Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/115292
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Biomedical Engineering | en_US |
| dc.contributor | Research Centre for Nanoscience and Nanotechnology | en_US |
| dc.creator | Ho, WKH | en_US |
| dc.creator | Zhang, Q | en_US |
| dc.creator | Zhorabe, F | en_US |
| dc.creator | Yan, J | en_US |
| dc.creator | Gu, Y | en_US |
| dc.creator | Wang, S | en_US |
| dc.creator | Yi, C | en_US |
| dc.creator | Zhang, Y | en_US |
| dc.creator | Yang, M | en_US |
| dc.date.accessioned | 2025-09-19T03:23:52Z | - |
| dc.date.available | 2025-09-19T03:23:52Z | - |
| dc.identifier.issn | 2050-750X | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/115292 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Royal Society of Chemistry | en_US |
| dc.rights | © The Royal Society of Chemistry 2025 | en_US |
| dc.rights | This article is Open Access Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) (https://creativecommons.org/licenses/by-nc/3.0/) | en_US |
| dc.rights | The following publication Ho, W. K. H., Zhang, Q., Zhorabe, F., Yan, J., Gu, Y., Wang, S., ... & Yang, M. (2025). A buoyant plasmonic microbubble-based SERS sensing platform for amyloid-beta protein detection in Alzheimer's disease. Journal of Materials Chemistry B, 2025, 13(29), 8883-8896 is available at https://doi.org/10.1039/d5tb00632e. | en_US |
| dc.title | A buoyant plasmonic microbubble-based SERS sensing platform for amyloid-beta protein detection in Alzheimer's disease | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 8883 | en_US |
| dc.identifier.epage | 8896 | en_US |
| dc.identifier.volume | 13 | en_US |
| dc.identifier.issue | 29 | en_US |
| dc.identifier.doi | 10.1039/d5tb00632e | en_US |
| dcterms.abstract | Amyloid-β (Aβ) plaques are a key pathological hallmark of Alzheimer's disease (AD), highlighting the need for highly sensitive bioassays for Aβ detection to enable AD diagnosis. Here, we synthesized a buoyant plasmonic substrate composed of polyvinyl alcohol microbubbles (MBs) decorated with in situ-reduced gold nanoparticles (Au NPs). Benefiting from its inherent buoyancy and near-infrared plasmonic properties, the Au/MB substrate serves as an ideal platform for biomolecular sensing via the surface-enhanced Raman spectroscopy (SERS) technique. Compared to conventional flat SERS substrates, the three-dimensional (3D) curved surface of the Au/MB substrate significantly increases the effective sensing area, while its inherent buoyancy facilitates the efficient removal of unbound targets, thereby enhancing detection specificity. By functionalizing Au/MB substrates with copper ions (Cu2+) and 4-mercaptobenzoic acid (4-MBA), we achieved sensitive detection of AD-related Aβ proteins. In the presence of the target analyte, the interaction between Aβ proteins and Cu2+ induces molecular deformation and orientation changes in 4-MBA, leading to distinct spectral changes in the SERS signals. The results demonstrate that the developed Au/MB-based SERS sensor enables sensitive detection of Aβ<inf>1-40</inf> oligomers with a sensitivity as low as 10−9 M. Therefore, this work not only establishes a foundational framework for designing buoyant plasmonic substrate-based SERS sensing platform but also paves the way for the quantitative detection of disease-associated protein biomarkers, contributing to advancements in AD diagnostics. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Journal of materials chemistry B, 7 Aug. 2025, v. 13, no. 29, p. 8883-8896 | en_US |
| dcterms.isPartOf | Journal of materials chemistry B | en_US |
| dcterms.issued | 2025-08-07 | - |
| dc.identifier.scopus | 2-s2.0-105009746948 | - |
| dc.identifier.pmid | 40576328 | - |
| dc.identifier.eissn | 2050-7518 | en_US |
| dc.description.validate | 202509 bchy | en_US |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | CDCF_2024-2025, OA_TA | - |
| dc.description.fundingSource | RGC | en_US |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | This work was supported by the Shenzhen Science and Technology Program-Basic Research Scheme (JCYJ20220531090808020), the Research Grants Council (RGC) of Hong Kong Collaborative Research Grant (C5005-23W and C5078-21E), the Research Grants Council (RGC) of Hong Kong General Research Grant (PolyU 15217621 and PolyU 15216622), the Guangdong-Hong Kong Technology Cooperation Funding Scheme (GHP/032/20SZ and SGDX20201103095404018), the Hong Kong Polytechnic University Shenzhen Institute Bai Cheng Bai Yuan Fund (I2022A002), PolyU Internal Fund (1-YWB4, 1-WZ4E, 1-CD8M, 1-WZ4E, 1-CEB1, 1-YWDU, 1-CE2J, 1-W02C, W40F, and WZ5Z). | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.TA | RSC (2025) | en_US |
| dc.description.oaCategory | TA | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| d5tb00632e.pdf | 3.68 MB | Adobe PDF | View/Open |
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