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Alafeef M, Pan D. Diagnostic Approaches For COVID-19: Lessons Learned and the Path Forward. ACS NANO 2022; 16:11545-11576. [PMID: 35921264 PMCID: PMC9364978 DOI: 10.1021/acsnano.2c01697] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 07/12/2022] [Indexed: 05/17/2023]
Abstract
Coronavirus disease 2019 (COVID-19) is a transmitted respiratory disease caused by the infection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although humankind has experienced several outbreaks of infectious diseases, the COVID-19 pandemic has the highest rate of infection and has had high levels of social and economic repercussions. The current COVID-19 pandemic has highlighted the limitations of existing virological tests, which have failed to be adopted at a rate to properly slow the rapid spread of SARS-CoV-2. Pandemic preparedness has developed as a focus of many governments around the world in the event of a future outbreak. Despite the largely widespread availability of vaccines, the importance of testing has not diminished to monitor the evolution of the virus and the resulting stages of the pandemic. Therefore, developing diagnostic technology that serves as a line of defense has become imperative. In particular, that test should satisfy three criteria to be widely adopted: simplicity, economic feasibility, and accessibility. At the heart of it all, it must enable early diagnosis in the course of infection to reduce spread. However, diagnostic manufacturers need guidance on the optimal characteristics of a virological test to ensure pandemic preparedness and to aid in the effective treatment of viral infections. Nanomaterials are a decisive element in developing COVID-19 diagnostic kits as well as a key contributor to enhance the performance of existing tests. Our objective is to develop a profile of the criteria that should be available in a platform as the target product. In this work, virus detection tests were evaluated from the perspective of the COVID-19 pandemic, and then we generalized the requirements to develop a target product profile for a platform for virus detection.
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Affiliation(s)
- Maha Alafeef
- Department of Chemical, Biochemical and Environmental
Engineering, University of Maryland Baltimore County, Interdisciplinary
Health Sciences Facility, 1000 Hilltop Circle, Baltimore, Maryland 21250,
United States
- Departments of Diagnostic Radiology and Nuclear
Medicine and Pediatrics, Center for Blood Oxygen Transport and Hemostasis,
University of Maryland Baltimore School of Medicine, Health Sciences
Research Facility III, 670 W Baltimore Street, Baltimore, Maryland 21201,
United States
- Department of Bioengineering, the
University of Illinois at Urbana−Champaign, Urbana, Illinois 61801,
United States
- Biomedical Engineering Department, Jordan
University of Science and Technology, Irbid 22110,
Jordan
| | - Dipanjan Pan
- Department of Chemical, Biochemical and Environmental
Engineering, University of Maryland Baltimore County, Interdisciplinary
Health Sciences Facility, 1000 Hilltop Circle, Baltimore, Maryland 21250,
United States
- Departments of Diagnostic Radiology and Nuclear
Medicine and Pediatrics, Center for Blood Oxygen Transport and Hemostasis,
University of Maryland Baltimore School of Medicine, Health Sciences
Research Facility III, 670 W Baltimore Street, Baltimore, Maryland 21201,
United States
- Department of Bioengineering, the
University of Illinois at Urbana−Champaign, Urbana, Illinois 61801,
United States
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Abdulhay E, Alafeef M, Hadoush H, Venkataraman V, Arunkumar N. EMD-based analysis of complexity with dissociated EEG amplitude and frequency information: a data-driven robust tool -for Autism diagnosis- compared to multi-scale entropy approach. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:5031-5054. [PMID: 35430852 DOI: 10.3934/mbe.2022235] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
OBJECTIVE Autism spectrum disorder (ASD) is usually characterised by altered social skills, repetitive behaviours, and difficulties in verbal/nonverbal communication. It has been reported that electroencephalograms (EEGs) in ASD are characterised by atypical complexity. The most commonly applied method in studies of ASD EEG complexity is multiscale entropy (MSE), where the sample entropy is evaluated across several scales. However, the accuracy of MSE-based classifications between ASD and neurotypical EEG activities is poor owing to several shortcomings in scale extraction and length, the overlap between amplitude and frequency information, and sensitivity to frequency. The present study proposes a novel, nonlinear, non-stationary, adaptive, data-driven, and accurate method for the classification of ASD and neurotypical groups based on EEG complexity and entropy without the shortcomings of MSE. APPROACH The proposed method is as follows: (a) each ASD and neurotypical EEG (122 subjects × 64 channels) is decomposed using empirical mode decomposition (EMD) to obtain the intrinsic components (intrinsic mode functions). (b) The extracted components are normalised through the direct quadrature procedure. (c) The Hilbert transforms of the components are computed. (d) The analytic counterparts of components (and normalised components) are found. (e) The instantaneous frequency function of each analytic normalised component is calculated. (f) The instantaneous amplitude function of each analytic component is calculated. (g) The Shannon entropy values of the instantaneous frequency and amplitude vectors are computed. (h) The entropy values are classified using a neural network (NN). (i) The achieved accuracy is compared to that obtained with MSE-based classification. (j) The consistency of the results of entropy 3D mapping with clinical data is assessed. MAIN RESULTS The results demonstrate that the proposed method outperforms MSE (accuracy: 66.4%), with an accuracy of 93.5%. Moreover, the entropy 3D mapping results are more consistent with the available clinical data regarding brain topography in ASD. SIGNIFICANCE This study presents a more robust alternative to MSE, which can be used for accurate classification of ASD/neurotypical as well as for the examination of EEG entropy across brain zones in ASD.
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Affiliation(s)
- Enas Abdulhay
- Biomedical Engineering department, Jordan University of Science and Technology, 22110 Irbid, Jordan
| | - Maha Alafeef
- Biomedical Engineering department, Jordan University of Science and Technology, 22110 Irbid, Jordan
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA
| | - Hikmat Hadoush
- Rehabilitation Sciences department, Jordan University of Science and Technology, 22110 Irbid, Jordan
| | - V Venkataraman
- Department of Mathematics, School of Arts, Science and Humanities, SASTRA Deemed University, Thanjavur, 613401, India
| | - N Arunkumar
- Biomedical Engineering department, Rathinam Technical Campus, Coimbatore, India
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Alafeef M, Moitra P, Dighe K, Pan D. RNA-extraction-free nano-amplified colorimetric test for point-of-care clinical diagnosis of COVID-19. Nat Protoc 2021; 16:3141-3162. [PMID: 33931780 DOI: 10.1038/s41596-021-00546-w] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Accepted: 03/30/2021] [Indexed: 02/07/2023]
Abstract
The global pandemic of coronavirus disease 2019 (COVID-19) highlights the shortcomings of the current testing paradigm for viral disease diagnostics. Here, we report a stepwise protocol for an RNA-extraction-free nano-amplified colorimetric test for rapid and naked-eye molecular diagnosis of COVID-19. The test employs a unique dual-prong approach that integrates nucleic acid (NA) amplification and plasmonic sensing for point-of-care detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with a sample-to-assay response time of <1 h. The RNA-extraction-free nano-amplified colorimetric test utilizes plasmonic gold nanoparticles capped with antisense oligonucleotides (ASOs) as a colorimetric reporter to detect the amplified nucleic acid from the COVID-19 causative virus, SARS-CoV-2. The ASOs are specific for the SARS-CoV-2 N-gene, and binding of the ASOs to their target sequence results in the aggregation of the plasmonic gold nanoparticles. This highly specific agglomeration step leads to a change in the plasmonic response of the nanoparticles. Furthermore, when tested using clinical samples, the accuracy, sensitivity and specificity of the test were found to be >98.4%, >96.6% and 100%, respectively, with a detection limit of 10 copies/μL. The test can easily be adapted to diagnose other viral infections with a simple modification of the ASOs and primer sequences. It also provides a low-cost, rapid approach requiring minimal instrumentation that can be used as a screening tool for the diagnosis of COVID-19 at point-of-care settings in resource-poor situations. The colorimetric readout of the test can even be monitored using a handheld optical reader to obtain a quantitative response. Therefore, we anticipate that this protocol will be widely useful for the development of biosensors for the molecular diagnostics of COVID-19 and other infectious diseases.
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Affiliation(s)
- Maha Alafeef
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.,Biomedical Engineering Department, Jordan University of Science and Technology, Irbid, Jordan.,Departments of Diagnostic Radiology and Nuclear Medicine and Pediatrics, Center for Blood Oxygen Transport and Hemostasis, University of Maryland Baltimore School of Medicine, Baltimore, MD, USA.,Department of Chemical, Biochemical and Environmental Engineering, University of Maryland Baltimore County, Baltimore, MD, USA
| | - Parikshit Moitra
- Departments of Diagnostic Radiology and Nuclear Medicine and Pediatrics, Center for Blood Oxygen Transport and Hemostasis, University of Maryland Baltimore School of Medicine, Baltimore, MD, USA
| | - Ketan Dighe
- Departments of Diagnostic Radiology and Nuclear Medicine and Pediatrics, Center for Blood Oxygen Transport and Hemostasis, University of Maryland Baltimore School of Medicine, Baltimore, MD, USA.,Department of Chemical, Biochemical and Environmental Engineering, University of Maryland Baltimore County, Baltimore, MD, USA
| | - Dipanjan Pan
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA. .,Departments of Diagnostic Radiology and Nuclear Medicine and Pediatrics, Center for Blood Oxygen Transport and Hemostasis, University of Maryland Baltimore School of Medicine, Baltimore, MD, USA. .,Department of Chemical, Biochemical and Environmental Engineering, University of Maryland Baltimore County, Baltimore, MD, USA.
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