Paper-based lateral-flow immunoassays (LFIAs) have achieved considerable commercial success and their impact in diagnostics is continuously growing. LFIA results are often obtained by visualizing by the naked eye color changes in given areas, providing a qualitative information about the presence/absence of the target analyte in the sample. However, this platform has the potential to provide ultrasensitive quantitative analysis for several applications. Indeed, LFIA is based on well-established immunological techniques, which have known in the last year great advances due to the combination of highly sensitive tracers, innovative signal amplification strategies and last-generation instrumental detectors. All these available progresses can be applied also to the LFIA platform by adapting them to a portable and miniaturized format. This possibility opens countless strategies for definitively turning the LFIA technique into an ultrasensitive quantitative method. Among the different proposals for achieving this goal, the use of enzyme-based immunoassay is very well known and widespread for routine analysis and it can represent a valid approach for improving LFIA performances. Several examples have been recently reported in literature exploiting enzymes properties and features for obtaining significative advances in this field. In this review, we aim to provide a critical overview of the recent progresses in highly sensitive LFIA detection technologies, involving the exploitation of enzyme-based amplification strategies. The features and applications of the technologies, along with future developments and challenges, are also discussed.

Calabria D., Calabretta M.M., Zangheri M., Marchegiani E., Trozzi I., Guardigli M., et al. (2021). Recent advancements in enzyme-based lateral flow immunoassays. SENSORS, 21(10), 1-19 [10.3390/s21103358].

Recent advancements in enzyme-based lateral flow immunoassays

Calabria D.
Primo
;
Calabretta M. M.;Zangheri M.;Marchegiani E.;Trozzi I.;Guardigli M.;Michelini E.;Mirasoli M.
Ultimo
2021

Abstract

Paper-based lateral-flow immunoassays (LFIAs) have achieved considerable commercial success and their impact in diagnostics is continuously growing. LFIA results are often obtained by visualizing by the naked eye color changes in given areas, providing a qualitative information about the presence/absence of the target analyte in the sample. However, this platform has the potential to provide ultrasensitive quantitative analysis for several applications. Indeed, LFIA is based on well-established immunological techniques, which have known in the last year great advances due to the combination of highly sensitive tracers, innovative signal amplification strategies and last-generation instrumental detectors. All these available progresses can be applied also to the LFIA platform by adapting them to a portable and miniaturized format. This possibility opens countless strategies for definitively turning the LFIA technique into an ultrasensitive quantitative method. Among the different proposals for achieving this goal, the use of enzyme-based immunoassay is very well known and widespread for routine analysis and it can represent a valid approach for improving LFIA performances. Several examples have been recently reported in literature exploiting enzymes properties and features for obtaining significative advances in this field. In this review, we aim to provide a critical overview of the recent progresses in highly sensitive LFIA detection technologies, involving the exploitation of enzyme-based amplification strategies. The features and applications of the technologies, along with future developments and challenges, are also discussed.
2021
Calabria D., Calabretta M.M., Zangheri M., Marchegiani E., Trozzi I., Guardigli M., et al. (2021). Recent advancements in enzyme-based lateral flow immunoassays. SENSORS, 21(10), 1-19 [10.3390/s21103358].
Calabria D.; Calabretta M.M.; Zangheri M.; Marchegiani E.; Trozzi I.; Guardigli M.; Michelini E.; Di Nardo F.; Anfossi L.; Baggiani C.; Mirasoli M....espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/833119
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