xu Chao Zhang Wei Wang Junjun Li Xingli Deng | 2020 | Chinese Neurosurgical Journal2020，6，4： | 3 |
| 3 | VEGF and EMMPRIN expression correlates with survival of patients with osteosarcoma显示文摘 | Quan Zhou Yong Zhu Zhansheng Deng Haitao Long Shaoxian Zhang Xingli Chen | 2009 | Surgical Oncology2009，，1： | 1 |
| 4 | Integrating phenotypic features and tissue-specific information to prioritize disease genes显示文摘Prioritization of candidate disease genes is crucial for improving medical care, and is one of the fundamental challenges in the post-genomic era. In recent years, different network-based methods for gene prioritization are proposed. Previous studies on gene prioritization show that tissue-specific protein-protein interaction(PPI) networks built by integrating PPIs with tissue-specific gene expression profiles can perform better than tissue-na¨?ve global PPI network. Based on the observations that diseases with similar phenotypes are likely to have common related genes, and genes associated with the same phenotype tend to interact with each other, we propose a method to prioritize disease genes based on a heterogeneous network built by integrating phenotypic features and tissue-specific information. In this heterogeneous network, the PPI network is built by integrating phenotypic features with a tissue-specific PPI network, and the disease network consists of the diseases that are associated with the same phenotype and tissue as the query disease. To determine the impacts of these two factors on gene prioritization, we test three typical network-based prioritization methods on heterogeneous networks consisting of combinations of different PPIs and disease networks built with or without phenotypic features and tissue-specific information. We also compare the proposed method with other tissuespecific networks. The results of case studies reveals that integrating phenotypic features with a tissue-specific PPI network improves the prioritization results. Moreover, the disease networks generated using our method not only show comparable performance with the widely used disease similarity dataset of 5080 human diseases,but are also effective for diseases that are not in the dataset. | Yue DENG Lin GAO Xingli GUO Bingbo WANG | 2016 | Science China(Information Sciences)2016，59，7： | 1 |
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