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Li X, Liu M, Men D, Duan Y, Deng L, Zhou S, Hou J, Hou C, Huo D. Rapid, portable, and sensitive detection of CaMV35S by RPA-CRISPR/Cas12a-G4 colorimetric assays with high accuracy deep learning object recognition and classification. Talanta 2024; 278:126441. [PMID: 38924982 DOI: 10.1016/j.talanta.2024.126441] [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: 04/02/2024] [Revised: 06/05/2024] [Accepted: 06/15/2024] [Indexed: 06/28/2024]
Abstract
Fast, sensitive, and portable detection of genetic modification contributes to agricultural security and food safety. Here, we developed RPA-CRISPR/Cas12a-G-quadruplex colorimetric assays that can combine with intelligent recognition by deep learning algorithms to achieve sensitive, rapid, and portable detection of the CaMV35S promoter. When the crRNA-Cas12a complex recognizes the RPA amplification product, Cas12 cleaves the G-quadruplex, causing the G4-Hemin complex to lose its peroxide mimetic enzyme function and be unable to catalyze the conversion of ABTS2- to ABTS, allowing CaMV35S concentration to be determined based on ABTS absorbance. By utilizing the RPA-CRISPR/Cas12a-G4 assay, we achieved a CaMV35S limit of detection down to 10 aM and a 0.01 % genetic modification sample in 45 min. Deep learning algorithms are designed for highly accurate classification of color results. Yolov5 objective finding and Resnet classification algorithms have been trained to identify trace (0.01 %) CaMV35S more accurately than naked eye colorimetry. We also coupled deep learning algorithms with a smartphone app to achieve portable and rapid photo identification. Overall, our findings enable low cost ($0.43), high accuracy, and intelligent detection of the CaMV35S promoter.
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Affiliation(s)
- Xuheng Li
- Key Laboratory for Biological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing 400044, PR China
| | - Meilin Liu
- Key Laboratory for Biological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing 400044, PR China
| | - Dianhui Men
- Key Laboratory for Biological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing 400044, PR China
| | - Yi Duan
- Key Laboratory for Biological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing 400044, PR China
| | - Liyuan Deng
- Key Laboratory for Biological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing 400044, PR China
| | - Shiying Zhou
- Key Laboratory for Biological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing 400044, PR China
| | - Jingzhou Hou
- Key Laboratory for Biological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing 400044, PR China; Chongqing Engineering and Technology Research Center of Intelligent Rehabilitation and Eldercare, Chongqing City Management College, Chongqing, 401331, PR China.
| | - Changjun Hou
- Key Laboratory for Biological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing 400044, PR China; Chongqing Key Laboratory of Bio-perception & Intelligent Information Processing, School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, 400044, PR China.
| | - Danqun Huo
- Key Laboratory for Biological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing 400044, PR China; Chongqing Key Laboratory of Bio-perception & Intelligent Information Processing, School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, 400044, PR China.
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Chen CH, Huang RL, Liu CC, Hong C, Chen Y, Shen CF, Cheng CM. Paper-Based procalcitonin and Interleukin-6 test strip with Spectrum-Based optical reader for enterovirus severity differentiation in children. Clin Chim Acta 2024; 565:119942. [PMID: 39214397 DOI: 10.1016/j.cca.2024.119942] [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: 04/12/2024] [Revised: 08/10/2024] [Accepted: 08/23/2024] [Indexed: 09/04/2024]
Abstract
Infectious diseases significantly impact global health, necessitating prompt diagnosis to mitigate life-threatening sepsis risk. Identifying patients at risk of severe neurological complications from enterovirus infections is challenging due to nonspecific initial presentations. Point-of-care testing (POCT) has emerged as a transformative tool, with low-cost lateral-flow colorimetric assays showing promise in deployable POCT devices. We developed a PCT/IL-6 rapid diagnostic system integrating lateral flow assay (LFA) test strips and a portable optical spectrum reader, allowing simultaneous semi-quantitative measurement of serum PCT and IL-6 within 30 min at the point of care. The system demonstrated a strong correlation with traditional ELISA and effectively differentiated severe pediatric enterovirus cases using serum samples. IL-6 showed superior discriminatory ability over PCT in identifying patients with severe neurological complications. This novel diagnostic platform holds great potential for early sepsis recognition and infectious disease management, especially in resource-limited settings.
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Affiliation(s)
- Cheng-Han Chen
- Department of Emergency Medicine, Taipei Veterans General Hospital, Taipei 11217, Taiwan; School of Medicine, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan
| | - Rui-Ling Huang
- Institute of Biomedical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Ching-Chuan Liu
- Department of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan
| | | | - Yunching Chen
- Institute of Biomedical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Ching-Fen Shen
- Department of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan; Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan.
| | - Chao-Min Cheng
- Institute of Biomedical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan.
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Mazur F, Han Z, Tjandra AD, Chandrawati R. Digitalization of Colorimetric Sensor Technologies for Food Safety. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2404274. [PMID: 38932639 DOI: 10.1002/adma.202404274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Revised: 06/06/2024] [Indexed: 06/28/2024]
Abstract
Colorimetric sensors play a crucial role in promoting on-site testing, enabling the detection and/or quantification of various analytes based on changes in color. These sensors offer several advantages, such as simplicity, cost-effectiveness, and visual readouts, making them suitable for a wide range of applications, including food safety and monitoring. A critical component in portable colorimetric sensors involves their integration with color models for effective analysis and interpretation of output signals. The most commonly used models include CIELAB (Commission Internationale de l'Eclairage), RGB (Red, Green, Blue), and HSV (Hue, Saturation, Value). This review outlines the use of color models via digitalization in sensing applications within the food safety and monitoring field. Additionally, challenges, future directions, and considerations are discussed, highlighting a significant gap in integrating a comparative analysis toward determining the color model that results in the highest sensor performance. The aim of this review is to underline the potential of this integration in mitigating the global impact of food spoilage and contamination on health and the economy, proposing a multidisciplinary approach to harness the full capabilities of colorimetric sensors in ensuring food safety.
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Affiliation(s)
- Federico Mazur
- School of Chemical Engineering and Australian Centre for Nanomedicine (ACN), The University of New South Wales, Sydney, NSW, 2052, Australia
| | - Zifei Han
- School of Chemical Engineering and Australian Centre for Nanomedicine (ACN), The University of New South Wales, Sydney, NSW, 2052, Australia
| | - Angie Davina Tjandra
- School of Chemical Engineering and Australian Centre for Nanomedicine (ACN), The University of New South Wales, Sydney, NSW, 2052, Australia
| | - Rona Chandrawati
- School of Chemical Engineering and Australian Centre for Nanomedicine (ACN), The University of New South Wales, Sydney, NSW, 2052, Australia
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4
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Jang WS, Lee JM, Lee E, Park S, Lim CS. Loop-Mediated Isothermal Amplification and Lateral Flow Immunochromatography Technology for Rapid Diagnosis of Influenza A/B. Diagnostics (Basel) 2024; 14:967. [PMID: 38732380 PMCID: PMC11083224 DOI: 10.3390/diagnostics14090967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 04/25/2024] [Accepted: 05/05/2024] [Indexed: 05/13/2024] Open
Abstract
Influenza viruses cause highly contagious respiratory diseases that cause millions of deaths worldwide. Rapid detection of influenza viruses is essential for accurate diagnosis and the initiation of appropriate treatment. We developed a loop-mediated isothermal amplification and lateral flow assay (LAMP-LFA) capable of simultaneously detecting influenza A and influenza B. Primer sets for influenza A and influenza B were designed to target conserved regions of segment 7 and the nucleoprotein gene, respectively. Optimized through various primer set ratios, the assay operated at 62 °C for 30 min. For a total of 243 (85 influenza A positive, 58 influenza B positive and 100 negative) nasopharyngeal swab samples, the performance of the influenza A/B multiplex LAMP-LFA was compared with that of the commercial AllplexTM Respiratory Panel 1 assay (Seegene, Seoul, Korea). The influenza A/B multiplex LAMP-LFA demonstrated a specificity of 98% for the non-infected clinical samples, along with sensitivities of 94.1% for the influenza A clinical samples and 96.6% for the influenza B clinical samples, respectively. The influenza A/B multiplex LAMP-LFA showed high sensitivity and specificity, indicating that it is reliable for use in a low-resource environment.
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Affiliation(s)
- Woong Sik Jang
- Emergency Medicine, College of Medicine, Korea University Guro Hospital, 148, Gurodong-ro, Guro-gu, Seoul 08308, Republic of Korea;
| | - Jun Min Lee
- BK21 Graduate Program, Department of Biomedical Sciences, College of Medicine, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea;
| | - Eunji Lee
- Department of Laboratory Medicine, College of Medicine, Korea University Guro Hospital, 148, Gurodong-ro, Guro-gu, Seoul 08308, Republic of Korea; (E.L.); (S.P.)
| | - Seoyeon Park
- Department of Laboratory Medicine, College of Medicine, Korea University Guro Hospital, 148, Gurodong-ro, Guro-gu, Seoul 08308, Republic of Korea; (E.L.); (S.P.)
| | - Chae Seung Lim
- Department of Laboratory Medicine, College of Medicine, Korea University Guro Hospital, 148, Gurodong-ro, Guro-gu, Seoul 08308, Republic of Korea; (E.L.); (S.P.)
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Lu P, Zhan C, Huang C, Miao L, Chen R, Zhao Y, Xianyu Y, Chen X, Chen Y. A Wash-Free Spheres-on-Sphere Strategy for On-Site and Multiplexed Biosensing. ACS NANO 2024; 18:8270-8282. [PMID: 38451231 DOI: 10.1021/acsnano.3c12289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Respiratory infections and food contaminants pose severe challenges to global health and the economy. A rapid on-site platform for the simultaneous detection of multiple pathogens is crucial for accurate diagnosis, appropriate treatment, and a reduced healthcare burden. Herein, we present a spheres-on-sphere (SOS) platform for multiplexed detection using a portable Coulter counter, which employs millimeter- and micron-sized spheres coupled with antibodies as multitarget probes. The assay allows for quantitative detection of multiple analytes within 20 min by simple mixing, enabling on-site detection. The platform shows high accuracy in identifying three respiratory viruses (SARS-CoV-2, influenza A virus, and parainfluenza virus) from throat swab samples, with LOD of 50.7, 32.4, and 49.1 pg/mL. It also demonstrates excellent performance in quantifying three mycotoxins (aflatoxin B1, deoxynivalenol, and ochratoxin A) from food samples. The SOS platform offers a rapid on-site approach with high sensitivity and specificity for applications in resource-limited settings.
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Affiliation(s)
- Peng Lu
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Chen Zhan
- College of Informatics, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Chenxi Huang
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Lin Miao
- The First School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
| | - Rui Chen
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Yongkun Zhao
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Yunlei Xianyu
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, Zhejiang, China
| | - Xiaohua Chen
- The First School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
| | - Yiping Chen
- College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China
- State Key Laboratory of Marine Food Processing and Safety Control, Dalian Polytechnic University, Dalian 116034, Liaoning, China
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Wang Z, Yan B, Ni Y, Cao Y, Qiu J, He R, Dong Y, Hao M, Wang W, Wang C, Su H, Yi B, Chang L. A portable, integrated microfluidics for rapid and sensitive diagnosis of Streptococcus agalactiae in resource-limited environments. Biosens Bioelectron 2024; 247:115917. [PMID: 38101186 DOI: 10.1016/j.bios.2023.115917] [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: 09/27/2023] [Revised: 11/23/2023] [Accepted: 12/05/2023] [Indexed: 12/17/2023]
Abstract
Streptococcus agalactiae (Group B Streptococcus, GBS) has been the leading cause of infections in newborns. Rapid and accurate diagnosis of GBS in pregnant women is a deterministic strategy to prevent newborn infection. Conventional detection methods based on nucleic acid amplification assay have been applied in GBS diagnosis in central laboratories, with demonstrated high sensitivity. However, their heavy dependence on instrumentation and trained technicians forms remarkable obstacles to GBS detection in wide scenarios, including self-testing, and bedside-/community-screening. Furthermore, the structures of GBS bring about extra challenges to the nucleic acid extraction and purification. Novel GBS diagnosis platforms integrating sample processing, amplification, and read-out, are highly desired in clinical. Here, we report a portable, integrated microfluidics that enables rapid extraction of DNA from sampling swabs (<10 min), power-free DNA amplification (<30 min), and simple read-out in GBS detection. The platform works without an external pump, achieving rapid and highly efficient DNA extraction from clinical samples, with a significantly reduced time from 6 h to less than 50 min. Systematic clinical tests based on 47 patient samples validated the high performance of the platform, highlighted with a low limit of detection (LOD, 103 copies/ml), high sensitivity (100%), and specificity (100%). Head-to-head comparisons showed that the device improved the LOD by an order of magnitude than the traditional PCR method, showing a simple yet powerful POCT platform for home-/community-based testing towards GBS (and other pathogens) prevention in remote areas.
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Affiliation(s)
- Zhiying Wang
- Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China; Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Bo Yan
- Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China; Gansu Province Clinical Research Center for Infertility, Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China
| | - Yali Ni
- Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China; Gansu Province Clinical Research Center for Infertility, Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China
| | - Yafei Cao
- Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China; Gansu Province Clinical Research Center for Infertility, Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China; The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, China
| | - Jie Qiu
- Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China
| | - Rui He
- Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China
| | - Yan Dong
- Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China
| | - Man Hao
- Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China
| | - Weikai Wang
- Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China; Gansu Province Clinical Research Center for Pediatric, Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China
| | - Cheng Wang
- Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China
| | - Haixiang Su
- Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China.
| | - Bin Yi
- Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China; Gansu Province Clinical Research Center for Pediatric, Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China.
| | - Lingqian Chang
- Gansu Provincial Maternity and Child-care Hospital (Gansu Provincial Central Hospital), Lanzhou, 730050, China; Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China.
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Lee S, Park JS, Woo H, Yoo YK, Lee D, Chung S, Yoon DS, Lee KB, Lee JH. Rapid deep learning-assisted predictive diagnostics for point-of-care testing. Nat Commun 2024; 15:1695. [PMID: 38402240 PMCID: PMC10894262 DOI: 10.1038/s41467-024-46069-2] [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: 09/19/2023] [Accepted: 02/12/2024] [Indexed: 02/26/2024] Open
Abstract
Prominent techniques such as real-time polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assay (ELISA), and rapid kits are currently being explored to both enhance sensitivity and reduce assay time for diagnostic tests. Existing commercial molecular methods typically take several hours, while immunoassays can range from several hours to tens of minutes. Rapid diagnostics are crucial in Point-of-Care Testing (POCT). We propose an approach that integrates a time-series deep learning architecture and AI-based verification, for the enhanced result analysis of lateral flow assays. This approach is applicable to both infectious diseases and non-infectious biomarkers. In blind tests using clinical samples, our method achieved diagnostic times as short as 2 minutes, exceeding the accuracy of human analysis at 15 minutes. Furthermore, our technique significantly reduces assay time to just 1-2 minutes in the POCT setting. This advancement has the potential to greatly enhance POCT diagnostics, enabling both healthcare professionals and non-experts to make rapid, accurate decisions.
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Affiliation(s)
- Seungmin Lee
- Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon, Seoul, 01897, Republic of Korea
- School of Biomedical Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul, 02841, Republic of Korea
| | - Jeong Soo Park
- Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon, Seoul, 01897, Republic of Korea
- School of Mechanical Engineering, Korea University, 145 Anam-ro, Seoungbuk-gu, Seoul, 02841, Republic of Korea
| | - Hyowon Woo
- Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon, Seoul, 01897, Republic of Korea
| | - Yong Kyoung Yoo
- Department of Electronic Engineering, Catholic Kwandong University, 24, Beomil-ro 579 beon-gil, Gangneung-si, Gangwon-do, 25601, Republic of Korea
| | - Dongho Lee
- CALTH Inc., Changeop-ro 54, Seongnam, Gyeonggi, 13449, Republic of Korea
| | - Seok Chung
- School of Mechanical Engineering, Korea University, 145 Anam-ro, Seoungbuk-gu, Seoul, 02841, Republic of Korea
| | - Dae Sung Yoon
- School of Biomedical Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul, 02841, Republic of Korea
- Interdisciplinary Program in Precision Public Health, Korea University, Seoul, 02841, Republic of Korea
- Astrion Inc, Seoul, 02841, Republic of Korea
| | - Ki-Baek Lee
- Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon, Seoul, 01897, Republic of Korea
| | - Jeong Hoon Lee
- Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon, Seoul, 01897, Republic of Korea.
- CALTH Inc., Changeop-ro 54, Seongnam, Gyeonggi, 13449, Republic of Korea.
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Lee I, Kwon SJ, Heeger P, Dordick JS. Ultrasensitive ImmunoMag-CRISPR Lateral Flow Assay for Point-of-Care Testing of Urinary Biomarkers. ACS Sens 2024; 9:92-100. [PMID: 38141036 PMCID: PMC11090086 DOI: 10.1021/acssensors.3c01694] [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] [Indexed: 12/24/2023]
Abstract
Rapid, accurate, and noninvasive detection of biomarkers in saliva, urine, or nasal fluid is essential for the identification, early diagnosis, and monitoring of cancer, organ failure, transplant rejection, vascular diseases, autoimmune disorders, and infectious diseases. We report the development of an Immuno-CRISPR-based lateral flow assay (LFA) using antibody-DNA barcode complexes with magnetic enrichment of the target urinary biomarkers CXCL9 and CXCL10 for naked eye detection (ImmunoMag-CRISPR LFA). An intermediate approach involving a magnetic bead-based Immuno-CRISPR assay (ImmunoMag-CRISPR) resulted in a limit of detection (LOD) of 0.6 pg/mL for CXCL9. This value surpasses the detection limits achieved by previously reported assays. The highly sensitive detection method was then re-engineered into an LFA format with an LOD of 18 pg/mL for CXCL9, thereby enabling noninvasive early detection of acute kidney transplant rejection. The ImmunoMag-CRISPR LFA was tested on 42 clinical urine samples from kidney transplant recipients, and the assay could determine 11 positive and 31 negative urinary samples through a simple visual comparison of the test line and the control line of the LFA strip. The LFA system was then expanded to quantify the CXCL9 and CXCL10 levels in clinical urine samples from images. This approach has the potential to be extended to a wide range of point-of-care tests for highly sensitive biomarker detection.
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Affiliation(s)
- Inseon Lee
- Department of Chemical and Biological Engineering, and Center for Biotechnology & Interdisciplinary Studies, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, United States
| | - Seok-Joon Kwon
- Department of Chemical and Biological Engineering, and Center for Biotechnology & Interdisciplinary Studies, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, United States
| | - Peter Heeger
- Comprehensive Transplant Center, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Jonathan S. Dordick
- Department of Chemical and Biological Engineering, and Center for Biotechnology & Interdisciplinary Studies, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, United States
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Niromand E, Mansoory MS, Ramezani G, Khazaei MR. Design, implementation and evaluation of e-learning program for common diseases to smartphone-based medical students: at a developing university. BMC MEDICAL EDUCATION 2024; 24:52. [PMID: 38200462 PMCID: PMC10782709 DOI: 10.1186/s12909-023-05023-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 12/31/2023] [Indexed: 01/12/2024]
Abstract
OBJECTIVE Mobile-based educational software offers a wealth of resources that can foster the growth of learners and facilitate the creation of an interactive learning environment. This environment encourages both students and instructors to engage in exploration and the examination of various medical issues. The objective of this study is to design, implement, and evaluate an electronic educational program focused on common medical conditions, specifically tailored for medical students and accessible through mobile phones. METHOD The study was conducted following an action research approach, which comprised four key stages: needs assessment, application design, training, and evaluation. This research took place at the Kermanshah University of Medical Sciences' Medical School. In the needs assessment phase, a formal survey was distributed to the teaching faculty members, requesting them to identify diseases and medical issues of high importance for medical interns' education that were suitable for virtual teaching. Each faculty member was asked to prioritize a minimum of three and a maximum of seven cases. Subsequently, 10 faculty members from various departments completed the survey, leading to the identification of 47 common diseases after eliminating duplicates. These 47 cases were then presented to 30 medical interns, who were asked to select the 20 most significant cases. The 20 diseases with the highest statistical frequency were selected for further development due to resource constraints. The mobile application was developed for the Android platform using the Java programming language and the Android Studio development environment. To assess the application's effectiveness from the students' perspective, a questionnaire was designed, encompassing 25 questions across five domains: satisfaction, performance, learning, usability, and educational effectiveness. The questionnaire employed a Likert scale, with response options ranging from 'completely disagree' to 'completely agree,' scored from 1 to 5. One hundred medical interns and trainees were invited to participate in the evaluation, with 92 of them completing the questionnaires. RESULTS The findings revealed a significant disparity in the average scores between students who underwent traditional teaching methods and those who engaged in mobile-based app-assisted education. This discrepancy was statistically significant across all three examined components. CONCLUSION Mobile-based learning represents a burgeoning educational approach with profound implications for healthcare education and the enhancement of patient care quality. The widespread integration of mobile phones into the educational framework offers a flexible teaching paradigm, fostering the potential for continuous lifelong learning.
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Affiliation(s)
- Elham Niromand
- Fertility and Infertility Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, 0000-0001-6406-6779, Iran
| | - Meysam Siyah Mansoory
- Department of Biomedical Engineering, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, 0000-0002-8160-7618, Iran
| | - Ghobad Ramezani
- Education Development Center, Kermanshah University of Medical Sciences, Kermanshah, 0000-0002-8192-5587, Iran
| | - Mohammad Rasool Khazaei
- Fertility and Infertility Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, 000000021965099x, Iran.
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10
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Lee S, Yoo YK, Han SI, Lee D, Cho SY, Park C, Lee D, Yoon DS, Lee JH. Advancing diagnostic efficacy using a computer vision-assisted lateral flow assay for influenza and SARS-CoV-2 detection. Analyst 2023; 148:6001-6010. [PMID: 37882491 DOI: 10.1039/d3an01189e] [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: 10/27/2023]
Abstract
Lateral flow assays (LFAs) have emerged as indispensable tools for point-of-care testing during the pandemic era. However, the interpretation of results through unassisted visual inspection by untrained individuals poses inherent limitations. In our study, we propose a novel approach that combines computer vision (CV) and lightweight machine learning (ML) to overcome these limitations and significantly enhance the performance of LFAs. By incorporating CV-assisted analysis into the LFA assay, we achieved a remarkable three-fold improvement in analytical sensitivity for detecting Influenza A and for SARS-CoV-2 detection. The obtained R2 values reached approximately 0.95, respectively, demonstrating the effectiveness of our approach. Moreover, the integration of CV techniques with LFAs resulted in a substantial amplification of the colorimetric signal specifically for COVID-19 positive patient samples. Our proposed approach, which incorporates a simple machine learning algorithm, provides substantial enhancements in assay sensitivity, improving diagnostic efficacy and accessibility of point-of-care testing without requiring significant additional resources. Moreover, the simplicity of the machine learning algorithm enables its standalone use on a mobile phone, further enhancing its practicality for point-of-care testing.
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Affiliation(s)
- Seungmin Lee
- Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon, Seoul 01897, Republic of Korea.
- School of Biomedical Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul 02841, Republic of Korea.
| | - Yong Kyoung Yoo
- Department of Electronic Engineering, Catholic Kwandong University, 24, Beomil-ro 579 beon-gil, Gangneung-si, Gangwon-do 25601, Republic of Korea
| | - Sung Il Han
- CALTH Inc., Changeop-ro 54, Seongnam, Gyeonggi 13449, Republic of Korea
| | - Dongho Lee
- CALTH Inc., Changeop-ro 54, Seongnam, Gyeonggi 13449, Republic of Korea
| | - Sung-Yeon Cho
- Vaccine Bio Research Institute, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Chulmin Park
- Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Dongtak Lee
- School of Biomedical Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul 02841, Republic of Korea.
- Center for Nanomedicine, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's hospital, Boston, MA 02115, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Dae Sung Yoon
- School of Biomedical Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul 02841, Republic of Korea.
- Interdisciplinary Program in Precision Public Health, Korea University, Seoul 02841, South Korea
- Astrion Inc., Seoul 02841, Republic of Korea
| | - Jeong Hoon Lee
- Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon, Seoul 01897, Republic of Korea.
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11
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Wu C, Tan P, Chen X, Chang H, Chen Y, Su G, Liu T, Lu Z, Sun M, Wang Y, Zou Y, Wang J, Rao H. Machine Learning-Assisted High-Throughput Strategy for Real-Time Detection of Spermine Using a Triple-Emission Ratiometric Probe. ACS APPLIED MATERIALS & INTERFACES 2023; 15:48506-48518. [PMID: 37796018 DOI: 10.1021/acsami.3c09836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/06/2023]
Abstract
In this study, we designed and fabricated a spermine-responsive triple-emission ratiometric fluorescent probe using dual-emissive carbon nanoparticles and quantum dots, which improve the sensor's accuracy and reduce interfering environmental effects. The probe is advantageous for the proportionate detection of spermine because it has good emission resolution, and the maximum points of the two emission peaks differ by 95 nm. As a proof of concept, cuvettes and a 96-well plate were combined with a smartphone and YOLO series algorithms to accomplish real-time, visual, and high-throughput detection of seafood and meat freshness. In addition, the reaction mechanism was verified by density functional theory and fundamental characterizations. Upon exposure to different amounts of spermine, the intensity of the fluorescent probe changed linearly, and the fluorescent color shifted from yellow-green to red, with a limit of detection of 0.33 μM. To enable visual identification of food-originated spermine, a hydrogel-based visual sensing platform was successfully developed utilizing the triple-emission fluorescent probe. Consequently, spermine could be identified and quantified without complicated equipment.
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Affiliation(s)
- Chun Wu
- College of Science, Sichuan Agricultural University, Xinkang Road, Yucheng District, Ya'an 625014, P. R. China
| | - Ping Tan
- College of Science, Sichuan Agricultural University, Xinkang Road, Yucheng District, Ya'an 625014, P. R. China
| | - Xianjin Chen
- College of Information Engineering, Sichuan Agricultural University, Xinkang Road, Yucheng District, Ya'an 625014, P. R. China
| | - Hongrong Chang
- College of Science, Sichuan Agricultural University, Xinkang Road, Yucheng District, Ya'an 625014, P. R. China
| | - Yuhui Chen
- College of Science, Sichuan Agricultural University, Xinkang Road, Yucheng District, Ya'an 625014, P. R. China
| | - Gehong Su
- College of Science, Sichuan Agricultural University, Xinkang Road, Yucheng District, Ya'an 625014, P. R. China
| | - Tao Liu
- College of Information Engineering, Sichuan Agricultural University, Xinkang Road, Yucheng District, Ya'an 625014, P. R. China
| | - Zhiwei Lu
- College of Science, Sichuan Agricultural University, Xinkang Road, Yucheng District, Ya'an 625014, P. R. China
| | - Mengmeng Sun
- College of Science, Sichuan Agricultural University, Xinkang Road, Yucheng District, Ya'an 625014, P. R. China
| | - Yanying Wang
- College of Science, Sichuan Agricultural University, Xinkang Road, Yucheng District, Ya'an 625014, P. R. China
| | - Yuanfeng Zou
- College of Veterinary Medicine, Sichuan Agricultural University, Huimin Road, Wenjiang District, Chengdu 611130, P. R. China
| | - Jian Wang
- College of Science, Sichuan Agricultural University, Xinkang Road, Yucheng District, Ya'an 625014, P. R. China
| | - Hanbing Rao
- College of Science, Sichuan Agricultural University, Xinkang Road, Yucheng District, Ya'an 625014, P. R. China
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12
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Omidfar K, Riahi F, Kashanian S. Lateral Flow Assay: A Summary of Recent Progress for Improving Assay Performance. BIOSENSORS 2023; 13:837. [PMID: 37754072 PMCID: PMC10526804 DOI: 10.3390/bios13090837] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 08/21/2023] [Accepted: 08/22/2023] [Indexed: 09/28/2023]
Abstract
Lateral flow tests are one of the most important types of paper-based point-of-care (POCT) diagnostic tools. It shows great potential as an implement for improving the rapid screening and management of infections in global pandemics or other potential health disorders by using minimally expert staff in locations where no sophisticated laboratory services are accessible. They can detect different types of biomarkers in various biological samples and provide the results in a little time at a low price. An important challenge regarding conventional LFAs is increasing their sensitivity and specificity. There are two main approaches to increase sensitivity and specificity, including assay improvement and target enrichment. Assay improvement comprises the assay optimization and signal amplification techniques. In this study, a summarize of various sensitivity and specificity enhancement strategies with an objective evaluation are presented, such as detection element immobilization, capillary flow rate adjusting, label evolution, sample extraction and enrichment, etc. and also the key findings in improving the LFA performance and solving their limitations are discussed along with numerous examples.
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Affiliation(s)
- Kobra Omidfar
- Biosensor Research Center, Endocrinology and Metabolism Molecular—Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran 1458889694, Iran
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Research Institute, Tehran University of Medical Sciences, Tehran 1458889694, Iran
| | - Fatemeh Riahi
- Biosensor Research Center, Endocrinology and Metabolism Molecular—Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran 1458889694, Iran
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Research Institute, Tehran University of Medical Sciences, Tehran 1458889694, Iran
| | - Soheila Kashanian
- Faculty of Chemistry, Razi University, Kermanshah 6714414971, Iran
- Nanobiotechnology Department, Faculty of Innovative Science and Technology, Razi University, Kermanshah 6714414971, Iran
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