1
|
Nashruddin SNABM, Salleh FHM, Yunus RM, Zaman HB. Artificial intelligence-powered electrochemical sensor: Recent advances, challenges, and prospects. Heliyon 2024; 10:e37964. [PMID: 39328566 PMCID: PMC11425101 DOI: 10.1016/j.heliyon.2024.e37964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Revised: 09/09/2024] [Accepted: 09/13/2024] [Indexed: 09/28/2024] Open
Abstract
Integrating artificial intelligence (AI) with electrochemical biosensors is revolutionizing medical treatments by enhancing patient data collection and enabling the development of advanced wearable sensors for health, fitness, and environmental monitoring. Electrochemical biosensors, which detect biomarkers through electrochemical processes, are significantly more effective. The integration of artificial intelligence is adept at identifying, categorizing, characterizing, and projecting intricate data patterns. As the Internet of Things (IoT), big data, and big health technologies move from theory to practice, AI-powered biosensors offer significant opportunities for real-time disease detection and personalized healthcare. Still, they also pose challenges such as data privacy, sensor stability, and algorithmic bias. This paper highlights the critical advances in material innovation, biorecognition elements, signal transduction, data processing, and intelligent decision systems necessary for developing next-generation wearable and implantable devices. Despite existing limitations, the integration of AI into biosensor systems shows immense promise for creating future medical devices that can provide early detection and improved patient outcomes, marking a transformative step forward in healthcare technology.
Collapse
Affiliation(s)
- Siti Nur Ashakirin Binti Mohd Nashruddin
- Institute of Informatics and Computing in Energy (IICE), Department of Computing, College of Computing & Informatics, Universiti Tenaga Nasional, 43000, Kajang, Selangor Darul Ehsan, Malaysia
| | - Faridah Hani Mohamed Salleh
- Institute of Informatics and Computing in Energy (IICE), Department of Computing, College of Computing & Informatics, Universiti Tenaga Nasional, 43000, Kajang, Selangor Darul Ehsan, Malaysia
| | - Rozan Mohamad Yunus
- Fuel Cell Institute, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia
| | - Halimah Badioze Zaman
- Institute of Informatics and Computing in Energy (IICE), Department of Computing, College of Computing & Informatics, Universiti Tenaga Nasional, 43000, Kajang, Selangor Darul Ehsan, Malaysia
| |
Collapse
|
2
|
Alissa M, Hjazi A. Utilising biosensor-based approaches for identifying neurotropic viruses. Rev Med Virol 2024; 34:e2513. [PMID: 38282404 DOI: 10.1002/rmv.2513] [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: 11/13/2023] [Revised: 01/01/2024] [Accepted: 01/03/2024] [Indexed: 01/30/2024]
Abstract
Neurotropic viruses, with their ability to invade the central nervous system, present a significant public health challenge, causing a spectrum of neurological diseases. Clinical manifestations of neurotropic viral infections vary widely, from mild to life-threatening conditions, such as HSV-induced encephalitis or poliovirus-induced poliomyelitis. Traditional diagnostic methods, including polymerase chain reaction, serological assays, and imaging techniques, though valuable, have limitations. To address these challenges, biosensor-based methods have emerged as a promising approach. These methods offer advantages such as rapid results, high sensitivity, specificity, and potential for point-of-care applications. By targeting specific biomarkers or genetic material, biosensors utilise technologies like surface plasmon resonance and microarrays, providing a direct and efficient means of diagnosing neurotropic infections. This review explores the evolving landscape of biosensor-based methods, highlighting their potential to enhance the diagnostic toolkit for neurotropic viruses.
Collapse
Affiliation(s)
- Mohammed Alissa
- Department of Medical Laboratory Sciences, College of Applied Medical Sciences, Prince Sattam Bin Abdulaziz, Al-Kharj, Saudi Arabia
| | - Ahmed Hjazi
- Department of Medical Laboratory Sciences, College of Applied Medical Sciences, Prince Sattam Bin Abdulaziz, Al-Kharj, Saudi Arabia
| |
Collapse
|
3
|
Gong H, Chen S, Tang L, Chen F, Chen C, Cai C. Ultra-Sensitive Portable Visual Paper-Based Viral Molecularly Imprinted Sensor without Autofluorescence Interference. Anal Chem 2023; 95:17691-17698. [PMID: 37978911 DOI: 10.1021/acs.analchem.3c03506] [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: 11/19/2023]
Abstract
Detection of the virus is the primary factor to discover and block the occurrence and development of the virus epidemic. Here, an ultrasensitive paper-based virus molecular imprinting sensor is developed to detect two viruses simultaneously in which the detection limit of the influenza virus (H5N1) is 16.0 aM (9.63 × 103 particles/mL) while that of the Hepatitis B Virus (HBV) is 129 fM (7.77 × 107 particles/mL). This paper-based sensor is low cost and is easy to cut, store, and carry. In addition, the visual semiquantitative detection of two viruses is achieved by using two aptamer-functionalized persistent luminescent nanoparticles as signal probes. These probes and the imprinted cavities on the paper-based material formed sandwich-type double recognition of the target viruses. This sensor has extremely high sensitivity to the H5N1 virus, which is of great value to solve the influenza epidemic with the most outbreaks in history, and also opens up a new way for the prevention and control of other virus epidemics. This cheap and portable visual sensor provides the possibility for self-service detection and can greatly reduce the pressure on medical staff and reduce the risk of virus infection caused by the concentration of people to be tested.
Collapse
Affiliation(s)
- Hang Gong
- College of Chemistry and Chemical Engineering, Yunnan Normal University, Kunming 650500, China
| | - Siyu Chen
- The key Laboratory for Green Organic Synthesis and Application of Hunan Province, College of Chemistry, Xiangtan University, Xiangtan 411105, China
| | - Li Tang
- The key Laboratory for Green Organic Synthesis and Application of Hunan Province, College of Chemistry, Xiangtan University, Xiangtan 411105, China
| | - Feng Chen
- The key Laboratory for Green Organic Synthesis and Application of Hunan Province, College of Chemistry, Xiangtan University, Xiangtan 411105, China
| | - Chunyan Chen
- The key Laboratory for Green Organic Synthesis and Application of Hunan Province, College of Chemistry, Xiangtan University, Xiangtan 411105, China
| | - Changqun Cai
- The key Laboratory for Green Organic Synthesis and Application of Hunan Province, College of Chemistry, Xiangtan University, Xiangtan 411105, China
| |
Collapse
|
4
|
Challhua R, Akashi L, Zuñiga J, Beatriz de Carvalho Ruthner Batista H, Moratelli R, Champi A. Portable reduced graphene oxide biosensor for detection of rabies virus in bats using nasopharyngeal swab samples. Biosens Bioelectron 2023; 232:115291. [PMID: 37060864 DOI: 10.1016/j.bios.2023.115291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 03/24/2023] [Accepted: 03/30/2023] [Indexed: 04/03/2023]
Abstract
Rabies is a lethal zoonotic disease caused by rabies virus (RABV) that affects human health and the economy. RABV is transmitted mainly by bats in Brazil, and surveillance in remote areas is hampered by the difficulty of properly collecting samples during fieldwork and the diagnosis is performed in laboratory conditions. Here, we report a portable electrochemical biosensor based on nucleic acid interactions for RABV detection in nasopharyngeal swab samples. The working electrode of the biosensor is composed of reduced graphene oxide (rGO) thin-film immobilized with cDNA through pi-pi stacking to enhance virus detection and specificity. Sensor performance was determined using RNA, and swab samples from bats. RNA detection shows good selectivity, and quantification presents a highly linear calibration curve (R2 = 0.990) using a concentration range of 0.145-25.39 ng/μL. A LOD of 0.104 ng/μL was reached with a sensitivity of 0.321 μA (ng/μL)-1. RABV detection in nasopharyngeal swab samples showed a good difference of positive sample from negative with a response time in seconds, ultra-fast detection compared to known techniques. Three biosensor groups were identified and named after physic-chemical surface characterization as: GO-1, GO-2, and rGO; with best performance for rGO group due to its sp2 hybridized network. Thus, we have successfully fabricated a promising electrochemical biosensor for fast in-situ detection of the RABV in swab samples, which can be expanded to other enveloped viruses that have RNA.
Collapse
|
5
|
Role of Brazilian bats in the epidemiological cycle of potentially zoonotic pathogens. Microb Pathog 2023; 177:106032. [PMID: 36804526 DOI: 10.1016/j.micpath.2023.106032] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 02/07/2023] [Accepted: 02/12/2023] [Indexed: 02/19/2023]
Abstract
Bats (Chiroptera) are flying mammals of great biodiversity and habits. These characteristics contribute for them being natural reservoirs and part of the epidemiological cycle of several potentially zoonotic pathogens, such as viruses, protozoa, fungi and bacteria. Brazil hosts approximately 15% of the world's bat diversity, with 181 distinct species, 68 genera and 9 families. About 60% of infectious diseases in humans are of zoonotic origin and, in the last decades, the detection of zoonotic pathogens in bats and their environment has been reported, such as Rabies virus (RABV) and Histoplasma capsulatum. Thus, the aim of this work was to review the reports of zoonotic pathogens associated with bats in Brazil in the past ten years. We reviewed the main pathogenic microorganisms described and the species of bats most frequently involved in the epidemiological cycles of these zoonotic agents. The obtained data show an upward trend in the detection of zoonotic pathogens in Brazilian bats, such as RABV, Bartonella sp., Histoplasma capsulatum and Leishmania spp., with emphasis on the bat species Artibeus lituratus, Carollia perspicillata, Desmodus rotundus and Molossus molossus. These findings highlight the importance of monitoring bat-associated microrganisms to early identify pathogens that may threaten bat populations, including potentially zoonotic microrganisms, emphasizing the importance of the One Health approach to prevent and mitigate the risks of the emergence of zoonotic diseases.
Collapse
|
6
|
Cai G, Yang J, Wang L, Chen C, Cai C, Gong H. A point-to-point "cap" strategy to construct a highly selective dual-function molecularly-imprinted sensor for the simultaneous detection of HAV and HBV. Biosens Bioelectron 2023; 219:114794. [PMID: 36279822 DOI: 10.1016/j.bios.2022.114794] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 10/02/2022] [Accepted: 10/07/2022] [Indexed: 11/19/2022]
Abstract
As an artificial biomimetic receptor, molecularly-imprinted polymer (MIP) has been widely used for the separation, enrichment and detection of various substances. However, due to the complexity of virus structure, huge volume and the existence of highly similar viruses, MIP shows unsatisfactory selectivity in virus detection. To overcome these issues, two kinds of virus nanoMIPs, just like a "cap", were synthesized by a solid-phase imprinting nanogel technique. The "cap" had no inner core and was much smaller than that of a conventional MIP, which was more favorable for mass transfer. Moreover, each "cap" could only combine with one target virus, which avoided the interference between large-volume virus molecules effectively. The two synthesized "caps" were mixed to construct a bifunctional MIP virus sensor for the simultaneous detection of Hepatitis A virus (HAV) and Hepatitis B virus (HBV). As expected, the selectivity factor (SF) for HBV detection reached 13.7, which was much higher than the reported virus MIP sensors (SF: 3-6), which was comparable to that of small molecular imprinting sensors. In addition, the high sensitivity toward HBV was 34.3 fM, and that of HAV was 27.1 pM. This method provides an idea for preparing high-selectivity biomacro-MIPs, as well as a method for the simultaneous detection of similar viruses with high sensitivity and selectivity. The recovery experiment of spiked serum showed that this method also has great practical application prospects.
Collapse
Affiliation(s)
- Ganping Cai
- Key Laboratory for Green Organic Synthesis and Application of Hunan Province, Key Laboratory of Environmentally Friendly Chemistry and Application of Ministry of Education, College of Chemistry, Xiangtan University, Xiangtan, 411105, China
| | - Junyu Yang
- Key Laboratory for Green Organic Synthesis and Application of Hunan Province, Key Laboratory of Environmentally Friendly Chemistry and Application of Ministry of Education, College of Chemistry, Xiangtan University, Xiangtan, 411105, China
| | - Lingyun Wang
- Key Laboratory for Green Organic Synthesis and Application of Hunan Province, Key Laboratory of Environmentally Friendly Chemistry and Application of Ministry of Education, College of Chemistry, Xiangtan University, Xiangtan, 411105, China; School of Materials Science and Engineering, Hunan Institute of Technology, Hengyang, 421002, China
| | - Chunyan Chen
- Key Laboratory for Green Organic Synthesis and Application of Hunan Province, Key Laboratory of Environmentally Friendly Chemistry and Application of Ministry of Education, College of Chemistry, Xiangtan University, Xiangtan, 411105, China
| | - Changqun Cai
- Key Laboratory for Green Organic Synthesis and Application of Hunan Province, Key Laboratory of Environmentally Friendly Chemistry and Application of Ministry of Education, College of Chemistry, Xiangtan University, Xiangtan, 411105, China.
| | - Hang Gong
- Key Laboratory for Green Organic Synthesis and Application of Hunan Province, Key Laboratory of Environmentally Friendly Chemistry and Application of Ministry of Education, College of Chemistry, Xiangtan University, Xiangtan, 411105, China.
| |
Collapse
|
7
|
Ghaleh HEG, Shahriary A, Izadi M, Farzanehpour M. Advances in early diagnosis of cervical cancer based on biosensors. Biotechnol Bioeng 2022; 119:2305-2312. [DOI: 10.1002/bit.28149] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 04/18/2022] [Accepted: 05/19/2022] [Indexed: 11/07/2022]
Affiliation(s)
| | - Alireza Shahriary
- Chemical Injuries Research Center, Systems biology and poisonings instituteBaqiyatallah University of Medical SciencesTehranIran
| | - Morteza Izadi
- Health Research CenterBaqiyatallah University of Medical SciencesTehranIran
| | - Mahdieh Farzanehpour
- Applied Virology Research CenterBaqiyatallah University of Medical sciencesTehranIran
| |
Collapse
|