Immunomodulatory Biomaterials for Implant Osseointegration: Knowledge Mapping (2005

Abstract

This study used bibliometric analysis to comprehensively map the research landscape of immunomodulatory biomaterials enhancing implant osseointegration between 2005 and 2025. Publications retrieved from the Web of Science Core Collection were analyzed to identify temporal trends, contributing countries, institutions, journals, cocitation networks, and keyword evolution. A total of 419 articles were identified. The annual output and citations increased steadily, with China, the United States, and Australia as major contributors. The terms ‘3D printing’, ‘scaffolds’, and ‘macrophage polarization’ emerged as recent hotspots, reflecting a shift from mechanistic exploration to clinical translation. Compared with prior reviews focusing mainly on mechanisms, this study also analyzed the depth of international collaboration, clinical orientation of journals, and bottlenecks in translational application. The field has evolved from theoretical construction (osteoimmunomodulation theory) to technological innovation (nanoengineering, dynamic response design). Future work should integrate intelligent responsive biomaterials with multiomics validation to accelerate the transition from passive repair to active regulation in bone regeneration.

Impact Statement

The findings redirect future investigations toward dynamic, microenvironment-responsive designs validated by multiomics and large-animal models, inform clinicians about next-generation precision implants, and guide funding agencies and regulators in prioritizing standards and incentives for translating immunomodulatory biomaterials into personalized osseointegration therapies.

Keywords

immunomodulation biomaterials implant osseointegration bibliometrics

Introduction

Immunomodulatory biomaterials have emerged as a transformative strategy to enhance implant osseointegration, addressing critical challenges in orthopedic and dental rehabilitation.¹ Despite advancements, clinical complications, such as implant-associated infections, chronic inflammation and immune-mediated rejection, remain significant barriers to long-term success.² For example, bacterial colonization on implant surfaces often triggers prolonged inflammation, disrupting bone regeneration and leading to implant failure.³ Similarly, improper immune responses to biomaterials can exacerbate fibrosis or foreign body reactions, further complicating osseointegration.⁴ These challenges highlight the need for biomaterials that can actively modulate immune responses while promoting bone repair.

In clinical practice, dental and orthopedic implant failures often result from inadequate osseointegration due to persistent inflammation or infection.⁵ Current clinical strategies, such as antibiotic therapy and surgical debridement, have limitations in eliminating infection and restoring normal bone remodelling.⁶ For example, bacterial biofilms on implant surfaces are highly resistant to antibiotics, leading to chronic infections and subsequent implant failure. In addition, the foreign body reaction triggered by implant materials can cause chronic inflammation, fibrous encapsulation, and implant loosening. These clinical issues highlight the urgent need for novel biomaterials that can regulate immune responses and promote bone integration. Recent research highlights the dual role of immune cells—particularly macrophages—in osseointegration.⁷ Achieving a balanced immune response, transitioning from proinflammatory (M1) to anti-inflammatory (M2) macrophage phenotypes, is critical for successful integration.⁸ Immunomodulatory biomaterials, such as surface-modified titanium alloys and three-dimensional (3D)-printed scaffolds, have shown promise in dynamically steering macrophage polarization and mitigating adverse immune reactions.⁹ For example, strontium-doped coatings suppress excessive inflammation while enhancing osteogenesis, offering a dual therapeutic effect.¹⁰

Despite these advances, the field lacks a comprehensive analysis of research trends, technological bottlenecks, and future directions. Existing reviews often focus on mechanistic insights rather than mapping the evolution of concepts or identifying translational gaps.¹¹ This study employs bibliometric analysis to evaluate 20 years of research on immunomodulatory biomaterials systematically, addressing three objectives: (1) identifying foundational theories and emerging technologies; (2) mapping global collaboration networks; and (3) forecasting future trends to bridge preclinical and clinical applications. By synthesizing these insights, this work aims to guide the development of next-generation biomaterials that resolve persistent clinical challenges through precision immunomodulation.

Materials and Methods

Data source and search strategy

Publications were systematically retrieved from the Web of Science Core Collection (WOS-CC) using the following search strategies:

Database—WOS-CC.

Time Span—1 March 2005–31 March 2025

The time span was deliberately set to capture the complete 20-year developmental arc of immunomodulatory biomaterials in implant osseointegration. Prior to 2005, the co-occurrence of ‘immunomodulation’ and ‘osseointegration’ was virtually absent in the WOS-CC, indicating an insufficient research foundation for bibliometric analysis. Starting in 2005, the emergence of key enabling technologies, such as nano-engineered surfaces, ion-doped coatings and early 3D-printed scaffolds, marked the onset of a distinct scientific discourse. Extending the window to March 2025 secures the inclusion of 2024’s record-high output and the 2025 burst signals for ‘3D printing’ and ‘macrophage polarization’, thereby providing both historical breadth and forward-looking insight into clinical translation trends.

Search Query—TS = (‘immunomodulat*’ OR ‘immune engineer’ OR ‘osteoimmun*’) AND (‘coating’ OR ‘scaffold’ OR ‘implant surface’ OR ‘3D print’) AND (‘osseointegration’ OR ‘bone regeneration’ OR ‘dental implant’) NOT TS = (‘drug delivery’ OR ‘gene therapy’ OR ‘stem cell’).

Refinement:

Document Types—Article, review article.

Languages—English.

Search Results: (1)

Initial hits—424 publications.

(2)

Following refinement—419 publications (articles: 360; reviews: 59) (Fig. 1).

FIG. 1.

Publications screening flowchart.

To evaluate clinical orientation, the scope and aims of journals in the corpus were reviewed and classified qualitatively as clinical-oriented (journals primarily publishing clinical or clinical-translational studies) versus preclinical/materials-oriented. This classification was used only for narrative summarization and did not alter the bibliometric counts.

Rationale for database selection

The WOS-CC was selected as the primary data source due to its rigorous curation of high-impact journals, comprehensive coverage of multidisciplinary research and widespread recognition in bibliometric studies.¹² Although the WOS-CC provides robust coverage of high-quality, peer-reviewed articles, it may underrepresent studies published in regional journals or non-English literature. To assess potential biases, a cross-check was performed with the Scopus abstract and citation database for 50 randomly selected high-citation articles. Over 90% of these articles were indexed in both databases, confirming WOS-CC’s adequacy in representing mainstream research. Nevertheless, the exclusion of non-English studies may marginally affect trends related to regional innovations, which warrants consideration in future studies.

Analytical tools and parameters

To guarantee methodological rigor and reproducibility, a multitool analytical workflow was adopted that combined complementary strengths rather than relying on a single program. First, the R package bibliometrix (v4.3.3) was employed for overall scientific-production profiling; its biblioAnalysis and summary functions generated annual publication counts, country collaboration world maps and descriptive statistics. Second, VOSviewer (v1.6.20) was configured with a minimum occurrence threshold of 5 to construct and visualize country-, institution-, author- and keyword-co-occurrence networks; the association strength normalization and LinLog/modularity algorithms were left at default to preserve cluster granularity. Third, CiteSpace (6.4R2) was used for dual-map journal overlays, cocitation networks and burst detection; the network was pruned with Pathfinder and ‘pruning the merged network’ options, γ was set to 0.8 after sensitivity tests confirmed stable burst patterns between 0.7 and 0.9 and time slicing was set to 1-year intervals between March 2005 and March 2025. Finally, HistCite (v12.03.17) served as a cross-validation tool for author and reference centrality scores; parameters were kept at default except for minimum local citation score ≥5 to align with the VOSviewer threshold. All analyses were run on the same deduplicated corpus to ensure internal consistency. All bibliometric data and derived counts were double-checked against the original Web of Science export to ensure factual accuracy.

Sensitivity analysis and cross-validation

To address concerns regarding result reliability, the following validation steps were performed: 1.

Parameter sensitivity testing—keyword thresholds in VOSviewer were adjusted (from 5 to 3), and stable cluster structures were observed (e.g., persistent dominance of ‘macrophage polarization’ and ‘3D printing’). CiteSpace’s γ parameter was varied (0.7–0.9), confirming that burst detection patterns remained consistent (e.g., ‘osteoimmunomodulation’ [OIM] consistently emerged as the strongest burst).

Cross-database consistency check—WOS-CC results were compared with Scopus using the same search strategy. Key trends (e.g., China’s leading contribution, prominence of Biomaterials journal) showed >85% overlap, supporting the reproducibility of findings.¹³

Tool intercomparison—cocitation networks were reanalyzed using HistCite (v12.03.17). Core references (Chen, 2016) retained high centrality scores, aligning with the CiteSpace results.¹⁴

Expert validatio—three independent experts were invited to evaluate the top 10 burst keywords and references. Consensus rates were >90%, confirming the clinical relevance of identified trends.

Results

Analysis of domain development trends

Annual publication volume trend

The search results based on the WOS-CC (1 March 2005–31 March 2025) identified 419 valid documents (articles and reviews) with temporal distribution characteristics as follows: first publicatio—2012 (search results for 2005–2011 yielded zero documents); peak output—115 documents in 2024 (accounting for 27.4% of total volume); latest data—36 documents published between January 2025 and March 2025 (all formally published) (Fig. 2).

FIG. 2.

Annual Scientific Production.

The literature output exhibited an ‘intermittent burst’ pattern:

Germination period (2012–2017)—average 4.3 documents per year.

Transition period (2018–2020)—average 20 documents per year.

Outbreak period (2021–2024)—average 74.5 documents per year.

As of 31 March 2025, 36 documents have been published. If linearly extrapolated, the projected annual output could reach 144 documents (R² = 0.94).

Country and institutional analysis

The above publications come from 43 countries and 552 institutions. The top 10 countries are distributed across Asia (n = 4), Europe (n = 5), North America (n = 1) and Oceania (n = 1). Among these countries, China has the highest number of publications (n = 320, 69.41%), followed by the United States (n = 40, 8.68%), Australia (n = 32, 6.94%) and Spain (n = 13, 2.82%) (Table 1).

Table 1.

Top 10 Countries/Institutions in Immunomodulatory Biomaterials for Osseointegration

Rank	Country	Counts	Institution	Counts
1	China	320 (69.41%)	Shanghai Jiao Tong University	52 (4.31%)
2	USA	40 (8.68%)	Chinese Academy of Sciences	50 (4.15%)
3	Australia	32 (6.94%)	Sichuan University	37 (3.07%)
4	Spain	13 (2.82%)	Fourth Military Medical University	20 (1.66%)
5	Germany	12 (2.60%)	Sun Yat-sen University	19 (1.58%)
6	Korea	10 (2.17%)	Huazhong University of Science and Technology	18 (1.49%)
7	Italy	8 (1.74%)	Queensland University of Technology	18 (1.49%)
8	India	7 (1.52%)	Peking University	17 (1.41%)
9	Netherlands	7 (1.52%)	Shandong University	15 (1.24%)
10	Portugal Saudi Arabia	6 (1.30%) 6 (1.30%)	Xi’an Jiaotong University	15 (1.24%)

Subsequently, the data were filtered and visualized based on countries with ≥5 publications, and a collaboration network was constructed according to the number of publications and relationships in each country (Fig. 3). Notably, there is a lot of positive cooperation between different countries. For example, China has close ties with the United States, Australia and Germany, and the United States has active collaborations with South Korea, Germany, and India.

FIG. 3.

The geographical distribution (A) and visualization of countries (B).

Nine of the top 10 institutions are located in China. The 4 institutions that have published the most related articles are Shanghai Jiao Tong University (n = 52, 4.31%), Chinese Academy of Sciences (n = 50, 4.15%), Sichuan University (n = 37, 3.07%), and Fourth Military Medical University (n = 20, 1.66%). The only non-Chinese institution to appear in the top 10 is Queensland University of Technology in Australia (18 articles, total citations: 1,610). The institutions were then visualized based on the number of articles published (up to 5), and a collaboration network was constructed based on the number of articles each institution has published and their relationships. As shown in Figure 4, cooperation among these institutions is extremely active. In addition to the wide geographic distribution, a focused review of Sino-foreign collaborative outputs indicates that collaborations involving China and partners such as the United States, Australia, and Spain feature among the more highly cited and innovation-oriented works. These joint efforts frequently combine complementary strengths (for example, material synthesis and surface engineering from Chinese groups with advanced bioengineering and analytical platforms from partner institutions) and are associated with both conceptual/theoretical contributions and technological innovations.

FIG. 4.

The visualization of institutions.

Journals and cocited journals

Publications related to ‘immunomodulatory biomaterials enhancing implant osseointegration’ have been published in 125 journals. The article with the most publications is from Bioactive Materials (n = 24, 5.73%), followed by Biomaterials (n = 21, 5.01%), Advanced Healthcare Materials (n = 19, 4.53%) and Chemical Engineering Journal (n = 18, 4.30%) (Fig. 5). Among the top 20 journals, that with the highest impact factor (IF) is Advanced Functional Materials (IF = 19), followed by Bioactive Materials (IF = 18.9). Fifty-one journals with ≥2 related publications each were then screened, and the journal network was mapped.

FIG. 5.

The most relevant sources.

As shown in Table 2, among the top 20 most cited journals, 6 have been cited >500 times. The journal with the highest citation count is Biomaterials (total citations: 2,602), followed by Acta Biomaterialia (total citations: 1,476), Bioactive Materials (total citations: 817), ACS Applied Materials & Interfaces (cocitations: 726), Materials Science & Engineering: C (total citations: 634) and Advanced Healthcare Materials (total citations: 519) (Fig. 6A). The journal with the highest IF is Advanced Materials (IF = 29.4), followed by Advanced Functional Materials (IF = 19.0). A cocitation network was constructed by filtering out journals with a minimum cocitation value of 150. As shown in Figure 6B, Biomaterials has a positive cocitation relationship with Acta Biomaterialia, Bioactive Materials, ACS Applied Materials & Interfaces, Materials Science & Engineering: C, Advanced Healthcare Materials and other journals.

FIG. 6.

The visualization of journals (A) and cocited journals (B).

Table 2.

Top 20 Journals and Cocited Journals

Rank	Journal	Articles	IF	JCR Q	Cocited journal	Citations	IF	JCR Q
1	Bioactive Materials	24 (5.73%)	18.9	Q1	Biomaterials	2602	14	Q1
2	Biomaterials	21 (5.01%)	14	Q1	Acta Biomaterialia	1476	9.7	Q1
3	Advanced Healthcare Materials	19 (4.53%)	10	Q1	Bioactive Materials	817	18.9	Q1
4	Chemical Engineering Journal	18 (4.30%)	15.1	Q1	ACS Applied Materials & Interfaces	726	9.5	Q1
5	ACS Applied Materials & Interfaces	16 (3.82%)	9.5	Q1	Materials Science & Engineering C	634	7.9	Q1
6	Acta Biomaterialia	15 (3.58%)	9.7	Q1	Advanced Healthcare Materials	519	10.0	Q1
7	Advanced Science	15 (3.58%)	15.1	Q1	Journal of Biomedical Materials Research Part A	492	3.9	Q3
8	Journal of Materials Chemistry B	13 (3.10%)	7.0	Q2	ACS Nano	415	17.1	Q1
9	Materials Today Bio	12 (2.86%)	8.2	Q1	Advanced Functional Materials	404	19.0	Q1
10	ACS Biomaterials Science & Engineering	11 (2.63%)	5.8	Q2	Advanced Materials	394	29.4	Q1
11	Frontiers in Bioengineering and Biotechnology	11 (2.63%)	5.8	Q2	Journal of Materials Chemistry B	374	7.0	Q2
12	Composites Part B: Engineering	10 (2.39%)	13.1	Q1	Clinical Oral Implants Research	369	4.3	Q2
13	International Journal of Nanomedicine	10 (2.39%)	8	Q2	International Journal of Molecular Sciences	326	5.6	Q2
14	Advanced Functional Materials	9 (2.15%)	19	Q1	Bone	321	4.1	Q2
15	Colloids and Surfaces B: Biointerfaces	9 (2.15%)	5.8	Q3	Advanced Science	312	15.1	Q1
16	Journal of Nanobiotechnology	9 (2.15%)	10.2	Q1	Biomaterials Science	290	6.6	Q2
17	Small	9 (2.15%)	13.3	Q1	Scientific Reports	282	4.6	Q2
18	Materials & Design	8 (1.91%)	9.4	Q2	International Journal of Nanomedicine	272	8.0	Q2
19	Biomaterials Science	6 (1.43%)	6.6	Q3	Colloids and Surfaces B: Biointerfaces	266	6.5	Q3
20	Biomedical Materials	6 (1.43%)	4.0	Q3	ACS Biomaterials Science & Engineering	262	5.8	Q2

IF, impact factor; JCR, Journal Citation Reports.

The dual-map overlay of the journals shows the citation relationships between journals and the cocited journals (Fig. 7). On the left is the cluster of citing journals, and on the right is the cluster of cited journals. As shown in the figure, the purple path represents the main citation pathway, indicating that articles published in journals such as those pertaining to chemistry, materials, physics, molecular biology and genetics are primarily cited by literature from journals pertaining to physics, materials and chemistry.

FIG. 7.

The dual-map overlay of journals.

In terms of clinical orientation, a review of journal scopes shows that the majority of publications are concentrated in materials and preclinical biomaterials journals, whereas journals that are primarily focused on clinical trials and clinical orthopedics are relatively underrepresented. Therefore, although ‘3D printing’ and ‘scaffolds’ emerged as hotspots in 2023–2025, most related work remains at the materials/preclinical stage rather than in clinical journals or large-scale clinical studies.

Authors’ publication status

A total of 2,786 authors participated in the study of immunomodulatory biomaterials for osseointegration of implants. Among the top 10 authors in terms of publication volume, 4 authors each published ≥10 articles (Table 3). A collaboration network was constructed based on authors with ≥5 publications (Fig. 8A). The nodes of Xiao, Yin, Wu, Chengtie, Chen, Zetao, and Zheng are the largest, as they have published the most related publications. Additionally, collaborations were observed among multiple authors. For example, Wu and Chengtie collaborated with Chen, Zetao, and Chang Jiang, and Zheng and Yufeng collaborated with Li, Bo, and others.

FIG. 8.

The visualization of authors (A) and cocited authors (B).

Table 3.

Top 10 Authors and Co-Cited Authors

Rank	Authors	Count	Co-cited authors	Citations
1	Xiao, Yin	16	Chen, ZT	329
2	Wu, Chengtie	12	Bai, L	105
3	Chen, Zetao	10	Spiller, KL	86
4	Zheng, Yufeng	10	Brown, BN	76
5	Li, Bo	9	Liu, Y	75
6	Bai, Jiaxiang	8	Franz, S	70
7	Chang, Jiang	8	Pajarinen, J	70
8	Han, Yong	8	Wu, CT	70
9	Geng, Dechun	7	Lee, J	65
10	Li, Kai	7	Schlundt, C	65

Among the 15,075 cocited authors, 8 authors were cocited >70 times (Table 3). The author with the most citations is Chen ZT (n = 329), followed by Bai L (n = 105) and Spiller KL (n = 86). Authors with a minimum cocitation value of 30 were selected to create a cocitation network diagram (Fig. 8B). As shown in the figure, there is also active collaboration among different cocited authors, such as Schlundt C and Lee J, Liu Y, and Pajarinen J.

Cocited references

In the past 20 years, there have been 22,251 cocited articles on the application of immunomodulatory biomaterials in the osseointegration of implants. In the top 10 cocited documents (Table 4), all the documents were cocited ≥39 times, up to 102 times. References with ≥20 cocitations were selected to construct the cocitation network (Fig. 9).

FIG. 9.

The visualization of cocited references.

Table 4.

Top 10 Co-Cited References

Rank	Cited reference	Citations
1	Chen ZT, 2016, mater today, v19, p304, doi 10.1016/j.mattod.2015.11.004	102
2	Franz S, 2011, biomaterials, v32, p6692, doi 10.1016/j.biomaterials.2011.05.078	65
3	Pajarinen J, 2019, biomaterials, v196, p80, doi 10.1016/j.biomaterials.2017.12.025	61
4	Lee J, 2019, adv healthc mater, v8, doi 10.1002/adhm.201801106	57
5	Zhu Yz, 2021, sci adv, v7, doi 10.1126/sciadv.abf6654	48
6	Spiller KL, 2015, biomaterials, v37, p194, doi 10.1016/j.biomaterials.2014.10.017	45
7	Bai L, 2018, biomaterials, v162, p154, doi 10.1016/j.biomaterials.2018.02.010	43
8	Chen ZT, 2015, biomaterials, v61, p126, doi 10.1016/j.biomaterials.2015.04.044	42
9	Mcwhorter FY, 2013, p natl acad sci usa, v110, p17253, doi 10.1073/pnas.1308887110	40
10	Anderson JM, 2008, semin immunol, v20, p86, doi 10.1016/j.smim.2007.11.004	39

According to Figure 9, ‘Chen ZT, 2016, mater today, v’ shows active cocited relationships with ‘Franz S, 2011, biomaterials’, ‘Pajarinen J, 2019, biomateria’ and ‘Lee J, 2019, adv healthc mate.’

Reference with citation bursts

‘Reference with citation bursts’ refers to the frequent citation of references in a specific field over a certain period. In this study, CiteSpace identified 20 references with a strong citation surge (Fig. 10). As shown in the figure, each reference was cited multiple times. A bar represents 1 year, and a red bar indicates a strong citation burst.¹² The earliest citation burst occurred in 2014 and the latest in 2023. The reference with the strongest citation burst intensity (intensity: 19.83) is titled ‘Osteoimmunomodulation for the development of advanced bone biomaterials’, authored by Chen ZT et al., published in Materials Today, with the citation burst occurring between 2017 and 2021. The reference with the second strongest citation burst intensity (intensity: 10.91) is titled ‘The effect of osteoimmunomodulation on the osteogenic effects of cobalt incorporated β-tricalcium phosphate’, also authored by Chen ZT et al., published in Biomaterials, with the citation burst occurring between 2015 and 2020. Overall, the intensity of the 15 references ranged from 4.82 to 19.83, and the duration of intensity ranged from 2 to 5 years. Table 5 summarizes the main research content of the 20 references, arranged in the order of the references shown in Figure 10.

FIG. 10.

Top 20 references with strong citation bursts.

Table 5.

The Main Research Contents of the 20 References with Strong Citations Bursts

Rank	Strength	Main research content
1	5.94	The theory of bone immune regulation (OIM) was proposed to emphasize the central role of immune cells in bone regeneration.
2	10.9	The discovery of cobalt-doped β-TCP inhibiting bone formation by activating the M1 phenotype of macrophages revealed the double-edged sword effect of immune response.
3	8.52	The Sr2ZnSi2O7 coating was developed to enhance the bone integration of titanium alloy through immunomodulation.
4	4.22	A multicellular evaluation model was proposed to verify the regulation of immune cells on bone formation ability.
5	19.8	The theory of OIM was systematically expounded to promote the design of bone materials from “osteogenesis oriented” to “immune regulation”.
6	7.64	To reveal the phenotypic plasticity of bone macrophages (OsteoMacs) and its effect on the response to biomaterials.
7	6.36	The surface wetting of titanium was proved to improve bone integration by regulating macrophage polarization.
8	5.08	The “nano bone immune regulation” strategy was proposed to accurately regulate the immune-bone formation balance through surface topology.
9	4.84	Nanotopology was modified with carboxylic acid to simultaneously optimize immune regulation and bone formation.
10	4.23	Cu-doped mesoporous silicon nanospheres (Cu-MSNs) were developed to promote bone regeneration through OSM signaling pathway.
11	7.98	The immunological engineering strategy was proposed to integrate the material properties and host inflammatory dynamics.
12	4.68	The key role of macrophage and mesenchymal stem cell interaction in bone healing was analyzed.
13	7.08	Strontium-doped bioactive glass (Sr-SBG) was designed to enhance bone regeneration by immunomodulation.
14	4.81	Strontium-containing microspheres (SrBGM) were developed to promote early angiogenesis by inducing M2 macrophage polarization.
15	8.3	TiO₂ coating (MAO-650) was prepared by microarc oxidation to simultaneously optimize osteogenesis, angiogenesis and anti-inflammatory effects.
16	5.85	Zinc modified polyether ether ketone (SPEEK) was proposed to enhance bone integration by regulating macrophage polarization.
17	4.53	Develop pH/ROS responsive scaffolds to dynamically adapt the immune microenvironment of diabetic bone defects.
18	6.2	The multistage functions of macrophages in bone regeneration and targeted regulation strategies were summarized.
19	4.95	A Zn²⁺/BMP-2 synergistic coating was designed to improve the performance of titanium implants through the immune-bone coupling effect.
20	4.5	BMP-4/MSNs were loaded by 3D bio-printing to promote the repair of diabetic bone defect.

β-TCP, β-Tricalcium Phosphate; BMP, bone morphogenetic protein; OSM, oncostatin M.

Hotspots and frontiers

Table 6 shows the top 20 high-frequency keywords in this study, representing the topics that have been long-term focused on in this field. Among these keywords, ‘bone regeneration’ appears 234 times and ‘immunomodulation’ appears 183 times, which represents the main direction of research on biomaterials for immune regulation in osseointegration of implants.

Table 6.

Top 20 Keywords

Rank	Keywords	Occurrences	Rank	Keywords	Occurrences
1	Bone regeneration	234	11	Osteoimmunology	16
2	Immunomodulation	183	12	Bone tissue engineering	13
3	Macrophages	60	13	Stem cells	13
4	Angiogenesis	42	14	Tissue engineering	13
5	Titanium implants	42	15	Bioceramics	12
6	Macrophage polarization	37	16	Biomaterials	11
7	3d printing	33	17	Diabetes	11
8	Inflammation	23	18	Osteogenic differentiation	10
9	Surface modification	22	19	Hydrogel	9
10	Antibacterial	21	20	Peek	9

The keywords were clustered through CiteSpace, as shown in Figure 11. A total of 10 clusters were obtained, representing different research directions, including #0 surface modifications, #1 de-cellularised bone matrix, #2 adhesion, #3 calcium phosphate cement, #4 bone regeneration, #5 barrier membrane, #6 regenerative medicine, #7 biomimetic repair, #8 3D printing and #9 surface structure.

FIG. 11.

Timeline of keyword clustering analysis.

Keywords with the strongest citation bursts can identify the technological frontiers or emerging trends driving the development of a field. Through CiteSpace, the top 15 sudden keywords in this field were obtained (Table 7). Among the 15 sudden keywords, 7 belong to #4, indicating that bone regeneration is the absolute core goal of the field. In recent years (2023–2025), the sudden keywords ‘scaffolds’ and ‘3D printing’ both rank at #8, suggesting that #8 is a recent research hotspot.

Table 7.

Top 15 Keywords with the Strongest Citation Bursts

Keywords	Year	Strength	Begin	End	Cluster
Gene expression	2014	2.29	2014	2019	#6
Bioceramic coatings	2015	2.83	2015	2019	#0
Induction	2017	2.26	2017	2019	#4
Osteoimmunology	2016	2.45	2019	2020	#4
Inflammation	2015	2.84	2021	2023	#4
Responses	2018	2.48	2021	2022	#9
Osteoblast differentiation	2014	2.27	2021	2022	#4
Bone formation	2018	2.17	2021	2022	#4
Cells	2018	4.32	2022	2025	#4
Ions	2020	2.35	2022	2025	#3
Bone regeneration	2014	8.91	2023	2025	#4
Scaffolds	2013	3.98	2023	2025	#8
Macrophage polarization	2016	3.62	2023	2025	#4
3d printing	2018	3.17	2023	2025	#8
Antibacterial	2019	2.17	2023	2025	#0

Discussion

General information

Between 2005 and 2011, the annual publications were zero, indicating that research on immunomodulatory biomaterials in osseointegration of implants had not yet begun, with a relative lack of research foundation. Between 2012 and 2017, research in this field was still in its infancy, with an average of 4.3 articles published annually. Between 2018 and 2020, the number of publications began to increase notably, averaging 20 articles per year. Starting from 2021, the number of related publications grew rapidly, averaging 74.5 articles per year. The growth trend became more pronounced in 2015, indicating that research on immunomodulatory biomaterials in osseointegration of implants was experiencing an explosive period, attracting increasing attention from scholars.

Compared with representative recent reviews that predominantly synthesize mechanistic findings, our study provides several distinct contributions. First, the time span and corpus are broader (2005–2025; 419 publications), enabling the detection of long-term trends and recent emergent hotspots. Second, we applied multiple bibliometric dimensions—including publication trends, country/institutional analyses, journals and cocitation structures, author networks, keyword evolution, and burst detection—to map both breadth and trajectory. Third, beyond quantitative mapping, we supplemented bibliometrics with targeted qualitative analyses on clinical orientation, collaboration depth (Sino-foreign cooperative outputs), and translational bottlenecks, which enhance the study’s clinical relevance. Finally, we offer actionable guidance by proposing a practical pathway to integrate multiomics profiling with dynamic material design for translational research. Taken together, these features distinguish our work from primarily mechanism-focused reviews and underline its broader translational and methodological value.

China is the country with the most research publications in this field (n = 320, 69.41%), followed by the United States (n = 40, 8.68%), Australia (n = 32, 6.94%), and Spain (n = 13, 2.82%). Australia, Italy and Portugal are countries where research started earlier. Among the top 10 research institutions, 9 are located in China. The only non-Chinese institution in the top 10 is Queensland University of Technology in Australia (18 articles, total citations: 1,610). The author Xiao Yin (n = 16), who has published the most articles, and the author Chen ZT (n = 329), who has been cited the most, both belong to this institution, which maintains good and close cooperation with the Chinese Academy of Sciences.

Bioactive Materials is the journal with the most articles on research related to immunomodulatory biomaterials in implant osseointegration (n = 24, 5.73%), followed by Biomaterials (n = 21, 5.01%). The journal with the highest IF is Advanced Materials (IF = 29.4), followed by Advanced Functional Materials (IF = 19). Biomaterials (IF = 14, Q1, times cited: 2,602) is the most frequently cited journal, followed by Acta Biomaterialia (IF = 9.7, Q1, times cited: 1,476). Clearly, these journals are all high-quality international publications that support research on immunomodulatory biomaterials and implant osseointegration. Additionally, current research on immunomodulatory biomaterials in implant osseointegration is mainly published in journals pertaining to chemistry, materials, and physics, as well as molecular biology- and genetics-related journals, with a few studies appearing in clinical-related journals, indicating that most research is still at the basic research stage, although some studies have entered the clinical validation phase.

Analysis of development trends

Theoretical framework and core breakthrough in the field

The origin and core ideas of bone immunomodulation theory

The theory of OIM was proposed in response to the reflection on traditional paradigms of bone biomaterial design. Early studies found that the host’s immune response following implantation of biomaterials (e.g., macrophage activation and release of inflammatory factors) not only affects material integration but also directly regulates the osteogenic process.¹⁵ In 2016, the Chen ZT team formally introduced the OIM theory, emphasizing that immune cells (especially macrophages) are the core indicators for evaluating material performance.¹⁶ The key points include the following: (i)

Immune-bone formation interaction network—macrophages indirectly regulate the bone formation differentiation of mesenchymal stem cells (MSCs) by secreting factors such as bone morphogenetic protein-2 (BMP-2) and vascular endothelial growth factor (VEGF), rather than the traditional direct stimulation of osteoblasts by materials.

(ii)

Pro/non-inflammatory polarization balance—M1 macrophages dominate the early inflammation clearance, whereas M2 macrophages promote bone regeneration by releasing oncostatin M (OSM) and other factors. The dynamic balance between the two is the key¹⁷ to bone integration.

Theoretical expansion and mechanism deepening

Macrophage spatiotemporal dynamics—Schlundt C proposed the functional heterogeneity of macrophages at different stages of bone healing (inflammatory phase, repair phase, remodeling phase), emphasizing that material design must match their phenotypic temporal transitions.¹⁸ For example, early on, brief M1 polarization is required to clear necrotic tissue, whereas later, M2 polarization is needed to promote angiogenesis and mineralization.

Synergistic signaling pathways—Wang T demonstrated that the surface topology of materials regulates macrophage pseudopod formation by activating the RhoA/Rho-associated protein kinase (ROCK) pathway, which, in turn, affects their polarization state and paracrine function.¹⁹

Keyword association and theoretical verification

The highlighted keywords ‘osteoimmunology’ and ‘macrophage polarization’ directly point to the core mechanism of OIM theory: (i)

Inflammation regulation—high citation reference confirmed that excessive M1 polarization (e.g., induced by calcium phosphate ceramics materials [controllable and programmable materials]) is associated with overexpression of interleukin (IL)−6 and tumor necrosis factor-α and inhibition of osteogenic differentiation, as reported in high-citation studies.²⁰

(ii)

Dynamic immune response—Chen ZT found that the ion release rate of materials was directly related to the phenotype transformation of macrophages, such as rapid release of cobalt ions to activate M1 phenotype, and slow release of strontium ions to induce M2 polarization.¹⁶

Evolution of technology path and hotspot correlation

Surface modification technology—the keyword ‘bioceramic coatings’ (burst strength: 2.83) and highly cited references^21,22 jointly reveal the core position of surface modification technology in immunomodulatory materials: (i)

Nano-topological engineering—Zhu YS constructed a honeycomb TiO₂ nanostructure (90 nm) on the surface of titanium. By activating the RhoA/ROCK pathway, macrophage pseudopod extension and M2 polarization were promoted, and bone integration was markedly enhanced.²²

(ii)

Chemically functionalized coating—Bai L prepared a TiO₂ coating (MAO-650) by microarc oxidation combined with 650°C heat treatment, which was highly wetted and synergistically optimized with hydroxyapatite nanoparticles to optimize the osteogenic and anti-inflammatory effects.²¹

(iii)

Ion doping strategy—Chen ZT developed a Sr2ZnSi2O7 coating to induce macrophage M2 polarization by sustained release of Sr²⁺/Zn²⁺, upregulate BMP-2/VEGF expression and promote angiogenesis and bone regeneration (bone regeneration, peak strength: 9.02).¹⁶

Multifactor coordination and intelligent materials

The references with citation bursts and the burst keywords ‘3D printing’ (emergence intensity: 3.18) and ‘scaffolds’ (support, emergence intensity: 4.05) indicate that multisignal synergy and intelligent response have become major topics in recent years.

Sequential release scaffold—Spiller KL designed an interferon gamma (promoting M1) and IL-4 (promoting M2) sequential release scaffold to simulate the natural process of inflammation and repair, considerably enhancing vascular maturity.²³

Coating design—Wang T (2022, Nat Commun, DOI: 10.1038/s41467-021–27816-1) integrated Zn²⁺ and BMP-2 peptide into a titanium coating, which induced M2 polarization by Zn²⁺ and directly promoted bone formation by BMP-2 to achieve dual immune-bone formation.¹⁹

Intelligent responsive material—Xie YJ developed a pH/ROS dual-responsive scaffold to adapt the acidic/high oxidative stress microenvironment of diabetic bone defects dynamically and regulate macrophage polarization and bone formation accurately (bone formation, emergent strength: 2.18).²⁴

Synergistic effect of antibacterial and immune strategy

The burst word ‘antibacterial’ (burst strength: 2.18) is associated with highly cited references,^16,25 revealing the necessity of an antibacterial—immune synergistic strategy.

Dual function of metal ions—Liu W proved that zinc-modified polyether ether ketone inhibits the formation of Staphylococcus aureus biofilm by releasing Zn²⁺ and induces macrophage M2 polarization to avoid excessive inflammation inhibiting osteoblast differentiation (burst strength: 2.27).²⁵

Copper ion regulation—Chen ZT found that copper-doped mesoporous silica nanospheres activated the OSM pathway by releasing Cu²⁺, which promoted the osteogenic differentiation of bone marrow MSCs while being antibacterial.¹⁶ Overall, although China dominates the publication volume in this field, international collaborations have contributed substantially to the field’s core theoretical breakthroughs (e.g., osteoimmunomodulation concepts) and technological innovations (e.g., smart surface coatings and responsive scaffolds). This suggests that global cooperation not only broadens research participation but also deepens the scientific impact through the combination of multidisciplinary expertise.

Research trends and challenges

Research hotspot migration

From early focus on gene expression (burst strength: 2.3) and fundamental mechanisms (2014–2019), the attention has shifted to clinically oriented technologies (e.g., 3D printing, smart responsive materials, 2020–2025). The sustained high popularity of the emergent terms ‘cells’ (burst strength: 4.37) and ‘bone regeneration’ (2023–2025) reflects the growing emphasis on multicellular interactions and translational medicine.

Core challenges

Most studies are limited to small animal models and lack large animal experiments. The spatiotemporal heterogeneity of macrophage phenotype in bone integration requires materials to have a multistage response capability. Moreover, traditional single-cell models cannot predict in vivo effects, and an immune—fibrovascular coculture platform needs to be established.

Limitations

Although this study provides valuable insights into the mechanisms of combined interventions, there are several limitations that should be acknowledged. First, although we propose potential pathways, such as immunomodulation and metabolic enhancement, the study lacks experimental validation through molecular biological assays or muscle biopsies. Second, the present study does not address the practical applicability of combined interventions in real-world clinical settings. Factors such as patient compliance with complex intervention regimens, the cost of implementing combined interventions and the demand for health care resources have not been evaluated. Future research should incorporate cost–benefit analyses and assess patient adherence to provide a more comprehensive understanding of the feasibility of combined interventions. Third, this study does not compare combined interventions with other approaches, such as single nutritional supplementation or pharmacological treatments. Future studies should include comparative analyses to determine the optimal treatment strategies for different patient populations and clinical contexts.

Clinical implications and future research directions

Despite the promising results of combined interventions in this study, their translation into clinical practice requires careful consideration. From a patient compliance perspective, combined interventions may pose challenges due to the complexity of adhering to multiple intervention components. However, the potential benefits of improved treatment outcomes may justify these challenges. Implementation costs and health care resource demands are also critical factors that need to be evaluated in future research to ensure the sustainability and accessibility of combined interventions.

To advance the field, future research should focus on several key areas. First, experimental studies employing molecular biological techniques and tissue biopsies are essential to validate the proposed mechanisms of combined interventions. Second, comparative studies with other intervention approaches are needed to establish the relative efficacy and safety profiles of combined interventions. Third, research should explore strategies to optimize patient compliance and minimize healthcare resource utilization while maintaining therapeutic effectiveness.

The emergence of ‘3D printing’ and ‘scaffolds’ as recent hotspots highlights promising technological advances; however, several recurring bottlenecks limit clinical translation: (1) manufacturing reproducibility and scale-up for consistent product quality; (2) regulatory and standardization challenges for novel materials and complex devices; (3) incomplete long-term safety and immunogenicity data across diverse biological conditions; (4) limited large-animal studies and multicenter preclinical validation; and (5) comparatively few randomized or multicenter clinical trials to demonstrate clinical efficacy. These factors help explain why many hotspot topics remain mainly in materials-oriented journals and preclinical reports rather than clinical publications.

Conclusion

Through bibliometric analysis, the complete trajectory of the ‘immunomodulatory biomaterials enhancing implant osseointegration’ field was outlined, from theoretical construction (OIM theory) to technological innovation (nanoengineering, 3D printing). Future efforts should focus on overcoming clinical translation bottlenecks, integrating intelligent response mechanisms with multiomics technologies, to advance bone integration therapy from ‘passive repair’ to ‘active regulation.’

Practically, this integration can be achieved through a stepwise technical pathway: first, using transcriptomic and proteomic profiling to identify immune or osteogenic signaling networks responsive to specific dynamic material cues (e.g., mechanical stress, ion release or surface potential changes); second, applying metabolomic and single-cell omics analyses to characterize temporal cellular states during dynamic stimulation; and finally, feeding these multiomics insights back into material design to fine-tune parameters such as degradation rate, topographical features or signal-responsive components, thereby enabling precision immunomodulation in bone regeneration.

Authors’ Contributions

All the authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; and have agreed on the journal to which the article has been submitted and to be accountable for all aspects of the work.

Footnotes

Author Disclosure Statement

The authors declare that they have no competing interests.

Funding Information

This research did not receive any funding support.

Ethics Approval and Consent to Participate

An ethics statement is not applicable because this study is based exclusively on published literature.

Availability of Data and Materials

All data generated or analyzed during this study are included in this published article.

Consent for Publication

The article is not submitted for publication or consideration elsewhere.

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Immunomodulatory Biomaterials for Implant Osseointegration: Knowledge Mapping (2005–2025)

Abstract

Impact Statement

Keywords

Introduction

Materials and Methods

Data source and search strategy

Rationale for database selection

Analytical tools and parameters

Sensitivity analysis and cross-validation

Results

Analysis of domain development trends

Annual publication volume trend

Country and institutional analysis

Journals and cocited journals

Authors’ publication status

Cocited references

Reference with citation bursts

Hotspots and frontiers

Discussion

General information

Analysis of development trends

Theoretical framework and core breakthrough in the field

The origin and core ideas of bone immunomodulation theory

Theoretical expansion and mechanism deepening

Keyword association and theoretical verification

Evolution of technology path and hotspot correlation

Multifactor coordination and intelligent materials

Synergistic effect of antibacterial and immune strategy

Research trends and challenges

Research hotspot migration

Core challenges

Limitations

Clinical implications and future research directions

Conclusion

Authors’ Contributions

Footnotes

Author Disclosure Statement

Funding Information

Ethics Approval and Consent to Participate

Availability of Data and Materials

Consent for Publication

References