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Li A, Mo X, Lu Y, Zhu G, Liu C, Yang X, Huang Y, Sheng J, Zhang H, Meng D, Zhao X. Digital SERS immunoassay of Interleukin-6 based on Au@Ag-Au nanotags. Biosens Bioelectron 2025; 270:116973. [PMID: 39581067 DOI: 10.1016/j.bios.2024.116973] [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: 09/07/2024] [Revised: 10/29/2024] [Accepted: 11/19/2024] [Indexed: 11/26/2024]
Abstract
Interleukin-6 (IL-6) is a crucial cytokine involved in inflammation and immune regulation. However, the detection of IL-6 with ultrasensitivity and high specificity remains a significant challenge due to the inherent complexity of biofluids. Herein, we present a digital surface enhanced Raman scattering (SERS) immunoassay using core-shell Au@Ag-Au nanotags for IL-6 detection with ultrasensitivity and high reliability. A low-cost silicon chip was functionalized as capture substrates, employing novel SERS nanotags that exhibit strong, robust and reproducible signals at single-nanoparticle resolution as the amplification element. We proposed two analytical methods to validate single-molecule events follow a Poisson distribution and to quantify protein biomarkers over a broad linear dynamic range, respectively. The strong alignment between theoretical and experimental results enhances the method's reliability. Our assay provides two readouts: colorimetric analysis by naked eyes for high concentrations (>1 ng/mL) and digital SERS analysis for low concentrations. Following method optimization, we obtained a linear range from 100 fg/mL to 1 ng/mL (R2 = 0.994) with a limit of detection (LOD) of 12.4 fg/mL, suitable for clinical applications. The method was tested for IL-6 quantification in healthy human serum and saliva, with recoveries from 92.4% to 105.3%. Finally, the immunoassay demonstrated strong consistency with the standard clinical laboratory method when tested with clinical serum samples. Thus, our proposed the digital SERS immunoassay is a promising tool for the precision clinical diagnosis of IL-6-related diseases or other conditions.
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Affiliation(s)
- Ao Li
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 211189, China; Southeast University Shenzhen Research Institute, Shenzhen, 518000, China; Institute of Biomaterials and Medical Devices, Southeast University, Suzhou, 215163, China
| | - Xiufang Mo
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 211189, China; Southeast University Shenzhen Research Institute, Shenzhen, 518000, China; Institute of Biomaterials and Medical Devices, Southeast University, Suzhou, 215163, China
| | - Yu Lu
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 211189, China; Southeast University Shenzhen Research Institute, Shenzhen, 518000, China; Institute of Biomaterials and Medical Devices, Southeast University, Suzhou, 215163, China
| | - Geng Zhu
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 211189, China; Southeast University Shenzhen Research Institute, Shenzhen, 518000, China; Institute of Biomaterials and Medical Devices, Southeast University, Suzhou, 215163, China
| | - Chang Liu
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 211189, China; Southeast University Shenzhen Research Institute, Shenzhen, 518000, China; Institute of Biomaterials and Medical Devices, Southeast University, Suzhou, 215163, China
| | - Xi Yang
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 211189, China; Southeast University Shenzhen Research Institute, Shenzhen, 518000, China; Institute of Biomaterials and Medical Devices, Southeast University, Suzhou, 215163, China
| | - Yan Huang
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 211189, China; Southeast University Shenzhen Research Institute, Shenzhen, 518000, China; Institute of Biomaterials and Medical Devices, Southeast University, Suzhou, 215163, China
| | - Jinliang Sheng
- State International Joint Research Center for Animal Health Breeding, College of Animal Science and Technology, Shihezi University, Shihezi, 832003, China
| | - Hui Zhang
- State International Joint Research Center for Animal Health Breeding, College of Animal Science and Technology, Shihezi University, Shihezi, 832003, China
| | - Dianhuai Meng
- Rehabilitation Medical Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
| | - Xiangwei Zhao
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 211189, China; Southeast University Shenzhen Research Institute, Shenzhen, 518000, China; Institute of Biomaterials and Medical Devices, Southeast University, Suzhou, 215163, China.
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Sun Q, Feng S, Xu H, Yu R, Dai B, Guo J, Fang M, Cui D, Wang K. A smartphone-integrated deep learning strategy-assisted rapid detection system for monitoring dual-modal immunochromatographic assay. Talanta 2025; 282:127043. [PMID: 39406103 DOI: 10.1016/j.talanta.2024.127043] [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: 08/26/2024] [Revised: 09/20/2024] [Accepted: 10/11/2024] [Indexed: 11/20/2024]
Abstract
This study focuses on the integration of a custom-built and optimally trained YOLO v5 model into a smartphone app developed with Java language. A dual-modal immunochromatographic rapid detection system based on a deep learning strategy for smartphones was developed for grade determination and predicting the concentration of aflatoxin B1 (AFB1). Innovative distance-type quantum dot microsphere fluorescent immunochromatographic chips enable semi-quantitative analysis by naked eye, and conventional colloidal gold nanoparticle colorimetric strips were also prepared. The compact and versatile hardware device making it easily integrable into smartphones of varying dimensions. Moreover, the wireless charging functionality of smartphones was to tackle power supply challenges. After optimized training, the accuracy, mAP@0.5, precision, and recall metrics of the YOLO v5 model all soared to 98 %. For the dual-modal immunochromatographic chips, the R2 values for the standard curve fits were as high as 0.993, with a broad linear range of 0.05-40 ng/mL and a standard deviation lower than 0.03 at each concentration. Finally, this system determined the grade of the AFB1 concentration with an accuracy of up to 98 % and it exhibited an ultra-sensitive quantitative detection capability with a limit of detection as low as 2.2 pg/mL, showcasing the reliability of the deep learning strategy for practical applications in smartphones. This robust technological foundation paves the way for potentially community-based, family-oriented, and personalized applications.
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Affiliation(s)
- Qingwen Sun
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Shaoqing Feng
- Department of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 200011, China
| | - Hao Xu
- School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Ruoyao Yu
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Bin Dai
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jinhong Guo
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Mengru Fang
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Daxiang Cui
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Kan Wang
- School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
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Balapure A, Dubey SK, Javed A, Chattopadhyay S, Goel S. A review: early detection of oral cancer biomarkers using microfluidic colorimetric point-of-care devices. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2024; 16:6098-6118. [PMID: 39206589 DOI: 10.1039/d4ay01030b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Oral squamous cell carcinoma (OSCC) is the most common type of head and neck cancers. OSCC constitutes 90% of the head and neck malignancies. The delayed identification of oral cancer is the primary cause of ineffective medical treatment. To address this issue, low-cost, reliable point-of-care devices that can be utilized for large-scale screening, even in low-resource settings, including rural areas and primary healthcare centers, are of great interest. Herein, a comprehensive analysis of numerous salivary biomarkers that exhibit significant variations in concentration between individuals with oral cancer and those without is given. Furthermore, the article explores several point-of-care devices that exhibit potential in the realm of oral cancer detection. The biomarkers are discussed with a focus on their structural characteristics and role in oral cancer progression. The devices based on colorimetry and microfluidics are discussed in detail, considering their compliance with the 'REASSURED' criteria given by the World Health Organization (WHO) and suitability for mass screening in low-resource settings. Finally, the discourse revolves around the fundamental aspects pertaining to the advancement of multiplex, cost-effective point-of-care devices designed for widespread screening purposes.
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Affiliation(s)
- Aniket Balapure
- MEMS, Microfluidics and Nanoelectronics (MMNE) Lab, Birla Institute of Technology and Science (BITS) Pilani, Hyderabad Campus, Jawahar Nagar, Kapra Mandal, Medchal District, 500 078, Telangana, India.
- Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science (BITS) Pilani, Hyderabad Campus, Jawahar Nagar, Kapra Mandal, Medchal District, 500 078, Telangana, India
| | - Satish Kumar Dubey
- MEMS, Microfluidics and Nanoelectronics (MMNE) Lab, Birla Institute of Technology and Science (BITS) Pilani, Hyderabad Campus, Jawahar Nagar, Kapra Mandal, Medchal District, 500 078, Telangana, India.
- Department of Mechanical Engineering, Birla Institute of Technology and Science (BITS) Pilani, Hyderabad Campus, Jawahar Nagar, Kapra Mandal, Medchal District, 500 078, Telangana, India
| | - Arshad Javed
- MEMS, Microfluidics and Nanoelectronics (MMNE) Lab, Birla Institute of Technology and Science (BITS) Pilani, Hyderabad Campus, Jawahar Nagar, Kapra Mandal, Medchal District, 500 078, Telangana, India.
- Department of Mechanical Engineering, Birla Institute of Technology and Science (BITS) Pilani, Hyderabad Campus, Jawahar Nagar, Kapra Mandal, Medchal District, 500 078, Telangana, India
| | - Samit Chattopadhyay
- Department of Biological Sciences, Birla Institute of Technology and Science (BITS) Pilani, K K Birla Goa Campus, NH-17B, Zuarinagar, Goa 403726, India
| | - Sanket Goel
- MEMS, Microfluidics and Nanoelectronics (MMNE) Lab, Birla Institute of Technology and Science (BITS) Pilani, Hyderabad Campus, Jawahar Nagar, Kapra Mandal, Medchal District, 500 078, Telangana, India.
- Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science (BITS) Pilani, Hyderabad Campus, Jawahar Nagar, Kapra Mandal, Medchal District, 500 078, Telangana, India
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Chheang L, Khachornsakkul K, Del-Rio-Ruiz R, Zeng W, Thongkon N, Thanasupsin SP, Sonkusale S. Simple distance-based thread analytical device integrated with ion imprinted polymer for Zn 2+ quantification in human urine samples. Analyst 2024; 149:3161-3168. [PMID: 38632945 DOI: 10.1039/d4an00076e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
This article presents the development of a distance-based thread analytical device (dTAD) integrated with an ion-imprinted polymer (IIP) for quantitative monitoring of zinc ions (Zn2+) in human urine samples. The IIP was easily chemically modified onto the thread channel using dithizone (DTZ) as a ligand to bind to Zn2+ with methacrylic acid (MAA) as a functional monomer and ethylene glycol dimethacrylate (EGDMA) as well as 2,2-azobisisobutyronitrile (AIBN) as cross-linking agents to enhance the selectivity for Zn2+ detection. The imprinted polymer was characterized using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy and Scanning Electron Microscopy-Energy Dispersive X-ray Spectroscopy (SEM-EDS). Under optimization, the linear detection range was from 1.0 to 20.0 mg L-1 (R2 = 0.9992) with a limit of detection (LOD) of 1.0 mg L-1. Other potentially interfering metal ions and molecules did not interfere with this approach, leading to high selectivity. Furthermore, our technique exhibits a remarkable recovery ranging from 100.48% to 103.16%, with the highest relative standard deviation (% RSD) of 5.44% for monitoring Zn2+ in human control urine samples, indicating high accuracy and precision. Similarly, there is no significant statistical difference between the results obtained using our method and standards on zinc supplement sample labels. The proposed method offers several advantages in detecting trace Zn2+ for point-of-care (POC) medical diagnostics and environmental sample analysis, such as ease of use, instrument-free readout, and cost efficiency. Overall, our developed dTAD-based IIP method holds potential for simple, affordable, and rapid detection of Zn2+ levels and can be applied to other metal ions' analysis.
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Affiliation(s)
- Lita Chheang
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.
- Nano Lab, Tufts University, Medford, MA 02155, USA
- Department of Chemistry, Faculty of Science, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand
- Department of Chemistry, Faculty of Science, Royal University of Phnom Penh, Federation of Russia Blvd, Tuol Kork, Phnom Penh, Cambodia
| | - Kawin Khachornsakkul
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.
- Nano Lab, Tufts University, Medford, MA 02155, USA
| | - Ruben Del-Rio-Ruiz
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.
- Nano Lab, Tufts University, Medford, MA 02155, USA
| | - Wenxin Zeng
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.
- Nano Lab, Tufts University, Medford, MA 02155, USA
| | - Nisakorn Thongkon
- Department of Chemistry, Faculty of Science, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand
| | - Sudtida Pliankarom Thanasupsin
- Chemistry for Green Society and Healthy Living Research Unit, Faculty of Science, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand
| | - Sameer Sonkusale
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.
- Nano Lab, Tufts University, Medford, MA 02155, USA
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Khachornsakkul K, Leelasattarathkul T. Photothermal biosensing integrated with microfluidic paper-based analytical device for sensitive quantification of sarcosine. Talanta 2024; 271:125628. [PMID: 38219320 DOI: 10.1016/j.talanta.2024.125628] [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: 08/11/2023] [Revised: 11/13/2023] [Accepted: 01/04/2024] [Indexed: 01/16/2024]
Abstract
This article presents the development of a photothermal biosensing integrated with microfluidic paper-based analytical device (PT-μPAD) as a quantitative biosensor method for monitoring sarcosine in human control urine, plasma, and serum samples. The device utilizes gold nanoparticles (AuNPs) as both a peroxidase-like nanozyme and a photothermal substrate to enable sarcosine detection. In our PT-μPAD, hydrogen peroxide (H2O2) is generated through the oxidation of sarcosine by a sarcosine oxidase (SOx) enzyme. Subsequently, the H2O2 flows through the paper microchannels to the detection zone, where it etches the pre-deposited AuNPs, inducing a temperature change upon exposure by a 532 nm laser. The temperature variation is then measured using a portable and inexpensive infrared thermometer. Under optimized conditions, we obtained a linear range between 10.0 and 40.0 nmol L-1 (R2 = 0.9954) and a detection limit (LOD) of 32.0 pmol L-1. These values fall within the clinical range for sarcosine monitoring in prostate cancer diagnostics in humans. Moreover, our approach exhibits high selectivity without interfering effects. Recovery studies in various human control samples demonstrated a range of 99.05-102.11 % with the highest RSD of 2.25 %. The PT-μPAD was further validated for sarcosine determination in human control urine and compared with a commercial ELISA assay, revealing no significant difference between these two methods at a 95 % confidence level. Overall, our proposed sarcosine biosensor is well-suited for prostate cancer monitoring, given its affordability, sensitivity, and user-friendliness, even for unskilled individuals. Moreover, this strategy has promising prospects for broader applications, potentially detecting various biomarkers as a point-of-care (POC) diagnostic tool.
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Affiliation(s)
- Kawin Khachornsakkul
- Division of Chemistry, Department of Science, Faculty of Science and Technology, Rajamangala University of Technology Krungthep, Bangkok, 10120, Thailand; Department of Electrical and Computer Engineering, Tufts University, Medford, MA, 02155, USA
| | - Tapparath Leelasattarathkul
- Division of Chemistry, Department of Science, Faculty of Science and Technology, Rajamangala University of Technology Krungthep, Bangkok, 10120, Thailand.
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Khachornsakkul K, Del-Rio-Ruiz R, Chheang L, Zeng W, Sonkusale S. Distance-based paper analytical device for multiplexed quantification of cytokine biomarkers using carbon dots integrated with molecularly imprinted polymer. LAB ON A CHIP 2024; 24:2262-2271. [PMID: 38501606 DOI: 10.1039/d4lc00055b] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/20/2024]
Abstract
This article introduces distance-based paper analytical devices (dPADs) integrated with molecularly imprinted polymers (MIPs) and carbon dots (CDs) for simultaneous quantification of cytokine biomarkers, namely C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-α), and interleukin-6 (IL-6) in human biological samples for diagnosis of cytokine syndrome. Using fluorescent CDs and MIP technology, the dPAD exhibits high selectivity and sensitivity. Detection is based on fluorescence quenching of CDs achieved through the interaction of the target analytes with the MIP layer on the paper substrate. Quantitative analysis is easily accomplished by measuring the distance length of quenched fluorescence with a traditional ruler and naked eye readout enabling rapid diagnosis of cytokine syndrome and the underlying infection. Our sensor demonstrated linear ranges of 2.50-24.0 pg mL-1 (R2 = 0.9974), 0.25-3.20 pg mL-1 (R2 = 0.9985), and 1.50-16.0 pg mL-1 (R2 = 0.9966) with detection limits (LODs) of 2.50, 0.25, and 1.50 pg mL-1 for CRP, TNF-α, and IL-6, respectively. This sensor also demonstrated remarkable selectivity compared to a sensor employing a non-imprinted polymer (NIP), and precision with the highest relative standard deviation (RSD) of 5.14%. The sensor is more accessible compared to prior methods relying on expensive reagents and instruments and complex fabrication methods. Furthermore, the assay provided notable accuracy for monitoring these biomarkers in various human samples with recovery percentages ranging between 99.22% and 103.58%. By integrating microfluidic systems, nanosensing, and MIPs technology, our developed dPADs hold significant potential as a cost-effective and user-friendly analytical method for point-of-care diagnostics (POC) of cytokine-related disorders. This concept can be further extended to developing diagnostic devices for other biomarkers.
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Affiliation(s)
- Kawin Khachornsakkul
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.
- Nano Lab, Tufts University, Medford, MA 02155, USA
| | - Ruben Del-Rio-Ruiz
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.
- Nano Lab, Tufts University, Medford, MA 02155, USA
| | - Lita Chheang
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.
- Nano Lab, Tufts University, Medford, MA 02155, USA
- Department of Chemistry, Faculty of Science, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand
| | - Wenxin Zeng
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.
- Nano Lab, Tufts University, Medford, MA 02155, USA
| | - Sameer Sonkusale
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.
- Nano Lab, Tufts University, Medford, MA 02155, USA
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Khachornsakkul K, Zeng W, Sonkusale S. Distance-based paper analytical devices integrated with molecular imprinted polymers for Escherichia coli quantification. Mikrochim Acta 2024; 191:253. [PMID: 38592400 DOI: 10.1007/s00604-024-06332-1] [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: 02/14/2024] [Accepted: 03/24/2024] [Indexed: 04/10/2024]
Abstract
The development of distance-based paper analytical devices (dPADs) integrated with molecularly imprinted polymers (MIPs) to monitor Escherichia coli (E. coli) levels in food samples is presented. The fluidic workflow on the device is controlled using a designed hydrophilic bridge valve. Dopamine serves as a monomer for the formation of the E. coli-selective MIP layer on the dPADs. The detection principle relies on the inhibition of the E. coli toward copper (II) (Cu2+)-triggered oxidation of o-phenylenediamine (OPD) on the paper substrate. Quantitative detection is simply determined through visual observation of the residual yellow color of the OPD in the detection zone, which is proportional to E. coli concentration. The sensing exhibits a linear range from 25.0 to 1200.0 CFU mL-1 (R2 = 0.9992) and a detection limit (LOD) of 25.0 CFU mL-1 for E. coli detection. Additionally, the technique is highly selective with no interference even from the molecules that have shown to react with OPD to form oxidized OPD. The developed device demonstrates accuracy and precision for E. coli quantification in food samples with recovery percentages between 98.3 and 104.7% and the highest relative standard deviation (RSD) of 4.55%. T-test validation shows no significant difference in E. coli concentration measured between our method and a commercial assay. The proposed dPAD sensor has the potential for selective and affordable E. coli determination in food samples without requiring sample preparation. Furthermore, this strategy can be extended to monitor other molecules for which MIP can be developed and integrated into paper-microfluidic platform.
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Affiliation(s)
- Kawin Khachornsakkul
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA, 02155, USA.
- Nano Lab, Tufts University, Medford, MA, 02155, USA.
| | - Wenxin Zeng
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA, 02155, USA
- Nano Lab, Tufts University, Medford, MA, 02155, USA
| | - Sameer Sonkusale
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA, 02155, USA.
- Nano Lab, Tufts University, Medford, MA, 02155, USA.
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Yang D, Hu C, Zhang H, Geng S. Recent Developments in Paper-Based Sensors with Instrument-Free Signal Readout Technologies (2020-2023). BIOSENSORS 2024; 14:36. [PMID: 38248413 PMCID: PMC10812998 DOI: 10.3390/bios14010036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 12/31/2023] [Accepted: 01/09/2024] [Indexed: 01/23/2024]
Abstract
Signal readout technologies that do not require any instrument are essential for improving the convenience and availability of paper-based sensors. Thanks to the remarkable progress in material science and nanotechnology, paper-based sensors with instrument-free signal readout have been developed for multiple purposes, such as biomedical detection, environmental pollutant tracking, and food analysis. In this review, the developments in instrument-free signal readout technologies for paper-based sensors from 2020 to 2023 are summarized. The instrument-free signal readout technologies, such as distance-based signal readout technology, counting-based signal readout technology, text-based signal readout technology, as well as other transduction technologies, are briefly introduced, respectively. On the other hand, the applications of paper-based sensors with instrument-free signal readout technologies are summarized, including biomedical analysis, environmental analysis, food analysis, and other applications. Finally, the potential and difficulties associated with the advancement of paper-based sensors without instruments are discussed.
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Affiliation(s)
- Danni Yang
- Chongqing Engineering Research Center of Pharmaceutical Sciences, Chongqing Medical and Pharmaceutical College, Chongqing 401331, China;
| | - Chengju Hu
- Health Management Center, The Affiliated Dazu Hospital of Chongqing Medical University, Chongqing 402360, China;
| | - Hao Zhang
- Chongqing Engineering Research Center of Pharmaceutical Sciences, Chongqing Medical and Pharmaceutical College, Chongqing 401331, China;
| | - Shan Geng
- Department of Endocrinology, The Affiliated Dazu Hospital of Chongqing Medical University, Chongqing 402360, China
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Khachornsakkul K, Del-Rio-Ruiz R, Zeng W, Sonkusale S. Highly Sensitive Photothermal Microfluidic Thread-Based Duplex Immunosensor for Point-of-Care Monitoring. Anal Chem 2023; 95:12802-12810. [PMID: 37578458 DOI: 10.1021/acs.analchem.3c01778] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Herein, we successfully developed a thread-based analytical device (μTAD) for simultaneous immunosensing of two biomolecules with attomolar sensitivity by using a photothermal effect. A photothermal effect exploits a strong light-to-heat energy conversion of plasmonic metallic nanoparticles at localized surface plasmon resonance. The key innovation is to utilize the cotton thread to realize this sensor and the use of chitosan modification for enhancing the microfluidic properties, for improving the efficiency of photothermal conversion, and for sensor stability. The developed μTAD sensor consists of (i) a sample zone, (ii) a conjugation zone coated with gold nanoparticles bound with an antibody (AuNPs-Ab2), and (iii) a test zone immobilized with a capture antibody (anti-Ab1). The prepared μTAD is assembled in a custom three-dimensional (3D) printed device which holds the laser for illumination and the thermometer for readout. The 3D-printed supportive device enhances signal response by focusing light and localizing the heat generated. For proof of concept, simultaneous sensing of two key stress and inflammation biomarkers, namely, cortisol and interleukin-6 (IL-6), are monitored using this technique. Under optimization, this device exhibited a detection linear range of 2.0-14.0 ag/mL (R2 = 0.9988) and 30.0-360.0 fg/mL (R2 = 0.9942) with a detection limit (LOD) of 1.40 ag/mL (∼3.86 amol/L) and 20.0 fg/mL (∼950.0 amol/L) for cortisol and IL-6, respectively. Furthermore, the analysis of both biomolecules in human samples indicated recoveries in the range of 98.8%-102.88% with the highest relative standard deviation being 3.49%, offering great accuracy and precision. These results are the highest reported sensitivity for these analytes using an immunoassay method. Our PT-μTAD strategy is therefore a promising approach for detecting biomolecules in resource-limited point-of-care settings.
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Affiliation(s)
- Kawin Khachornsakkul
- Department of Electrical and Computer Engineering, Tufts University, Medford, Massachusetts 02155, United States
- Nano Lab, Tufts University, Medford, Massachusetts 02155, United States
| | - Ruben Del-Rio-Ruiz
- Department of Electrical and Computer Engineering, Tufts University, Medford, Massachusetts 02155, United States
- Nano Lab, Tufts University, Medford, Massachusetts 02155, United States
| | - Wenxin Zeng
- Department of Electrical and Computer Engineering, Tufts University, Medford, Massachusetts 02155, United States
- Nano Lab, Tufts University, Medford, Massachusetts 02155, United States
| | - Sameer Sonkusale
- Department of Electrical and Computer Engineering, Tufts University, Medford, Massachusetts 02155, United States
- Nano Lab, Tufts University, Medford, Massachusetts 02155, United States
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10
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Zhu L, Fu W, Zhu B, Feng Q, Ying X, Li S, Chen J, Xie X, Pan C, Liu J, Chen C, Chen X, Zhu D. An integrated microfluidic electrochemiluminescence device for point-of-care testing of acute myocardial infarction. Talanta 2023; 262:124626. [PMID: 37244239 DOI: 10.1016/j.talanta.2023.124626] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 04/26/2023] [Accepted: 05/01/2023] [Indexed: 05/29/2023]
Abstract
Heart-type fatty acid binding protein (H-FABP) is an early biomarker for acute myocardial infarction. The concentration of H-FABP in circulation sharply increases during myocardial injury. Therefore, fast and accurate detection of H-FABP is of vital significance. In this study, we developed an electrochemiluminescence device integrated with microfluidic chip (designed as m-ECL device) for on-site detection of H-FABP. The m-ECL device is consisted of a microfluidic chip that enable easy liquid handling as well as an integrated electronic system for voltage supply and photon detection. A sandwich-type ECL immunoassay strategy was employed for H-FABP detection by using Ru (bpy)32+ loaded mesoporous silica nanoparticles as ECL probes. This device can directly detect H-FABP in human serum without any pre-treatment, with a wide linear range of 1-100 ng/mL and a low limit of detection of 0.72 ng/mL. The clinical usability of this device was evaluated using clinical serum samples from patients. The results obtained from m-ECL device are well matched with those obtained from ELISA assays. We believe this m-ECL device has extensive application prospects for point-of-care testing of acute myocardial infarction.
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Affiliation(s)
- Lihang Zhu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine; Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, 310003, Zhejiang, China; Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education of China, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, 310027, Zhejiang, China
| | - Wenxuan Fu
- Institute of Analytical Chemistry, Department of Chemistry, Key Laboratory of Excited-State Materials of Zhejiang Province, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Boyu Zhu
- Institute of Analytical Chemistry, Department of Chemistry, Key Laboratory of Excited-State Materials of Zhejiang Province, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Qian Feng
- Department of Gastroenterology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, Zhejiang, China
| | - Xudong Ying
- Institute of Analytical Chemistry, Department of Chemistry, Key Laboratory of Excited-State Materials of Zhejiang Province, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Shuang Li
- Academy of Medical Engineering and Translational Medicine, Tianjin University, 300072, Tianjin, China
| | - Jing Chen
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, China
| | - Xiaoya Xie
- Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education of China, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, 310027, Zhejiang, China
| | - Chenying Pan
- Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education of China, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, 310027, Zhejiang, China
| | - Jun Liu
- Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education of China, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, 310027, Zhejiang, China
| | - Chao Chen
- GuoZhen Health Technology Co., Ltd, 100142, Beijing, China
| | - Xing Chen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine; Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, 310003, Zhejiang, China; Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education of China, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, 310027, Zhejiang, China.
| | - Danhua Zhu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine; Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, 310003, Zhejiang, China.
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Khachornsakkul K, Rybicki FJ, Sonkusale S. Nanomaterials integrated with microfluidic paper-based analytical devices for enzyme-free glucose quantification. Talanta 2023; 260:124538. [PMID: 37087948 DOI: 10.1016/j.talanta.2023.124538] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 04/05/2023] [Accepted: 04/07/2023] [Indexed: 04/25/2023]
Abstract
In this study, nanomaterials capable of enzyme-free glucose quantification and colorimetric readout are integrated into a microfluidic paper-based analytical devices (μPADs). Gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were utilized as a peroxidase-like nanozyme and a colorimetric probe to achieve glucose monitoring. In this developed device, glucose is oxidized by AuNPs to generate hydrogen peroxide (H2O2), which flows in the paper microchannels toward detection zones. H2O2 then etches the immobilized AgNPs to induce a color change. The intensity of color change is easily monitored using a smartphone application. Following method optimization, we obtained a linear range from 0.50 to 10.0 mmol L-1 (R2 = 0.9921) and a detection limit (LOD) of 340.0 μmol L-1. This falls in the clinically relevant range for glucose monitoring and diabetes diagnosis in humans. In addition, the total analysis time is just 20 min, which is significantly less than the same experiment performed in the solution phase. Also, our method is markedly selective; other substrates do not interfere. The recovery test in human control samples was in the range of 98.47-102.34% and the highest relative standard deviation (RSD) was 3.58%. The enzyme-free approach for glucose sensing is highly desirable for diabetes diagnosis as it replaces the more expensive enzyme with cheaper nanomaterials. Furthermore, since nanomaterials are more environmentally stable compared to enzymes, it has the potential for widespread deployment as point-of-care diagnostics (POC) in resource-limited settings.
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Affiliation(s)
- Kawin Khachornsakkul
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA, 02155, USA; Nano Lab, Tufts University, Medford, MA, 02155, USA.
| | - Frank John Rybicki
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA, 02155, USA; Nano Lab, Tufts University, Medford, MA, 02155, USA
| | - Sameer Sonkusale
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA, 02155, USA; Nano Lab, Tufts University, Medford, MA, 02155, USA.
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