{"title":"通过基于 ML 的分类,识别工程纳米结构金属氧化物中有关细胞吸收的表面改性剂的结构特征。","authors":"Indrasis Dasgupta, Totan Das, Biplab Das, Shovanlal Gayen","doi":"10.3762/bjnano.15.75","DOIUrl":null,"url":null,"abstract":"<p><p>Nanoparticles (NPs) are considered as versatile tools in various fields including medicine, electronics, and environmental science. Understanding the structural aspects of surface modifiers in nanoparticles that govern their cellular uptake is crucial for optimizing their efficacy and minimizing potential cytotoxicity. The cellular uptake is influenced by multiple factors, namely, size, shape, and surface charge of NPs, as well as their surface functionalization. In the current study, classification-based ML models (i.e., Bayesian classification, random forest, support vector classifier, and linear discriminant analysis) have been developed to identify the features/fingerprints that significantly contribute to the cellular uptake of ENMOs in multiple cell types, including pancreatic cancer cells (PaCa2), human endothelial cells (HUVEC), and human macrophage cells (U937). The best models have been identified for each cell type and analyzed to detect the structural fingerprints/features governing the cellular uptake of ENMOs. The study will direct scientists in the design of ENMOs of higher cellular uptake efficiency for better therapeutic response.</p>","PeriodicalId":8802,"journal":{"name":"Beilstein Journal of Nanotechnology","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11285082/pdf/","citationCount":"0","resultStr":"{\"title\":\"Identification of structural features of surface modifiers in engineered nanostructured metal oxides regarding cell uptake through ML-based classification.\",\"authors\":\"Indrasis Dasgupta, Totan Das, Biplab Das, Shovanlal Gayen\",\"doi\":\"10.3762/bjnano.15.75\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Nanoparticles (NPs) are considered as versatile tools in various fields including medicine, electronics, and environmental science. Understanding the structural aspects of surface modifiers in nanoparticles that govern their cellular uptake is crucial for optimizing their efficacy and minimizing potential cytotoxicity. The cellular uptake is influenced by multiple factors, namely, size, shape, and surface charge of NPs, as well as their surface functionalization. In the current study, classification-based ML models (i.e., Bayesian classification, random forest, support vector classifier, and linear discriminant analysis) have been developed to identify the features/fingerprints that significantly contribute to the cellular uptake of ENMOs in multiple cell types, including pancreatic cancer cells (PaCa2), human endothelial cells (HUVEC), and human macrophage cells (U937). The best models have been identified for each cell type and analyzed to detect the structural fingerprints/features governing the cellular uptake of ENMOs. The study will direct scientists in the design of ENMOs of higher cellular uptake efficiency for better therapeutic response.</p>\",\"PeriodicalId\":8802,\"journal\":{\"name\":\"Beilstein Journal of Nanotechnology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11285082/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Beilstein Journal of Nanotechnology\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.3762/bjnano.15.75\",\"RegionNum\":4,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Beilstein Journal of Nanotechnology","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.3762/bjnano.15.75","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Identification of structural features of surface modifiers in engineered nanostructured metal oxides regarding cell uptake through ML-based classification.
Nanoparticles (NPs) are considered as versatile tools in various fields including medicine, electronics, and environmental science. Understanding the structural aspects of surface modifiers in nanoparticles that govern their cellular uptake is crucial for optimizing their efficacy and minimizing potential cytotoxicity. The cellular uptake is influenced by multiple factors, namely, size, shape, and surface charge of NPs, as well as their surface functionalization. In the current study, classification-based ML models (i.e., Bayesian classification, random forest, support vector classifier, and linear discriminant analysis) have been developed to identify the features/fingerprints that significantly contribute to the cellular uptake of ENMOs in multiple cell types, including pancreatic cancer cells (PaCa2), human endothelial cells (HUVEC), and human macrophage cells (U937). The best models have been identified for each cell type and analyzed to detect the structural fingerprints/features governing the cellular uptake of ENMOs. The study will direct scientists in the design of ENMOs of higher cellular uptake efficiency for better therapeutic response.
期刊介绍:
The Beilstein Journal of Nanotechnology is an international, peer-reviewed, Open Access journal. It provides a unique platform for rapid publication without any charges (free for author and reader) – Platinum Open Access. The content is freely accessible 365 days a year to any user worldwide. Articles are available online immediately upon publication and are publicly archived in all major repositories. In addition, it provides a platform for publishing thematic issues (theme-based collections of articles) on topical issues in nanoscience and nanotechnology.
The journal is published and completely funded by the Beilstein-Institut, a non-profit foundation located in Frankfurt am Main, Germany. The editor-in-chief is Professor Thomas Schimmel – Karlsruhe Institute of Technology. He is supported by more than 20 associate editors who are responsible for a particular subject area within the scope of the journal.