A poor imitation of a natural process: A call to reconsider the iPSC engineering technique

ZhangY.; YaoL.; YuX.; OuJ.; HuiN.; LiuS.

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A poor imitation of a natural process: A call to reconsider the iPSC engineering technique

机译：对自然过程的模仿很差：要求重新考虑iPSC工程技术

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Reprogramming somatic cells into a pluripotent state is expected to initiate a new era in medicine. Because the precise underlying mechanism of reprogramming remains unclear, many efforts have been made to optimize induced pluripotent stem cell (iPSC) engineering. However, satisfactory results have not yet been attained. In this review, we focus on recent roadblocks in iPSC reprogramming engineering, such as the inefficiency of the process, tumorigenicity and heterogeneity of the generation. We conclude that cell reprogramming is a naturally occurring phenomenon rather than a biological technique. We will only be able to mimic the natural process of reprogramming when we fully understand its underlying mechanism. Finally, we highlight the alternative method of direct conversion, which avoids the use of iPSCs to generate cell materials for patient-specific cell therapy.

机译：将体细胞重编程为多能状态有望启动医学的新纪元。由于重编程的确切基本机制尚不清楚，因此已进行了许多努力来优化诱导多能干细胞（iPSC）工程。但是，尚未获得令人满意的结果。在这篇综述中，我们重点介绍iPSC重编程工程中的最新障碍，例如过程效率低下，致癌性和异质性。我们得出结论，细胞重编程是自然现象，而不是生物学技术。当我们完全了解重新编程的基本机制时，我们才能模仿它的自然过程。最后，我们重点介绍了直接转化的另一种方法，该方法避免了使用iPSC生成用于患者特异性细胞治疗的细胞材料。

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《Cell cycle》 |2012年第24期|共9页
作者
ZhangY.; YaoL.; YuX.; OuJ.; HuiN.; LiuS.;
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正文语种 eng
中图分类细胞生物学;
关键词
Delivery system; Direct conversion; Efficiency; Identification; iPSC engineering; Natural reprogramming; Reprogramming; Reprogramming factor cocktails; Safety;

机译：交付系统;直接转换;效率;识别;iPSC工程;自然重编程;重编程;因子组合重编程;安全性;

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6. A poor imitation of a natural process [O] . Yemin Zhang, Lin Yao, Xiya Yu, 2012

机译：对自然过程的不良模仿
7. EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed TarekShahriar Abstract—An EMD-chaos based approach is proposed todiscriminate EEG signals corresponding to healthy persons,and epileptic patients during seizure-free intervals and seizureattacks. An electroencephalogram (EEG) is first empiricallydecomposed to intrinsic mode functions (IMFs). The nonlineardynamics of these IMFs are quantified in terms of the largestLyapunov exponent (LLE) and correlation dimension (CD).This chaotic analysis in EMD domain is applied to a large groupof EEG signals corresponding to healthy persons as well asepileptic patients (both with and without seizure attacks). It isshown that the values of the obtained LLE and CD exhibitfeatures by which EEG for seizure attacks can be clearlydistinguished from other EEG signals in the EMD domain.Thus, the proposed approach may aid researchers in developingeffective techniques to predict seizure activities. Index Terms—Electroencephalogram (EEG), empiricalmode decomposition (EMD), largest Lyapunov exponent (LLE),correlation dimension (CD), epileptic seizures. The Authors are with the Electrical and Electronic EngineeringDepartment, Bangladesh University of Engineering and Technology,Dhaka-1000, Bangladesh (e-mail: imamul@eee.buet.ac.bd) PDF Cite: S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed Tarek Shahriar, "EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain," International Journal of Computer and Electrical Engineering vol. 4, no. 3, pp. 326-330, 2012. PREVIOUS PAPER Perception of Emotions Using Constructive Learningthrough Speech NEXT PAPER Physical Layer Impairments Aware OVPN Connection Selection Mechanisms Copyright © 2008-2013. International Association of Computer Science and Information Technology Press (IACSIT Press) [O] . S. M. Shafiul Alam, Syed TarekShahriar 2012

机译：EEG信号在EMD域S. S. Shafiul Alam，S中的非线性动力学使用非线性动力学。 M. Shafiul Alam，Aurangozeb和Syed Tarekshahriar摘要 - 基于EMD Chaos的方法，提出了对应于健康人的EEG信号，癫痫发作期间的癫痫患者和Seizureattacks。脑电图（EEG）首先被凭经上分解为内在模式功能（IMF）。这些IMF的非线性动力学在最大范围的指数（LLE）和相关尺寸（CD）方面是量化的。本域中的混沌分析应用于与健康人相对应的大型脑电图（Asepileptic患者）（两者都有癫痫发作）。因此，所获得的LLE和CD表展的价值可以从EMD领域的其他EEG信号中清晰地区分脑电图的表达展示。本拟议的方法可以帮助研究人员以预测癫痫发作的癫痫发作技术。索引术语 - 脑电图（EEG），仿真态分解（EMD），最大的Lyapunov指数（LLE），相关维度（CD），癫痫发作。作者与电气电子和电子工程公司，孟加拉国工程和技术大学，孟加拉国达卡 - 1000（电子邮件：imamul@eee.buet.ac.bd）pdf cite：s. m. shafiul Alam，s。 M. Shafiul Alam，Aurangozeb和Syed Tarek Shahriar，“EEG信号歧视在EMD领域的非线性动态，”计算机电气工程卷国际杂志。 4，不。 3，pp。326-330,2012，上一篇论文对情绪的看法，使用建设性的学习言论下一篇论文物理层障碍意识到OVPN连接选择机制版权所有©2008-2013。国际计算机科学与信息技术协会出版社（IACSIT Press）

A poor imitation of a natural process: A call to reconsider the iPSC engineering technique

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