Novel ruthenium doped TiO2/reduced graphene oxide hybrid as highly selective sensor for the determination of ambroxol

Bukkitgar, Shikandar D.; Shetti, Nagaraj P.; Malladi, Ramesh S.; Reddy, Kakarla Raghava; Kalanur, Shankara S.; Aminabhavi, Tejraj M.

doi:10.1016/j.molliq.2019.112368

Cited by 83 publications

(29 citation statements)

References 48 publications

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“…The early detection of viruses is essential for the prevention and treatment of the associated diseases ( Ambinder et al, 2010 ). Many diagnostic techniques have been developed for virus detection involving quantitative PCR (qPCR) ( Pansri et al, 2020 ), real-time RCR (rtPCR) ( Corman et al, 2020 ), nucleic acid amplification tests ( Xie et al, 2020 ), high-throughput sequencing ( Massart et al, 2018 ), IgM-IgG combined antibody testing ( Li et al, 2020c ), IgA antibody ( Lu et al, 2020 ) and antigen testing ( Yang et al, 2020 ), electrochemical sensors ( Bukkitgar and Shetti 2016a , 2016b ; Bukkitgar et al, 2020 ; Kumar et al, 2019 ; Shetti et al 2019b , 2019d ), etc. However, most of the assays are high cost and need tedious sample processes.…”

Section: Introductionmentioning

confidence: 99%

Metal-organic frameworks for virus detection

Wang

et al. 2020

Biosensors and Bioelectronics

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Virus severely endangers human life and health, and the detection of viruses is essential for the prevention and treatment of associated diseases. Metal-organic framework (MOF), a novel hybrid porous material which is bridged by the metal clusters and organic linkers, has become a promising biosensor platform for virus detection due to its outstanding properties including high surface area, adjustable pore size, easy modification, etc. However, the MOF-based sensing platforms for virus detection are rarely summarized. This review systematically divided the detection platforms into nucleic acid and immunological (antigen and antibody) detection, and the underlying sensing mechanisms were interpreted. The nucleic acid sensing was discussed based on the properties of MOF (such as metal ion, functional group, geometry structure, size, porosity, stability, etc.), revealing the relationship between the sensing performance and properties of MOF. Moreover, antibodies sensing based on the fluorescence detection and antigens sensing based on molecular imprinting or electrochemical immunoassay were highlighted. Furthermore, the remaining challenges and future development of MOF for virus detection were further discussed and proposed. This review will provide valuable references for the construction of sophisticated sensing platform for the detection of viruses, especially the 2019 coronavirus.

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Section: Introductionmentioning

confidence: 99%

Metal-organic frameworks for virus detection

Wang

et al. 2020

Biosensors and Bioelectronics

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“…Nanomaterials range from 1 to 100 nm size; when these particles are used in biosensors, various limitations and challenges can be controlled as these materials have nanoscale features such as conductance, properties including- thermal, chemical, unique optical, magnetic, and increased strength, which cannot be found in the other domain. Nanomaterials can be magnetic nanoparticles, noble metal nanoparticles, quantum dots, carbon nanostructures that have been used in sensor fabrications [ [76] , [77] , [78] , [79] , [80] , [81] ],[ 82 ]. As regards the detection of COVID-19 biosensors based on gold nanoparticles (AuNPs), graphene, nanoislands (AuNIs) and nanowires are used [ 83 ],.…”

Section: Biosensors As Point-of-care Diagnosismentioning

confidence: 99%

Point of care detection of COVID-19: Advancement in biosensing and diagnostic methods

Suleman

Shukla²,

Malhotra

et al. 2021

Chemical Engineering Journal

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117

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“…Electrochemical investigations favour significant advantages such as simplicity in design, higher sensitivity and selectivity, low cost equipment, lower power need and easy to integrate within the microfluidic devices compared to other proposed methods [48] , [49] , [50] . Electrochemical investigations have also demonstrated excellent applications in health care applications [51] , [52] .…”

Section: Current Scenario In the Detection Of Virusesmentioning

confidence: 99%