Method Article

Sirtuin Family in Bone Marrow Mesenchymal Stem Cell Research: A Bibliometric Analysis with Web of Science and R

DOI:

10.3791/68913

⸱

December 30th, 2025

 ,  , 
1Department of Prosthodontics, Tianjin Stomatological Hospital, School of Medicine, Nankai University, 2Tianjin Key Laboratory of Oral and Maxillofacial Function Reconstruction, 3Department of Periodontics, Tianjin Stomatological Hospital, School of Medicine, Nankai University

In This Article

Summary

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This study provides a bibliometric protocol for identifying research trends of the Sirtuin family in bone marrow mesenchymal stem cell studies using Web of Science and R.

Abstract

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This study presents a comprehensive bibliometric protocol for systematically mapping research trends and knowledge structures of the Sirtuins (SIRTs) family in bone marrow mesenchymal stem cell research. The protocol involves structured literature retrieval from the Web of Science Core Collection using predefined search terms, the application of explicit inclusion and exclusion criteria to screen English-language articles and reviews and in-depth bibliometric analysis via the bibliometrix package in R. Key methodological steps include data retrieval and cleaning, descriptive statistical analysis, keyword co-occurrence assessment, collaboration network mapping and the generation of thematic evolution and conceptual structure maps. Our analysis of 496 eligible articles (2009-2024) revealed a marked increase in annual publications, with China emerging as the leading contributor. Soochow University and author LI Y were identified as the most productive institution and author, respectively. High-frequency keywords included 'mesenchymal stem cells', 'oxidative stress' and 'SIRT1', with thematic mapping highlighting motor themes such as senescence and oxidative stress. This reproducible and transparent methodological framework not only delineates current research hotspots but also provides a rigorous, scalable approach for large-scale literature synthesis, supporting future scientific evaluations and trend assessments in the field with enhanced clarity and reproducibility.

Introduction

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Stem cells are undifferentiated cells capable of self-renewal and differentiation, offering considerable therapeutic potential. Adult stem cells, such as bone marrow mesenchymal stem cells (BMSCs), are widely used in tissue regeneration due to their accessibility and lack of ethical issues compared with embryonic stem cells1. They are non-hematopoietic cells from bone marrow capable of differentiating into various cell types and are involved in tissue repair and disease treatment2,3.

Adult stem cells are present in various tissues, including bone marrow, fat, and skin, and they avoid the ethical concerns associated with embryonic stem cells4. These cells maintain the stem cell pool and support tissue regeneration through differentiation5,6. Bone marrow in particular contains mesenchymal stem cells that migrate to damaged tissues and contribute to regeneration7,8. Applications include treatment for cancer, intervertebral disc degeneration, and immune disorders9,10.

The Sirtuin (SIRTs) family consists of seven NAD+-dependent enzymes (SIRT1-SIRT7) that regulate diverse cellular functions, including gene expression and DNA repair and metabolism11. Importantly, their activity is modulated by various specific activators (e.g., resveratrol for SIRT1, NAD⁺precursors) and inhibitors (e.g., nicotinamide, EX-527 for SIRT1), which are crucial research tools and potential therapeutic agents12. These proteins are localized in different subcellular compartments and have been implicated in critical biological processes. Several studies have highlighted the importance of SIRTs in regulating the oxidative stress response, ageing, and osteogenic differentiation in BMSCs12,13. Bone marrow mesenchymal stem cells are non-hematopoietic cells derived from bone marrow capable of differentiating into various cell types such as osteoblasts, chondrocytes, and adipocytes, playing vital roles in tissue repair and the treatment of various diseases, including intervertebral disc degeneration, cancer, and immune disorders2,9,10.

Despite the growing body of literature on SIRTs and BMSCs, a comprehensive synthesis of research trends and knowledge structures is lacking. Although traditional narrative and systematic reviews offer in-depth discussion and critical appraisal, they can be subjective and time-consuming, especially for large and rapidly evolving fields. In contrast, bibliometric analysis provides a quantitative objective approach to analyzing large volumes of publication data, enabling the identification of research trends, key contributors, and emerging hotspots through statistical and network analysis14. Knowledge mapping further enhances this by visually representing the intellectual structure and dynamic developments within a research field, offering a unique advantage in mapping the conceptual landscape and revealing hidden patterns that might be missed in qualitative reviews15,16,17.

This study employs a bibliometric approach to map the knowledge structure of SIRTs in BMSC research. It is important to note that the analysis is based solely on English-language articles and reviews retrieved from the Web of Science (WOS) Core Collection, which, while ensuring data quality and consistency, may exclude relevant studies published in other languages or indexed in other databases. Nonetheless, by utilizing the bibliometrix package in R, this study aims to objectively analyze the development, collaboration networks, and thematic focuses in this field, thereby providing valuable insights and guiding future research directions.

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Protocol

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This study only used publicly available bibliographic data and did not involve humans or animals. Therefore, ethics committee approval was not required.

1. Study design

  1. Carry out a retrospective bibliometric analysis of published literature on the SIRTs family in bone marrow mesenchymal stem cell research.
  2. Collect literature from the WOS Core and perform structured retrieval, screening, quantitative analysis, and visualization of bibliographic data.

2. Literature retrieval

  1. Open the WOS Core and select the SCI-Expanded database (all operation codes and inspection points are shown in (Supplemental File 1).
  2. Use the following search strategy: TS=('Mesenchymal Stem Cell*' OR 'Mesenchymal Stromal Cell*' OR 'Bone Marrow Stromal Cell*' OR 'Multipotent Mesenchymal Stromal Cell' OR 'Bone Marrow Mesenchymal Stem Cell*') AND TS=('SIRT*' OR 'Sirtuin' OR 'Sirtuins' OR 'SIRT1' OR 'SIRT2' OR 'SIRT3' OR 'SIRT6')
  3. Filter results to include only English-language journal articles and review articles.
  4. Limit the publication date to 1 November 2024.
  5. Export the selected references as a plain text file with full records and cited references.

3. Literature screening

  1. Use the following inclusion criteria:
    1. Study type: original research articles and review articles
    2. Language: articles published in English
  2. Use the following exclusion criteria:
    1. Remove duplicate publications.
    2. Exclude studies not primarily related to SIRTs and BMSCs (e.g., studies focusing on other SIRT targets, other cell types, or unrelated diseases).
    3. Exclude article types such as meeting abstracts, conference proceedings, editorials, letters, errata, book chapters, and patents.
    4. Exclude studies for which the full text is not accessible.

4. Data cleaning

  1. Open the exported text file in R using the bibliometrix package.
  2. Convert the text file to a data frame using the function convert2df().
  3. Exclude duplicated articles.
  4. Screen the titles and abstracts to remove irrelevant literature.

5. Data analysis

  1. Install the R packages, bibliometrix, ggplot2, igraph, factoextra, and wordcloud, from the Comprehensive R Archive Network using the install.packages() function.
  2. Analyze the number of annual publications, author productivity, country contributions, institutional outputs, and citation metrics.
  3. Identify keyword frequency and growth trends using keywordGrowth().
  4. Construct collaboration networks among countries and institutions using networkPlot().
  5. Assess journal distribution and impact using source analysis functions.

6. Visualization

  1. Use the thematicMap() and conceptualStructure() functions to generate thematic evolution and conceptual structure maps.
  2. Export graphs in high-resolution formats (Portable Document Format [PDF] or Tagged Image File Format [TIFF]) for figure presentation.

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Results

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General publication data

A total of 580 articles were retrieved from the WOS Core Collection using the detailed search strategy. After applying the predefined inclusion and exclusion criteria to remove 84 unrelated records (e.g., studies not primarily focused on SIRTs in BMSCs or irrelevant publication types such as meeting abstracts) or duplicates, 496 eligible articles were included in the final analysis. All included articles were published in English and focused on the SIR...

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Discussion

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At present, there are many studies on the SIRTs family and BMSCs, yet a comprehensive synthesis of research trends is lacking. Sirtuin 6 is a unique member of the known SIRTs family and has a variety of functions in different molecular pathways related to DNA repair, glycolysis, gluconeogenesis, tumorigenesis, neurodegeneration and cardiac hypertrophy18,19. Its broad regulatory roles highlight its major translational potential in age-related diseases and cancer t...

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Disclosures

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The authors have no conflicts of interest to disclose.

Acknowledgements

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We thank all members of our research group for their contributions and feedback during manuscript preparation.

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
computer running the Windows 11 operating systemMicrosoft Corporation, Redmond, WA, USA)
Rversion 4.4.1, R Foundation for Statistical Computing, Vienna, Austriabibliometrix (version 4.3.1), ggplot2, igraph, factoextra, and wordcloud packages

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Tags

Mesenchymal Stem CellsR PackageOxidative StressSIRT1SenescenceKeyword Co Occurrence

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