Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/99718
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Applied Physics | - |
| dc.contributor | Department of Biomedical Engineering | - |
| dc.creator | Li, L | en_US |
| dc.creator | Song, M | en_US |
| dc.creator | Lao, X | en_US |
| dc.creator | Pang, SY | en_US |
| dc.creator | Liu, Y | en_US |
| dc.creator | Wong, MC | en_US |
| dc.creator | Ma, Y | en_US |
| dc.creator | Yang, M | en_US |
| dc.creator | Hao, J | en_US |
| dc.date.accessioned | 2023-07-19T00:54:34Z | - |
| dc.date.available | 2023-07-19T00:54:34Z | - |
| dc.identifier.issn | 0264-1275 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/99718 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier Ltd | en_US |
| dc.rights | © 2022 The Author(s). Published by Elsevier Ltd. | en_US |
| dc.rights | This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). | en_US |
| dc.rights | The following publication Li, L., Song, M., Lao, X., Pang, S. -., Liu, Y., Wong, M. -., . . . Hao, J. (2022). Rapid and ultrasensitive detection of SARS-CoV-2 spike protein based on upconversion luminescence biosensor for COVID-19 point-of-care diagnostics. Materials and Design, 223, 111263 is available at https://doi.org/10.1016/j.matdes.2022.111263. | en_US |
| dc.subject | Upconversion nanoparticles | en_US |
| dc.subject | Au nanorods | en_US |
| dc.subject | COVID-19 point-of-care diagnostics | en_US |
| dc.subject | FRET effect | en_US |
| dc.subject | SARS-CoV-2 spike protein | en_US |
| dc.title | Rapid and ultrasensitive detection of SARS-CoV-2 spike protein based on upconversion luminescence biosensor for COVID-19 point-of-care diagnostics | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.volume | 223 | en_US |
| dc.identifier.doi | 10.1016/j.matdes.2022.111263 | en_US |
| dcterms.abstract | Here, we firstly introduce a detection system consisting of upconversion nanoparticles (UCNPs) and Au nanorods (AuNRs) for an ultrasensitive, rapid, quantitative and on-site detection of SARS-CoV-2 spike (S) protein based on Förster resonance energy transfer (FRET) effect. Briefly, the UCNPs capture the S protein of lysed SARS-CoV-2 in the swabs and subsequently they are bound with the anti-S antibodies modified AuNRs, resulting in significant nonradiative transitions from UCNPs (donors) to AuNRs (acceptors) at 480 nm and 800 nm, respectively. Notably, the specific recognition and quantitation of S protein can be realized in minutes at 800 nm because of the low autofluorescence and high Yb-Tm energy transfer in upconversion process. Inspiringly, the limit of detection (LOD) of the S protein can reach down to 1.06 fg mL−1, while the recognition of nucleocapsid protein is also comparable with a commercial test kit in a shorter time (only 5 min). The established strategy is technically superior to those reported point-of-care biosensors in terms of detection time, cost, and sensitivity, which paves a new avenue for future on-site rapid viral screening and point-of-care diagnostics. | - |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Materials and design, Nov. 2022, v. 223, 111263 | en_US |
| dcterms.isPartOf | Materials and design | en_US |
| dcterms.issued | 2022-11 | - |
| dc.identifier.scopus | 2-s2.0-85140772431 | - |
| dc.identifier.eissn | 1873-4197 | en_US |
| dc.identifier.artn | 111263 | en_US |
| dc.description.validate | 202307 bcch | - |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | OA_Scopus/WOS | - |
| dc.description.fundingSource | RGC | en_US |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | PolyU Internal Research Fund | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | CC | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Li_Rapid_Ultrasensitive_Detection.pdf | 3.94 MB | Adobe PDF | View/Open |
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