Bibliometric analysis of literature on stem cells in regenerative medicine and their clinical applications (2010 to 2024):
A scoping review
Article information
Abstract
Stem cells in regenerative medicine are advancing rapidly, with significant progress made in recent years. Our bibliometric review is a significant contribution to the field and is essential for advancing research. However, there is a noticeable lack of reviews that focus on stem cells and their clinical applications in regenerative medicine. Our study addressed this gap using advanced tools such as R-Studio and VOSviewer to explore publication volumes, intellectual structures, and emerging trends in the field, ensuring the validity and reliability of our findings. We utilized Scopus and Web of Science to extract 1,274 relevant articles and employed rigorous descriptive analysis, co-occurrence analysis, and text-mining techniques. Our study identified the most influential journals based on productivity and citation volume. These journals are: International Journal of Molecular Sciences, Stem Cell Reviews and Reports, Biomaterials, Stem Cell Research and Therapy, Regenerative Therapy, Stem Cells Translational Medicine, and Cytotherapy. The top-cited articles highlight mRNA, stem cell reprogramming, and innovative therapeutic techniques. Our analysis of the links between stem cells and disease underscores the significant focus on mesenchymal stem cells and pluripotent stem cells, with the most frequently treated conditions being knee osteoarthritis, various types of cancer, and cardiovascular diseases. We also identified emerging areas classified as materials, methods, and technologies such as biopolymers, nanotechnology, deep learning, Kyoto Encyclopedia of Genes and Genomes, three-dimensional printers, and bioprinting. By investigating this focused area, this study provides valuable insights into the current landscape and future directions of stem cell-based regenerative medicine with a clear clinical translation pathway.
INTRODUCTION
Regenerative medicine is a rapidly advancing field that has made significant progress in recent years [1,2]. The field of regenerative medicine aims to restore, regrow, and replace damaged cells, tissues, organs, and body parts, offering the potential to cure diseases and numerous conditions that are currently difficult to treat [3]. Self-renewal and differentiation are unique stem cell properties that make them central for regenerative medicine. Stem cells exhibit significant heterogeneity, impacting their regenerative potential and clinical applications in regenerative medicine. Their origin and differentiation potential can broadly categorize stem cells. There are several main types of stem cells, such as embryonic stem cells (ESCs), induced pluripotent stem cells (iPSCs), mesenchymal stem cells (MSCs), and hematopoietic stem cells (HSCs) utilized in regenerative medicine. Stem cells from various tissues like bone marrow and adipose tissue, and each source offers unique advantages and challenges in terms of accessibility, differentiation potential, and ethical considerations [4]. Various materials, methods, and technologies (MMTs) have been developed to study and utilize stem cells effectively. MMTs facilitate the growth and differentiation of stem cells and enhance their application in clinical settings.
Despite the popularity and relevance of this topic, recent bibliometric studies on stem cells or regenerative medicine focused on clinical applications are lacking. Several highly focused bibliometric analyses have examined various stem cell types that offer exciting possibilities in regenerative medicine.
For instance, studies have explored stem cell research in precision medicine, therapeutic trends of priming MSCs [5,6], stem cell research in Alzheimer’s disease [7], trends in regenerative medicine [8], MSCs in cardiovascular disease [9], umbilical cord MSCs [10], human ESCs [11]. The studies primarily focus on particular stem cell types in clinical applications. Therefore, a gap exists in bibliometric analysis reviews regarding wide range of stem cell applications in regenerative medicine specifically targeted towards clinical applications.
Additionally, we found no bibliometric reviews that suggested trends and priorities in this area of research. In response, our study aims to answer the following research questions (RQs):
RQ1. What is the evolution in the development of clinical applications of stem cells in the regenerative medicine (CAoSCiRM) research field, and which journals are the most productive?
RQ2. What are the most influential journals supporting the development of the CAoSCiRM field?
RQ3. What are the most cited articles in the studied field?
RQ4. What is the intellectual structure of CAoSCiRM research field?
RQ5. What links between diseases/conditions and types of stem cells can be mapped in our field of study?
RQ6. What are the emerging trends of the MMTs in the CAoSCiRM field?
In our study, we aim to synthesize recent important findings in the field and address RQs by using the Scopus and Web of Science (WOS) databases. To extract relevant research papers using the keywords related to specific types of stem cells, “regenerative medicine,” and “clinical.” We used descriptive analysis (RQs1–3), co-occurrence analysis (RQs4 and 6), and a text-mining technique (RQ5) to investigate the studied domain comprehensively. In the study, we used the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA), which is designed to help transparently report how data was extracted, cleaned, and screened [12].
This study expands our current knowledge base by conducting a detailed bibliometric analysis of the publication activity in stem cells. It examines the volume of publications, influential journals, and citation metrics, providing a strong framework for understanding the evolution and impact of research in this area. This analysis not only maps the intellectual landscape of stem cell research but also provides a valuable reference for future scholars looking to navigate and contribute to this rapidly growing field. Additionally, the study employs innovative text-mining techniques to analyze abstracts and titles, representing a significant methodological advancement. By identifying the coverage of different stem cell types in the existing literature, this research offers new insights into the critical areas of current studies and identifies potentially under-explored ones. This approach enhances our ability to systematically categorize and assess the breadth of stem cell research, ensuring that emerging trends and critical gaps are accurately identified. Lastly, the study offers a forward-looking analysis of emerging topics and provides strategic recommendations for future research, which is a critical contribution to the field. By identifying gaps and suggesting new avenues for investigation, this work addresses current limitations and paves the way for future theoretical and empirical advancements in regenerative medicine. This proactive approach is essential for fostering innovative research that can ultimately lead to clinical applications, advancing both scientific knowledge and the therapeutic potential in the field of stem cell interventions.
MATERIALS AND METHODS
Bibliometric analysis is a crucial tool for evaluating scientific output and discerning the contributions of individual [13] researchers, institutions, and countries across various fields of knowledge. When performing a rigorous bibliometric analysis, it is imperative to utilize credible and pertinent data sources. According to the authors [14], Scopus and WOS databases are the most suitable for these purposes. It is worth noting that WOS is synced with MEDLINE, allowing you to retrieve articles using PubMed ID, eliminating the need to access this database separately [13] at the same time, some studies using other databases show that it provides fewer publications due to its narrower scope and coverage [15].
The PRISMA flow diagram provides detailed information for data extraction and search queries (https://osf.io/g6tqc/). As of May 8, 2024, a total of 11,126 relevant publications were retrieved from the two databases, WOS and Scopus (Fig. 1). Using filters, we excluded 6,409 records (Document type: article; Language: English; Years: 2010 to 2024). R Studio was used to preprocess the data, remove duplicates and merge two databases. We excluded articles lacking the author’s keywords and abstracts. During the selection process, systematic and bibliometric reviews were removed because they did not reflect the primary findings of the studies. We conducted a content analysis of the abstracts to remove irrelevant articles from our database. Irrelevant publications included the use of stem cells in animals and the lack of information on clinical trials. Thus, 1,274 publications were used for further analysis. In Fig. 1, we also indicate which methods were used for analysis and visualization.
Our selected and refined data were then analyzed using descriptive analysis, co-occurrence analysis and text-mining technique. Descriptive analysis was used for RQs1–3. We specifically explored publication volumes on CAoSCiRM (RQ1) and investigated the most cited journals and articles (RQs2–3) using a pivot table. The results were visualized using a combo graph and tables.
Co-occurrence analysis was employed for the two RQs, 4 and 6 different visualization types supported them. Precisely, RQ4 on the exploration of the intellectual structure of the studied domain was explored by means of analysis of the author’s keywords. This analysis was supplemented by network visualization [16] and created with the use of VOSviewer software version 1.6.20 (Centre for Science and Technology Studies, Leiden University). In RQ6, terms related to various MMTs in the field of specific stem cells are used to describe the developments over time in combo graphs containing attributes of bibliometric analysis [16,17]. The overlay visualization is identical to the network visualization except that items’ colors range from blue (lowest score) to green to yellow (highest score).
For RQ5, links between diseases/conditions and types of stem cells were identified by applying a text-mining of abstracts and titles. The text-mining feature of the VOSviewer facilitated the generation of a term map that relies on the natural language processing algorithms [16,17].
RESULTS
Journals that have made valuable contributions to the CAoSCiRM development
To gain insights into the development of publications on CAoSCiRM and their significant contributions to the field, we conducted an analysis of the top 10 most prolific journals and the total number of publications over time (Fig. 2). A pivot table was used to analyze the sample dataset. It revealed a rich corpus of articles from 570 journals dedicated to this field.
Of 570 journals, 386 (68%) published only one article from 2010 to 2024. Additionally, 19 journals published more than 10 articles, with the top 10 accounting for 22% of the total publications. As we can see, for 14 years, there has been a general growth trend with peaks in 2013, 2015, and 2020–2022. From 2020 to 2022, three key journals (International Journal of Molecular Sciences, Stem Cell Research and Therapy, and Stem Cell Reviews and Reports) made significant contributions to developing the CAoSCiRM research field.
In section 1, we have identified the journals with the highest output in the CAoSCiRM field, reflecting the productivity and volume of research contributions over time. However, productivity alone does not capture the influence or impact of these contributions on the field. To understand the significance of these journals more comprehensively, it is essential to evaluate not only the quantity of publications but also the quality, as indicated by citation impact. Therefore, in section 2, we examine the most cited journals within the CAoSCiRM domain.
Top 10 most cited journals in the CAoSCiRM field
Comparing productivity with citation impact allows us to highlight journals that are both prolific and influential, offering a more nuanced view of which journals drive the field forward. This approach provides insights into where impactful research is concentrated and identified journals that play a pivotal role in shaping research trends and advancements in CAoSCiRM. We analyzed the top 10 most cited journals. Notably, based on citation counts, eight journals are also included in the top 10 list of most productive journals (refer to Table 1). Hence, these journals can be deemed the most influential in this field of research.
The average citation score for this field of study is 26.8. Table 1 shows nine of the top 10 journals with an average citation score greater than this.
In section 2, key journals driving the field, including the International Journal of Molecular Sciences (n= 41), StemStem Cell Reviews and Reports (n= 40), and Cell Research and Therapy (n= 36), and three journals stand out with the highest average citation scores: Stem Cells Translational Medicine (54.5), Stem Cell Research and Therapy (45.9), and Biomaterials (41.2).
Top 10 most cited research papers in the field (2010 to 2024)
We showcased the most cited articles to give researchers a thorough grasp of the field’s current advancements and the most impactful articles. Specifically, Table 2 exhibits the top 10 most cited articles directly pertinent to the CAoSCiRM field.
It is not surprising that paper 1# [18] given the widespread adoption of mRNA technology in various scientific fields, including its application in developing mRNA vaccines, it has become highly cited. In addition, papers 4# [19] and 6# [20] also focus on novel stem cell reprogramming and differentiation methods. These papers might be crucial in significant advancements in stem cell biology, reprogramming, and therapeutic applications, pushing the field’s boundaries. Their high citations reflect their broad impact across the field.
Papers 2# [21], 3# [22], 5# [23], 7# [24], and 6# [20] highlight the development of novel innovative techniques, methods, biomaterials, and their applications in cell therapy and tissue engineering to treat various diseases. Additionally, paper 3# investigates a method to control the survival of adoptively transferred immune cells, improving the safety of this cell therapy approach. Papers #8 [25] and #9 [26] highlight MSCs and the regenerative potential of those cells. Paper #10 [27] this paper focuses on optimizing the preparation of platelet-rich plasma (PRP), a source of growth factors used in regenerative medicine. The papers are published in prestigious, high-impact journals like Cell Stem Cell, Nature, New England Journal of Medicine, Lancet, Biomaterials, and Current Stem Cell Research and Therapy, indicating the quality and significance of the research.
In section 3, the papers might be among the top 10 cited because they conducted groundbreaking research with clinical relevance using innovative technologies.
Intellectual structure of the CAoSCiRM research field (2010 to 2024)
The network visualization shows the clustering of keywords in the sample database (Fig. 3). We focused on keywords that appeared at least five times, which matches the default threshold set in VOSviewer. Co-occurrence analysis identified 3,415 keywords in the sample database. A thesaurus file was prepared to combine synonyms and plurals. Author’s keywords (n= 145) met the threshold criteria.
VOSviewer formed nine clusters in the network visualization (Fig. 3). Cluster sizes varied significantly, with the largest red cluster (n= 33) and the smallest light brown cluster (n= 6). We chose not to display the main keyword, “regenerative medicine,” on the map.
The red cluster (Fig. 3) is centered on “tissue engineering” and delves into biomaterials such as “hydrogel,” “nanoparticles,” and “chitosan” which play a supportive role in cell-based tissue repair, particularly for cartilage and bone. Emerging techniques like “bioprinting” and “microRNA” [18] are also present here, signaling a growing interest in advanced methods for scaffold creation and tissue regeneration.
The green, purple, and pink clusters predominantly explore “stem cells therapy, regeneration, and transplantation.” The green cluster with the main keyword “induced pluripotent stem cells” highlights the potential of pluripotent stem cells (PSCs) [28] and other stem cells, such as “adult stem cells,” “embryonic stem cells,” and “embryonic stem cells” for “stem cell therapy” and “tissue regeneration” applications. Keywords point toward exploring the methods “cell culture,” “automation,” addressing the fundamental “developmental biology” stem cell functions such as “self- renewal,” “differentiation,” “multipotency,” “reprogramming,” “pluripotency,” and “apoptosis” [8]. The purple cluster is more aligned with “cell transplantation” strategies, whereas the pink cluster investigates the therapeutic potential of MSCs, particularly in treating conditions like cancer, liver cirrhosis [29], and heart disease, with an emphasis on the challenges of “clinical translation” [30].
The blue cluster looks into “MSC” derived from sources such as the “umbilical cord” [31] and “Wharton’s jelly,” examining their contributions to “vasculogenesis” and modulation of the immune system [32]. Additionally, this cluster includes studies on “exosomes” and “epigenetics” in MSC-based therapies [33], reflecting an interest in the cellular and molecular mechanisms underlying their therapeutic potential.
The yellow cluster underscores the role of “growth factors” in MSC proliferation and differentiation, highlighting the importance of bioreactors for scaling up MSC production for clinical use. This cluster also addresses the impact of aging [34], wound healing [35] on stem cell functionality [36].
The light blue cluster is primarily concerned with “adipose-derived stem cells” (ADSCs) and their applications in treating osteoarthritis and cartilage repair. There is also notable interest in employing biomaterials like “PRP” in combination with adipose-derived cells to enhance regenerative outcomes [37-39].
The orange cluster examines the role of “extracellular vesicles” and the “secretome” derived from adipose stem cells, especially in modulating inflammation and “immune system responses” [36,40,41]. Research here includes potential applications as “miRNA” involved in cell reprogramming and differentiation [18].
Finally, the brown cluster addresses “bone marrow-derived MSCs” in the context of therapies for heart failure and tendon repair. The presence of keywords like “clinical trials” and “safety” indicates that this research often focuses on translating autologous MSC therapies to clinical settings, with an eye to mitigating immune rejection risks [32,42].
In section 4, the CAoSCiRM field reflects a complex, multi-dimensional approach, investigating various types of stem cells and biomaterials aimed at regenerative therapies. Key research themes include the development of biomaterials for tissue engineering, using MSCs for immune modulation, and advancing cell-based treatments for conditions such as heart disease, osteoarthritis, and cancer. The ongoing emphasis on clinical translation demonstrates a commitment to bridging laboratory research and practical applications within regenerative medicine.
Links between diseases and types of stem cells in our field of study
The intellectual structure results highlighted exploring different types of stem cells and their sources in the context of regenerative and repair therapies for clinical applications. This knowledge has provided the basis for analyzing potential connections between different diseases and types of stem cells for treatment.
When a researcher is investigating a particular question, such as the connection between diseases and types of stem cells, relying solely on keyword analysis may not be adequate. A comprehensive review of abstracts and titles is crucial for gaining insights into the diverse applications of stem cells for addressing a wide range of diseases and injuries. Thus, we have chosen text mining as part of our research methodology.
The VOSviewer defined a noun phrase as a sequence of consecutive words ending in a noun, with preceding words being nouns or adjectives. Using binary counting, each term was counted once per article. Our text-mining analysis identified 26,597 terms (noun phrases) with a minimum of three occurrences. The VOSviewer software created 11 clusters and generated a bibliometric map visualizing 270 selected terms to showcase the research landscape. By examining the clusters, we identified which stem cell types frequently co-occur with terms related to specific diseases and conditions.
Most detected stem cells by text mining
The various types of MSCs (‘“mscs,” ’stromal cells’’) are located in almost every cluster (e.g., “human mesenchymal stem cells,” “adult mesenchymal stem cell,” “wj msc,” “imsc,” “primary msc,” “placental msc,” “allo hmsc”). Our results indicate a strong focus on MSCs, particularly those derived from bone marrow (e.g., “bm msc,” “human bone marrow mesenchymal stem cell”) and adipose tissue (e.g., “ADSC”). The orange cluster includes keywords: “pluripotent stem cells” (PSCs) (198 occurrences), “embryonic stem cell” (ESCs), and induced pluripotent stem cells (“ipsc”). In the purple cluster, we observe “adult stem cells” (97 occurrences), which are linked to various tissues, such as bone marrow, and skin. Umbilical cord MSCs (“ucmscs”) (35 occurrences, orange cluster) derived from the umbilical cord, was also found in our cluster. The keywords: “stromal cells” (light blue cluster), “fibroblast” (coral cluster, also includes “dermal fibroblast” and “human fibroblasts”), “endothelial cells” (red cluster), “epithelial cells” (orange cluster), and “chondrogenic progenitor cells” (blue cluster) are present in our analysis. In the green cluster, the keyword “hematopoietic stem cells” (30 occurrences) has links with “bone fracture” and umbilical cord blood; these stem cells give rise to all blood cell types. In the same cluster, the term “neural stem cells” (11 occurrences) are visible, which are located in the brain, these stem cells can differentiate into neurons, astrocytes, and oligodendrocytes [43]. In the pink cluster, the “dental pulp stem cells” (38 occurrences) appear; these stem cells have the potential to differentiate into various cell types, including odontoblasts, osteoblasts, and neural cells [44].
Detected diseases and the link with stem cells by text mining
Network visualization not only shows the identified stem cells in the titles and abstracts of articles but also the diseases they are associated with. We analyzed terms and grouped them based on different diseases and conditions treated with stem cell therapies and links to different types of stem cells.
The largest group, “Bone, cartilage, and tendon disorders” (Fig. 4), is represented by terms from clusters that are colored blue, pink, and brown. The terms within this group include “knee osteoarthritis,” “chondrogenesis,” “cartilage regeneration,” “bone formation,” “cartilage repair,” “knee injury,” “tendon injury,” “bone fracture,” “bone healing,” “cartilage tissue engineering,” “spinal cord injury,” “knee joint,” “low back pain,” “bone disease,” “osteoarthritic knee,” “chronic low back pain,” “knee pain,” “degenerative disc disease,” “knee replacement,” “intervertebral disc degeneration.” This group also encompasses “musculoskeletal disorder,” “musculoskeletal injury,” and “musculoskeletal condition.” The keywords related to “Bone, cartilage, and tendon disorders” are primarily associated with MSCs and ADSC and dental pulp stem cells. Additionally, HSCs are associated with bone marrow transplantation with terms such as “bone marrow stem cells” and “autologous bone marrow stem cells.”
The group labelled “Cancer” contains the following terms from the orange cluster: “cancer,” “cancer treatment,” “carcinogenesis,” “teratoma formation,” and “carcinogenesis.” In addition, other keywords such as “oncology” and “cancer therapy” are associated with the blue cluster, while “breast cancer cell” is related to the red cluster. MSCs and PSCs, which include both iPSCs and ESCs, are frequently mentioned in association with cancer, cancer treatment, oncology, and cancer therapy.
The group “Cardiovascular diseases” encompasses terms such as “heart failure,” “coronary artery disease,” “critical limb ischemia,” “cardiovascular disease,” “ischemic disease,” “heart disease,” “acute myocardial infarction,” “cardiac disease,” “chronic heart failure,” and “vascular disease.” It shows homogeneity and focus in the red cluster. Cardiovascular diseases linked with cardiac stem cells and MSCs and HSCs. Endothelial cells, also linked with vascular regeneration, are associated with cardiovascular disease (15 cases) and ischemic conditions.
The group “Wound healing and skin regeneration” is based on the following terms from the yellow cluster: “burn,” “chronic wound,” “skin,” “skin regeneration,” “skin wound,” “tissue damage,” “wound,” and “wound healing.” In addition to these terms, the topic is supported by other keywords from different clusters, such as “tissue healing,” “tissue injury,” and “tissue remodeling.” ADSCs and MSCs fibroblasts are being investigated for their role in wound healing (34 cases), indicating their widespread use in tissue regeneration.
The group labelled “Diabetes” is associated with terms from the purple cluster such as “diabete,” “diabetic foot ulcer,” “clot,” and “obesity.” Adult and endothelial stem cells demonstrate the link in treating metabolic disorders, e.g., diabetes and obesity.
The “Organ regeneration” group includes terms associated with kidney, liver and lung diseases. In the light blue cluster, the following terms could be observed: “end stage liver disease,” “liver cirrhosis,” “liver disease,” “damaged organ,” and “fetal liver.” In the red cluster, the terms “acute kidney injury,” “chronic kidney disease,” and “kidney disease” are observed. The terms “chronic lung disease” and “lung disease” were observed in the brown cluster.
The group “Neurodegenerative diseases” includes the following terms from the green cluster: “Alzheimer’s,” “neurodegenerative disease,” “neurogenesis,” “neurological disorder,” “Parkinson’s,” “spinal cord injury,” and “neurological disorder.” PSCs (ESCs, iPSCs) and neural stem cells are closely associated with neurodegenerative diseases (19 occurrences) such as Alzheimer’s and Parkinson’s.
The small group “Autoimmune diseases” consists of terms from the green cluster—“autoimmune disease” and “sclerosis,” from the light green cluster “t cell”, and from the brown cluster “chronic inflammation.”
The last subgroup was not indicated in Fig. 4 and consisted of aging-associated terms such as “aging,” “degenerative disease,” and “degenerative disorder.” We also didn’t show subgroups related to diseases and conditions of organs such as “eye,” “tooth,” “gastrointestinal disorder,” “hair follicle,” and “embryogenesis,” which have fewer weights of occurrences.
To summaries, based on the weight of occurrences, the most frequently treated disease “bone” and “cartilage disorders.” The largest group identified involved terms related to “musculoskeletal issues,” with “MSCs” being prominently linked to treatments. This is followed by “cancer,” keywords associated with cancer therapy frequently co-occurred with MSCs and PSCs. “Cardiovascular disease” terms related to heart conditions showed a strong association with cardiac stem cells and MSCs. “Wound healing,” the role of ADSCs and MSCs in skin regeneration and wound healing was significantly noted. “Metabolic disorders,” adult and endothelial stem cells were linked to diabetes and obesity treatments. “Organ regeneration” terms related to kidney, liver, and lung diseases were identified, indicating potential for organ regeneration therapies. “Neurodegenerative diseases” PSCs and neural stem cells were highlighted in relation to conditions like Alzheimer’s and Parkinson’s.
Research of the materials, methods and technologies employed in the realm of stem cells for regenerative medicine
Our next focus was analyzing MMTs to identify central, influential MMTs keywords, emerging topics, high impact and ongoing research. We conducted the co-occurrence analysis of the sample dataset (1,274 articles) with a threshold in the minimum number of occurrences of three. This enabled us to expand the number of keywords that met the threshold criteria (n= 1,867). We selected 94 keywords related to MMTs. In the first step, we manually reviewed keywords for their relevance to regenerative medicine. To maintain a specialized focus, we excluded general terms and techniques that are commonly used across various laboratory contexts, such as flow cytometry and Western blotting. In the second step, we grouped the keywords into categories: MMTs. In the third step, we further distributed the keywords into subgroups and evaluated them based on key attributes, including the frequency of occurrences, total link strength, and average citation scores, as well as emerging research areas indicated by the average year of publication. The structured selection and categorization process enabled us to highlight MMTs that are central, impactful, and increasingly relevant in the field.
Further, we fragmented the keywords into subgroups, e.g., imaging, cell culturing, molecular biology, and analyses (Fig. 5).
Emerging topics, emerging research areas
We used the average publication year scores to select emerging research areas in each group. “Biopolymers,” “hydrogel scaffolds,” and “nanotechnology” (Fig. 5B, materials), “deep learning,” “machine learning,” “three-dimensional (3D) bioprinting” (Fig. 5A, technology), “gene set enrichment analysis,” “Kyoto Encyclopedia of Genes and Genomes (KEGG)” (Fig. 5E, methods, analysis) “3D imaging” (Fig. 5B, methods, imaging), “3D culture,” “3D cell culture,” and “xeno-free culture” (Fig. 5F, methods, cell culturing), and “gene targeting” (Fig. 5C, methods) are recent and growing areas of interest, reflecting evolving research trends.
High-impact topics
“3D printers” dominate in terms of connectivity, frequency, and citations, indicating a central and highly impactful topic in the CAoSCiRM field. The recent publication year suggests it remains a focus of current research, while “bioprinting” also shows high impact with substantial citations, reflecting its importance and influence. Although “microRNA 145” is less connected, its high average citations highlight its substantial impact (Fig. 5A, technology). “Meta-analysis” is highly connected and impactful, with the highest average citations, underscoring its role in synthesizing research findings. “Proteomics” shows high connectivity and significant citations, reflecting its importance in studying protein expressions and functions (Fig. 5E, materials, analyses). “Vectors,” although not the most recent or most connected topic, have the highest average citations. This indicates that research involving vectors, perhaps more specialized, is highly impactful and foundational.
Highly connected and frequent keywords
“Electroporation” (Fig. 5A, technology) is highly connected and frequently mentioned, indicating its significance in the research community. Although it has moderate citations, its connectivity highlights its importance. “Topography” is another central topic with strong connectivity and a reasonable citation rate, indicating its continued relevance. “Diagnostic imaging” (Fig. 5D, methods, imaging) is highly connected and frequently mentioned, indicating its central role in medical imaging research. Its high citation rate suggests significant impact and relevance. “Tissue scaffolds,” “hydrogels,” and “scaffolds” (Fig. 5B, materials) are highly connected, frequently researched, and significantly impactful keywords in the field of materials science. Their strong connectivity, high occurrences, and substantial citation rates collectively highlight their central and influential role in advancing research and innovation. “Gene silencing” (Fig. 5C, methods, molecular biology) is the most interconnected keyword, suggesting it plays a central role in the research network. Its high occurrence frequency indicates it is a frequently researched topic, making it a cornerstone of current research in the field. “Micro-computed tomography” shows significant connectivity and impact, as evidenced by its high average citations. Its recent publication year indicates ongoing research interest. “RNA sequencing” (Fig. 5E, methods, analysis) stands out with the highest total link strength, indicating a central role in data analysis and genetic research. Despite its high connectivity, it has a moderate citation rate, suggesting ongoing interest and usage. “Data analysis software” shows significant connectivity and impact, as evidenced by its high average citations. This indicates its crucial role in supporting various data analysis methods. “Single cell RNA sequencing” is another highly connected and recent topic with significant research interest and impact. “Monolayer culture,” “cell encapsulation,” and “co-culture” are highly cited, indicating their considerable influence and importance in research (Fig. 5F, methods, cell culturing).
DISCUSSION AND CONCLUSIONS
Top most productive and most cited journals
The analysis of publication trends in the CAoSCiRM field reveals the rapidly growing field with significant progress made in the past decade. This is evident from the increasing number of publications observed between 2020 and 2022. The analysis showed that while a large number of journals (68%) published only one article on this topic (from 2010 to 2024), the leading group of 19 journals each published more than 10 articles. This suggests that some journals have become leading platforms for disseminating research on the clinical use of stem cell technologies. Three key journals, International Journal of Molecular Sciences, Stem Cell Research and Therapy, and Stem Cell Reviews and Reports, stand out for their prolific contributions during this period. These journals, along with others identified as the most cited, represent the leading sources of high-quality research in the field. The high average citation scores for these journals further emphasize their influence.
Most cited papers
Analyzing the most cited papers provides valuable insights into the current advancements and areas of intense focus within the field. The prominence of research on novel stem cell reprogramming and differentiation methods (papers #1, #4, and #6) highlights their potential to revolutionize stem cell therapies. Additionally, the focus on innovative technologies and biomaterials for cell therapy and tissue engineering (papers #2, #3, #5, #7, and #8) underscores the importance of developing new tools for successful clinical translation. Furthermore, papers on MSCs and PRP (papers #8 and #10) reflect the ongoing investigation into promising cell sources and therapeutic approaches for regeneration. These findings highlight the significant strides made in stem cell applications for regenerative medicine. The emphasis on innovative methods with a clear path to clinical application bodes well for the future of this field. Researchers can leverage the insights gained from these highly cited publications to propel further advancements and bring stem cell-based therapies to patients.
Intellectual structure of the CAoSCiRM field
The intellectual structure analysis of the field demonstrated the exploration of different types of MMTs used for regenerative and repair therapies. The emphasis lies on treating various conditions and diseases by modulating stem cell functions. Based on the keywords from intellectual structure, we identified some challenges in clinical trials for regenerative medicine and some potential ideas for addressing the critical challenges for trends for future studies.
Biomaterial and tissue engineering challenges. The “tissue engineering” cluster highlights the focus on developing “biomaterials,” “scaffolds,” “hydrogels,” and other biomaterial-based approaches for regenerative applications, particularly in bone and cartilage repair. This might suggest that the challenge is engineering suitable biomaterial platforms that can effectively support and guide tissue regeneration in a clinical setting [45]. Therefore, a possible future direction for novel actual direction for studies would be developing and exploring biomimetic and smart biomaterials, integrating “3D bioprinting” and bioactive molecules to create patient-specific tissue constructs that dynamically respond to the body’s needs for improved regeneration [46-50].
The combination of the following clusters might indicate another big challenge which is related to stem cell sources, differentiation (“self-renewal,” “differentiation,” “multipotency,” “reprogramming,’’ “pluripotencym,” and “apoptosis”), manufacturing and scalability (“growth factors” and “good manufacturing practice”) and immunomodulatory properties. Optimizing the isolation, proliferation, and directed differentiation of various stem cell types (e.g., iPSCs, ESCs, MSCs) to ensure their safety and efficacy for clinical applications. This should be followed by establishing reliable, reproducible, and scalable processes for the large-scale production and quality control of stem cell-based products [51,52]. Therefore, another current research trend in stem cell-based therapies might focus on overcoming changes related to scalable manufacturing, quality control, and immunomodulatory properties. This includes developing standardized protocols for the isolation, expansion and directed differentiation of various stem cell types to ensure consistency and reproducibility. Exploring gene editing tools (clustered regularly interspaced palindromic repeats [CRISPR]-Cas9, “microRNA”) to change genetic defects and enhance the immunomodulatory and paracrine effects of stem cells to improve the therapeutic potential of stem cells. Establishing robust manufacturing processes for large-scale production, including automated cell culture systems and closed-system bioreactors [53-55]. Artificial intelligence (AI) could help scientists understand how stem cell therapies can be combined with gene therapy, immunotherapy, or biomaterials for synergistic effects.
An exciting emerging area of stem cell research is the therapeutic potential of exosomes [33]. These tiny membrane vesicles secreted by stem cells carry important biological molecules. Interestingly, research suggests that exosomes can mimic some of the therapeutic effects of stem cells themselves, offering potential benefits such as increased safety, improved delivery, large-scale production [33].
Diseases and cells
Our text-mining analysis that reveals stem cell applications for diseases and injuries and clinical applications provides insights into the current trends and priorities in this rapidly evolving field. Consistent with our results, researchers highlight the significant attention and research efforts directed towards MSCs [56], particularly those derived from bone marrow and adipose tissue. The versatility, accessibility, and therapeutic potential of MSCs make them a prime target for regenerative medicine applications. We also emphasized the prominent role PSCs, including ESCs and iPSCs, in regenerative medicine research. This aligns with the broader literature, which recognizes the unique capabilities of these stem cell types and their promise for future clinical applications.
Beyond the focus on MSCs and PSCs, our study also acknowledges the importance of other stem cell sources, such as “fibroblast,” “umbilical cord-derived stem cells,” “hematopoietic stem cells,” “neural stem cells,” “dental pulp stem cells,” “endothelial cells,” “epithelial cells,” and “chondrogenic progenitor cells.”
Our results pointed out that bone marrow and adipose tissue-derived MSCs currently dominate stem cells in the field, so there might be a need to expand the field of stem cell sources and applications. This expansion is driven by the need to overcome limitations associated with their availability, multipotency, and immunomodulatory properties. Promising alternatives such as fibroblasts, menstrual blood-derived stem cells, and other types of alternatives are gaining momentum due to their availability and potential for large-scale distribution, paving the way for more cost-effective and easily accessible stem cell therapies [57,58]. Our analysis did not pick up menstrual blood-derived stem cells. The critical disease and condition targets identified in our study include musculoskeletal disorders, cancer, cardiovascular diseases, wound healing, diabetes, organ regeneration, neurodegenerative diseases, and autoimmune conditions. This alignment underscores the translational efforts in the field to address unmet medical needs. Based on these results, we can highlight another potential use for stem cells: using them to produce red blood cells (RBCs) [59]. RBC transfusion is a common medical intervention, but there are limitations due to the limited donor blood supply. In vitro, the expansion of RBCs from stem cells offers a promising alternative to address this problem [59].
Research of the materials, methods and technologies employed in the realm of stem cells for regenerative medicine
The analysis of MMTs revealed both established and emerging trends, giving insights into the CAoSCiRM field’s landscape. By analyzing 1,274 articles and increasing the number of detected keywords to 1,867, we identified about 94 MMT-related keywords categorized into materials, technologies, and methods (analysis, imaging, cell culture, molecular biology).
Emerging research areas
In the materials group, “biopolymers,” “hydrogel scaffolds,” and “nanotechnology” are emerging areas. The moderate citation rates for “biopolymers” suggest the early stages of research, while the high citation rates for “hydrogel scaffolds” underscore their significant early impact. This focus on innovative materials indicates a shift towards increasing stem cell structural and functional integration in regenerative medicine. Incorporating nanotechnology and innovative materials science with traditional biomaterials drives the CAoSCiRM field forward, promising new and more effective treatments.
The advent of “deep learning” and “machine learning” in the technology group shows a growing intersection between computational methods and regenerative medicine. The emergence of “3D bioprinting” signifies the development of sophisticated fabrication technologies, although its moderate citation rates suggest it is still maturing. These advancements reflect the increasing importance of computational and fabrication technology in driving the CAoSCiRM field forward.
Despite their low citation rates, methods in the analysis subgroup, “gene set enrichment analysis” and “KEGG,” highlight new methodologies for understanding complex genetic interactions. The imaging subgroup revealed “3D imaging” as a nascent but promising area with the potential to revolutionize cell visualization and analysis. The development of these methods underscores the importance of advancing analytical and imaging technology in understanding and manipulating stem cells.
High-impact topics
Several topics stood out due to their high impact, as evidenced by citation rates. The technology group showed that “3D printers” and “bioprinting” are highly impactful, indicating significant advancements and widespread research interest. This underscores their role in advancing tissue engineering and regenerative medicine. With high average citations, “microRNA 145” signifies its importance in the regulatory mechanisms of stem cells. “Meta-analysis” and “proteomics” methods are crucial for synthesizing research findings and understanding protein expressions. Their high citation rates reflect their foundational role in advancing the field.
Despite being a specialized topic, “vectors” showed the highest average citations, highlighting their foundational importance in genetic manipulation technology. High-impact issues such as 3D printers and bioprinting [31,60] highlight significant advancements, while emerging topics like biopolymers and machine learning suggest future research directions.
Highly connected and frequent keywords
Keywords such as “3D printers,” “electroporation,” “topography,” and various scaffold-related terms (e.g., “tissue scaffolds” and “hydrogels”) emerged as highly connected and frequently researched. Their centrality and citation rates highlight their influential role in the research network. “3D printers” dominate in terms of connectivity, frequency, and citations, and this keyword underscores the pivotal role of 3D printing technology in current regenerative medicine research. “Electroporation” and “topography” have robust connectivity, indicating their significant role in facilitating gene delivery and understanding cell-material interactions. “Gene silencing” is the most interconnected keyword. It underscores its critical role in molecular biology and therapeutic strategies. Keywords “diagnostic imaging” and “RNA sequencing” indicate crucial imaging and genetic analysis methodologies, with high citation rates reflecting their importance. The frequent and highly connected keywords underscore the foundational elements driving the field forward. This analysis provides a valuable roadmap for researchers, highlighting critical areas for future investigation and potential technological advancements in regenerative medicine.
The field has evolved from foundational technology to leveraging multidisciplinary expertise to drive innovation. Integrating expertise across disciplines will be paramount as the field continues to advance. Collaboration between stem cell biologists, geneticists, engineers, and clinicians will be crucial for translating promising laboratory findings into practical clinical applications [31]. This collaborative approach holds the key to unlocking the full potential of regenerative medicine in treating a broad spectrum of diseases and injuries.
Challenges in clinical applications
Despite advancements in stem cell technologies, some challenges remain in translating these innovative technologies into clinical practice, including issues related to scalability, consistency [61] of outcomes across different patient population, and regulatory hurdles [62] that must be navigated to ensure safety and efficacy [63]. For instance, the inter-donor variability [64] observed in MSCs poses a significant change for clinical applications, necessitating the development of standardized protocols for cell processing and characterization [65,66] to enhance reproducibility and predictability of treatment outcomes. Additionally, the regulatory frameworks for stem cell therapies are still evolving, which can impede the shift transition from laboratory findings to clinical applications. Establishing clear guidelines for the evaluation of new technologies is crucial for fostering innovation while ensuring patient safety [62,67,68]. Long term efficacy and safety of stem cell-based therapies remain under-explored, underscoring the need for comprehensive clinical trials that not only assess immediate therapeutic effects but also monitor potential adverse outcomes over extended periods [63,66,69].
In conclusion, stem cell and regenerative medicine research has transformed over the past two decades. The field has progressed from establishing foundational technology to integrating cutting-edge technology and multidisciplinary expertise. As research advances, translating laboratory findings into practical clinical applications will be crucial for realizing the full potential of regenerative medicine.
While studies offer more specialized, in-depth knowledge within specific subfields of regenerative medicine, our study covers a more recent period. It provides a broader, panoramic view of the research landscape to help contextualize and inform the more focused research efforts. It can also help understand the current focus areas and potentially guide future research and clinical directions. Therefore, our findings can provide valuable insights for researchers, clinicians, and policymakers in regenerative medicine.
Overall, the similarities between our bibliometric analysis and the other papers strengthen the validity and significance of our findings. The collective insights can inform future research directions, guide clinical translation efforts, and contribute to the ongoing advancement of regenerative medicine as a promising and transformative field of medical science.
FUTURE RESEARCH TOPICS IN STEM CELL THERAPY
The findings from sections 4, 5, and 6 highlighted gaps in the current knowledge, enabling us to propose future research directions that could advance the field of CAoSCiRM. Below are some examples of the most promising research areas.
Innovations
• Developing AI tools to tailor stem cell therapies to individual patients based on their unique needs and genetic makeup is revolutionary.
• Deep learning data analysis can help us understand how stem cell therapies can be combined with gene therapy, immunotherapy, or biomaterials for synergistic effects.
• Optimizing and improving reprogramming efficiency and ensuring genomic stability.
• The use of 3D bioprinting and additive manufacturing technologists to create customized, patient-specific tissue constructs.
• Develop biomimetic and smart biomaterials that dynamically respond to the local microenvironment and guide tissue regeneration.
• Exploring how nanotechnology can enhance stem cell delivery and effectiveness holds significant promise.
Improving efficiency
• Investigating readily available and alternative and scalable cell types like fibroblasts and menstrual blood-derived stem cells can lead to more affordable and accessible treatments.
• Generating RBCs from stem cells offers a promising solution to overcome limitations in blood transfusions.
• Researching the therapeutic potential of exosomes (as a tool), tiny membrane vesicles derived from stem cells, opens avenues for safer and more manageable therapies.
• Investigating the use of stem cells to treat rare and orphan diseases with limited treatment options holds immense promise.
• Studying how bioelectrical signals influence tissue repair can lead to innovative interventions that promote the body’s natural healing abilities.
• Incorporate bioactive molecules, such as growth factors and cell-adhesive peptides, into biomaterial scaffolds to enhance cell attachment, proliferation, and differentiation.
• Development of standardized protocols for the isolation, expansion, and directed differentiation of various stem cell types to ensure consistency and reproducibility.
• Expend the use of gene editing tools, such as CRISPR-Cas9 and microRNA, to change genetic defects and enhance the therapeutic potential of stem cells.
• Researching the potential of stem cell therapies to slow down age-related degeneration and promote healthy aging is a significant avenue.
Ethics
• Investigating the challenges and ethical considerations surrounding stem cell therapies would provide a well-rounded perspective on the field’s future directions. Evaluating stem cell therapies’ lasting effects and potential risks across various applications is crucial.
The successful integration of MMTs into clinical settings will require robust collaboration among researchers, clinicians, and regulatory bodies to address these challenges collectively and develop practical solutions that facilitate the translation of laboratory discoveries into effective therapies [62,70].
LIMITATIONS
The study’s reliance on Scopus and WOS databases, albeit comprehensive, may limit the breadth of the literature surveyed. While efforts were made to include all relevant studies, some important publications might have been omitted if they were not indexed in the chosen databases. Certain prominent journals in the field of stem cell research may not be ranking among the top 10 in terms of productivity or citation frequency. This result may be attributed to the specialized nature of the CAoSCiRM research field, which can limit broader academic engagement and visibility. The analysis spans from 2010 to 2024, providing a focused but finite examination window. Future researchers may offer a similar study in 5 to 7 years to compare our results and progress. The chosen keywords, while comprehensive, might need to include relevant studies. Expanding the keyword set or using different search strategies could improve coverage. Some important document types may have been missed by focusing on publications in English. By recognizing these limitations, we emphasize the need for continuous updates and expansions of bibliometric analyses to incorporate new data, methodologies, and perspectives. Such iterative evaluations are essential to accurately reflect the ongoing advancements and challenges in the dynamic CAoSCiRM research field.
CONTRIBUTIONS
1. This analysis identified journals that significantly contributed to the field’s growth, highlighting publications fostering the development of clinical applications.
2. We revealed the most cited journals and papers, providing scientists with a roadmap to the most influential research in the CAoSCiRM field. This helps scientists stay informed about the most promising areas of study for translating stem cell therapies into clinical practice.
3. The analysis of the intellectual structure of this field shows how research has concentrated, from a cluster describing materials from various sources to cell culture and tissue engineering to stem cell applications, therapies and therapeutic potential to identify immune system disorders, safety and efficacy.
4. By revealing the most studied stem cell types (mesenchymal and pluripotent), our research guides scientists in their choice of cell types for specific therapeutic applications. In addition, findings on the most frequently studied conditions (osteoarthritis, cancer, cardiovascular diseases) inform scientists about the areas with the most significant potential impact (understanding treatment targets).
5. We demonstrated the dynamics of MMTs over the period.
6. By uncovering areas with limited research (e.g., other stem cell types and different diseases), our work highlights opportunities for further investigation.
7. Our analysis provides a quantitative measure (benchmarking progress) of the field’s growth and evolution. This data helps assess progress towards clinical translation and secure funding for future research.
Notes
No potential conflict of interest relevant to this article was reported.
AUTHOR CONTRIBUTIONS
Conception or design: MKN.
Acquisition, analysis, or interpretation of data: MKN, GD.
Drafting the work or revising: MKN, GD.
Final approval of the manuscript: MKN, GD.