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The Recent Evolution of the Application of Single-Cell Analysis in Kidney Diseases: A bibliometric analysis
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  • Marady Hun,
  • Huai Wen,
  • Min Wen,
  • Qiuwei Tian,
  • Zisai Wang,
  • Phanna Han,
  • Tharith Wun,
  • Tin Som,
  • Boren Preap,
  • Mingyi Zhao,
  • Qingnan He
Marady Hun
Central South University Third Xiangya Hospital
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Huai Wen
Central South University Third Xiangya Hospital
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Min Wen
Central South University Third Xiangya Hospital
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Qiuwei Tian
Central South University Third Xiangya Hospital
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Zisai Wang
Central South University Third Xiangya Hospital
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Phanna Han
The Second Xiangya Hospital of Central South University
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Tharith Wun
Xiangya Hospital Central South University
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Tin Som
Central South University Third Xiangya Hospital
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Boren Preap
The Second Xiangya Hospital of Central South University
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Mingyi Zhao
Central South University Third Xiangya Hospital

Corresponding Author:zhao_mingyi@csu.edu.cn

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Qingnan He
Central South University Third Xiangya Hospital
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Abstract

Abstract There is increasing interest in employing Single-Cell Analysis (SCA) technologies to improve the efficiency of renal disease diagnosis and treatment. Nevertheless, comprehensive studies summarizing and analyzing research trends in the field are lacking. There is increasing interest in employing Single-Cell Analysis (SCA) technologies to improve the efficiency of renal disease diagnosis and treatment. Nevertheless, comprehensive studies summarizing and analyzing research trends in the field are lacking. This article discusses the use of bibliometric analysis to evaluate the progress and potential of Single-Cell Analysis (SCA) technologies in the field of kidney disease. The study identified 1,606 articles and reviews published between 1999 and 2023, involving 11,737 authors from 2,317 institutions across 67 countries or regions. The major contributors to SCA in kidney disease were highlighted, including top authors, institutes, countries, and journals. Research hotspots included molecular and pathological aspects, with disease-, molecular-, and pathological-related keywords such as expression, EGFR, gene-expression, activation, gene, cell, protein, mechanism, mutation, inflammation, resistance, apoptosis, and T-cell. Key kidney-related disease keywords included SLE, AKI, CKD, renal fibrosis, diabetic kidney disease, nephrotic syndrome, IgA nephropathy, and kidney transplantation. The authors note that the field of SCA in kidney-related disease research is rapidly growing, with the potential for further expansion. SCA technologies could provide novel diagnostic, therapeutic, and prognostic approaches and support routine clinical diagnosis and individualized treatment.