比色适体传感器结合深度学习手机应用检测PD-L1细胞外囊泡数据表

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• 源站标题：Data Sheet 1_Colorimetric aptasensor coupled with a deep-learning-powered smartphone app for programmed death ligand-1 expressing extracellular vesicles.docx
• DOI：10.3389/fimmu.2024.1479403.s001
• 发布日期：2025-01-23
• 文件数：1 个
• 文件总体积：353.90 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Colorimetric_aptasensor_coupled_with_a_deep-learning-powered_smartphone_app_for_programmed_death_ligand-1_expressing_extracellular_vesicles_docx/28261931

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• Data Sheet 1_Colorimetric aptasensor coupled with a deep-learning-powered smartphone app for programmed death ligand-1 expressing extracellular vesicl.docx（353.90 KB）

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数据说明

Lung cancer is a devastating public health threat and a leading cause of cancer-related deaths. Therefore, it is imperative to develop sophisticated techniques for the non-invasive detection of lung cancer. Extracellular vesicles expressing programmed death ligand-1 (PD-L1) markers (PD-L1@EVs) in the blood are reported to be indicative of lung cancer and response to immunotherapy. Our approach is the development of a colorimetric aptasensor by combining the rapid capturing efficiency of (Fe3O4)-SiO2-TiO2 for EV isolation with PD-L1 aptamer-triggered enzyme-linked hybridization chain reaction (HCR) for signal amplification. The numerous HRPs catalyze their substrate dopamine (colorless) into polydopamine (blackish brown). Change in chromaticity directly correlates with the concentration of PD-L1@EVs in the sample. The colorimetric aptasensor was able to detect PD-L1@EVs at concentrations as low as 3.6×102 EVs/mL with a wide linear range from 103 to 1010 EVs/mL with high specificity and successfully detected lung cancer patients’ serum from healthy volunteers’ serum. To transform the qualitative colorimetric approach into a quantitative operation, we developed an intelligent convolutional neural network (CNN)-powered quantitative analyzer for chromaticity in the form of a smartphone app named ExoP, thereby achieving the intelligent analysis of chromaticity with minimal user intervention or additional hardware attachments for the sensitive and specific quantification of PD-L1@EVs. This combined approach offers a simple, sensitive, and specific tool for lung cancer detection using PD-L1@EVs. The addition of a CNN-powered smartphone app further eliminates the need for specialized equipment, making the colorimetric aptasensor more accessible for low-resource settings.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fimmu.2024.1479403.s001（source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Colorimetric_aptasensor_coupled_with_a_deep-learning-powered_smartphone_app_for_programmed_death_ligand-1_expressing_extracellular_vesicles_docx/28261931）。