2.1 Search strategy

A systematic literature search was performed in the Web of Science Core Collection (WoS-CC) using the advanced search module. The query " TS=(hydrogel OR hydrogels) AND (TS=(heal OR healing) OR TS=(regenerate OR regeneration)) AND TS=(Cartilage)" was executed to identify relevant publications, with the publication timeframe restricted to January 1, 2005, through December 31, 2024.

2.2 Inclusion and exclusion criteria

2.3 Analysis of the data

The exported documents are then transferred to visualization tools such as Citespace 6.4.1 and VOSviewer 1.6.20 for analyzing visual representations.This method allows for the management of a vast amount of information and multi - faceted analysis. It also enables the generation of visual analysis diagrams to enhance the comprehension of research hotspots and development trends. For related data analysis and chart production, Microsoft Office Excel 2021 is employed. All citation data extracted from WoS exclude self-citations to more accurately reflect the external impact of the publications.

The initial retrieval yielded 3035 articles, and following the screening process, 2339 articles were ultimately included. The full records and references were selected and exported as the literature (Fig. 1).

Close

Fig. 1 PRISMA flow diagram illustrating the systematic literature search and screening process for publications on hydrogel-assisted cartilage repair (2005–2024).

Export to PPT

3.1 Development Trajectory of scholarly output over the past two decades

Within a defined time span, the quantity of published papers and their citation counts can serve as an effective indicator of the research progress and development trend in a particular field. Fig. 2 depicts the extent of publications and citations within hydrogel-assisted cartilage repair research over the past two decades. Between 2005 and 2024, the volume of publications has, in general, experienced a notable upward trend. In 2005, the number of publications was merely 8. However, by 2024, this figure had escalated to 279. Notably, after 2015, the growth rate of publications witnessed a remarkable surge. In particular, from 2019 to 2024, the number of publications experienced a significant increase, climbing from 232 to 279. The citation count has been rising steadily as well, despite a somewhat slower pace compared to the growth in publication volume.In 2005, the number of citations was 8, but it increased to 16,399 in 2024. The growth rate of citations also accelerated significantly after 2015, from 139 citations in 2015 to 16,399 citations in 2024. A connection exists between publication count and citation frequency. When publication output goes up, citation numbers also rise, suggesting that a greater number of publications might result in more citations. This correlation becomes more obvious after 2015, possibly because more research is published and cited, forming a positive feedback loop. Overall, from 2005 to 2024, the quantity of publications and citations has demonstrated a marked upward trend.

Close

Fig. 2 Development trajectory of published works in the last two decades.

Export to PPT

3.2 The geographical spread of scholarly works on a country - by - country basis

Within this field of study, scholarly contributions have come from 62 countries/regions. Table 1 lists the 10 nations with the highest number of publications on cartilage repair using hydrogels. China ranks first with 955 papers, representing 40.83 % of the global publication output.The United States (494 papers, 21.12 %) and South Korea (166 papers, 7.10 %) followed closely.

Fig. 3a shows three key indicators of research performance in a certain field: H-index, average citation count, and total citation count. Within this domain, China and the United States are at the forefront of research accomplishments, surpassing other countries/regions in terms of research quality (H-index), research influence (average citation count), and overall influence (total citation count) (Table 2).Although the United Kingdom does not have an advantage in H-index, its average citation count is the highest, indicating high research influence. South Korea, Germany, and Japan also perform well in these indicators, showing that these countries/regions have certain strength and influence in this field of research. Fig. 3b depicts the yearly variation trend of the quantity of publications in a certain field from 2005 to 2024 across different nations and regions. The stacked bar chart is employed to show the publication counts for each country across various years. Between 2005 and 2024, the volume of publications from all countries/regions and regions has been on the rise. The upward trend has become more pronounced after 2015, suggesting a marked expansion of research activities in this field in recent years. In 2015, there was a marked growth in the number of publications from Mainland China, which then became a key player in this research area. By 2024, the number of publications in China had climbed to the highest level.The number of publications of USA remained stable during the entire period, although the growth rate may not be as fast as China, the total volume is still considerable. The growth trend of SOUTH KOREA mirrors that of the United States, with the volume of publications rising annually, demonstrating ongoing research investment.Japan's publication output has increased in a relatively stable manner, although it may not be as large as China and the United States in total, it still maintains stable research output. The number of publications of GERMANY, IRAN, ITALY, NETHERLANDS, ENGLAND, and INDIA also shows a growth trend, but the growth amplitude and total volume are relatively small.

Close

Fig. 3 National/Regional Contributions and Research Impact.(a) Bibliometric indicators (overall citations, average citations per paper, and Hirsch index) for the top ten productive countries/regions (Data source: Web of Science).(b) Annual publication trends of the top ten productive countries/regions from 2005 to 2024 (Data source: Web of Science).

Export to PPT

3.3 Analysis of international collaboration

Among the 62 countries/regions, 40 showed collaborative relationships based upon the inclusion criteria of over 5 papers (Fig. 4a). The node size represents each country's publication volume, with the color and thickness of the lines indicating the strength of cooperation between countries/regions. Among them, China and the USA are the two largest nodes in the figure, indicating that these two countries/regions have the highest research output and the most extensive cooperative relationships in this field. The nodes of South Korea, Germany, India, etc. are also relatively large, showing their importance in this field. The relatively thick link between China and the USA implies a tight collaborative bond between these two nations. Other countries/regions such as Japan, the UK, France, etc. also show connections with major countries/regions, indicating their varying degrees of cooperative relationships with these countries/regions. Several obvious cooperative clusters can be seen in the figure, such as the close cooperation between China and Canda, Iran, Singapore, etc. in Asian countries/regions. European countries/regions such as Germany, France, and the UK also form a cooperation network, showing a regional tendency of cooperation. There are also cooperative relationships between the United States and Japan, South Korea, etc. in the Americas, as well as some European countries/regions. It is evident that international collaboration is actively pursued, and this mutually beneficial model accelerates the progress of the hydrogel - mediated cartilage repair research area. Fig. 4b can analyze the evolution of cooperation by observing the color of the connections. The connection between China and Iran was brighter in 2020 and 2021, which may indicate that these countries/regions have more frequent cooperation in recent years. Fig. 4c displays the layout of the international/regional cooperative network on the global map.

Close

Fig. 4 International Collaboration Networks in Hydrogel for Cartilage Repair Research.(a) Cooperative relationships among countries/regions with more than 5 publications (Data source: VOSviewer).(b) Temporal evolution of international collaborations (Data source: VOSviewer).(c) Geographical distribution of publications across countries/regions (Data source: VOSviewer).

Export to PPT

Close

Fig. 5 Author Collaboration and Co-citation Networks.(a) Collaborative network among authors in hydrogel for cartilage repair research (Data source: VOSviewer).(b) Co-citation network of authors (Data source: VOSviewer).

Export to PPT

3.4 Author analysis

An analysis of 11,270 authors' data shows Table 3 lists the top 10 authors by number of papers. Rui L. Reis from Universidade do Minho tops the list, with 55 papers, an H - index of 32, and 57.04 average citations per paper.This indicates a high level of productivity and significant impact in the field. Coming in next is Kelly, Daniel J. from Trinity College Dublin, who has 30 publications, an H-index of 21, and an average of 55.63 citations per paper.Other notable authors include Fan, Yujiang from Sichuan University, Wang, Dong-An from Nanyang Technological University, and Zhou, Guangdong from Shanghai Jiao Tong University, all of whom have made substantial contributions to the field. The table highlights the strong research performance of these authors, as evidenced by their high publication counts and citation metrics.The network visualizations of author collaborations and co-citation patterns generated by VOSviewer are presented in Fig. 5a and 5b.The network is densely interconnected, indicating a high level of collaboration among researchers in the field. Key authors such as Rui L. Reis, Kelly, Daniel J., and Zhou, Guangdong are central nodes in the network, showing their pivotal roles in connecting various research groups. The visualization also reveals clusters of authors who frequently collaborate, such as the group around Zhang, Xingdong and Yin, Jingbo, which suggests strong thematic or regional collaborations. The network analysis highlights the collaborative nature of the research community, with many authors working together across institutions and countries/regions.The third image provides a more detailed co-authorship network, showing the connections between authors and their collaborators. The network uses color - coding to signify distinct clusters. Each color corresponds to a group of authors who have worked together extensively.For example, the green cluster includes authors such as Holland, T.A. and Elisseeff, J., while the red cluster includes Liu, Y. and Zhang, Y. The visualization shows that while there are core clusters of collaborators, there are also connections between different clusters, indicating a dynamic and interconnected research community. This analysis helps to identify key collaborators and research groups in the field, providing insights into the structure of the academic network.

3.5 Examination of research - publishing entities

Based upon the analysis of publishing - institution - related data, Fig. 6a spotlights the 10 institutions with the highest publication counts out of 1488. The bar chart in Fig. 6a, generated by VOSviewer, illustrates the leading institutions regarding publication count, H-index, and total citations. According to the chart, Shanghai Jiao Tong University is in the leading position with 137 publications and 5165 total citations. Coming in second is the Chinese Academy of Sciences, which has 109 publications and 4426 citations. Sichuan University follows closely behind, with 85 publications and 3937 citations.The H-index values also indicate strong research performance, with Shanghai Jiao Tong University (H-index of 43) and the Chinese Academy of Sciences (H-index of 40) at the forefront. This suggests that these institutions are not only prolific in publishing but also have a significant impact in the field. Fig. 6b from VOSviewer presents a network visualization of institutional collaborations. The network is densely connected, indicating a high level of collaboration among various institutions. Major institutions like Shanghai Jiao Tong University, the Chinese Academy of Sciences, and Zhejiang University are core nodes, highlighting their crucial roles in the research network. The visual representation also exhibits groups of institutions that frequently work together, such as the cluster consisting of Shanghai Jiao Tong University, the Chinese Academy of Sciences, and Wuhan University, indicating solid regional and thematic cooperation. Fig. 6c provides a density visualization of the same institutional network. The density map emphasizes the aggregation of institutions in particular zones, with the previously mentioned group, including Shanghai Jiao Tong University and the Chinese Academy of Sciences, constituting a concentrated cluster.This indicates a high level of activity and collaboration in these areas. The map also shows that while there are core clusters, there are connections to other regions, suggesting a global reach in the research collaborations. Fig. 6d from CiteSpace presents a temporal view of institutional collaborations, showing the evolution of research networks over time. The timeline spans from 2005 to 2024, with nodes representing institutions and links indicating collaborations. The visualization reveals that early collaborations were primarily among a few key institutions, but over time, the network has expanded to include more institutions, particularly from China. The appearance of fresh collaborations and the reinforcement of current ones highlight the vibrant character of the research area. Institutions such as Shanghai Jiao Tong University and the Chinese Academy of Sciences have consistently held central positions over the years, indicating their lasting impact and guidance in the field.

Close

Fig. 6 Institutional Productivity and Collaboration Patterns.(a) Publication counts and total citations of the top 10 prolific institutions (Data source: Web of Science).(b) Collaborative network among institutions (Data source: VOSviewer).(c) Density visualization of institutional collaboration (Data source: VOSviewer).(d) Temporal evolution of institutional collaborations from 2005 to 2024 (Data source: CiteSpace).

Export to PPT

3.6 Literature sources and journal analysis

In this research field, 405 journals have published a total of 2339 articles. Among them, "ACTA BIOMATERIALIA" ranked first with 105 papers (H-index 52, average citation count 79.79 times), followed by "BIOMATERIALS" (83 papers, H-index 57, average citation count 112.92 times) and "INTERNATIONAL JOURNAL OF BIOLOGICAL" (77 papers, average H-index 26, average citation count 26.97 times). Fig. 7a, created by VOSviewer, displays a network visualization of journals within this research domain.The network map reveals a dense and interconnected structure, indicating a high level of collaboration and citation exchange among various journals. Key journals such as "biomaterials," "acta biomater," and "j biomed mater res" are central nodes in the network, highlighting their significant influence and widespread citation in the field. The dimensions of the nodes are determined by the number of publications or citations, where a larger size indicates a more significant impact.The color coding reflects different clusters of journals, suggesting thematic or regional groupings. For example, journals related to biomaterials and tissue engineering form a distinct cluster, while those focused on orthopedics and cartilage repair form another. This visual representation makes it possible to determine the core journals that propel research within the field and to clarify the relationships between distinct journal clusters.Fig. 7b generated by CiteSpace provides a temporal view of journal collaborations and citation patterns from 2005 to 2024. The timeline at the bottom shows the evolution of the journal network over the years. The visualization reveals that early research was primarily published in a few key journals, but over time, the network has expanded to include a broader range of publications. Notably, journals like "biomaterials" and "acta biomater" have maintained their central positions throughout the years, indicating their sustained influence and leadership in the field. The debut of new journals and the fortification of ties between existing ones point to a vibrant and expanding research community. The color coding in the network corresponds to different time periods, with earlier journals shown in blue and more recent ones in red. This temporal analysis helps to understand the historical development and future trends in journal publications and collaborations.

Close

Fig. 7 Journal Co-citation and Collaboration Patterns.(a) Network of journals co-cited more than 50 times (Data source: VOSviewer).(b) Temporal evolution of journal citation patterns from 2005 to 2024 (Data source: CiteSpace).

Export to PPT

Close

Fig. 8 Dual Mapping Overlay of Journals in Hydrogel for Cartilage Repair Research(Data source: CiteSpace).

Export to PPT

The dual-map overlay visualization (Fig. 1) integrates two layers of information to provide a multifaceted view of journal interactions. The base layer represents the citation network among journals, while the overlay highlights specific thematic clusters and their interconnections. The citation network is characterized by dense connections, indicating a high level of citation exchange among journals in the field.Central journals such as "Biomaterials" and "Acta Biomaterialia" are prominently featured, reflecting their significant influence and frequent citation by other journals. The overlay highlights separate thematic groupings, with each one corresponding to a particular area of study within the larger domain of cartilage regeneration.For example, clusters related to "tissue engineering," "orthopedics," and "biomedical materials" are clearly delineated, showing the diversity of research themes and their interconnections.The visualization reveals interdisciplinary connections between different clusters, indicating collaborations and knowledge exchange across various research areas.Journals in the "biomedical materials" cluster are shown to have strong links with those in the "orthopedics" and "tissue engineering" clusters, highlighting the integrated nature of research in this field.The color coding in the visualization indicates temporal trends, With older studies displayed in blue and newer ones in red.This reveals the evolution of research themes over time, showing how certain clusters have emerged or gained prominence in recent years.

3.7 Analysis of literature sources

Fig. 9a, created by VOSviewer, illustrates the network structure of key references within this research domain. The network map reveals a dense and interconnected structure, indicating a high level of citation exchange among various seminal works. Key references such as those by Chung (2008), Kim (2011), and Huey (2012) are central nodes in the network, highlighting their significant influence and widespread citation in the field. The dimensions of the nodes are determined by the number of citations, with a larger size indicating a more substantial impact.The color coding reflects different clusters of references, suggesting thematic or regional groupings. For example, references related to biomaterials and tissue engineering form a distinct cluster, while those focused on orthopedics and cartilage repair form another. This visual representation makes it possible to determine the key references that propel research within the field and to clarify the connections between distinct clusters of references. Fig. 9b, generated by CiteSpace, displays the twenty most - cited references with the strongest citation bursts from 2005 to 2024.The table includes details such as the reference title, authors, publication year, citation strength, and the period during which the citation burst occurred. Notably, the reference by Chung (2008) has the highest citation strength of 17.35, indicating a significant increase in citations between 2009 and 2013. Other key references include those by Kim (2011) and Huey (2012), which also show strong citation bursts during specific periods. This analysis helps to identify emerging trends and influential works that have shaped the field in recent years.

Close

Fig. 9 Reference Mapping and Citation Burst Analysis.(a) Network visualization of cited references (Data source: VOSviewer).(b) Top 20 references with the strongest citation bursts (Data source: CiteSpace).

Export to PPT

3.8 Keyword Co - occurrence, clustering, and burst analysis

Fig. 10 a presents the keyword network related to cartilage regeneration research. This network is closely connected, indicating a high level of collaboration and interdisciplinary research in this field. Key terms such as "cartilage", "mesenchymal stem cells", "hydrogel", and "chondrocytes" stand out significantly, highlighting their core positions in the research. The dimensions of the nodes are determined by the frequency of occurrence, with larger nodes being linked to keywords that have higher citation counts.Color coding reflects different clusters of related keywords, indicating different but interrelated research topics. For example, the red cluster includes terms such as "biomaterials" and "3D printing", indicating that it focuses on materials science and manufacturing technology, while the blue cluster includes terms such as "osteoarthritis" and "repair", pointing to clinical applications and treatment strategies. Fig. 10 b conducts a detailed clustering analysis of the same research field. The visualization results show 19 different clusters, each labeled with a representative keyword. These clusters are color-coded and spatially arranged to indicate their relationships and overlaps. It is notable that cluster #0, "Cartilage Regeneration", is the largest and most core, indicating its fundamental importance in this field. Other important clusters include #6 ″Mesenchymal Stem Cells", #13 ″3D Printing", and #17 ″Osteochondral Regeneration", further emphasizing the multidisciplinary nature of the research. Cluster labels and their positions indicate that although there is a core research area, there is also significant cross-fusion between different themes (such as stem cell research and biomaterial development). Fig. 10c displays the temporal evolution of the keyword network, illustrating how research topics have developed over time.The timeline at the bottom ranges from 2005 to 2024, with nodes and links representing keywords and their relationships in different years. This visualization chart reveals that early research (2005–2010) focused on basic topics such as "cartilage", "chondrocytes", and "hydrogel". Over time, new themes emerged, such as "3D bioprinting" and "exosomes", indicating technological progress and exploration of new treatment strategies. Time analysis also shows that some research topics have persisted over the years, such as "cartilage repair" and "tissue engineering", while others have declined or changed. This dynamic evolution reflects the continuous innovation and adaptation in this field. Fig. 10d presents the 20 keywords with the most prominent citation bursts, reflecting the peaks of research activities and interests. These keywords are ordered by their burst intensity, which quantifies the citation intensity within a specific time period.The visualization shows that "growth" had the strongest citation burst from 2005 to 2013, reflecting a significant period of interest in growth factors and their role in cartilage regeneration. Other keywords with significant citation bursts include "chondrocytes" (2006–2010), "in vivo" (2008–2017), and "transplantation" (2008–2017), highlighting the focus on cells and treatment strategies during these periods. Recently, keywords such as "injectable hydrogel" (2021–2024) and "3D bioprinting" (2022–2024) have shown strong citation bursts, indicating new trends in biomaterial development and advanced manufacturing technologies.

Close

Fig. 10 Keyword Analysis and Evolution in Hydrogel for Cartilage Repair Research.(a) Co-occurrence network of keywords (Data source: VOSviewer).(b) Keyword clustering analysis from 2005 to 2024 (Data source: CiteSpace).(c) Timeline visualization of keyword evolution (Data source: CiteSpace).(d) Top 20 keywords with the strongest citation bursts (Data source: CiteSpace).

Export to PPT

4.1 Current situation and development trends of hydrogel for cartilage repair

From 2005 to 2024, this study has comprehensively investigated the research on hydrogels for cartilage repair using bibliometric and visualization analysis methods.The research results showed that this field has achieved remarkable progress in the past two decades, attracting the attention and in-depth research of numerous scientific research teams worldwide.

From the national ranking data, China has a significant leading position in the research output quantity in this field, with 955 published articles, accounting for 40.83 %. This reflects that China has invested a large amount of scientific research resources and manpower in this research direction, and has rich scientific research outputs. However, although the number of published articles is high, the average citation times are 35.17 times, which is lower than that of the United States' 63.87 times. The disparity between China's high publication volume and its comparatively lower average citation rate may be attributed to several factors, including a greater focus on applied and incremental research, differing funding mechanisms and evaluation systems that incentivize quantity, and potentially lower rates of international collaboration on high-impact projects compared to the US. In contrast, the higher average citation impact of the US likely reflects its established research infrastructure, stronger emphasis on foundational and disruptive innovation, and deeper integration within global scientific networks. Although the United States has slightly fewer published articles than China, its average citation times and H-index are higher, the research in the United States demonstrates superior academic excellence and impact, and its research results are more likely to be recognized and approved by international peers. Although countries/regions like South Korea, Iran, and Germany have made some research contributions, their number of publications and influence still lag significantly behind China and the United States.It is important to highlight that the mean citation frequency of Reis, Rui L. and Kelly, Daniel J. is comparatively high, reaching 72.72 times, which may indicate that their research results in certain specific research directions or subfields have high innovation and practicality, and can attract more international citations. The average citation times of Iran are relatively low, which may be related to factors such as the scientific research environment, the degree of international cooperation, and the selection of research topics, and further analysis of the reasons for the low quality of scientific research output is needed.

The evolution of research foci, as revealed by keyword burst detection and timeline analysis, signals critical translational shifts within the field. The strong emergence of keywords such as "3D bioprinting" and "exosomes" after 2020 highlights a strategic pivot from developing passive hydrogel scaffolds to creating active, complex, and patient-specific tissue constructs. 3D bioprinting addresses the long-standing challenge of fabricating scaffolds with precise anatomical shapes and heterogeneous cellular distribution, which is crucial for repairing the intricate osteochondral interface. Concurrently, the integration of "exosomes" into hydrogel systems represents a move towards cell-free, acellular therapeutic strategies that harness the regenerative potential of bioactive factors while mitigating the safety and regulatory concerns associated with direct cell transplantation. These trends are not merely technological advancements but are direct responses to the major translational barriers in cartilage repair: achieving structural integration with native tissue and ensuring controlled, sustained biological activity in the defect site. Furthermore, the persistent high frequency of keywords related to "mechanical properties" and "injectable hydrogels" underscores the continuous effort to balance surgical practicality (minimally invasive delivery) with functional performance (matching native tissue mechanics), which are non-negotiable requirements for clinical adoption.

From the perspective of research institutions and authors, authors such as Reis, Rui L. and Kelly, Daniel J. have high publication and H-index levels, and the institutions they belong to are also representative. The AvePark Parque Ciencia & Tecnol institution where Reis, Rui L. works may have provided him with a good research environment and resource support, enabling him to continuously produce high-quality research results in this field. Royal College of Surgeons - Ireland where Kelly, Daniel J. works is also a well-known research institution, which to some extent reflects the research strength and international influence of this institution in the related field. Although Jos Malda has relatively fewer published articles, his average citation times are as high as 154.92 times, indicating that his research results have high international influence and recognition. This may be due to the adoption of unique research methods in his research, solving key scientific problems, or having important application prospects, which has attracted the attention and citations of many scholars. Other authors such as Zhou, Guangdong and Dong - an Wang have also made contributions to the development of this field, but their influence and international reputation may be relatively low, which is closely related to factors such as the resources of their research institutions, the opportunities for international cooperation, and the strength of their research teams.

4.2 Research hotspots and frontier directions

Bibliometric analysis reveals that key research areas in hydrogel for cartilage repair primarily center around biocompatibility and bioactivity, mechanical property enhancement, tissue engineering, regenerative medicine, and clinical application.The biocompatibility and bioactivity of hydrogels are the key factors influencing their application in cartilage repair. Research findings have shown that hydrogels with good biocompatibility and bioactivity can more effectively promote the proliferation and differentiation of chondrocytes, thus accelerating the repair process of cartilage tissue.^14–16 For example, some studies have significantly enhanced their promoting effect on cartilage repair by introducing growth factors or bioactive molecules into the hydrogels.^17–19 Levinson et al. examined the cartilage - forming effect of heparin - HA hydrogel loaded with TGF - β1 on fetal human chronic progenitor cells (hCCs).²⁰ Fan et al. created an acellular, double - crosslinked hydrogel system. They combined TGF - β3 and kartogenin (KGN) - conjugated polyurethane nanoparticles (PN - KGN) for cartilage regeneration.²¹ Cartilage tissue in the physiological state is subject to complex mechanical stresses, so the mechanical properties of hydrogels are crucial for their application in cartilage repair.^22–24 In recent years, by adjusting factors like crosslinking density and polymer composition, researchers have successfully developed a range of hydrogel materials with excellent mechanical properties.

Dual - network hydrogels, first proposed by the research team led by Gong in 2003, enhance mechanical properties through the integration of fragile, highly cross - linked polymers with supple, lightly cross - linked ones^25,26

Gan et al. incorporated oligomers of dopamine methacrylate into GelMA and developed a hydrogel with better mechanical properties than a single mesh GelMA hydrogel.²⁷

These hydrogels can not only withstand mechanical loads similar to natural cartilage but also maintain good stability during the repair process. Hydrogels, as an ideal scaffold material for tissue engineering, have broad application prospects in cartilage tissue engineering and regenerative medicine. Research demonstrates that combining hydrogels with chondrocytes or stem cells can create 3D cartilage tissue - engineering scaffolds. Due to their adjustable material properties similar to tissues, these materials are used as substrates, scaffolds, and encapsulation agents for stem cells,²⁸providing a favorable microenvironment for the regeneration of soft tissue bone. The bibliometric patterns observed, including the rise of specific research themes and international collaboration networks, are intrinsically linked to funding priorities and policy-level trends. The significant output from China aligns with its national strategic focus on advanced biomaterials and regenerative medicine as outlined in its multi-year scientific development plans. The sustained high-impact research from the US and European countries likely reflects long-standing, stable funding for foundational biomedical and engineering research from both public and private sectors. The emergence of interdisciplinary keywords like "3D bioprinting" and "drug delivery" signals a successful, albeit ongoing, integration of engineering, biology, and clinical medicine—a convergence often explicitly encouraged by major funding agencies worldwide through targeted calls for proposals on "convergence research" or "biofabrication."As research on hydrogels for cartilage repair deepens, clinical application and transformation have gradually become hotspots.²⁹ Some studies have successfully applied hydrogels to cartilage repair experiments in animal models and achieved good results. For instance, Maihemuti et al. injected Cy5 - labeled bionic lubricant (HA - PGMP - CAP) into OA rats' joints to investigate retention. They found that HA - PGMP - CAP molecules can form a durable, stable lubrication layer on cartilage surfaces, facilitating cartilage lubrication recovery.³⁰However, translating hydrogels from laboratory research to clinical application still faces many challenges, such as biological safety, long-term stability, and individual differences, which still need to be further studied and addressed.

4.3 Limitations

This bibliometric analysis has certain limitations that should be acknowledged. The study relied exclusively on the Web of Science Core Collection database, which, despite its comprehensive coverage of high-quality journals, may have introduced selection bias by excluding relevant research indexed in other databases such as Scopus or PubMed. Additionally, the assessment of research impact through citation-based metrics is inherently constrained by the citation window effect. Publications from more recent years, particularly those after 2020, have had less time to accumulate citations compared to older works, potentially skewing the evaluation of their true academic influence and obscuring the identification of emerging trends. The analytical focus on published literature may also overlook significant contributions from unpublished research or ongoing clinical trials. Furthermore, while this study provides a comprehensive overview of the field from 2005 to 2024, it does not encompass earlier foundational research that may have shaped the development of hydrogel applications in cartilage repair.