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      The Perspectives of Biomarkers based Electrochemical Immunosensors, Artificial intelligence and the Internet of Medical Things towards COVID-19 Diagnosis and Management

      review-article
      Author(s): a , 1 , a , b , 1 , c , d , a , ∗
      Publication date (Electronic):
      Journal: Materials Today. Chemistry
      Publisher: Elsevier Ltd.
      Keywords: Artificial intelligence, biomarker, COVID-19, immunosensors, internet of medical things, point-of-care, SARS-CoV-2, SARS, Severe acute respiratory syndrome, MERS, Middle East respiratory syndrome, CoV, Coronavirus, CoV-2, Coronavirus 2, WHO, World health organization, COVID-19, Coronavirus disease 2019, CDC, Center for Disease Control and Prevention, SoA, State of the art, PCR, Polymerase chain reaction, POC, point of care, rRT-PCR, real-time reverse transcription-polymerase chain reaction, ELISA, Enzyme-linked immunosorbent assay, β-CoVs, Beta coronaviruses, SAA, serum amyloid A, IL, Interleukin, RdRp, RNA dependent RNA polymerase, ACE2, Angiotensin-converting enzyme 2, TMPRSS2, Transmembrane serine protease 2, EM, Electron microscope, CFT, Complement fixation test, HI, Haemagglutination inhibition, DID, Double immunodiffusion, ENIA, europium nanoparticle-based immunoassay, CT, computer tomography, RT-LAMP, reverse transcription-loop-mediated isothermal amplification, PPT, Plasmonic Photothermal, LSPR, localized surface plasmon resonance, BSL-4, Biosafety level 4

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          Abstract

          The WHO has declared the COVID-19 an international health emergency due to the severity of infection progression which become more severe due to its continuous spread globally and the unavailability of appropriate therapy and diagnostics systems. Thus, there is a need for efficient devices to detect SARS-CoV-2 infection at an early stage. Nowadays, the RT-PCR technique is being applied for detecting this virus around the globe; however, factors such as stringent expertise, long diagnostic times, invasive and painful screening, and high costs have restricted the use of RT-PCR methods for rapid diagnostics. Therefore, the development of cost-effective, portable, sensitive, prompt, and selective sensing systems to detect SARS-CoV-2 in biofluids at fM/pM/nM concentrations would be a breakthrough in diagnostics. Immunosensors that show increased specificity and sensitivity are considerably fast, and don’t imply costly reagents or instruments, reducing the cost for COVID-19 detection. The current developments in immunosensors perhaps signify the most significant opportunity for a rapid assay to detect COVID-19, without the need of highly skilled professionals and specialized tools to interpret results. Artificial intelligence (AI) and the Internet of Medical Things (IoMT) can also be equipped with this immunosensing approach to investigate useful networking through database management, sharing, and analytics to prevent and manage COVID-19. Herein, we represent the collective concepts of biomarkers based immunosensors along with AI and IoMT as smart sensing strategies with bioinformatics approach to monitor non-invasive early stage SARS-CoV-2 development, with fast POC diagnostics as the crucial goal. This approach should be implemented quickly and verified practicality for clinical samples before being set in the present times for mass-diagnostic research.

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Chaolin Huang, Yeming Wang, Xingwang Li … (2020)
          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, China

            Dawei Wang, Bo Hu, Fangfang Zhu … (2020)
            In December 2019, novel coronavirus (2019-nCoV)-infected pneumonia (NCIP) occurred in Wuhan, China. The number of cases has increased rapidly but information on the clinical characteristics of affected patients is limited.
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              Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia

              Qun Li, Xuhua Guan, Peng Wu … (2020)
              Abstract Background The initial cases of novel coronavirus (2019-nCoV)–infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the first 425 confirmed cases in Wuhan to determine the epidemiologic characteristics of NCIP. Methods We collected information on demographic characteristics, exposure history, and illness timelines of laboratory-confirmed cases of NCIP that had been reported by January 22, 2020. We described characteristics of the cases and estimated the key epidemiologic time-delay distributions. In the early period of exponential growth, we estimated the epidemic doubling time and the basic reproductive number. Results Among the first 425 patients with confirmed NCIP, the median age was 59 years and 56% were male. The majority of cases (55%) with onset before January 1, 2020, were linked to the Huanan Seafood Wholesale Market, as compared with 8.6% of the subsequent cases. The mean incubation period was 5.2 days (95% confidence interval [CI], 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days. In its early stages, the epidemic doubled in size every 7.4 days. With a mean serial interval of 7.5 days (95% CI, 5.3 to 19), the basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9). Conclusions On the basis of this information, there is evidence that human-to-human transmission has occurred among close contacts since the middle of December 2019. Considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere. Measures to prevent or reduce transmission should be implemented in populations at risk. (Funded by the Ministry of Science and Technology of China and others.)
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                Author and article information

                Journal
                Journal ID (nlm-ta): Mater Today Chem
                Journal ID (iso-abbrev): Mater Today Chem
                Title: Materials Today. Chemistry
                Publisher: Elsevier Ltd.
                ISSN (Electronic): 2468-5194
                Publication date PMC-release: 11 February 2021
                Publication date (Electronic): 11 February 2021
                Electronic Location Identifier: 100443
                Affiliations
                [a ]Special center for Nanoscience, Jawaharlal Nehru University, New Delhi-110067, India
                [b ]Amity Institute of Applied Sciences, Amity University, Noida, Uttar Pradesh-201301, India
                [c ]National Institute of Immunology, New Delhi-110067, India
                [d ]Sri Aurobindo College, Delhi University, New Delhi – 110017, India
                Author notes
                [∗ ]Corresponding author. ; Tel.: +11 26704740 / 26704699
                [1]

                These authors contributed equally to this work.

                Article
                Publisher Item ID: S2468-5194(21)00023-9 Publisher ID: 100443
                DOI: 10.1016/j.mtchem.2021.100443
                PMC ID: 7877231
                PubMed ID: 33615086
                SO-VID: d14e236b-2d73-4a24-b66f-0e93a629f875
                Copyright © © 2021 Elsevier Ltd. All rights reserved.
                License:

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                Date received : 27 September 2020
                Date revision received : 1 December 2020
                Date accepted : 4 February 2021
                Categories
                Subject: Article

                Keywords: artificial intelligence,biomarker,covid-19,immunosensors,internet of medical things,point-of-care,sars-cov-2,sars, severe acute respiratory syndrome,mers, middle east respiratory syndrome,cov, coronavirus,cov-2, coronavirus 2,who, world health organization,covid-19, coronavirus disease 2019,cdc, center for disease control and prevention,soa, state of the art,pcr, polymerase chain reaction,poc, point of care,rrt-pcr, real-time reverse transcription-polymerase chain reaction,elisa, enzyme-linked immunosorbent assay,β-covs, beta coronaviruses,saa, serum amyloid a,il, interleukin,rdrp, rna dependent rna polymerase,ace2, angiotensin-converting enzyme 2,tmprss2, transmembrane serine protease 2,em, electron microscope,cft, complement fixation test,hi, haemagglutination inhibition,did, double immunodiffusion,enia, europium nanoparticle-based immunoassay,ct, computer tomography,rt-lamp, reverse transcription-loop-mediated isothermal amplification,ppt, plasmonic photothermal,lspr, localized surface plasmon resonance,bsl-4, biosafety level 4
                Data availability:
                Keywords: artificial intelligence, biomarker, covid-19, immunosensors, internet of medical things, point-of-care, sars-cov-2, sars, severe acute respiratory syndrome, mers, middle east respiratory syndrome, cov, coronavirus, cov-2, coronavirus 2, who, world health organization, covid-19, coronavirus disease 2019, cdc, center for disease control and prevention, soa, state of the art, pcr, polymerase chain reaction, poc, point of care, rrt-pcr, real-time reverse transcription-polymerase chain reaction, elisa, enzyme-linked immunosorbent assay, β-covs, beta coronaviruses, saa, serum amyloid a, il, interleukin, rdrp, rna dependent rna polymerase, ace2, angiotensin-converting enzyme 2, tmprss2, transmembrane serine protease 2, em, electron microscope, cft, complement fixation test, hi, haemagglutination inhibition, did, double immunodiffusion, enia, europium nanoparticle-based immunoassay, ct, computer tomography, rt-lamp, reverse transcription-loop-mediated isothermal amplification, ppt, plasmonic photothermal, lspr, localized surface plasmon resonance, bsl-4, biosafety level 4

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