1
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Mikaeeli Kangarshahi B, Naghib SM, Rabiee N. DNA/RNA-based electrochemical nanobiosensors for early detection of cancers. Crit Rev Clin Lab Sci 2024; 61:473-495. [PMID: 38450458 DOI: 10.1080/10408363.2024.2321202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 02/02/2024] [Accepted: 02/16/2024] [Indexed: 03/08/2024]
Abstract
Nucleic acids, like DNA and RNA, serve as versatile recognition elements in electrochemical biosensors, demonstrating notable efficacy in detecting various cancer biomarkers with high sensitivity and selectivity. These biosensors offer advantages such as cost-effectiveness, rapid response, ease of operation, and minimal sample preparation. This review provides a comprehensive overview of recent developments in nucleic acid-based electrochemical biosensors for cancer diagnosis, comparing them with antibody-based counterparts. Specific examples targeting key cancer biomarkers, including prostate-specific antigen, microRNA-21, and carcinoembryonic antigen, are highlighted. The discussion delves into challenges and limitations, encompassing stability, reproducibility, interference, and standardization issues. The review suggests future research directions, exploring new nucleic acid recognition elements, innovative transducer materials and designs, novel signal amplification strategies, and integration with microfluidic devices or portable instruments. Evaluating these biosensors in clinical settings using actual samples from cancer patients or healthy donors is emphasized. These sensors are sensitive and specific at detecting non-communicable and communicable disease biomarkers. DNA and RNA's self-assembly, programmability, catalytic activity, and dynamic behavior enable adaptable sensing platforms. They can increase biosensor biocompatibility, stability, signal transduction, and amplification with nanomaterials. In conclusion, nucleic acids-based electrochemical biosensors hold significant potential to enhance cancer detection and treatment through early and accurate diagnosis.
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Affiliation(s)
- Babak Mikaeeli Kangarshahi
- Nanotechnology Department, School of Advanced Technologies, Iran University of Science and Technology (IUST), Tehran, Iran
| | - Seyed Morteza Naghib
- Nanotechnology Department, School of Advanced Technologies, Iran University of Science and Technology (IUST), Tehran, Iran
| | - Navid Rabiee
- Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Perth, Western Australia, Australia
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2
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Liu A, Zhang X, Liu Z, Li Y, Peng X, Li X, Qin Y, Hu C, Qiu Y, Jiang H, Wang Y, Li Y, Tang J, Liu J, Guo H, Deng T, Peng S, Tian H, Ren TL. The Roadmap of 2D Materials and Devices Toward Chips. NANO-MICRO LETTERS 2024; 16:119. [PMID: 38363512 PMCID: PMC10873265 DOI: 10.1007/s40820-023-01273-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 10/30/2023] [Indexed: 02/17/2024]
Abstract
Due to the constraints imposed by physical effects and performance degradation, silicon-based chip technology is facing certain limitations in sustaining the advancement of Moore's law. Two-dimensional (2D) materials have emerged as highly promising candidates for the post-Moore era, offering significant potential in domains such as integrated circuits and next-generation computing. Here, in this review, the progress of 2D semiconductors in process engineering and various electronic applications are summarized. A careful introduction of material synthesis, transistor engineering focused on device configuration, dielectric engineering, contact engineering, and material integration are given first. Then 2D transistors for certain electronic applications including digital and analog circuits, heterogeneous integration chips, and sensing circuits are discussed. Moreover, several promising applications (artificial intelligence chips and quantum chips) based on specific mechanism devices are introduced. Finally, the challenges for 2D materials encountered in achieving circuit-level or system-level applications are analyzed, and potential development pathways or roadmaps are further speculated and outlooked.
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Affiliation(s)
- Anhan Liu
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100049, People's Republic of China
| | - Xiaowei Zhang
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100049, People's Republic of China
| | - Ziyu Liu
- School of Microelectronics, Fudan University, Shanghai, 200433, People's Republic of China
| | - Yuning Li
- School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, 100044, People's Republic of China
| | - Xueyang Peng
- High-Frequency High-Voltage Device and Integrated Circuits R&D Center, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, People's Republic of China
- School of Integrated Circuits, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Xin Li
- State Key Laboratory of Dynamic Measurement Technology, Shanxi Province Key Laboratory of Quantum Sensing and Precision Measurement, North University of China, Taiyuan, 030051, People's Republic of China
| | - Yue Qin
- State Key Laboratory of Dynamic Measurement Technology, Shanxi Province Key Laboratory of Quantum Sensing and Precision Measurement, North University of China, Taiyuan, 030051, People's Republic of China
| | - Chen Hu
- High-Frequency High-Voltage Device and Integrated Circuits R&D Center, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, People's Republic of China
- School of Integrated Circuits, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Yanqing Qiu
- High-Frequency High-Voltage Device and Integrated Circuits R&D Center, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, People's Republic of China
- School of Integrated Circuits, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Han Jiang
- School of Microelectronics, Fudan University, Shanghai, 200433, People's Republic of China
| | - Yang Wang
- School of Microelectronics, Fudan University, Shanghai, 200433, People's Republic of China
| | - Yifan Li
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100049, People's Republic of China
| | - Jun Tang
- State Key Laboratory of Dynamic Measurement Technology, Shanxi Province Key Laboratory of Quantum Sensing and Precision Measurement, North University of China, Taiyuan, 030051, People's Republic of China
| | - Jun Liu
- State Key Laboratory of Dynamic Measurement Technology, Shanxi Province Key Laboratory of Quantum Sensing and Precision Measurement, North University of China, Taiyuan, 030051, People's Republic of China
| | - Hao Guo
- State Key Laboratory of Dynamic Measurement Technology, Shanxi Province Key Laboratory of Quantum Sensing and Precision Measurement, North University of China, Taiyuan, 030051, People's Republic of China.
| | - Tao Deng
- School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, 100044, People's Republic of China.
| | - Songang Peng
- High-Frequency High-Voltage Device and Integrated Circuits R&D Center, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, People's Republic of China.
- IMECAS-HKUST-Joint Laboratory of Microelectronics, Beijing, 100029, People's Republic of China.
| | - He Tian
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100049, People's Republic of China.
| | - Tian-Ling Ren
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100049, People's Republic of China.
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Bodily TA, Ramanathan A, Wei S, Karkisaval A, Bhatt N, Jerez C, Haque MA, Ramil A, Heda P, Wang Y, Kumar S, Leite M, Li T, Zhao J, Lal R. In pursuit of degenerative brain disease diagnosis: Dementia biomarkers detected by DNA aptamer-attached portable graphene biosensor. Proc Natl Acad Sci U S A 2023; 120:e2311565120. [PMID: 37956285 PMCID: PMC10666025 DOI: 10.1073/pnas.2311565120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 09/25/2023] [Indexed: 11/15/2023] Open
Abstract
Dementia is a brain disease which results in irreversible and progressive loss of cognition and motor activity. Despite global efforts, there is no simple and reliable diagnosis or treatment option. Current diagnosis involves indirect testing of commonly inaccessible biofluids and low-resolution brain imaging. We have developed a portable, wireless readout-based Graphene field-effect transistor (GFET) biosensor platform that can detect viruses, proteins, and small molecules with single-molecule sensitivity and specificity. We report the detection of three important amyloids, namely, Amyloid beta (Aβ), Tau (τ), and α-Synuclein (αS) using DNA aptamer nanoprobes. These amyloids were isolated, purified, and characterized from the autopsied brain tissues of Alzheimer's Disease (AD) and Parkinson's Disease (PD) patients. The limit of detection (LoD) of the sensor is 10 fM, 1-10 pM, 10-100 fM for Aβ, τ, and αS, respectively. Synthetic as well as autopsied brain-derived amyloids showed a statistically significant sensor response with respect to derived thresholds, confirming the ability to define diseased vs. nondiseased states. The detection of each amyloid was specific to their aptamers; Aβ, τ, and αS peptides when tested, respectively, with aptamers nonspecific to them showed statistically insignificant cross-reactivity. Thus, the aptamer-based GFET biosensor has high sensitivity and precision across a range of epidemiologically significant AD and PD variants. This portable diagnostic system would allow at-home and POC testing for neurodegenerative diseases globally.
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Affiliation(s)
| | - Anirudh Ramanathan
- Department of Bioengineering, University of California, San Diego, CA92093
| | - Shanhong Wei
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai200050, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Abhijith Karkisaval
- Department of Mechanical and Aerospace Engineering, University of California, San Diego, CA92093
| | - Nemil Bhatt
- Mitchell Center for Neurodegenerative Disorders, Department of Neurology, University of Texas Medical Branch, Galveston, TX77555
| | - Cynthia Jerez
- Mitchell Center for Neurodegenerative Disorders, Department of Neurology, University of Texas Medical Branch, Galveston, TX77555
| | - Md Anzarul Haque
- Mitchell Center for Neurodegenerative Disorders, Department of Neurology, University of Texas Medical Branch, Galveston, TX77555
| | - Armando Ramil
- Department of Bioengineering, University of California, San Diego, CA92093
| | - Prachi Heda
- Department of Bioengineering, University of California, San Diego, CA92093
| | - Yi Wang
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai200050, China
| | - Sanjeev Kumar
- Department of Computer Science, University of Illinois Urbana-Champaign, Champaign, IL61820
| | - Mikayla Leite
- Department of Bioengineering, University of California, San Diego, CA92093
| | - Tie Li
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai200050, China
| | - Jianlong Zhao
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai200050, China
| | - Ratnesh Lal
- Department of Bioengineering, University of California, San Diego, CA92093
- Department of Mechanical and Aerospace Engineering, University of California, San Diego, CA92093
- Materials Science and Engineering Program, University of California, San Diego, CA92093
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4
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Sun T, Feng B, Huo J, Xiao Y, Wang W, Peng J, Li Z, Du C, Wang W, Zou G, Liu L. Artificial Intelligence Meets Flexible Sensors: Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses. NANO-MICRO LETTERS 2023; 16:14. [PMID: 37955844 PMCID: PMC10643743 DOI: 10.1007/s40820-023-01235-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 09/24/2023] [Indexed: 11/14/2023]
Abstract
The recent wave of the artificial intelligence (AI) revolution has aroused unprecedented interest in the intelligentialize of human society. As an essential component that bridges the physical world and digital signals, flexible sensors are evolving from a single sensing element to a smarter system, which is capable of highly efficient acquisition, analysis, and even perception of vast, multifaceted data. While challenging from a manual perspective, the development of intelligent flexible sensing has been remarkably facilitated owing to the rapid advances of brain-inspired AI innovations from both the algorithm (machine learning) and the framework (artificial synapses) level. This review presents the recent progress of the emerging AI-driven, intelligent flexible sensing systems. The basic concept of machine learning and artificial synapses are introduced. The new enabling features induced by the fusion of AI and flexible sensing are comprehensively reviewed, which significantly advances the applications such as flexible sensory systems, soft/humanoid robotics, and human activity monitoring. As two of the most profound innovations in the twenty-first century, the deep incorporation of flexible sensing and AI technology holds tremendous potential for creating a smarter world for human beings.
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Affiliation(s)
- Tianming Sun
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
- College of Materials Science and Engineering, Shanxi Province, Taiyuan University of Technology, Taiyuan, 030024, People's Republic of China
| | - Bin Feng
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Jinpeng Huo
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Yu Xiao
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Wengan Wang
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Jin Peng
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Zehua Li
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Chengjie Du
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Wenxian Wang
- College of Materials Science and Engineering, Shanxi Province, Taiyuan University of Technology, Taiyuan, 030024, People's Republic of China.
| | - Guisheng Zou
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China.
| | - Lei Liu
- Department of Mechanical Engineering, State Key Laboratory of Tribology in Advanced Equipment, Key Laboratory for Advanced Manufacturing by Materials Processing Technology, Ministry of Education of PR China, Tsinghua University, Beijing, 100084, People's Republic of China.
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5
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Cheng N, Lou B, Wang H. Discovering the digital biomarker of hepatocellular carcinoma in serum with SERS-based biosensors and intelligence vision. Colloids Surf B Biointerfaces 2023; 226:113315. [PMID: 37086688 DOI: 10.1016/j.colsurfb.2023.113315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/31/2023] [Accepted: 04/11/2023] [Indexed: 04/24/2023]
Abstract
By its many virtues, non-biomarker-reliant molecular detection has recently shown bright prospects for cancer screening but its clinical application is hindered by the shortage of measurable criteria that are analogous to biomarkers. Here, we report a digital biomarker, as a new-concept serum biomarker, of hepatocellular carcinoma (HCC) found with SERS-based biosensors and a deep neural network "digital retina" for visualizing and explicitly defining spectral fingerprints. We validate the discovered digital biomarker (a collection of 10 characteristic peaks in the serum SERS spectra) with unsupervised clustering of spectra from an independent sample batch comprised normal individuals and HCC cases; the validation results show clustering accuracies of 95.71% and 100.00%, respectively. Furthermore, we find that the digital biomarker of HCC shares a few common peaks with three clinically applied serum biomarkers, which means it could convey essential biomolecular information similar to these biomarkers. Accordingly, we present an intelligent method for early HCC detection that leverages the digital biomarker with similar traits as biomarkers. Employing the digital biomarker, we could accurately stratify HCC, hepatitis B, and normal populations with linear classifiers, exhibiting accuracies over 92% and area under the receiver operating curve values above 0.93. It is anticipated that this non-biomarker-reliant molecular detection method will facilitate mass cancer screening.
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Affiliation(s)
- Ningtao Cheng
- School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China.
| | - Bin Lou
- Department of Laboratory Medicine, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310003, China
| | - Hongyang Wang
- International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Hospital, Shanghai 200438, China; National Center for Liver Cancer, Shanghai 201805, China.
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6
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Saha S, Sachdev M, Mitra SK. Recent advances in label-free optical, electrochemical, and electronic biosensors for glioma biomarkers. BIOMICROFLUIDICS 2023; 17:011502. [PMID: 36844882 PMCID: PMC9949901 DOI: 10.1063/5.0135525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
Abstract
Gliomas are the most commonly occurring primary brain tumor with poor prognosis and high mortality rate. Currently, the diagnostic and monitoring options for glioma mainly revolve around imaging techniques, which often provide limited information and require supervisory expertise. Liquid biopsy is a great alternative or complementary monitoring protocol that can be implemented along with other standard diagnosis protocols. However, standard detection schemes for sampling and monitoring biomarkers in different biological fluids lack the necessary sensitivity and ability for real-time analysis. Lately, biosensor-based diagnostic and monitoring technology has attracted significant attention due to several advantageous features, including high sensitivity and specificity, high-throughput analysis, minimally invasive, and multiplexing ability. In this review article, we have focused our attention on glioma and presented a literature survey summarizing the diagnostic, prognostic, and predictive biomarkers associated with glioma. Further, we discussed different biosensory approaches reported to date for the detection of specific glioma biomarkers. Current biosensors demonstrate high sensitivity and specificity, which can be used for point-of-care devices or liquid biopsies. However, for real clinical applications, these biosensors lack high-throughput and multiplexed analysis, which can be achieved via integration with microfluidic systems. We shared our perspective on the current state-of-the-art different biosensor-based diagnostic and monitoring technologies reported and the future research scopes. To the best of our knowledge, this is the first review focusing on biosensors for glioma detection, and it is anticipated that the review will offer a new pathway for the development of such biosensors and related diagnostic platforms.
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Affiliation(s)
| | - Manoj Sachdev
- Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
| | - Sushanta K. Mitra
- Micro and Nanoscale Transport Laboratory, Department of Mechanical and Mechatronics Engineering, Waterloo Institute for Nanotechnology, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
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Ban DK, Bodily T, Karkisaval AG, Dong Y, Natani S, Ramanathan A, Ramil A, Srivastava S, Bandaru P, Glinsky G, Lal R. Rapid self-test of unprocessed viruses of SARS-CoV-2 and its variants in saliva by portable wireless graphene biosensor. Proc Natl Acad Sci U S A 2022; 119:e2206521119. [PMID: 35763566 PMCID: PMC9282385 DOI: 10.1073/pnas.2206521119] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 05/26/2022] [Indexed: 12/20/2022] Open
Abstract
We have developed a DNA aptamer-conjugated graphene field-effect transistor (GFET) biosensor platform to detect receptor-binding domain (RBD), nucleocapsid (N), and spike (S) proteins, as well as viral particles of original Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) coronavirus and its variants in saliva samples. The GFET biosensor is a label-free, rapid (≤20 min), ultrasensitive handheld wireless readout device. The limit of detection (LoD) and the limit of quantitation (LoQ) of the sensor are 1.28 and 3.89 plaque-forming units (PFU)/mL for S protein and 1.45 and 4.39 PFU/mL for N protein, respectively. Cognate spike proteins of major variants of concern (N501Y, D614G, Y453F, Omicron-B1.1.529) showed sensor response ≥40 mV from the control (aptamer alone) for fM to nM concentration range. The sensor response was significantly lower for viral particles and cognate proteins of Middle East Respiratory Syndrome (MERS) compared to SARS-CoV-2, indicating the specificity of the diagnostic platform for SARS-CoV-2 vs. MERS viral proteins. During the early phase of the pandemic, the GFET sensor response agreed with RT-PCR data for oral human samples, as determined by the negative percent agreement (NPA) and positive percent agreement (PPA). During the recent Delta/Omicron wave, the GFET sensor also reliably distinguished positive and negative clinical saliva samples. Although the sensitivity is lower during the later pandemic phase, the GFET-defined positivity rate is in statistically close alignment with the epidemiological population-scale data. Thus, the aptamer-based GFET biosensor has a high level of precision in clinically and epidemiologically significant SARS-CoV-2 variant detection. This universal pathogen-sensing platform is amenable for a broad range of public health applications and real-time environmental monitoring.
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Affiliation(s)
- Deependra Kumar Ban
- Department of Mechanical and Aerospace Engineering, University of California, San Diego, CA 92093
| | - Tyler Bodily
- Department of Bioengineering, University of California, San Diego, CA 92093
| | - Abhijith G. Karkisaval
- Department of Mechanical and Aerospace Engineering, University of California, San Diego, CA 92093
| | - Yongliang Dong
- Department of Mechanical and Aerospace Engineering, University of California, San Diego, CA 92093
| | - Shreyam Natani
- Department of Mechanical and Aerospace Engineering, University of California, San Diego, CA 92093
| | - Anirudh Ramanathan
- Department of Bioengineering, University of California, San Diego, CA 92093
| | - Armando Ramil
- Department of Bioengineering, University of California, San Diego, CA 92093
| | | | - Prab Bandaru
- Department of Mechanical and Aerospace Engineering, University of California, San Diego, CA 92093
- Materials Science, University of California, San Diego, CA 92093
| | - Gennadi Glinsky
- Institute of Engineering in Medicine, University of California, San Diego, CA 92093
| | - Ratnesh Lal
- Department of Mechanical and Aerospace Engineering, University of California, San Diego, CA 92093
- Department of Bioengineering, University of California, San Diego, CA 92093
- Materials Science, University of California, San Diego, CA 92093
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8
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Dai C, Liu Y, Wei D. Two-Dimensional Field-Effect Transistor Sensors: The Road toward Commercialization. Chem Rev 2022; 122:10319-10392. [PMID: 35412802 DOI: 10.1021/acs.chemrev.1c00924] [Citation(s) in RCA: 64] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The evolutionary success in information technology has been sustained by the rapid growth of sensor technology. Recently, advances in sensor technology have promoted the ambitious requirement to build intelligent systems that can be controlled by external stimuli along with independent operation, adaptivity, and low energy expenditure. Among various sensing techniques, field-effect transistors (FETs) with channels made of two-dimensional (2D) materials attract increasing attention for advantages such as label-free detection, fast response, easy operation, and capability of integration. With atomic thickness, 2D materials restrict the carrier flow within the material surface and expose it directly to the external environment, leading to efficient signal acquisition and conversion. This review summarizes the latest advances of 2D-materials-based FET (2D FET) sensors in a comprehensive manner that contains the material, operating principles, fabrication technologies, proof-of-concept applications, and prototypes. First, a brief description of the background and fundamentals is provided. The subsequent contents summarize physical, chemical, and biological 2D FET sensors and their applications. Then, we highlight the challenges of their commercialization and discuss corresponding solution techniques. The following section presents a systematic survey of recent progress in developing commercial prototypes. Lastly, we summarize the long-standing efforts and prospective future development of 2D FET-based sensing systems toward commercialization.
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Affiliation(s)
- Changhao Dai
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China.,Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Yunqi Liu
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Dacheng Wei
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China.,Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
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9
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Du Y, Zhang P, Liu W, Tian J. Optical Imaging of Epigenetic Modifications in Cancer: A Systematic Review. PHENOMICS (CHAM, SWITZERLAND) 2022; 2:88-101. [PMID: 36939779 PMCID: PMC9590553 DOI: 10.1007/s43657-021-00041-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Revised: 12/10/2021] [Accepted: 12/17/2021] [Indexed: 02/07/2023]
Abstract
Increasing evidence has demonstrated that abnormal epigenetic modifications are strongly related to cancer initiation. Thus, sensitive and specific detection of epigenetic modifications could markedly improve biological investigations and cancer precision medicine. A rapid development of molecular imaging approaches for the diagnosis and prognosis of cancer has been observed during the past few years. Various biomarkers unique to epigenetic modifications and targeted imaging probes have been characterized and used to discriminate cancer from healthy tissues, as well as evaluate therapeutic responses. In this study, we summarize the latest studies associated with optical molecular imaging of epigenetic modification targets, such as those involving DNA methylation, histone modification, noncoding RNA regulation, and chromosome remodeling, and further review their clinical application on cancer diagnosis and treatment. Lastly, we further propose the future directions for precision imaging of epigenetic modification in cancer. Supported by promising clinical and preclinical studies associated with optical molecular imaging technology and epigenetic drugs, the central role of epigenetics in cancer should be increasingly recognized and accepted.
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Affiliation(s)
- Yang Du
- grid.9227.e0000000119573309CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 China
- grid.410726.60000 0004 1797 8419The University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Pei Zhang
- grid.9227.e0000000119573309CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 China
- grid.412474.00000 0001 0027 0586Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Supportive Care Center and Day Oncology Unit, Peking University Cancer Hospital and Institute, Beijing, 100142 China
| | - Wei Liu
- grid.412474.00000 0001 0027 0586Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Supportive Care Center and Day Oncology Unit, Peking University Cancer Hospital and Institute, Beijing, 100142 China
| | - Jie Tian
- grid.9227.e0000000119573309CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 China
- grid.64939.310000 0000 9999 1211Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, 100191 China
- grid.440736.20000 0001 0707 115XSchool of Life Science and Technology, Xidian University, Xi’an, 710071 Shaanxi China
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10
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Zhan S, Jiang J, Zeng Z, Wang Y, Cui H. DNA-templated coinage metal nanostructures and their applications in bioanalysis and biomedicine. Coord Chem Rev 2022. [DOI: 10.1016/j.ccr.2021.214381] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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11
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Biosensors for circulating tumor cells (CTCs)-biomarker detection in lung and prostate cancer: Trends and prospects. Biosens Bioelectron 2022; 197:113770. [PMID: 34768065 DOI: 10.1016/j.bios.2021.113770] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 09/30/2021] [Accepted: 11/02/2021] [Indexed: 02/07/2023]
Abstract
Cancer is one of the leading cause of death worldwide. Lung cancer (LCa) and prostate cancer (PCa) are the two most common ones particularly among men with about 20% of aggressive metastatic form leading to shorter overall survival. In recent years, circulating tumor cells (CTCs) have been investigated extensively for their role in metastatic progression and their involvement in reduced overall survival and treatment responses. Analysis of these cells and their associated biomarkers as "liquid biopsy" can provide valuable real-time information regarding the disease state and can be a potential avenue for early-stage detection and possible selection of personalized treatments. This review focuses on the role of CTCs and their associated biomarkers in lung and prostate cancer, as well as the shortcomings of conventional methods for their isolation and analysis. To overcome these drawbacks, biosensors are an elegant alternative because they are capable of providing valuable multiplexed information in real-time and analyzing biomarkers at lower concentrations. A comparative analysis of different transducing elements specific for the analysis of cancer cell and cancer biomarkers have been compiled in this review.
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Farhana FZ, Umer M, Saeed A, Pannu AS, Husaini S, Sonar P, Firoz SH, Shiddiky MJA. e-MagnetoMethyl IP: a magnetic nanoparticle-mediated immunoprecipitation and electrochemical detection method for global DNA methylation. Analyst 2021; 146:3654-3665. [PMID: 33949437 DOI: 10.1039/d1an00345c] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The quantification of global 5-methylcytosine (5mC) content has emerged as a promising approach for the diagnosis and prognosis of cancers. However, conventional methods for the global 5mC analysis require large quantities of DNA and may not be useful for liquid biopsy applications, where the amount of DNA available is limited. Herein, we report magnetic nanoparticles-assisted methylated DNA immunoprecipitation (e-MagnetoMethyl IP) coupled with electrochemical quantification of global DNA methylation. Carboxyl (-COOH) group-functionalized iron oxide nanoparticles (C-IONPs) synthesized by a novel starch-assisted gel formation method were conjugated with anti-5mC antibodies through EDC/NHS coupling (anti-5mC/C-IONPs). Anti-5mC/C-IONPs were subsequently mixed with DNA samples, in which they acted as dispersible capture agents to selectively bind 5mC residues and capture the methylated fraction of genomic DNA. The target-bound Anti-5mC/C-IONPs were magnetically separated and directly adsorbed onto the gold electrode surface using gold-DNA affinity interaction. The amount of DNA adsorbed on the electrode surface, which corresponds to the DNA methylation level in the sample, was electrochemically estimated by differential pulse voltammetric (DPV) study of an electroactive indicator [Ru(NH3)6]3+ bound to the surface-adsorbed DNA. Using a 200 ng DNA sample, the assay could successfully detect differences as low as 5% in global DNA methylation levels with high reproducibility (relative standard deviation (% RSD) = <5% for n = 3). The method could also reproducibly analyze various levels of global DNA methylation in synthetic samples as well as in cell lines. The method avoids bisulfite treatment, does not rely on enzymes for signal generation, and can detect global DNA methylation using clinically relevant quantities of sample DNA without PCR amplification. We believe that this proof-of-concept method could potentially find applications for liquid biopsy-based global DNA methylation analysis in point-of-care settings.
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Affiliation(s)
- Fatema Zerin Farhana
- Department of Chemistry, Bangladesh University of Engineering and Technology (BUET), Dhaka 1000, Bangladesh.
| | - Muhammad Umer
- Queensland Micro- and Nanotechnology Centre (QMNC), Griffith University, Nathan Campus, QLD 4111, Australia.
| | - Ayad Saeed
- Queensland Micro- and Nanotechnology Centre (QMNC), Griffith University, Nathan Campus, QLD 4111, Australia.
| | - Amandeep Singh Pannu
- School of Chemistry and Physics, Queensland University of Technology (QUT), Brisbane 4000, Australia and Centre for Material Science, Queensland University of Technology (QUT), Brisbane 4000, Australia
| | - Sediqa Husaini
- School of Environment and Science (ESC), Griffith University, Nathan Campus, QLD 4111, Australia
| | - Prashant Sonar
- School of Chemistry and Physics, Queensland University of Technology (QUT), Brisbane 4000, Australia and Centre for Material Science, Queensland University of Technology (QUT), Brisbane 4000, Australia
| | - Shakhawat H Firoz
- Department of Chemistry, Bangladesh University of Engineering and Technology (BUET), Dhaka 1000, Bangladesh.
| | - Muhammad J A Shiddiky
- Queensland Micro- and Nanotechnology Centre (QMNC), Griffith University, Nathan Campus, QLD 4111, Australia. and School of Environment and Science (ESC), Griffith University, Nathan Campus, QLD 4111, Australia
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Kim S, Park S, Cho YS, Kim Y, Tae JH, No TI, Shim JS, Jeong Y, Kang SH, Lee KH. Electrical Cartridge Sensor Enables Reliable and Direct Identification of MicroRNAs in Urine of Patients. ACS Sens 2021; 6:833-841. [PMID: 33284011 DOI: 10.1021/acssensors.0c01870] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Urinary miRNAs are biomarkers that demonstrate considerable promise for the noninvasive diagnosis and prognosis of diseases. However, because of background noise resulting from complex physiological features of urine, instability of miRNAs, and their low concentration, accurate monitoring of miRNAs in urine is challenging. To address these limitations, we developed a urine-based disposable and switchable electrical sensor that enables reliable and direct identification of miRNAs in patient urine. The proposed sensing platform combining disposable sensor chips composed of a reduced graphene oxide nanosheet and peptide nucleic acid facilitates the label-free detection of urinary miRNAs with high specificity and sensitivity. Using real-time detection of miRNAs in patient urine without pretreatment or signal amplification, this sensor allows rapid, direct detection of target miRNAs in a broad dynamic range with a detection limit down to 10 fM in human urine specimens within 20 min and enables simultaneous quantification of multiple miRNAs. As confirmed using a blind comparison with the results of pathological examination of patients with prostate cancer, the sensor offers the potential to improve the accuracy of early diagnosis before a biopsy is taken. This study holds the usefulness of the practical sensor for the clinical diagnosis of urological diseases.
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Affiliation(s)
- Seongchan Kim
- Center for Biomaterials, Biomedical Research Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
| | - Sungwook Park
- Center for Biomaterials, Biomedical Research Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
| | - Young Soo Cho
- Center for Biomaterials, Biomedical Research Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
| | - Younghoon Kim
- Center for Biomaterials, Biomedical Research Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
| | - Jong Hyun Tae
- Department of Urology, Korea University, School of Medicine, Seoul 02841, Republic of Korea
| | - Tae Il No
- Department of Urology, Korea University, School of Medicine, Seoul 02841, Republic of Korea
| | - Ji Sung Shim
- Department of Urology, Korea University, School of Medicine, Seoul 02841, Republic of Korea
| | - Youngdo Jeong
- Center for Biomaterials, Biomedical Research Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
- Department of HY-KIST Bio-convergence, Hanyang University, Seoul 04763, Republic of Korea
| | - Seok Ho Kang
- Department of Urology, Korea University, School of Medicine, Seoul 02841, Republic of Korea
| | - Kwan Hyi Lee
- Center for Biomaterials, Biomedical Research Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea
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Mohapatra SS, Frisina RD, Mohapatra S, Sneed KB, Markoutsa E, Wang T, Dutta R, Damnjanovic R, Phan MH, Denmark DJ, Biswal MR, McGill AR, Green R, Howell M, Ghosh P, Gonzalez A, Ahmed NT, Borresen B, Farmer M, Gaeta M, Sharma K, Bouchard C, Gamboni D, Martin J, Tolve B, Singh M, Judy JW, Li C, Santra S, Daunert S, Zeynaloo E, Gelfand RM, Lenhert S, McLamore ES, Xiang D, Morgan V, Friedersdorf LE, Lal R, Webster TJ, Hoogerheide DP, Nguyen TD, D’Souza MJ, Çulha M, Kondiah PPD, Martin DK. Advances in Translational Nanotechnology: Challenges and Opportunities. APPLIED SCIENCES (BASEL, SWITZERLAND) 2020; 10:10.3390/app10144881. [PMID: 38486792 PMCID: PMC10938472 DOI: 10.3390/app10144881] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The burgeoning field of nanotechnology aims to create and deploy nanoscale structures, devices, and systems with novel, size-dependent properties and functions. The nanotechnology revolution has sparked radically new technologies and strategies across all scientific disciplines, with nanotechnology now applied to virtually every area of research and development in the US and globally. NanoFlorida was founded to create a forum for scientific exchange, promote networking among nanoscientists, encourage collaborative research efforts across institutions, forge strong industry-academia partnerships in nanoscience, and showcase the contributions of students and trainees in nanotechnology fields. The 2019 NanoFlorida International Conference expanded this vision to emphasize national and international participation, with a focus on advances made in translating nanotechnology. This review highlights notable research in the areas of engineering especially in optics, photonics and plasmonics and electronics; biomedical devices, nano-biotechnology, nanotherapeutics including both experimental nanotherapies and nanovaccines; nano-diagnostics and -theranostics; nano-enabled drug discovery platforms; tissue engineering, bioprinting, and environmental nanotechnology, as well as challenges and directions for future research.
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Affiliation(s)
- Shyam S. Mohapatra
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
- Departments of Molecular Medicine and Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
- James A. Haley Veterans Hospital, Tampa, FL 33612, USA
| | - Robert D. Frisina
- Department of Chemical and Biomedical Engineering and Global Center for Hearing and Speech Research, University of South Florida, Tampa, FL 33620, USA
| | - Subhra Mohapatra
- Departments of Molecular Medicine and Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
- James A. Haley Veterans Hospital, Tampa, FL 33612, USA
| | - Kevin B. Sneed
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Eleni Markoutsa
- Departments of Molecular Medicine and Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
- James A. Haley Veterans Hospital, Tampa, FL 33612, USA
| | - Tao Wang
- Departments of Molecular Medicine and Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
- James A. Haley Veterans Hospital, Tampa, FL 33612, USA
| | - Rinku Dutta
- Departments of Molecular Medicine and Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
- James A. Haley Veterans Hospital, Tampa, FL 33612, USA
| | - Ratka Damnjanovic
- Department of Chemical and Biomedical Engineering and Global Center for Hearing and Speech Research, University of South Florida, Tampa, FL 33620, USA
| | - Manh-Huong Phan
- Department of Physics, University of South Florida, Tampa, FL 33620, USA
| | - Daniel J. Denmark
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Manas R. Biswal
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Andrew R. McGill
- Departments of Molecular Medicine and Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
- James A. Haley Veterans Hospital, Tampa, FL 33612, USA
| | - Ryan Green
- Departments of Molecular Medicine and Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
- James A. Haley Veterans Hospital, Tampa, FL 33612, USA
| | - Mark Howell
- Departments of Molecular Medicine and Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
- James A. Haley Veterans Hospital, Tampa, FL 33612, USA
| | - Payal Ghosh
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Alejandro Gonzalez
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Nadia Tasnim Ahmed
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Brittney Borresen
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Mitchell Farmer
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Melissa Gaeta
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Krishna Sharma
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Christen Bouchard
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Danielle Gamboni
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Jamie Martin
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Bianca Tolve
- Taneja College of Pharmacy Graduate Programs, University of South Florida, Tampa, FL 33612, USA
| | - Mandip Singh
- College of Pharmacy and Pharmaceutical Sciences, Florida A&M University, Tallahassee, FL 32307, USA
| | - Jack W. Judy
- University of Florida Department of Electrical and Computer Engineering and Nanoscience Institute for Medical and Engineering Technology, Gainesville, FL 32611, USA
| | - Chenzhong Li
- Department of Biomedical Engineering, Florida International University, Miami, FL 33174, USA
| | - Swadeshmukul Santra
- NanoScience Technology Center, University of Central Florida, Burnett School of Biomedical Sciences, Department of Chemistry and Department of Materials Science and Engineering, Orlando, FL 32826, USA
| | - Sylvia Daunert
- Department of Biochemistry and Molecular Biology, University of Miami, Miller School of Medicine, and Department of Chemistry, Miami, FL 33124, USA
| | - Elnaz Zeynaloo
- Department of Biochemistry and Molecular Biology, University of Miami, Miller School of Medicine, and Department of Chemistry, Miami, FL 33124, USA
| | - Ryan M. Gelfand
- School of Science and Engineering, Tulane University, New Orleans, LA 70118, USA
| | - Steven Lenhert
- Department of Biological Science, Florida State University, Tallahassee, FL 32306, USA
| | - Eric S. McLamore
- Agricultural and Biological Engineering, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL 32603, USA
| | - Dong Xiang
- Agricultural and Biological Engineering, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL 32603, USA
| | - Victoria Morgan
- Agricultural and Biological Engineering, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL 32603, USA
| | | | - Ratnesh Lal
- Center for Excellence in Nanomedicine and Engineering, University of California San Diego, IEM, La Jolla, CA 92093, USA
| | - Thomas J. Webster
- Department of Chemical Engineering, Northeastern University, Boston, MA 02115, USA
| | - David P. Hoogerheide
- National Institute of Standards and Technology, Center for Neutron Research, Gaithersburg, MD 20899, USA
| | - Thanh Duc Nguyen
- Department of Mechanical Engineering, University of Connecticut, Storrs, CT 06269, USA
| | - Martin J. D’Souza
- Department of Pharmaceutical Sciences, Nanotechnology Laboratory, Mercer University, Atlanta, GA 30341, USA
| | - Mustafa Çulha
- Knight Cancer Institute, Cancer Early Detection Advanced Research (CEDAR), Oregon Health and Science University, Portland, OR 97239, USA
| | - Pierre P. D. Kondiah
- Wits Advanced Drug Delivery Platform Research Unit, Department of Pharmacy and Pharmacology, School of Therapeutic Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, 7 York Road, Parktown 2193, South Africa
| | - Donald K. Martin
- Faculté de Pharmacie and TIMC-IMAG (UMR 5525), University Grenoble Alpes, SyNaBi, 38000 Grenoble, France
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