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| 1 | Molecular characterization and m RNA expression of ribosomal protein L8 in Rana nigromaculata during development and under exposure to hormones显示文摘Like Xenopus laevis, some species of the Rana genus are also used to study endocrine disrupting chemicals(EDCs). Although ribosomal protein L8(rpl8) is the most-used reference gene for analyzing gene expression by quantitative reverse transcription polymerase chain reaction in Rana, its suitability as the reference gene has never been validated in any species of the Rana genus. We characterized rpl8 c DNA in Rana nigromaculata, a promising native species in East Asia for assaying endocrine disrupting effects. We found that the rpl8 c DNA consisted of919 bp and encoded 257 amino acids, exhibiting high identities of amino acid sequence with known rpl8 in other Rana species. Then, we examined the stability of m RNA expression during development. Compared with elongation factor 1 alpha 1, another common housekeeping gene, neither stage-specific nor tissue-specific expression of the rpl8 gene was found in all tissues examined(brain, liver, intestine, tail, testis and ovary) during R. nigromaculata development. Finally, we investigated rpl8 expression under exposure to hormones. No change in rpl8 m RNA expression was found under exposure to thyroid hormone(T4) and estrogen(estradiol), whereas expression of the corresponding biomarker genes was induced.Our results show that rpl8 is an appropriate reference gene for analyzing gene expression by quantitative reverse transcription polymerase chain reaction for assaying EDCs using R. nigromaculata, and might also provide support for using rpl8 as a reference gene in other Rana species due to the high conservation of rpl8 among the Rana genus. | Qinqin Lou Shan Cao Wei Xu Yinfeng Zhang Zhanfen Qin Wuji Wei | 2014 | Journal of Environmental Sciences2014，26，11： | 6 |
| 2 | Precise output loads control of load-diffusion components with topology optimization显示文摘The purpose of this paper is to present a novel topology optimization approach to control precisely the output loads under static loads and harmonic excitations.We introduce the Artificial Bar Element(ABE)at the designated output positions,where the output loads are equivalently measured and constrained with the nodal displacements of ABE.Optimization model is then formulated considering the output load constraints as well as the minimization of strain energy and dynamic displacement responses respectively under the static and dynamic conditions.The influences of the ABEs stiffness,different material usages of the design domain,widths of the output loads constraint intervals and variation ratios of output loads are discussed in detail.The proposed method is verified with several numerical examples with clear and reasonable load transfer paths. | Yinfeng CAO Xiaojun GU Jihong ZHU Weihong ZHANG | 2020 | Chinese Journal of Aeronautics2020，33，3： | 5 |
| 3 | Security in Edge Blockchains:Attacks and Countermeasures显示文摘Edge blockchains,the blockchains running on edge computing infrastructures,have attracted a lot of attention in recent years.Thanks to data privacy,scalable computing resources,and distributed topology nature of edge computing,edge blockchains are considered promising solutions to facilitating future blockchain applications.However,edge blockchains face unique security issues caused by the de⁃ployment of vulnerable edge devices and networks,including supply chain attacks and insecure consensus offloading,which are mostly not well studied in previous literature.This paper is the first survey that discusses the attacks and countermeasures of edge blockchains.We first summarize the three-layer architecture of edge blockchains:blockchain management,blockchain consensus,and blockchain lightweight cli⁃ent.We then describe seven specific attacks on edge blockchain components and discuss the countermeasures.At last,we provide future re⁃search directions on securing edge blockchains.This survey will act as a guideline for researchers and developers to design and implement se⁃cure edge blockchains. | CAO Yinfeng CAO Jiannong WANG Yuqin WANG Kaile LIU Xun | 2022 | ZTE Communications2022，20，4： | 0 |
| 4 | Stem cell properties and neural differentiation of sheep amniotic epithelial cells显示文摘This study was designed to verify the stem cell properties of sheep amniotic epithelial cells and their capacity for neural differentiation. Immunofluorescence microscopy and reverse transcription-PCR revealed that the sheep amniotic epithelial cells were positive for the embryonic stem cell marker proteins SSEA-1, SSEA-3, SSEA-4, TRA-1-60 and TRA-1-81, and the totipotency-associated genes Oct-4, Sox-2 and Rex-1, but negative for Nanog. Amniotic epithelial cells expressed β-III-tubulin, glial fibrillary acidic protein, nestin and microtubule-associated protein-2 at 28 days after induction with serum-free neurobasal-A medium containing B-27. Thus, sheep amniotic epithelial cells could differentiate into neurons expressing β-III-tubulin and microtubule-associated protein-2, and glial-like cells expressing glial fibrillary acidic protein, under specific conditions. | Xuemin Zhu Xiumei Wang Guifang Cao Fengjun Liu Yinfeng Yang Xiaonan Li Yuling Zhang Yan Mi Junping Liu Lingli Zhang | 2013 | Neural Regeneration Research2013，8，13： | 0 |
| 5 | Predicting Illness Severity and Short-Term Outcomes of COVID-19:A Retrospective Cohort Study in China显示文摘Introduction COVID-19,caused by SARS-CoV-2,is a highly contagious disease.1 By April 8,2020,more than 1,350,000 patients were diagnosed with COVID-19 globally,with more than 79,000 deaths worldwide attributable to the disease.2 Recent clinical data reported that mild and critical patients manifested different symptoms.Most of the mild patients with COVID-19 had symptoms such as fever,cough,and mild pneumonia,whereas the critical cases presented dyspnea,respiratory failure,sepsis,organ dysfunction,and even eventual death. | Chuming Chen Haihui Wang Zhichao Liang Ling Peng Fang Zhao Liuqing Yang Mengli Cao Weibo Wu Xiao Jiang Peiyan Zhang Yinfeng Li Li Chen Shiyan Feng Jianming Li Lingxiang Meng Huishan Wu Fuxiang Wang Quanying Liu Yingxia Liu | 2020 | The Innovation2020，1，1： | 0 |
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