Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/114190
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | School of Optometry | - |
| dc.contributor | Department of Food Science and Nutrition | - |
| dc.contributor | Research Centre for SHARP Vision | - |
| dc.contributor | Department of Applied Biology and Chemical Technology | - |
| dc.creator | Chan, KKY | - |
| dc.creator | Cheung, JKW | - |
| dc.creator | Chung, SYC | - |
| dc.creator | Kong, HK | - |
| dc.creator | Bian, J | - |
| dc.creator | Zhou, L | - |
| dc.creator | Do, CW | - |
| dc.creator | Lam, TC | - |
| dc.date.accessioned | 2025-07-15T08:44:10Z | - |
| dc.date.available | 2025-07-15T08:44:10Z | - |
| dc.identifier.uri | http://hdl.handle.net/10397/114190 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Nature Publishing Group | en_US |
| dc.rights | Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. | en_US |
| dc.rights | © The Author(s) 2025 | en_US |
| dc.rights | The following publication Chan, K.Ky., Cheung, J.Kw., Chung, Sy.R. et al. A Comprehensive Proteome of Human Corneal Epithelial Cells Constructed by Cross-platform DIA-Mass Spectrometry. Sci Data 12, 848 (2025) is available at https://doi.org/10.1038/s41597-025-05004-w. | en_US |
| dc.title | A comprehensive proteome of human corneal epithelial cells constructed by cross-platform DIA-Mass spectrometry | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.volume | 12 | - |
| dc.identifier.doi | 10.1038/s41597-025-05004-w | - |
| dcterms.abstract | The corneal epithelium serves as the front barrier against environmental stimuli and pathogens on the ocular surface. A comprehensive protein profile of the corneal epithelium would be crucial for understanding the molecular mechanisms that are related to corneal disease. This work demonstrated a library-free data-independent acquisition (DIA) approach across different mass spectrometers and proteomic software to build a comprehensive proteomic dataset for human corneal epithelial cells (HCECs). With the combinational use of different data-independent acquisition technologies of multiple mass spectrometers, including Sciex ZenoTOF 7600 (DIA-SWATH), Bruker TimsTOF Pro2 (DIA-PASEF), and ThermoFisher Orbitrap Fusion Lumos (DIA-HRMS1), protein identification and quantification were performed with superior sensitivity and resolution. By using a library-free DIA approach, this study constructed a more diverse and unbiased proteomic profile of human corneal epithelial cells (HCECs), comprising 11,954 protein groups (1% FDR). This represents the largest corneal proteome reported to date. All raw proteomic data were deposited to ProteomeXchange Consortium via Proteomics Identifications database (PRIDE) with the dataset identifier accession number PXD059451. Our findings hold the potential to enhance future understanding of corneal pathologies and transformative therapeutics. | - |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Scientific data, 2025, v. 12, 848 | - |
| dcterms.isPartOf | Scientific data | - |
| dcterms.issued | 2025 | - |
| dc.identifier.eissn | 2052-4463 | - |
| dc.identifier.artn | 848 | - |
| dc.description.validate | 202507 bcch | - |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | a3887 | en_US |
| dc.identifier.SubFormID | 51561 | en_US |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | InnoHK initiative of the Innovation and Technology Commission of the Hong Kong Special Administrative Region Government | en_US |
| dc.description.fundingText | The Research Centre for SHARP Vision at The Hong Kong Polytechnic University | 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 | |
|---|---|---|---|---|
| s41597-025-05004-w.pdf | 4.83 MB | Adobe PDF | View/Open |
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