{"title":"利用机器学习驱动的智能表面增强拉曼光谱载玻片实时跟踪细胞对纳米塑料及其载流子效应的响应","authors":"Ruili Li, Shuting Huang, Yuyang Hu, Xiaotong Sun, Zhipeng Zhang, Zaixuan Yang, Qi Liu, Xiaoqing Chen","doi":"10.1021/acs.analchem.5c00504","DOIUrl":null,"url":null,"abstract":"Research on nanoplastic (NP) toxicity and their “carrier effects” on human health remains nascent, especially for real-time, in situ monitoring of metabolic reactions in live cells. Herein, we developed smart surface-enhanced Raman spectroscopy (SERS) slides using a cyclic centrifugation-enhanced electrostatic loading (CCEL) method to facilitatively track live-cell metabolic signals. The designed core–shell polystyrene NPs (mPS) with embedded Raman probes successfully identified intracellular accumulation via a distinct Raman-silent peak. The smart SERS slide effectively monitored the metabolic changes induced by mPS at the molecular level, distinguishing different stages of membrane interaction, the endocytosis process, endosomal aggregation, and cell apoptosis. Besides, this platform was employed to perform a real-time, in situ comparison of cell cycle alterations induced by bare NPs and their “carrier effects”, revealing that NPs extended both the S and G2 phases in BEAS-2B cells, while the “carrier effects” further prolonged G2 and disrupted S-phase progression. Additionally, we integrated machine learning algorithms to accurately predict the cell cycle impacts associated with mPS and their “carrier effects”. This study provides a label-free, in situ, real-time method for monitoring NP-induced metabolic changes in live cells, laying the groundwork for further investigation into cytotoxic behaviors and strategies to mitigate NP toxicity.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"8 1","pages":""},"PeriodicalIF":6.7000,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cell Response to Nanoplastics and Their Carrier Effects Tracked Real-Timely with Machine Learning-Driven Smart Surface-Enhanced Raman Spectroscopy Slides\",\"authors\":\"Ruili Li, Shuting Huang, Yuyang Hu, Xiaotong Sun, Zhipeng Zhang, Zaixuan Yang, Qi Liu, Xiaoqing Chen\",\"doi\":\"10.1021/acs.analchem.5c00504\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Research on nanoplastic (NP) toxicity and their “carrier effects” on human health remains nascent, especially for real-time, in situ monitoring of metabolic reactions in live cells. Herein, we developed smart surface-enhanced Raman spectroscopy (SERS) slides using a cyclic centrifugation-enhanced electrostatic loading (CCEL) method to facilitatively track live-cell metabolic signals. The designed core–shell polystyrene NPs (mPS) with embedded Raman probes successfully identified intracellular accumulation via a distinct Raman-silent peak. The smart SERS slide effectively monitored the metabolic changes induced by mPS at the molecular level, distinguishing different stages of membrane interaction, the endocytosis process, endosomal aggregation, and cell apoptosis. Besides, this platform was employed to perform a real-time, in situ comparison of cell cycle alterations induced by bare NPs and their “carrier effects”, revealing that NPs extended both the S and G2 phases in BEAS-2B cells, while the “carrier effects” further prolonged G2 and disrupted S-phase progression. Additionally, we integrated machine learning algorithms to accurately predict the cell cycle impacts associated with mPS and their “carrier effects”. This study provides a label-free, in situ, real-time method for monitoring NP-induced metabolic changes in live cells, laying the groundwork for further investigation into cytotoxic behaviors and strategies to mitigate NP toxicity.\",\"PeriodicalId\":27,\"journal\":{\"name\":\"Analytical Chemistry\",\"volume\":\"8 1\",\"pages\":\"\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2025-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Analytical Chemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1021/acs.analchem.5c00504\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical Chemistry","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acs.analchem.5c00504","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
Cell Response to Nanoplastics and Their Carrier Effects Tracked Real-Timely with Machine Learning-Driven Smart Surface-Enhanced Raman Spectroscopy Slides
Research on nanoplastic (NP) toxicity and their “carrier effects” on human health remains nascent, especially for real-time, in situ monitoring of metabolic reactions in live cells. Herein, we developed smart surface-enhanced Raman spectroscopy (SERS) slides using a cyclic centrifugation-enhanced electrostatic loading (CCEL) method to facilitatively track live-cell metabolic signals. The designed core–shell polystyrene NPs (mPS) with embedded Raman probes successfully identified intracellular accumulation via a distinct Raman-silent peak. The smart SERS slide effectively monitored the metabolic changes induced by mPS at the molecular level, distinguishing different stages of membrane interaction, the endocytosis process, endosomal aggregation, and cell apoptosis. Besides, this platform was employed to perform a real-time, in situ comparison of cell cycle alterations induced by bare NPs and their “carrier effects”, revealing that NPs extended both the S and G2 phases in BEAS-2B cells, while the “carrier effects” further prolonged G2 and disrupted S-phase progression. Additionally, we integrated machine learning algorithms to accurately predict the cell cycle impacts associated with mPS and their “carrier effects”. This study provides a label-free, in situ, real-time method for monitoring NP-induced metabolic changes in live cells, laying the groundwork for further investigation into cytotoxic behaviors and strategies to mitigate NP toxicity.
期刊介绍:
Analytical Chemistry, a peer-reviewed research journal, focuses on disseminating new and original knowledge across all branches of analytical chemistry. Fundamental articles may explore general principles of chemical measurement science and need not directly address existing or potential analytical methodology. They can be entirely theoretical or report experimental results. Contributions may cover various phases of analytical operations, including sampling, bioanalysis, electrochemistry, mass spectrometry, microscale and nanoscale systems, environmental analysis, separations, spectroscopy, chemical reactions and selectivity, instrumentation, imaging, surface analysis, and data processing. Papers discussing known analytical methods should present a significant, original application of the method, a notable improvement, or results on an important analyte.