Dataset Information

A Machine-Learning-Based Bibliometric Analysis of Cell Membrane-Coated Nanoparticles in Biomedical Applications over the Past Eleven Years.

ABSTRACT: Cell membrane encapsulation is a growing concept in nanomedicine, for it achieves the purpose of camouﬂage nanoparticles, realizing the convenience for drug delivery, bio-imaging, and detoxification. Cell membranes are constructed by bilayer lipid phospholipid layers, which have unique properties in cellular uptake mechanism, targeting ability, immunomodulation, and regeneration. Current medical applications of cell membranes include cancers, inflammations, regenerations, and so on. In this article, a general bibliometric overview is conducted of cell membrane-coated nanoparticles covering 11 years of evolution in order to provide researchers in the field with a comprehensive view of the relevant achievements and trends. The authors analyze the data from Web of Science Core Collection database, and extract the annual publications and citations, most productive countries/regions, most influential scholars, the collaborations of journals and institutions. The authors also divided cell membranes into several subgroups to further understand the application of different cell membranes in medical scenarios. This study summarizes the current research overview in cell membrane-coated nanoparticles and intuitively provides a direction for future research.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC10069317 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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A Machine-Learning-Based Bibliometric Analysis of Cell Membrane-Coated Nanoparticles in Biomedical Applications over the Past Eleven Years.

Zhang Yiyin Y Jin Shengxi S Li Duguang D Chen Guoqiao G Chen Yongle Y Xia Qiming Q Mao Qijiang Q Li Yiling Y Yang Jing J Fan Xiaoxiao X Lin Hui H

Global challenges (Hoboken, NJ) 20230222 4

Cell membrane encapsulation is a growing concept in nanomedicine, for it achieves the purpose of camouﬂage nanoparticles, realizing the convenience for drug delivery, bio-imaging, and detoxification. Cell membranes are constructed by bilayer lipid phospholipid layers, which have unique properties in cellular uptake mechanism, targeting ability, immunomodulation, and regeneration. Current medical applications of cell membranes include cancers, inflammations, regenerations, and so on. In this arti ...[more]

PMID: 37020629

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Project description:Introduction Research on hepatocellular carcinoma (HCC) has grown significantly, and researchers cannot access the vast amount of literature. This study aimed to explore the research progress in studying HCC over the past 30 years using a machine learning-based bibliometric analysis and to suggest future research directions. Methods Comprehensive research was conducted between 1991 and 2020 in the public version of the PubMed database using the MeSH term “hepatocellular carcinoma.” The complete records of the collected results were downloaded in Extensible Markup Language format, and the metadata of each publication, such as the publication year, the type of research, the corresponding author’s country, the title, the abstract, and the MeSH terms, were analyzed. We adopted a latent Dirichlet allocation topic modeling method on the Python platform to analyze the research topics of the scientific publications. Results In the last 30 years, there has been significant and constant growth in the annual publications about HCC (annual percentage growth rate: 7.34%). Overall, 62,856 articles related to HCC from the past 30 years were searched and finally included in this study. Among the diagnosis-related terms, “Liver Cirrhosis” was the most studied. However, in the 2010s, “Biomarkers, Tumor” began to outpace “Liver Cirrhosis.” Regarding the treatment-related MeSH terms, “Hepatectomy” was the most studied; however, recent studies related to “Antineoplastic Agents” showed a tendency to supersede hepatectomy. Regarding basic research, the study of “Cell Lines, Tumors,’’ appeared after 2000 and has been the most studied among these terms. Conclusion This was the first machine learning-based bibliometric study to analyze more than 60,000 publications about HCC over the past 30 years. Despite significant efforts in analyzing the literature on basic research, its connection with the clinical field is still lacking. Therefore, more efforts are needed to convert and apply basic research results to clinical treatment. Additionally, it was found that microRNAs have potential as diagnostic and therapeutic targets for HCC.

Dataset Information

A Machine-Learning-Based Bibliometric Analysis of Cell Membrane-Coated Nanoparticles in Biomedical Applications over the Past Eleven Years.

Publications

A Machine-Learning-Based Bibliometric Analysis of Cell Membrane-Coated Nanoparticles in Biomedical Applications over the Past Eleven Years.

Similar Datasets

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