Team:Tsinghua-A/test

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We do scientific research
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And software engineering
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Cooperation is the thorough conviction that nobody can get there unless everybody gets there. <cite>Virginia Burden, Nett Media</cite>
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The value of a man resides in what he gives and not in what he is capable of receiving. <cite>Albert Einstein</cite>
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<h2>We live with <strong>research</strong></h2>
 
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TagSys is an interest research group launched by Prof. Yunhao Liu and Dr. Lei Yang in 2012, in the School of Software, Tsinghua University. With the deep background of computer science, communications, and mathematics, the group is dedicated to establishing a research and practice environment to improve the current technologies and systems on RFID technology, security & privacy preserving, battery-free sensing, and pervasive computing. Such group has attract a wide attention in both academic and industry. Besides participating academic Symposiums, the group is often invited to give talk, training, consulting and auditing to industrial partners. Thus, it has a close relationship with its partners, aiming to strengthen collaborative applied research activities between the industry and research organizations.
 
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<h3>Lei Yang</h3>
 
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<h3>Xuan Ding</h3>
 
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Ph.D candidate
 
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<h3>Tong Zhu</h3>
 
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Ph.D
 
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<h3>Yi Guo</h3>
 
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Ph.D student
 
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<h3>Hongliang Wei</h3>
 
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Ph.D student
 
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Master student
 
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<h3>Qiongzheng Lin</h3>
 
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Ph.D student
 
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Master student
 
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<h3>Yekui Chen</h3>
 
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Master student
 
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<h3>Jiyun Wu</h3>
 
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Master student
 
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<h3>Fan Dang</h3>
 
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Ph.D student
 
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<h3>Chunhui Duan</h3>
 
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Ph.D student
 
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Based on modeling work, we find that negative feedback can contribute to the network’s adaptation to DNA copy number variation. So we analysed the following three-node networks, A and B. The difference between A and B is the output nodes of network A has negative feedback.
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We transfected this two circuits into mammalian cells (Hela cell). By testing the mean value of EYFP (Enhance Yellow Fluorescent Protein, the output of our circuits), and the relationship between the EYFP and the DNA copy number, we can prove the hypothesis.  
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<span class="date">January, 2012 - Present</span>
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Over the past several years, reports on baggage mishandling or lose have been paid more and more attention. According to statistics, there are totally 160 million baggage transported in China in 2011. Among these baggages, 2.3 million were lost or mishandled, and the airlines had paid a compensation of 3.7 million US$ for them. We are collaborating with the Hainan Airline, the Beijing Capital International Airport (BCIA) and Sanya Phoenix International Airport (SPIA) to conduct aRFID-Assisted Sortation System, called TagAssist. The Hainan Airline, which is the third biggest airline enterprise in China, suffers a lot of problems with baggage losses incurred by the manual sortation in BCIA T1, and SPIA. The ultimate goal of TagAssist is to pursue a guarantee for the passengers, “Never lose your baggage!”. To achieve this goal, TagAssist provides a automatically baggage track and check technique to wipe out the wrong sortation as much as possible. Currently, this system is under further development and is going to benefit people greatly.
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With the rapid economic development, people are seeking for life with higher quality. The TagHome project is an ongoing work for building an intelligent and user-friendly home system for normal families. It transforms the traditional homes into integrated systems with user-friendly interfaces and adaptive automation controls. With assistance of large amount of sensors and actuators, the homes can automatically adjust to the requirements of the users as they wish. Unlike existing intelligent home systems, this project focuses on the construction of comprehensive services covering all aspects of family life. With the centralized management of the network provider and services provided by third-party institutions, our system can provide services including medical, security and etc. This project is supported by the Shanxi Broadcast&TV Network Intermediary. The prototype has been implemented in the building of Shanxi Broadcast&TV Network Intermediary. Currently, this system is under further testing and is going to be implemented in a residential area.
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<h4>Construction </h4>
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We constructed the following circuit A ,B and C .The circuit A corresponds to the network A ,while the circuit B is the implementation of network B. Circuit C is used as a control design to testify the function of A and B.
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In circuit A, as we can see, the input is miR-21, which can repress the plasmid pz371 and K1116002(The plasmid’s information can be found in parts). K1116002 induced by rtTA and Dox, serves as an auxiliary node, producing the LacI gene to inhibit the expression of EYFP. EYFP(Enhance Yellow Fluorescent Protein )is used as output. Besides, the miR-FF3 restrains the expression of LacI. The reason that we get the most of post-transcriptional control can be seen in Supplementary text.
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                In circuit B, however, the plasmid K1116003 does not have FF3 target, leading to the contrast between circuit A and B. We can see miR-21 can’t target at pZ349 and pZ331 in circuit C , that is, there is no input in circuit C. The miR-21, used to distinguish cancer cell from normal cells ,is endogenous in Hela cell.
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Radio-frequency identification (RFID) is the wireless non-contact use of radio-frequency electromagnetic fields to automatically identify and track tags attached to objects. Unlike a bar code, the tag does not necessarily need to be within line of sight of the reader, and may be embedded in the tracked object. One of the most promising applications of RFID is anti-counterfeiting, i.e., to verify the authenticity of the products. Counterfeiting is considered as one of the most serious threats to the world economy, and statistics have shown that the counterfeit goods account for 5% of the world trade every year. In the Tagerify project we study the RFID batch authentication issue and propose the first probabilistic approach, termed as Single Echo based Batch Authentication (SEBA), to meet the requirement of prompt and reliable batch authentications in our large scale anti-counterfeiting solution. Experimental results demonstrate the effectiveness of SEBA in fast batch authentications as well as its significant improvement compared to existing approaches.
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miRNAs function as posttranscriptional regulators which have distinguished features compared to transcriptional regulators, intervening late in gene expression process, with the capability to counteract variation from the upstream processes (Margaret et al., 2012). Research shows that while conducting experiment on an incoherent feedforward motif in mammalian cells, posttranscriptional regulation results in superior adaptation behavior, higher absolute expression levels and lower intrinsic fluctuations (Bleris et al., 2011). miRNAs can serve as buffers against variation during gene expression; transient increases in transcription factor activity would propagate to increases in target miRNA transcription while would be counteracted by increased miRNA and vice versa. Therefore, under the miRNA posttranscriptional regulation, protein output can be uncoupled from fluctuations in transcription factor concentration or activity (Margaret et al., 2012). miRNAs also possess good stability which, consistent with theoretical constraints, meets the need for enough molecules of a regulator to achieve a small reduction in the noise of a target gene (Lestas et al., 2010).  
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Screen locking/unlocking is important for modern smart phones to avoid the unintentional operations and secure the personal stuff. Once the phone is locked, the user should take a specific action or produce some secret information to unlock the phone. The existing unlocking approaches can be categorized into four groups: motion, password, pattern, and fingerprint. Existing approaches do not support smart phones well due to the deficiency of security, high cost, and poor usability. In this project, we design a handshaking biometric-based approach to unlock the smart phone. Comparing with the existing methods, there are two major advantages of our approach. The first advantage is the difficulty to forge. Using our approach, the authentication process is based on the features of the user’s habits and motions, which is much harder for unauthorized users to obtain. The second advantage is the simplicity and convenience. Our approach can free users from remembering a large number of passwords or complicated patterns for unlocking their phones.
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  We took advantage of another fluorescent protein(mkate ) as reference gene, which has no influence in our design. Published literature generally supports the view that in transient transfections, fluorescence depends linearly on the copy number of transfected plasmids (Tseng et al, 1997; Pollard et al, 1998;Cohenet al,2009; Schwakeet al, 2010). While strictly speaking, this reporter level also depends on many other potentially fluctuating parameters such as global synthesis and degradation rates(Leonidas Bleris et al,2011),it is more legitimately use the normalized quotient to instead of the value of EYFP.
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  Apparently, the output of circuit C is lower than circuit B .Having the negative feedback compared with circuit B, the expression of EYFP in circuit A is strongest.
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                  Then we analysed the output of constructed designs varies with the DNA copy number. Facing with the difficulty of counting the copy number directly, we employed the reference gene to reflect .We think the copy number is high when the expression intensity of mkate is strong. One hundred thousand positive Hela cells was collected to obtain the relationship between EYFP and make.
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  From the figure 2, we learned that in circuit A, with the increase of the expression intensity of makte, the value of EYFP gradually reaches saturation. In another word, the circuit A’s output reaches saturation fast with the increase of copy number. We came to a conclusion circuit A’s adaptation to DNA copy number is higher than circuit B’s. So, the negative feedback works.
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<td>Name</td><td>description</td><td>Part Type</td><td>Designer</td>
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<td><a href="http://parts.igem.org/Part:BBa_K1116000">K1116000</td><td>LacI with miR-21 and miR-FF3 target</td><td>Composite</td><td>Lei Wei</td>
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<td><a href="http://parts.igem.org/Part:BBa_K1116001">K1116001</td><td>LacI with miR-21 and miR-FF5 target</td><td>Composite</td><td>Shuguang Peng</td>
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<td><a href="http://parts.igem.org/Part:BBa_K1116002">K1116002</td><td>TRE-LacI with miR-21 and miR-FF3 target</td><td>Composite</td><td>Shuguang Peng</td>
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<td><a href="http://parts.igem.org/Part:BBa_K1116003">K1116003</td><td>TRE-LacI with miR-21 and miR-FF5 target</td><td>Composite</td><td>Shuguang Peng</td>
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<td><a href="http://parts.igem.org/Part:BBa_K1116004">K1116004</td><td>CAG-EYFP-miRNA-FF3</td><td>Composite</td><td>Shuguang Peng</td>
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<td><a href="http://parts.igem.org/Part:BBa_K1116005">K1116005</td><td>CAG-Cerulean-hsa-miR-21</td><td>Composite</td><td>Shuguang Peng</td>
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<h4>Discussion</h4>
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<p>
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Due to some restrictions in wetlab, we only finished the above-mentioned experiment. We found that the number of Hela cells who possesses high copy number is  comparatively low. We also noticed the circuit C’s output is higher than expected in Figure 1.This may cause wrong judge when use the design to detect miR-21. Some measures will be taken to solve this question.
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        Besides, we are going to endeavor to construct the other networks mentioned in modeling work.
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<td style="background:orange; text-align:center; line-height:200%; font-size:20px"><strong>Reference:</strong></td>
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<td><li><strong>Yi Guo, Lei Yang, Xuan Ding,</strong> Jinsong Han, Yunhao Liu, "OpenSesame: Unlocking Smart Phone through Handshaking Biometrics," in IEEE INFOCOM 2013.</li></td>
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<td><li>[1]Bleris, L., Xie, Z., Glass, D., Adadey, A., Sontag, E., and Benenson, Y. (2011).
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Synthetic incoherent feedforward circuits show adaptation to the amount of
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their genetic template. Mol. Syst. Biol.7, 519
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</li></td>
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<td><li><strong>Xuan Ding,</strong> Wei Wang, Meng Wan, Ming Gu, "Seamless Privacy: Privacy-Preserving Subgraph Counting in Interactive Social Network Analysis," accepted to appear in CyberC 2013.</li></td>
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<td><li>[2]Ebert M S, Sharp P A. Roles for microRNAs in conferring robustness to biological processes[J]. Cell, 2012, 149(3): 515-524.</li></td>
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<td><li><strong>Xuan Ding,</strong> Wei Wang, "Enabling Dynamic Analysis of Anonymized Social Network Data," in Proceedings of the International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC 2012), pp. 21-26.</li></td>
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<td><li>[3] Lestas I, Vinnicombe G, Paulsson J. Fundamental limits on the suppression of molecular fluctuations[J]. Nature, 2010, 467(7312): 174-178.
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<td><li>ShaoJie Tang, <strong>Lei Yang,</strong> "Morello: A quality-of-monitoring oriented sensing scheduling protocol in Sensor Networks," in IEEE INFOCOM 2012.</li></td>
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<td><li>Yubo Yan, Panlong Yang, Lizhao You, <strong>Bowen Li,</strong> "Demo Abstract: Online Optimal Channel Sensing, Probing, Accessing in USRP Networks." ICCPS 2012: 225.</li></td>
 
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<td><li><strong>Bowen Li,</strong> Panlong Yang, Xiang-Yang Li, ShaoJie Tang, Yunhao Liu, Qihui Wu, "Almost optimal dynamically-ordered multi-channel accessing for cognitive networks." INFOCOM 2012: 3081-3085.</li></td>
 
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<td><li><strong>Bowen Li,</strong> Panlong Yang, Jinlong Wang, Qihui Wu, Xiang-Yang Li, Yunhao Liu, "Observation vs statistics: Near optimal online channel access in cognitive radio networks." MASS 2012: 458-462.</li></td>
 
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<td><li>Panlong Yang, Yubo Yan, <strong>Bowen Li,</strong> Deke Guo, Yafei Zhang, "SPAWN: Sensing, Probing and Accessing with sWitching eNergy Cost in Multichannel WSN." MSN 2012: 132-139.</li></td>
 
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<td><li><strong>Xuan Ding,</strong> Lan Zhang, Zhiguo Wan, Ming Gu, "De-anonymizing Dynamic Social Networks," in IEEE Global Telecommunications Conference (GLOBECOM 2011).</li></td>
 
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<td><li><strong>Lei Yang,</strong> Jinsong Han, etal, "Season: Shelving Interference and Joint Identification in Large-scale RFID Systems," in Proceeding of IEEE INFOCOM, 2011.</li></td>
 
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<td><li><strong>Bowen Li,</strong> Panlong Yang, Jinlong Wang, Qihui Wu, Nan Xia, "Non-Bayesian Learning of Channel Sensing Order for Dynamic Spectrum Access Networks." CyberC 2011: 529-534.</li></td>
 
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<td><li><strong>Bowen Li,</strong> Panlong Yang, Xiang-Yang Li, Jinlong Wang, Qihui Wu, "Finding Optimal Action Point for Multi-Stage Spectrum Access in Cognitive Radio Networks." ICC 2011: 1-5.</li></td>
 
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<td><li><strong>Bowen Li,</strong> Panlong Yang, Jinlong Wang, Qihui Wu, Xiang-Yang Li, "Optimal Time-Frequency Diversity Exploitation for Multichannel System under Rayleigh Fading." MASS 2011: 381-390.</li></td>
 
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<td><li><strong>Xuan Ding,</strong> Lan Zhang, Zhiguo Wan, Ming Gu, “A brief survey on de-anonymization attacks in online social networks,” in Proceedings of the International Conference on Computational Aspects of Social Networks (CASoN 2010), pp. 611-615.</li></td>
 
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<td><li>Lan Zhang, <strong>Xuan Ding,</strong> Zhiguo Wan, Ming Gu, Xiangyang Li, “WiFace: A secure geosocial networking system using WiFi-based multi-hop MANET,” in Proceedings of the 1st ACM Workshop on Mobile Cloud Computing and Services: Social Networks and Beyond (MCS 2010), pp. 1-8.</li></td>
 
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<td><li>Wei Wang, <strong>Xuan Ding,</strong> Chunping Li, Hui Wang, “A novel evaluation method for defect prediction in software systems,” in Proceedings of the International Conference on Computational Intelligence and Software Engineering (CiSE 2010), pp. 1-5.</li></td>
 
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<td><li><strong>Lei Yang,</strong> Jinsong Han etal, "Identification-Free Batch Authentication for RFID Tags", in Proceeding of IEEE ICNP, 2010.</li></td>
 
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<td><li><strong>Lei Yang,</strong> Jinsong Han, "Utilizing RF Interference to Enable Private Estimation in RFID Systems", in Proceeding of IEEE ICPADS, 2010.</li></td>
 
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<td><li><strong>Lei Yang,</strong> Jinsong Han, "Revisiting Tag Collision Problem in RFID Systems", in Proceedings of IEEE ICPP, 2010.</li></td>
 
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<td><li><strong>Lei Yang,</strong> Yong Qi, Jinsong Han, Cheng Wang, Yunhao Liu, "Shelving Interference and Joint Identification in Large-Scale RFID System," IEEE TPDS, 2013, to be appeared.</li></td>
 
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<td><li><strong>Bowen Li,</strong> Panlong Yang, Jinlong Wang, Qihui Wu, Shaojie Tang, Xiang-Yang Li, Yunhao Liu, "Almost Optimal Dynamically-Ordered Channel Sensing and Accessing for Cognitive Networks," IEEE Transactions on Mobile Computing, 31 July 2013.</li></td>
 
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<tr class="paper year2012">
 
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<td><li>Longfei Shangguan, <strong>Lei Yang,</strong> etal , "Exploiting RF Interference for Private Cardinality Estimation in RFID System", in Ad Hoc & Sensor Wireless Networks, 2012.</li></td>
 
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<td><li><strong>Bowen Li,</strong> Panlong Yang, Jinlong Wang, Liang Shen, Yitao Xu, Yijing Liu, Xiang-Yang Li: Optimal Action Point for Dynamic Spectrum Utilization Under Rayleigh Fading. Ad Hoc & Sensor Wireless Networks17(1-2): 1-32 (2012).</li></td>
 
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<td><li><strong>Bowen Li,</strong> Panlong Yang, Jinlong Wang, Qihui Wu, ShaoJie Tang, Xiang-Yang Li, Yunhao Liu: Optimal Frequency-Temporal Opportunity Exploitation for Multichannel Ad Hoc Networks. IEEE Trans. Parallel Distrib. Syst.23(12): 2289-2302 (2012).</li></td>
 
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<td><li>Lan Zhang, <strong>Xuan Ding,</strong> Zhiguo Wan, Ming Gu, Xiangyang Li, “WiFace: A secure geosocial networking system using WiFi-based multihop MANET,” in ZTE Communications, vol. 9, no. 1, pp. 27-32.</li></td>
 
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Our address: Room 11-201, East main building, School of Software, Tsinghua University, Beijing, China<br>
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Latest revision as of 01:26, 29 October 2013


wiki learned from TagSys - School of Software, Tsinghua University

Overview

Based on modeling work, we find that negative feedback can contribute to the network’s adaptation to DNA copy number variation. So we analysed the following three-node networks, A and B. The difference between A and B is the output nodes of network A has negative feedback.
We transfected this two circuits into mammalian cells (Hela cell). By testing the mean value of EYFP (Enhance Yellow Fluorescent Protein, the output of our circuits), and the relationship between the EYFP and the DNA copy number, we can prove the hypothesis.

Construction

We constructed the following circuit A ,B and C .The circuit A corresponds to the network A ,while the circuit B is the implementation of network B. Circuit C is used as a control design to testify the function of A and B.
In circuit A, as we can see, the input is miR-21, which can repress the plasmid pz371 and K1116002(The plasmid’s information can be found in parts). K1116002 induced by rtTA and Dox, serves as an auxiliary node, producing the LacI gene to inhibit the expression of EYFP. EYFP(Enhance Yellow Fluorescent Protein )is used as output. Besides, the miR-FF3 restrains the expression of LacI. The reason that we get the most of post-transcriptional control can be seen in Supplementary text.
In circuit B, however, the plasmid K1116003 does not have FF3 target, leading to the contrast between circuit A and B. We can see miR-21 can’t target at pZ349 and pZ331 in circuit C , that is, there is no input in circuit C. The miR-21, used to distinguish cancer cell from normal cells ,is endogenous in Hela cell.

Supplementary text

miRNAs function as posttranscriptional regulators which have distinguished features compared to transcriptional regulators, intervening late in gene expression process, with the capability to counteract variation from the upstream processes (Margaret et al., 2012). Research shows that while conducting experiment on an incoherent feedforward motif in mammalian cells, posttranscriptional regulation results in superior adaptation behavior, higher absolute expression levels and lower intrinsic fluctuations (Bleris et al., 2011). miRNAs can serve as buffers against variation during gene expression; transient increases in transcription factor activity would propagate to increases in target miRNA transcription while would be counteracted by increased miRNA and vice versa. Therefore, under the miRNA posttranscriptional regulation, protein output can be uncoupled from fluctuations in transcription factor concentration or activity (Margaret et al., 2012). miRNAs also possess good stability which, consistent with theoretical constraints, meets the need for enough molecules of a regulator to achieve a small reduction in the noise of a target gene (Lestas et al., 2010).











Experimental Characterization

We took advantage of another fluorescent protein(mkate ) as reference gene, which has no influence in our design. Published literature generally supports the view that in transient transfections, fluorescence depends linearly on the copy number of transfected plasmids (Tseng et al, 1997; Pollard et al, 1998;Cohenet al,2009; Schwakeet al, 2010). While strictly speaking, this reporter level also depends on many other potentially fluctuating parameters such as global synthesis and degradation rates(Leonidas Bleris et al,2011),it is more legitimately use the normalized quotient to instead of the value of EYFP.


Apparently, the output of circuit C is lower than circuit B .Having the negative feedback compared with circuit B, the expression of EYFP in circuit A is strongest.

Then we analysed the output of constructed designs varies with the DNA copy number. Facing with the difficulty of counting the copy number directly, we employed the reference gene to reflect .We think the copy number is high when the expression intensity of mkate is strong. One hundred thousand positive Hela cells was collected to obtain the relationship between EYFP and make.


From the figure 2, we learned that in circuit A, with the increase of the expression intensity of makte, the value of EYFP gradually reaches saturation. In another word, the circuit A’s output reaches saturation fast with the increase of copy number. We came to a conclusion circuit A’s adaptation to DNA copy number is higher than circuit B’s. So, the negative feedback works.

Parts

NamedescriptionPart TypeDesigner
K1116000LacI with miR-21 and miR-FF3 targetCompositeLei Wei
K1116001LacI with miR-21 and miR-FF5 targetCompositeShuguang Peng
K1116002TRE-LacI with miR-21 and miR-FF3 targetCompositeShuguang Peng
K1116003TRE-LacI with miR-21 and miR-FF5 targetCompositeShuguang Peng
K1116004CAG-EYFP-miRNA-FF3CompositeShuguang Peng
K1116005CAG-Cerulean-hsa-miR-21CompositeShuguang Peng








Discussion

Due to some restrictions in wetlab, we only finished the above-mentioned experiment. We found that the number of Hela cells who possesses high copy number is comparatively low. We also noticed the circuit C’s output is higher than expected in Figure 1.This may cause wrong judge when use the design to detect miR-21. Some measures will be taken to solve this question.
Besides, we are going to endeavor to construct the other networks mentioned in modeling work.


Reference:
  • [1]Bleris, L., Xie, Z., Glass, D., Adadey, A., Sontag, E., and Benenson, Y. (2011). Synthetic incoherent feedforward circuits show adaptation to the amount of their genetic template. Mol. Syst. Biol.7, 519
  • [2]Ebert M S, Sharp P A. Roles for microRNAs in conferring robustness to biological processes[J]. Cell, 2012, 149(3): 515-524.
  • [3] Lestas I, Vinnicombe G, Paulsson J. Fundamental limits on the suppression of molecular fluctuations[J]. Nature, 2010, 467(7312): 174-178.