Browsing by Author "Zhang, Qiang"

Now showing 1 - 9 of 9
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    A novel mathematical method for disclosing oscillations in gene transcription: A comparative study
    (Public Library of Science, 2018) Antoulas, Athanasios C.; Zhu, Bokai; Zhang, Qiang; York, Brian; O'Malley, Bert W.; Dacso, Clifford C.
    Circadian rhythmicity, the 24-hour cycle responsive to light and dark, is determined by periodic oscillations in gene transcription. This phenomenon has broad ramifications in physiologic function. Recent work has disclosed more cycles in gene transcription, and to the uncovering of these we apply a novel signal processing methodology known as the pencil method and compare it to conventional parametric, nonparametric, and statistical methods. Methods: In order to assess periodicity of gene expression over time, we analyzed a database derived from livers of mice entrained to a 12-hour light/12-hour dark cycle. We also analyzed artificially generated signals to identify differences between the pencil decomposition and other alternative methods. Results: The pencil decomposition revealed hitherto-unsuspected oscillations in gene transcription with 12-hour periodicity. The pencil method was robust in detecting the 24-hour circadian cycle that was known to exist, as well as confirming the existence of shorter-period oscillations. A key consequence of this approach is that orthogonality of the different oscillatory components can be demonstrated. thus indicating a biological independence of these oscillations, that has been subsequently confirmed empirically by knocking out the gene responsible for the 24-hour clock. Conclusion: System identification techniques can be applied to biological systems and can uncover important characteristics that may elude visual inspection of the data. Significance: The pencil method provides new insights on the essence of gene expression and discloses a wide variety of oscillations in addition to the well-studied circadian pattern. This insight opens the door to the study of novel mechanisms by which oscillatory gene expression signals exert their regulatory effect on cells to influence human diseases.
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    Colors of Single-Wall Carbon Nanotubes
    (Wiley, 2021) Wei, Nan; Tian, Ying; Liao, Yongping; Komatsu, Natsumi; Gao, Weilu; Lyuleeva‐Husemann, Alina; Zhang, Qiang; Hussain, Aqeel; Ding, Er-Xiong; Yao, Fengrui; Halme, Janne; Liu, Kaihui; Kono, Junichiro; Jiang, Hua; Kauppinen, Esko I.
    Although single-wall carbon nanotubes (SWCNTs) exhibit various colors in suspension, directly synthesized SWCNT films usually appear black. Recently, a unique one-step method for directly fabricating green and brown films has been developed. Such remarkable progress, however, has brought up several new questions. The coloration mechanism, potentially achievable colors, and color controllability of SWCNTs are unknown. Here, a quantitative model is reported that can predict the specific colors of SWCNT films and unambiguously identify the coloration mechanism. Using this model, colors of 466 different SWCNT species are calculated, which reveals a broad spectrum of potentially achievable colors of SWCNTs. The calculated colors are in excellent agreement with existing experimental data. Furthermore, the theory predicts the existence of many brilliantly colored SWCNT films, which are experimentally expected. This study shows that SWCNTs as a form of pure carbon, can display a full spectrum of vivid colors, which is expected to complement the general understanding of carbon materials.
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    Data-Driven Model Reduction for Optimal Control of Large-scale Dynamical Systems
    (2019-04-19) Zhang, Qiang; Antoulas, Athanasios
    In the thesis, we investigate data-driven model reduction for optimal control of large-scale dynamical systems. Optimal control problems play an important role in many engineering applications. However, computational cost is the bottleneck for obtaining optimal control of large-scale dynamic systems. Model reduction which approximates the large-scale complex model accurately by a smaller reduced order model can largely reduce the computation cost. In the thesis, a new model reduction approach, the Loewner Framework, is investigated for generating reduced order models for linear-quadratic optimal control problems. The Loewner Framework is a data-driven model reduction method which can construct the reduced order models from measurements directly. The property gives Loewner framework more flexibility compared with other model-driven methods. Besides, the Loewner framework is an interpolation-based method that requires much less computation cost than SVD-based model reduction methods for large-scale dynamical systems. In this thesis, the iterative error system approximation approach which has an aposteriori error bound is developed for the model reduction of optimal control problems. On several optimal control problems involving CD player, damped Euler-Bernoulli beam and water pollution problem, Loewner framework shows unique performance compared with other methods like balanced truncation and rational Krylov method.
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    Diverse Applications of Nanomedicine
    (American Chemical Society, 2017) Pelaz, Beatriz; Alexiou, Christoph; Alvarez-Puebla, Ramon A.; Alves, Frauke; Andrews, Anne M.; Ashraf, Sumaira; Balogh, Lajos P.; Ballerini, Laura; Bestetti, Alessandra; Brendel, Cornelia; Bosi, Susanna; Carril, Monica; Chan, Warren C.W.; Chen, Chunying; Chen, Xiaodong; Chen, Xiaoyuan; Cheng, Zhen; Cui, Daxiang; Du, Jianzhong; Dullin, Christian; Escudero, Alberto; Feliu, Neus; Gao, Mingyuan; George, Michael; Gogotsi, Yury; Grünweller, Arnold; Gu, Zhongwei; Halas, Naomi J.; Hampp, Norbert; Hartmann, Roland K.; Hersam, Mark C.; Hunziker, Patrick; Jian, Ji; Jiang, Xingyu; Jungebluth, Philipp; Kadhiresan, Pranav; Kataoka, Kazunori; Khademhosseini, Ali; Kopeček, Jindřich; Kotov, Nicholas A.; Krug, Harald F.; Lee, Dong Soo; Lehr, Claus-Michael; Leong, Kam W.; Liang, Xing-Jie; Lim, Mei Ling; Liz-Marzán, Luis M.; Ma, Xiaowei; Macchiarini, Paolo; Meng, Huan; Möhwald, Helmuth; Mulvaney, Paul; Nel, Andre E.; Nie, Shuming; Nordlander, Peter; Okano, Teruo; Oliveira, Jose; Park, Tai Hyun; Penner, Reginald M.; Prato, Maurizio; Puntes, Victor; Rotello, Vincent M.; Samarakoon, Amila; Schaak, Raymond E.; Shen, Youqing; Sjöqvist, Sebastian; Skirtach, Andre G.; Soliman, Mahmoud G.; Stevens, Molly M.; Sung, Hsing-Wen; Tang, Ben Zhong; Tietze, Rainer; Udugama, Buddhisha N.; VanEpps, J. Scott; Weil, Tanja; Weiss, Paul S.; Willner, Itamar; Wu, Yuzhou; Yang, Lily; Yue, Zhao; Zhang, Qian; Zhang, Qiang; Zhang, Xian-En; Zhao, Yuliang; Zhou, Xin; Parak, Wolfgang J.
    The design and use of materials in the nanoscale size range for addressing medical and health-related issues continues to receive increasing interest. Research in nanomedicine spans a multitude of areas, including drug delivery, vaccine development, antibacterial, diagnosis and imaging tools, wearable devices, implants, high-throughput screening platforms, etc. using biological, nonbiological, biomimetic, or hybrid materials. Many of these developments are starting to be translated into viable clinical products. Here, we provide an overview of recent developments in nanomedicine and highlight the current challenges and upcoming opportunities for the field and translation to the clinic.
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    Factorization of the Loewner Matrix Pencil and Its Consequences
    (2022-04-19) Zhang, Qiang; Antoulas, Athanasios
    In this thesis, we derive a factorization of the Loewner pencil in data-driven modeling and explore its consequences. The Loewner framework is a data-driven modeling and complexity reduction method that can be used to learn models of dynamical systems from measurements of their transfer function. One key feature of the Loewner framework consists in the fact that it does not need an exact description of the original dynamical system to start with, which is typically described by ordinary or partial differential equations (ODEs, PDEs). Instead of having full access to the coefficient matrices that scale these equations, one requires only transfer function measurement values. Finally, by arranging the given data in a specific way, one can construct with basically no computational effort a realization (dynamical system) that explains the data. The Loewner pencil plays a central role in the system realization constructed by the Loewner framework. More precisely, the two Loewner matrices that enter the pencil represent the coefficient matrices that scale the internal variable vector and its derivative. Consequently, the eigenvalues of the pencil are the poles of the surrogate Loewner model and are used to characterize the dynamics of the system. In this thesis, the Loewner pencil is factorized in terms of generalized Cauchy matrices that are composed of poles, residues of the system, and measurement points. It is shown that the factors given by the generalized Cauchy matrices are Krylov projection matrices for a particular system realization. Using the factorization of the generalized Loewner matrix, the eigenvalue decomposition (EVD) of the Loewner pencil is hence available. Based on this EVD and eigenvalue perturbation theory for matrix pencils, we explore two types of eigenvalue sensitivities. The first one is defined for unstructured perturbations of the Loewner pencil, while the second one is defined for structured perturbations. The motivation for studying these two sensitivities is that they reflect the robustness of the Loewner surrogate model. We will show that the unstructured perturbation sensitivity is related to the numerical conditioning of the Loewner pencil and can be used in comparison to the pseudo spectrum of the pencil. Moreover, it is shown that the structured perturbation sensitivity can be used to estimate eigenvalue perturbations as a result of the noise in the data. We also discuss how the choice of data affects the two sensitivities. Finally, we will extend our framework to the time-series data and show its application in the research of biological rhythms.
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    Ion Segregation in Aqueous Solutions
    (American Chemical Society, 2012) Bian, Hongtao; Li, Jiebo; Zhang, Qiang; Chen, Hailong; Zhuang, Wei; Gao, Yi Qin
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    Q493K and Q498H substitutions in Spike promote adaptation of SARS-CoV-2 in mice
    (Elsevier, 2021) Huang, Kun; Zhang, Yufei; Hui, Xianfeng; Zhao, Ya; Gong, Wenxiao; Wang, Ting; Zhang, Shaoran; Yang, Yong; Deng, Fei; Zhang, Qiang; Chen, Xi; Yang, Ying; Sun, Xiaomei; Chen, Huanchun; Tao, Yizhi Jane; Zou, Zhong; Jin, Meilin
    Background: An ideal animal model to study SARS-coronavirus 2 (SARS-CoV-2) pathogenesis and evaluate therapies and vaccines should reproduce SARS-CoV-2 infection and recapitulate lung disease like those seen in humans. The angiotensin-converting enzyme 2 (ACE2) is a functional receptor for SARS-CoV-2, but mice are resistant to the infection because their ACE2 is incompatible with the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein . Methods: SARS-CoV-2 was passaged in BALB/c mice to obtain mouse-adapted virus strain. Complete genome deep sequencing of different generations of viruses was performed to characterize the dynamics of the adaptive mutations in SARS-CoV-2. Indirect immunofluorescence analysis and Biolayer interferometry experiments determined the binding affinity of mouse-adapted SARS-CoV-2 WBP-1 RBD to mouse ACE2 and human ACE2. Finally, we tested whether TLR7/8 agonist Resiquimod (R848) could also inhibit the replication of WBP-1 in the mouse model. Findings: The mouse-adapted strain WBP-1 showed increased infectivity in BALB/c mice and led to severe interstitial pneumonia. We characterized the dynamics of the adaptive mutations in SARS-CoV-2 and demonstrated that Q493K and Q498H in RBD significantly increased its binding affinity towards mouse ACE2. Additionally, the study tentatively found that the TLR7/8 agonist Resiquimod was able to protect mice against WBP-1 challenge. Therefore, this mouse-adapted strain is a useful tool to investigate COVID-19 and develop new therapies. Interpretation: We found for the first time that the Q493K and Q498H mutations in the RBD of WBP-1 enhanced its interactive affinities with mACE2. The mouse-adapted SARS-CoV-2 provides a valuable tool for the evaluation of novel antiviral and vaccine strategies. This study also tentatively verified the antiviral activity of TLR7/8 agonist Resiquimod against SARS-CoV-2 in vitro and in vivo. Funding: This research was funded by the National Key Research and Development Program of China (2020YFC0845600) and Emergency Science and Technology Project of Hubei Province (2020FCA046) and Robert A. Welch Foundation (C-1565).
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    Super-stretchable, Transparent Carbon Nanotube-Based Capacitive Strain Sensors for Human Motion Detection
    (Nature Publishing Group, 2013) Cai, Le; Song, Li; Luan, Pingshan; Zhang, Qiang; Zhang, Nan; Gao, Qingqing; Zhao, Duan; Zhang, Xiao; Tu, Min; Yang, Feng; Zhou, Wenbin; Fan, Qingxia; Luo, Jun; Zhou, Weiya; Ajayan, Pulickel M.; Xie, Sishen
    Realization of advanced bio-interactive electronic devices requires mechanically compliant sensors with the ability to detect extremely large strain. Here, we design a new multifunctional carbon nanotube (CNT) based capacitive strain sensors which can detect strains up to 300% with excellent durability even after thousands of cycles. The CNT-based strain gauge devices exhibit deterministic and linear capacitive response throughout the whole strain range with a gauge factor very close to the predicted value (strictly 1), representing the highest sensitivity value. The strain tests reveal the presented strain gauge with excellent dynamic sensing ability without overshoot or relaxation, and ultrafast response at sub-second scale. Coupling these superior sensing capabilities to the high transparency, physical robustness and flexibility, we believe the designed stretchable multifunctional CNT-based strain gauge may have various potential applications in human friendly and wearable smart electronics, subsequently demonstrated by our prototypical data glove and respiration monitor.
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    The opposite effects of sodium and potassium cations on water dynamics
    (Royal Society of Chemistry, 2017) Zhang, Qiang; Chen, Hailong; Wu, Tianmin; Jin, Tan; Pan, Zhijun; Zheng, Junrong; Gao, Yiqin; Zhuang, Wei
    Water rotational dynamics in NaSCN and KSCN solutions at a series of concentrations are investigated using femtosecond infrared spectroscopy and theory. Femtosecond infrared measurements, consistent with previous NMR observations, detect that sodium slows down while potassium accelerates the water O–H bond rotation. Results of reported neutron scattering measurements, on the other hand, suggested that these two cations have similar structure-breaking effects on water, and therefore should both accelerate water rotation through the presumably dominating large-amplitude angular jump component. To explain this discrepancy, theoretical studies with both classical and ab initio models were carried out, which indicate that both ions indeed accelerate the large-amplitude angular jump rotation of the water molecules, while the observed cation specific effect originates from the non-negligible opposite impact of the sodium and potassium cations on the diffusive rotation of water molecules.