Skip to main content
Wiley Open Access Collection logoLink to Wiley Open Access Collection
. 2025 Jan 24;14(20):2404768. doi: 10.1002/adhm.202404768

TPMS‐Gyroid Scaffold‐Mediated Up‐Regulation of ITGB1 for Enhanced Cell Adhesion and Immune‐Modulatory Osteogenesis

Jing Wang 1,2,3,4, Zenan Huang 1,2,3,4, Zhenzhong Han 1,2,3,4, Jing Luan 1,2,3,4, Zihan Li 2, Xutong Guo 2, Dongxu Yang 2, Yazhou Cui 1,2,3,4,5,, Jinxiang Han 1,2,3,4,, Duo Xu 1,2,3,4,
PMCID: PMC12333476  PMID: 39853929

Abstract

The porous structure is crucial in bone tissue engineering for promoting osseointegration. Among various structures, triply periodic minimal surfaces (TPMS) ‐Gyroid has been extensively studied due to its superior mechanical and biological properties. However, previous studies have given limited attention to the impact of unit cell size on the biological performance of scaffolds. In this research, four TPMS‐Gyroid titanium scaffolds with different unit cell sizes (TG15, TG20, TG25, and TG30) are fabricated using Selective Laser Melting (SLM) to explore their effects on osseointegration. Mechanical tests revealed that TG15 and TG20 exhibited superior compressive strength. In vitro experiments demonstrated that TG20 facilitated better cell adhesion through robust integrin protein expression initially, which subsequently enhanced cell proliferation and osteogenic differentiation. Furthermore, macrophages on TG20 showed higher Integrin β1 (ITGB1) expression, promoting their polarization to the M2 phenotype, which suppressed inflammation, fostered bone integration, and angiogenesis. In vivo studies confirmed TG20's effectiveness in promoting bone ingrowth by reducing inflammation. This study highlights TG20's structural advantages, making it a promising bone scaffold with exceptional osteogenic and angiogenic properties through osteoimmune microenvironment modulation. Therefore, TG20 holds significant potential for applications in bone tissue engineering.

Keywords: bio‐inspired bone scaffold, integrin, osseointegration, osteoimmunomodulatory, TPMS‐ Gyroid scaffolds


A) SLM generates biomimetic bone scaffolds with consistent porosity but varying TPMS‐Gyroid unit cell designs (TG15, TG20, TG25, TG30). B) By enhancing the expression of ITGB1, TPMS‐Gyroid scaffolds can facilitate osteogenic differentiation in BMSCs and promote M2 polarization in macrophages. C) The TG20 group exhibits the most significant effect in promoting M2 polarization of macrophages (C of TOC draw by figdraw ID:RPRAA55b5b). D) M2 polarization of macrophages further promotes angiogenesis and osteogenesis, thereby enhancing bone integration.

graphic file with name ADHM-14-0-g006.jpg

1. Introduction

As populations age and expand, the burden of functional impairments caused by bone diseases like osteonecrosis, osteoporotic fractures, and bone tumors grows increasingly severe.[ 1 , 2 ] Addressing weight‐bearing bone defects remains a significant challenge in orthopedic surgery, where advanced clinical strategies now include the use of 3D‐printed titanium alloy and biopolymer implants.[ 3 , 4 , 5 , 6 ] Both biopolymer scaffolds and titanium scaffolds are utilized in these strategies, each offering unique benefits and drawbacks.[ 7 ] Biopolymer scaffolds are known for their superior biocompatibility, bioactivity, and osteoconductivity.[ 8 , 9 ] And, titanium scaffolds excel in providing mechanical support due to their high strength and durability, making them suitable for weight‐bearing applications. Within these strategies, scaffolds play a crucial role in bone tissue engineering by providing structural support for new bone tissue.[ 10 ] However, the mismatch in modulus between implants and surrounding bones often leads to uneven stress distribution at the bone‐implant interface, causing stress shielding, which can shorten implant lifespan.[ 11 ] To address this, porous scaffolds have been developed,[ 12 , 13 ] mimicking natural bone's interconnected porous structure of cortical and trabecular bone to better match human skeleton stiffness, promote bony ingrowth, and enhance implant longevity.[ 14 ]

Triply periodic minimal surfaces (TPMS) have emerged as a distinctive approach to improving the performance of porous scaffold. TPMS structure has a mean curvature of zero in three directions, similar to the natural curvature of trabecular bone, making them an ideal choice for describing the aforementioned biomorphic space.[ 15 ] TPMS‐Gyroid typically offer several advantages over traditional strut‐based structures. They have the potential to enhance the mechanical strength, thermal stability, and surface area‐to‐volume efficiency of materials.[ 16 , 17 ] And this structure with a high surface area‐to‐volume ratio typically enhances cell adhesion, migration, proliferation, and nutrient transport.[ 18 ] TPMS‐Gyroid structure contributes to excellent stress distribution owing to its uniform structure.[ 17 ] Additionally, the key parameters of these structures, such as unit cell sizes and porosities, can be readily adjusted by modifying the control equation to better meet the mechanical property requirements.

The design of the TPMS‐Gyroid is achieved by modifying two key parameters in the governing equation: unit cell sizes and porosity.[ 19 ] Each unique set of values yields a distinct TPMS‐Gyroid.[ 20 ] The impact of structural characteristics on bone integration ability has been a focal point in research concerning TPMS‐Gyroid scaffolds. However, previous studies have predominantly concentrated on the effects of porosity while neglecting the critical factor of unit cell sizes.[ 21 , 22 ] Some investigations have also examined how variations in parameters such as pore size and wall thickness influence performance.[ 23 , 24 , 25 ] However, these adjustments do not facilitate precise structural modifications. Currently, there is a scarcity of research addressing how unit cell sizes affect the performance of TPMS‐Gyroid scaffolds, and the underlying mechanisms remain unclear. Optimizing an ideal TPMS‐Gyroid scaffold for enhanced bone integration through careful manipulation of these key parameters, along with elucidating their biological mechanisms, presents an urgent challenge that needs to be addressed.

The size of the unit cell alters the structure and shape of the TPMS‐Gyroid, which in turn, according to some literature reports, influences the expression of integrins on cells, ultimately affecting their phenotype. In macrophages, the shape changes resulting from scaffold shape influence the expression of ITGB1 within the integrin family.[ 26 , 27 , 28 ] ITGB1 subsequently activates the PI3K/Akt pathway, which negatively regulates the activation of NF‐κB. This signaling cascade promotes the expression of M2 phenotype markers while downregulating the production of inflammatory cytokines, thereby influencing macrophage polarization. macrophages are versatile and responsive, capable of polarizing into two types in response to various signals: activated inflammatory macrophages (M1) and anti‐inflammatory macrophages (M2).[ 29 , 30 ] Typically, M1 macrophages are involved in the inflammatory response by releasing pro‐inflammatory mediators such as interleukin 1beta (IL‐1β), interleukin 6 (IL‐6), and tumor necrosis factor α (TNF‐α). These pro‐inflammatory cytokines hinder osteoblast differentiation, resulting in low‐bone mass phenotypes.[ 31 , 32 ] In contrast, M2 macrophages produce interleukin‐1 receptor antagonist (IL‐1RA) and interleukin 10 (IL‐10), which create an anti‐inflammatory microenvironment and expedite tissue healing. It is therefore crucial to study the effect of the unit cell size of the TPMS‐Gyroid structure on macrophages in order to optimise the TPMS‐Gyroid scaffold.[ 33 , 34 , 35 ]

Despite extensive research on the influence of porosity or pore size on scaffold properties, a notable gap remains in understanding how variations in unit cell sizes affect scaffold behavior. In this study, we fabricated TPMS‐Gyroid titanium scaffolds with four different unit cell sizes using selective laser melting (SLM) to mimic the complex physical features in the native bone structure. To align with the typical porosity range observed in human cancellous bone, which is between 50% and 90%, a porosity of 70% was selected as a constant parameter.[ 36 , 37 ] The range of unit cell size is 1.5–3 mm. This was conducted in order to evaluate the most suitable scaffold morphology for bone growth. In vitro experiments, we conducted to investigate the differences in compressive performance, elastic modulus, cell adhesion, cell proliferation, osteogenic differentiation, angiogenesis and osteoimmunomodulatory of different scaffolds. In vivo experiments, we conducted to meticulously evaluate the bone regeneration process around the implant by micro‐CT and histological sections, and to verify the mechanism of macrophage polarization affecting osseointegration from the perspective of the bone immune microenvironment. This endeavor aims to contribute to advancements in TPMS‐Gyroid scaffolds for bone tissue engineering by establishing a robust framework for enhancing osteogenic and angiogenic properties through structural parameter optimization.

2. Results

2.1. Preparation and Characterization of the Scaffolds

Different Gyroid unit cell sizes (1.5, 2, 2.5, and 3 mm), uniform porosity distribution, and 0.7 porosity levels were designed using the MATLAB for STL modeling (Figure  1A). Following the pre‐processing of the STL file, the scaffold fabrication was conducted utilizing a SLM 3D printer.[ 38 ] As depicted in the Figure 1B, the printed scaffold displayed with no apparent structural flaws. Subsequent SEM (Scanning Electron Microscope) analysis was performed on the printed scaffold to thoroughly assess its microstructure (Figure 1B). The SEM analysis unveiled a relatively uniform and stable scaffold structure, featuring smooth surface transitions and the lack of notable structural defects like fractures or disintegration. The SEM/EDS (Energy Dispersive X‐Ray Spectrometer) analysis of the 3D printed surface indicates that the chemical composition aligns with that of the raw powder, exhibiting minimal oxidation (Figure 1C).

Figure 1.

Figure 1

Characterization of TPMS‐Gyroid scaffolds. A) Digital and images of TPMS‐Gyroid scaffolds. B) SEM image of TPMS‐ Gyroid scaffolds. C) The EDS results for TPMS‐Gyroid scaffolds. D) Compressive stress–strain curves of scaffolds. E) Elastic modulus and F) Yield strength of the scaffolds. p < 0.05.

As depicted in Figure 1D, the compressive curves of TPMS‐Gyroid structures exhibited initial elastic deformation, followed by a notable decrease in stress with increasing strain, culminating in sudden collapse after a fluctuating period. This fluctuation resulted from the gradual breakdown of the structures layer by layer during compression. We could also observe the mechanical strength of scaffolds decreased with the increase of unit cell size, and there are no significant differences between TG15 and TG20 (Figure 1F). The observed mechanical strength decrease with increasing unit cell size can be attributed to the anisotropy of the scaffolds. Specifically, smaller unit cell sizes (TG15 and TG20) increased the anisotropy of the scaffolds, leading to higher yield strengths.[ 39 ]

2.2. Biocompatibility of hBMSCs on Different TPMS‐Gyroid Scaffolds

SEM was employed to reveal the morphology of human bone marrow mesenchymal stem cells (hBMSCs) on diverse TPMS‐Gyroid scaffolds (Figure  2A). The results showed that the hBMSCs on the TG20 scaffold had a flatter and more morphological spread than those on the other scaffolds.[ 40 ] Some studies have shown that flatter morphological spread means that the scaffold has better cell adhesion capacity.[ 41 , 42 ] The adhesion of hBMSCs could further affect the cell proliferation and osteogenic ability.[ 27 ] To this end, we determined the relative gene expression levels of focal adhesion kinase (PTK2), vinculin (VCL) and integrin receptors Integrin β1 (ITGB1) in hBMSCs on various scaffold.[ 43 ] The gene expression of PTK2 and VCL in the TG20 group was significantly higher than those in the other groups, which proved that shuffling the scaffold could lead to better cell adhesion in hBMSCs (Figure 2B). ITGB1 which is a regulatory gene for cell adhesion, also show the same trend (Figure 2C). The results of immunofluorescence (IF) showed that at the edge of hBMSCs, we could observe more green spots representing focal adhesions (white arrows) in TG20 group, which also proved that the TG20 group scaffold had the most prominent property in cell adhesion (Figure 2D). Cell proliferation over time was assessed using the cell counting kit‐8 (CCK‐8) assay. As depicted in Figure 2E, no significant differences were observed in various groups on day 1. However, the TG20 scaffolds exhibited notably superior cell proliferation compared to the other groups at 4 and 7 days.

Figure 2.

Figure 2

In vitro results of osteogenesis tested with hBMSCs: A) SEM images of hBMSCs after incubation for 3 days. The PTK2, VCL B), and ITGB1 C) gene expression of hBMSCs cultured directly on scaffolds. D) Representative VCL immunofluorescence staining images. E) CCK‐8 assay showing cell proliferation after culturing with different scaffolds for 1, 4 and 7 days, respectively. F) Gross view (inset) images of ARS staining. p < 0.05.

To assess the TPMS‐Gyroid scaffolds on the osteogenic differentiation of hBMSCs, Alizarin Red S (ARS) staining was carried out. The Figure 2F and Figure S1A (Supporting Information) showed that calcium nodules could be observed in all groups, however, a significant increase in the number of calcium nodules was observed in the TG20. The quantitative evaluation also supported this result (Figure S1B, Supporting Information).

To evaluate the osteogenic gene expressions of hBMSCs. The expression levels of osteogenesis‐related gene OCN, RUNX2, and BSP, was shown in Figure S2 (Supporting Information). The results revealed that the expression levels of Osteocalcin (OCN), Runt‐related transcription factor 2 (RUNX2), and Bone sialoprotein (BSP) in TG20 were the highest among all groups.

2.3. Effects of Different TPMS‐Gyroid Scaffolds on Macrophage Polarization

Considering that hBMSCs can obtain higher cell adhesion and integrin expression through the TG20 scaffold, and the integrin family influences the phenotype of macrophages.[ 27 , 44 ] Therefore, it is speculated that the macrophages in the bone microenvironment will also be affected, so as to further regulate the osseointegration of each group of TPMS‐Gyroid scaffolds.[ 41 ] The role of macrophages as the primary immune cells in contact with an implant surface is crucial for innate immunity and wound healing. Macrophages can differentiate into pro‐inflammatory M1 or pro‐healing M2 phenotypes. Macrophages of the M2 phenotypes can promote osseointegration by secreting cytokines such as TGF‐β, IL‐10 and FGF2. Therefore, identifying the phenotypes of macrophages and the expression of ITGB1 within them is crucial for studying the importance of the unit cell size of TPMS‐Gyroid scaffolds on bone integration.

We examined the expression of M1 and M2 marker in the macrophage RAW264.7 cells by using the methods of IF, RT‐qPCR, and ELISA. The proliferation of macrophages after 1, 3, and 5 days of culture was evaluated using the CCK‐8 assay. As depicted in the Figure S3 (Supporting Information), the TG20 group demonstrated the highest rate of cell proliferation on Day 1 and Day 3. It is worth noting that compared with the TG20 group, the cell proliferation rates of the TG15 and TG25 groups were significantly reduced, while the difference was not significant compared to the TG30 group.

To determine differences in macrophage adhesion and integrin expression in different groups, macrophages seeded on different scaffolds were tested. As shown in Figure 3A, the Raw264.7 cells on the TG20 scaffold covered a larger area compared with the other groups, suggesting better promoting cellular‐adhesion ability than other groups. And The ITGB1 genes was more expressed in this group of macrophages (Figure S4, Supporting Information).

Figure 3.

Figure 3

In vitro immune responses of macrophages on various TPMS‐Gyroid scaffolds. A) Morphologies of Raw264.7 cells cultured on various TPMS‐Gyroid scaffolds for 3 day. B) Cytokine secretion of inflammatory cytokines IL‐6, IL‐1RA and IL‐10. Data are presented as mean ± SD (n = 3). indicates significant differences ( p < 0.05). C) RAW264.7 cells polarization was evaluated through immunofluorescence staining of CD206 (M2) and CD86 (M1). Scale bar = 100 µm. D,E) Quantitative analysis of CD206 and CD86 in immunofluorescence staining. F,G) Relative mRNA expression levels of macrophage‐related genes concerning TNF‐α, IL‐1β, iNOS, IL‐10, IL‐1RA, and Arg‐1. p < 0.05.

Subsequently, the fold changes in M1 and M2 macrophages gene expression were standardized to those of the TG15 group. In this context, inducible nitric oxide synthase (iNOS), TNF‐α, and IL‐1β were identified as M1‐related genes due to their pro‐inflammatory characteristics. Conversely, Arginase 1 (Arg‐1), IL‐10, and IL‐1RA were categorized as M2‐related genes for their roles in anti‐inflammatory responses and growth promotion. The inflammatory gene expression level of IL‐1β was highest in the TG30 group compared to other groups. Regarding the M2‐related genes, the gene expression of IL‐10 in the TG20 group was twice as high as that in the TG30 group as shown in Figure 3F,G.

To explore the impact of 4 different scaffolds on RAW 264.7 macrophages and the related molecular mechanisms, culture supernatant was collected, and the levels of various inflammation‐related cytokines were measured using ELISA. The concentration of IL‐6 was found highest in the TG30 group on Day 3. The TG20 group elicited the most significant secretion of IL‐10 and IL‐1RA in RAW 264.7 macrophages among all groups (Figure 3B).

In vitro polarization of macrophages was qualitatively assessed through immunofluorescence staining of the expression levels of CD206 and CD86. On confocal laser microscopy, signals labeled as M1 and M2 could be clearly observed. IF staining revealed the presence of CD206 (yellow, M2 macrophage marker) and CD86 (red, M1 macrophage marker) as shown in Figure 3C. The Figure 3D,E illustrated that LPS (Lipopolysaccharide) stimulation in the TG30 group significantly increased the proportion of M1 macrophages (CD86) compared to the other groups. Conversely, in the TG20 group, most macrophages exhibited the anti‐inflammatory M2 phenotype marked by CD206.

2.4. Osteogenic Activity and Angiogenesis in Macrophage‐Conditioned Medium

To investigate the impact of macrophage polarization on osteogenic differentiation, hBMSCs were induced using macrophage‐conditioned medium (MCM). After 14 days of culture, hBMSCs were assessed using ALP (Alkaline Phosphatase) staining, revealing positive ALP expression in all groups. Notably, the TG20 and TG15 groups demonstrated the highest osteogenic potential after 14 days of culture, whereas the TG25 and TG30 groups exhibited a similar osteogenic effect on hBMSCs (Figure 4B). The quantitative ALP activity values were consistent with the staining results, as depicted in Figure 4D. Similar results were observed in the ARS staining after 21 days of culture (Figure 4A,C).

Figure 4.

Figure 4

Effects of inflammatory microenvironment derived from the macrophage for BMSCs. The images of ARS staining A) and ALP staining B). The quantitative measurement of ARS (C) staining and D)ALP staining. E) The relative gene expression of osteogenic (RUNX2, OCN, and BSP). F) The result of Western blot for osteogenic (COL1, p‐RUNX2, and BMP2). G) Representative RUNX2 immunofluorescence staining images and quantitative analysis H). Scale bar = 100 µm. p < 0.05.

Quantitative analysis of osteogenic gene expression was conducted using RT‐qPCR. The results showed that early osteogenic gene RUNX2 in the TG20 group was expressed at a higher level than the other three groups on Day 14. The expression of the BSP and OCN genes in the TG20 group were significantly higher than those in TG30 group (Figure 4E).

Analysis of osteogenic‐related proteins was conducted using Western blotting and IF techniques. The Western blotting results revealed that the expression of collagen I (COL1), BMP2 and phospho‐RUNX2 (p‐RUNX2) in the TG30 group was significantly lower compared to the other three groups (Figure 4F). Gray value analysis indicated that protein expression was notably higher in the TG20 group (Figure S5, Supporting Information). The IF analysis of RUNX2 also supported this finding (Figure 4G,H).

As shown in Figure 5H,I, HUVECs migration was evident in all groups, and the most amounts of migrated cells could be observed in TG20 group. The matrigel assay was used to support the tubular formation of HUVECs. Quantitative analysis of the nodes (primary stage of angiogenesis), meshes (middle stage of angiogenesis), total mesh area, and total tube length indicated that the formation of tubular structured cells was enhanced with MCM from TG20 group (Figure 5A–F). The expression levels of angiogenesis‐related genes were estimated by using RT‐qPCR (Figure 5G). The HUVECs cultured with TG20 MCM depicted higher fold change in the expression of hypoxia inducible factor‐1α (HIF‐1α) and vascular endothelial growth factor (VEGF) than those cultured with TG15 and TG30. In brief, the results corroborated that TG20 group could enhance osteogenesis and angiogenesis by increasing M2 polarization of macrophages.

Figure 5.

Figure 5

Effects of angiogenesis derived from the various MCM. A) Tube formation of HUVECs. Scale bar = 200 µm. B) immunofluorescence images of tube formation (DAPI and F‐actin). Scale bar = 200 µm. C–F) Quantification of, nodes, junctions, meshes, and total length. G) The relative gene expression of HUVECs (HIF‐1α and VEGF). H) Representative images of the transwell migration assay and I) quantitative analysis of migrated HUVECs determined by crystal violet staining (n = 3). p < 0.05.

2.5. Bone Remodeling and Macrophage Phenotypes In Vivo

In vivo, Arg‐1 (green, M2 macrophage maker) and iNOS (red, M1 macrophage maker) were detected by IF staining. We observed larger amounts of macrophages expressing M1 markers (iNOS) after coincubation with TG30 scaffold (Figure 6A). On the contrary, infiltration of the M1 macrophages was decreased in the TG20 group and the proportion of anti‐inflammatory M2 macrophages (Arg‐1) was increased.

As depicted in Figure  6B,C, the fluorescence intensity of HIF1‐α and RUNX2 increased correspondingly with Arg‐1 in all groups, and the highest intensity appeared in TG20 group. The ability of promoting osteogenesis and angiogenic was opposite to expression of iNOS. Further quantitative analysis showed that comparing to TG30 group, the iNOS intensity decreased to 51%, 33% and 69%, respectively (p < 0.05) (Figure 6D–F). These results suggested that the mechanism of TG20 scaffold promoting osteogenesis and angiogenic was regulating the polarization of macrophages In vivo.

Figure 6.

Figure 6

Polarization characterization In vivo at day 7. A) Immunofluorescence staining images of Arg‐1/iNOS/DAPI for osteoimmune microenvironment. B) Immunofluorescence staining images of RUNX2/OCN/DAPI for osteogenesis. C) Immunofluorescence staining images of HIF‐1α/DAPI for angiogenesis. Scale bar in (A) (B) and (C) is 50 µm. Representative immunofluorescence staining images and quantitative analysis of macrophages (D), osteogenesis (E), and angiogenesis (F). p < 0.05.

2.6. New Bone Formation Assessment

To confirm the occurrence of osteogenesis In vivo, the scaffold location was observed by using micro‐CT. The 3D microcomputed reconstruction tomography revealed that the scaffolds remained in their original position for as long as 10 weeks without dislocation or deformation. The reconstructed images of the newly formed bone demonstrated that the osseous tissue enveloped and penetrated the internal structure of the scaffolds, with clearer observations at 10 weeks (Figure 7A).

Figure 7.

Figure 7

In vivo osseointegration of different implants: A) Reconstructed (transverse, sagittal) and 3D Micro‐CT images of scaffolds (white) and new bone (orange). Quantitative analysis of the micro‐CT data, including BV/TV B), Tb.Sp C) and BV D). p < 0.05.

The quantitative results indicated that every scaffold exhibited significantly higher bone volume (BV) and bone volume over total volume (BV/TV) values at 10 weeks than at 5 weeks, which corroborated the 3D imaging characteristics. Regardless of whether it was 5 weeks or 10 weeks, the TG20 scaffold presented the highest rate of newly formed bone among all groups, significantly higher than that for the TG15 group (Figure 7B,D). Similarly, the trabecular separation/spacing (Tb. Sp) also supported that the TG20 scaffold possessed the most powerful ability of osseointegration (Figure 7C). The results showed that bone volume around the implant increased over time and that bone tissue growth gradually matured at different intervals. At 10 weeks, it could be observed the greatest bone ingrowthin the TG20 group, with ≈1.23 times higher BV than in the TG15.

Hard tissue sections were stained with H&E and Goldner trichrome to observe the appearance of the new bone formation surrounding the scaffolds (Figure 8). After 5 weeks of implantation, the newly formed bone matrix was similar to the TPMS‐Gyroid scaffolds. At 10 weeks, more new bones were observed to tightly connected with the pores of the scaffold and grow into the pores. The H&E staining images (Figure  8A) showed that in TG20 group, new bone tissue around the implants was thicker than other groups. The contact area of the scaffold with new bone in TG20 group was also significantly increased compared with that in the other groups. Additionally, similar results were observed in Goldner staining images (Figure 8B). This trend is consistent with the results obtained from micro‐CT. Overall, TG20 group implants not only promoted the formation of new bone, but had a positive effect on its maturation.

Figure 8.

Figure 8

Histological observation of the peri‐implant tissues after A) H&E staining and B) Goldner staining at 5 weeks and 10 weeks. Scale bar of black = 2 mm. Scale bar white = 500 µm.

3. Discussion

In this study, TPMS‐Gyroid scaffolds with different unit cell sizes of 1.5 mm (TG15), 2 mm (TG20), 2.5 mm (TG25), and 3 mm (TG30) were fabricated via SLM for bone tissue engineering applications. With a fixed porosity rate of 70%, the study investigated the impact of varying unit cell sizes on TPMS‐Gyroid scaffolds, providing a deeper mechanistic understanding of how cells perceive and interact with these scaffolds. The surface morphologies observed by SEM showed that the TPMS‐Gyroid scaffolds are constructed by a sequential surface structure with high relative surface areas and improved permeability, which lead to admirable biological adaptability. Regarding the mechanical properties of the scaffolds, we conducted compression tests. The results indicate that there are no statistical differences in the elastic moduli among the four groups of scaffolds, all residing ≈ 10 GPa. Comparing these values to the elastic moduli of normal cortical and cancellous bones, all four scaffolds are deemed suitable for use. Regarding the yield strength, the scaffolds in the TG15 and TG20 groups exhibited higher values than those in the TG25 and TG30 groups. It is crucial that the yield strength of the scaffolds significantly exceeds the maximum stress the implantation site can endure. Simultaneously, the elastic modulus of the scaffolds should closely match the bone at the implantation site to ensure a good interface match and enhance durability. Considering these factors, the mechanical properties of the TG15 and TG20 scaffolds better align with current requirements for bone tissue engineering applications.

The results of In vitro experiments on hBMSCs co‐culture with scaffolds showed that hBMSCs on scaffolds of different unit cell sizes showed different cell adhesion morphologies, which may be related to factors such as the curvature or shape of the scaffold.[ 28 , 42 , 45 ] The shape of the cell membrane is limited by the scaffold structure, and the curvature‐mediated interaction of the cell membrane is critical in many biological processes. Studies have shown that the shape of cells can regulate the expression of integrins, and the expression of integrins affects the amount of focal adhesion proteins. The regulation of this integrin affects the ability of cells to adhesion, which causes intracellular pressure gradients, which trigger intracellular movements and alter cell phenotypes.[ 46 ] For hBMSCs in TPMS‐Gyroid scaffolds, this change is manifested by high expression of the integrin family ITGB1, and further improvement of cell proliferation and osteogenic ability through the ITGB1/FAK/ERK1/2 signaling pathway.[ 41 , 43 , 47 ] The results of In vitro experiments also confirmed this point, and the expression of integrin and focal adhesion of hBMSCs in TG20 group was the highest, and its osteogenic ability was also the most powerful. Therefore, the TG20 group is more suitable for cell adhesion, so as to obtain better biocompatibility and osseointegration.

The shape of macrophages, which are key cells that bind to the surface of implants, is controlled by the unit cell size of the TPMS‐Gyroid structure, resulting in varying levels of ITGB1 expression.[ 48 ] ITGB1 further activates the PI3K/Akt pathway, which negatively regulates the activation of NF‐κB,[ 44 ] thereby promoting the expression of M2 phenotype markers and downregulating the expression of inflammatory cytokines.[ 49 ] The polarization state of macrophages influences their production of proinflammatory cytokines and mediators.[ 50 , 51 ] M1 macrophages function in the host defense system during inflammatory conditions, acting as microbial‐clearing and antigen‐presenting cells through the release of proinflammatory factors. Conversely, M2 macrophages contribute to inflammation resolution by producing anti‐inflammatory compounds and growth factors.[ 50 , 52 , 53 ] Hence, modulating the unit cell size within the scaffold structure can further regulate the expression level of ITGB1.[ 48 ] This regulatory mechanism significantly enhances the expression of M2 markers in macrophages, subsequently modulating the immune microenvironment surrounding the implant through the suppression of inflammatory responses. This process facilitates wound healing and promotes bone tissue regeneration. Through in vitro experiments, we validated the polarization levels of macrophages and the expression of ITGB1. As described previously, the TPMS scaffolds, particularly the TG20 group, were found to enhance macrophage M2 polarization by increasing ITGB1 expression.

During the bone remodeling process, immunoregulation and angiogenesis are essential prerequisites for enhancing osteogenesis.[ 54 ] Our research validated that TPMS‐Gyroid scaffold, especially TG20 group can comodulate the immune response by polarizing M1 macrophages to the M2 phenotype, which can mitigate inflammatory responses.[ 55 ] The results indicated that the M2 phenotype of macrophages regulated immune response and promoted the expression of ALP and RUNX2 by BMSCs. ALP plays a critical role in early osteogenesis and hydrolyzes various types of phosphates to promote osteoblast maturation.[ 56 , 57 ] RUNX2 regulates anabolic bone formation and calcium metabolism.[ 58 ] The M2 macrophages could exert an essential effect on osteoblast propagation, differentiation, and bone mineralization at the stimulation of cytokines such as FGF2, IL‐10 and TGF‐β.[ 56 , 59 ] Moreover, angiogenesis, a sequential cascade during the healing of bone defect, is also essential for the regenerative process, and robust angiogenesis can restore the blood supply to compromised osseous tissues.[ 60 ] The existence of functional vascular network can generate a distinct metabolic and molecular microenvironment to mediate the construction of bone vasculature and to maintain osteoprogenitors recruitment and osteogenic differentiation. As reported, the secretion level of VEGF is positively related to polarization of M2 macrophages, and the secretion of VEGF into the extracellular environment plays a crucial role in promoting endothelial cell viability, propagation, migration, and thus protecting vascularization.[ 61 , 62 ] The result showed that the macrophage polarization in the TG20 group could effectively enhance cell migration, stimulate the capillary tube formation of HUVECs.

We sufficiently demonstrated in this study that the structure of TG20 was the most suitable for osseointegration. However, several limitations remain to be addressed. While we investigated the impact of TPMS‐Gyroid scaffolds with various unit cell sizes on osteogenesis and macrophage polarization through integrin expression, the mechanism by which scaffold structure transduces physical signals to regulate biochemical cues modulating integrin expression remains unclear. Additionally, due to limitations in slicing technology, we did not discuss the direction of bone growth. Further research into RNA sequencing and the specific molecular mechanisms underlying osteogenesis and immune modulation capacities is also warranted in the future.

4. Conclusion

To investigate the impact of unit cell size on osseointegration in TPMS‐Gyroid scaffolds and optimize the optimal unit cell size, we successfully developed four types of TPMS‐Gyroid scaffolds. The results indicated that the TG20 scaffold, among the four tested groups, exhibited superior ability to promote ITGB1 expression, which in turn enhanced cell adhesion, osteogenic differentiation, and modulated macrophage phenotype. This modulation of macrophage phenotype, specifically toward M2 polarization, further promoted bone formation and angiogenesis. This is finding underscores unit cell size as a crucial parameter for tailored design in specific biomechanical environments. These results not only deepen our understanding of cell‐material interactions but also pave new avenues for preclinical research on TPMS‐Gyroid scaffolds.

5. Experimental Section

TPMS‐Gyroid Scaffolds Designed

The scaffolds were designed via MATLAB. The samples size was 10 × 10 × 10 mm3 for mechanical testing, 10 × 10 × 2 mm3 and 20 × 20 × 2 mm3 for In vitro experiments. A cylindrical lattice cell was specified with a height and diameter of 6 mm (φ 6 × 6 mm3) for In vivo experiments. The scaffolds were generated with unit cell sizes of 1.5, 2, 2.5, and 3 mm, porosity of 70%, respectively.

TG:sin2πxacos2πya+sin2πyacos2πza+sin2πzacos2πxa=C (1)

The surface of gyroids was modelled using Equation (1), According to Equation (1), “a” represents the unit cell size, “C” represents the offset parameter for lattice structures, and “x, y, z” represents the spatial coordinates within the scaffold interior. Subsequently, the finalized model was exported as an STL file for 3D printed. the overall structure of scaffolds can be tailored by modifying both the unit cell size “a” and the offset parameter “C”. Some studies have noted a linear relationship between C and porosity,[ 63 ] and similar findings have been confirmed through the tests, as illustrated in the accompanying Figure S6 (Supporting Information).

Fabrication of the Scaffolds

All specimens in this study were manufactured using Ti6Al4 V metal powder on a SLM metal 3D printer (AF250, China). The initial STL files underwent post‐processing, which involved positioning the models at the appropriate printing angle and generating supporting structures. The printing parameters were configured as follows: a laser spot size of 60 µm, fill scanning power of 181 W, layer thickness of 0.05 mm, fill scanning speed of 0.89 m s−1, contour scanning speed of 0.89 m s−1, contour scanning power of 146 W, and scanning spacing of 0.08 mm.

Post‐Treatment

After 3D printing, the scaffolds underwent a series of post‐processing steps to ensure their quality and suitability for further experiments. Specifically, the printed scaffolds underwent a heat treatment at 900 °C for 3 h to eliminate stress and repair crystalline defects. Following cooling, the scaffolds were subjected to ultrasonic cleaning to remove any excess powder. To ensure sterility, the scaffolds were then washed three times each with ultrapure water and anhydrous ethanol before being dried and stored for future use. If intended for use in cellular experiments, the scaffolds were additionally subjected to autoclaving for sterilization.

Sample Characterization

Uni‐axial compression tests were conducted at a loading rate of 0.4 mm min−1 utilizing an EZ20 Universal Material Testing Machine from Lloyd Instruments Ltd., UK. The material compositions of the lattices were analyzed by using Energy Dispersive X‐Ray Spectrometer (EDS) from Oxford Instruments, UK. Scanning Electron Microscopy (SEM) at a 30 kV acceleration voltage, performed with a ZEISS EVO18 instrument, was employed to assess the printed quality of the structures.

Cell Culture

The endothelial cell line (HUVEC, ATCC) and human bone marrow mesenchymal stem cells (hBMSCs; Cyagen) were utilized in the In vitro experiment. The hBMSCs were cultured in alpha modification (α‐MEM) solutions containing 10% fetal bovine serum (FBS; Gibco, USA). The murine‐derived macrophage cells (RAW264.7) obtained from the Cell Bank/Stem Cell Bank at the Chinese Academy of Sciences were cultured in Dulbecco's Modified Eagle's Medium (DMEM; Gibco, USA) Human monocytes (THP‐1 cells obtained from the Cell Bank/Stem Cell Bank at the Chinese Academy of Sciences) were used in the experiment. The THP‐1 cell line was cultured in RPMI 1640 medium (Gibco, USA). All cell were supplemented with 10% FBS, 100 µg mL−1 streptomycin, and 100 U mL−1 penicillin, and maintained at 37 °C in a humidified atmosphere with 5% CO2. Cell passages were performed when cells reached 80–90% confluence. The culture medium was refreshed every two days to maintain cell viability and growth.

Preparation of MCM from Macrophages

THP‐1 and Raw264.7 cells were cultured in DMEM on 4 groups scaffold at a density of 2 × 104 cells well−1 and incubated for 3 days. THP‐1 cells were cultured with Phorbol 12‐myristate 13‐acetate (PMA) (100 ng mL−1) and LPS (10 ng mL−1). The medium was collected and centrifuged at 1500 rpm for 15 min, and the supernatant was obtained after removing debris using a 0.22 µm filter

Proliferation of Cells

The Cell Counting Kit‐8 (CCK‐8) assay was used to assess the proliferation of hBMSCs incubated with TPMS‐Gyroid scaffolds (TG15, TG20, TG25 and TG30). The absorbance of the samples was measured at 450 nm using a microplate reader to evaluate cell viability and proliferation over the specified time points.

Osteogenic Activity

For osteogenic differentiation induction, hBMSCs were seeded at a density of 1 × 105 cells/well on 6‐well plates and maintained in osteogenic differentiation basal medium (Cyagen Biosciences, China) containing 10% FBS, 10 mM β‐glycerophosphate, 0.1 µM dexamethasone and 0.25 mm ascorbate for a duration of 7,14 or 21 days.

For Alkaline Phosphatase (ALP) and Alizarin Red S (ARS) staining were carried out. The hBMSCs at a density of 2 × 104 cells cm−2 were cultured in a 24‐well plate. After a 14‐day incubation, osteogenic differentiation was evaluated by measuring ALP levels using a BCIP/NBT Kit (Beyotime Biotechnology, China). After culturing hBMSCs at a density of 2 × 104 cells/well for 21 days, mineralized nodules were observed using the ARS assay. The absorbance of the samples was measured at 562 nm using a spectrophotometer, and the average value of three measurements for each sample was recorded to assess mineralization levels indicative of osteogenic differentiation.

RT‐qPCR

RNA was extracted from the cells using TRIzol reagent (Life Technologies, USA). The extracted RNA was then reverse transcribed into cDNA using ReverTra Ace qPCR RT Master Mix with gDNA Remover (TOYOBO, Japan). Reverse transcription quantitative polymerase chain reaction (RT‐qPCR) was performed using Realtime PCR Master Mix (TOYOBO, Japan), on a LightCycler 480 instrument (Roche, Switzerland). and the primer sequences used in this experiment are detailed in Table S1 (Supporting Information).

Western Blotting

The total proteins were extracted from cells using Radio Immunoprecipitation Assay (RIPA) lysis buffer, and the protein concentrations were quantified using the bicinchoninic acid (BCA) assay. Equal amounts of proteins were separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS‐PAGE) and transferred onto a PVDF blotting membrane. The membranes were blocked with 5% (w/v) skimmed milk (Cell Signaling Technology, USA) at room temperature for 1 h. Subsequently, they were incubated with primary antibodies overnight at 4 °C. The secondary antibody was applied and detected using chemiluminescent HRP Substrate (Millipore). GAPDH was utilized as a control, and the antibodies used in this experiment are detailed in Table S2 (Supporting Information).

Immunofluorescence (IF) Staining

The cells were fixed with 4% paraformaldehyde and permeabilized using 0.5% Triton X‐100. Subsequently, the cells were blocked in PBS with 10% goat serum for 1 h and then incubated overnight at 4 °C with primary antibodies. Following primary antibody incubation, the cells were washed and incubated with secondary antibodies. Additionally, Alexa Fluor 594‐phalloidin (diluted 1/200) was used for F‐actin staining, and DAPI was used for nuclear staining. Cell images were captured using a fluorescence microscope (OLYMPUS FLUOVIEW FV3000).

Cytokine Secretion Assays

The levels of inflammatory cytokines (IL‐1RA, IL‐6 and IL‐10) secreted by RAW264.7 cells after 3 days of culture were quantified using the enzyme‐linked immunosorbent assay (ELISA) kits (R&D Systems, USA; Boster Bio, China) following the manufacturer's protocols.

Angiogenic Assays

The 12‐well plates and tips were pre‐chilled at −20°C. Matrigel Matrix (Corning, USA) was thawed at 4 °C and dispensed into a pre‐chilled 12‐well plate on ice at a volume of 600 µL per well. The plate was then incubated at 37 °C for 1 h, and 500 µL of CM was added to each well for culturing with 1 × 105 HUVECs for 6–24 h. Subsequently, the cells were fixed using 4% paraformaldehyde, stained with Alexa Fluor 594‐Phalloidin (Solarbio, China) and DAPI, and observed under an inverted fluorescence microscope (OLYMPUS IX73, Tokyo, Japan). The Angiogenesis Analyzer plugin of ImageJ‐Fiji was used to process the images. This process was repeated three times.

Migration of HUVECs

In brief, the migration of HUVECs was assessed using 24 mm transwell inserts with 8.0 µm pore‐size membranes (Corning, USA). THP‐1 cells were cultured in DMEM supplemented with 10% fetal bovine serum and 100 ng mL−1 PMA in a 6‐well plate for 48 h. HUVECs were seeded in transwell inserts at a density of 1 × 105 cells/well insert and cultured in DMEM supplemented with 10% FBS and 1% (v/v) penicillin/streptomycin. After 24 ho of incubation, the cells were washed, fixed in a 4% paraformaldehyde buffer solution, and stained with crystal violet for 30 min. The unmigrated cells on the upper surface of the transwell inserts were removed, and the inserts were washed with PBS. The samples were visualized under a phase‐contrast microscope (OLYMPUS IX73, Tokyo, Japan).

In Vivo Experiments

The animal protocol received approval from the Animal Ethics Committee at The First Affiliated Hospital of Shandong First Medical University (Shandong, China) (2024‐S6076). In vivo experiment, 2.5 kg female New Zealand white rabbits were randomly allocated to four groups: TG15, TG20, TG25, and TG30. The defect with a 3 mm radius in the distal femur was operated, and then implanted the scaffolds to evaluate the osseointegration capabilities of these groups.

Immunohistochemistry and Immunofluorescence In Vivo

Following a 7‐day post‐implantation period, the animals were humanely euthanized by administering a lethal dose of anesthetic. Subsequently, femoral bone specimens were harvested, properly fixed, and decalcified post‐implant removal. A 3% hydrogen peroxide solution was utilized to deactivate endogenous peroxidase enzymes. The processed femoral bone specimens were then embedded in paraffin and incubated overnight at 4 °C with antibodies targeting RUNX2, OPN, HIF‐1α, iNOS, and Arg‐1. Tissue sections underwent TSA multiple fluorescence immunostaining with secondary antibodies. Finally, the sections were examined under a fluorescence microscope at various magnifications, and the average staining intensity was quantitatively analyzed using ImageJ‐Fiji.

Micro‐CT Evaluation

Two batches of animals were euthanized, and the femurs containing the implants were collected after 5 and 10 weeks, respectively, for further analysis. The femoral condyles were dissected and immersed in a 10% buffered formalin solution for preservation and evaluation. The specimens were scanned using a micro‐computed tomography (micro‐CT), with scanning parameters configured to 90 kV, 88 µA, and a voxel size of 144 µm. The reconstructed cross‐sectional images were exported for further analysis and evaluation.

Histology Evaluation

The fixed femur specimens were dehydrated through a series of graded ethanol solutions. The specimens were then embedded in polymethylmethacrylate and longitudinally sectioned using an iKa system (300 CP, Exakt) to attain a thickness of 100 µm. The sections underwent grinding and polishing processes, leading to a final thickness of ≈ 15 µm, suitable for subsequent H&E and Goldner staining. Ultimately, the prepared sections were used for histological assessment.

Statistical Analysis

The results of the biological tests were reported as the standard error of the mean based on a minimum of 3 biological replicates (n = 3). Comparison of parameters for multiple groups were performed by one‐way analysis of variance (ANOVA) with the Tukey significant difference post hoc test. Statistical analysis and exponential curve fitting were conducted with SPSS 19.0 software. A significance level of p < 0.05 was used to determine statistical significance.

Conflict of Interest

The authors declare no conflict of interest.

Supporting information

Supporting Information

ADHM-14-0-s001.docx (465.8KB, docx)

Acknowledgements

J.W. and Z.H. contributed equally to this work. This research was supported by the Shandong Province Natural Science Foundation (Grant No. ZR2022QH218), the Academic Promotion Programme of Shandong First Medical University (2019LJ001), the Innovation Project of Shandong Academy of Medical Sciences.

Wang J., Huang Z., Han Z., Luan J., Li Z., Guo X., Yang D., Cui Y., Han J., Xu D., TPMS‐Gyroid Scaffold‐Mediated Up‐Regulation of ITGB1 for Enhanced Cell Adhesion and Immune‐Modulatory Osteogenesis. Adv. Healthcare Mater. 2025, 14, 2404768. 10.1002/adhm.202404768

Contributor Information

Yazhou Cui, Email: yzcui@sdfmu.edu.cn.

Jinxiang Han, Email: jxhan9888@aliyun.com.

Duo Xu, Email: xuduo@sdfmu.edu.cn.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  • 1. Wang N., Fuh J. Y. H., Dheen S. T., Kumar A. S., J. Biomed. Mater. Res. B Appl. Biomater. 2021, 109, 160. [DOI] [PubMed] [Google Scholar]
  • 2. Arash A., Yuncang L., Milan B., Cuie W., Acta Mater. 2018, 158, 354. [Google Scholar]
  • 3. Zhang J., Zhou W., Wang H., Lin K., Chen F., J. Mater. Sci. Technol. 2019, 35, 336. [Google Scholar]
  • 4. Wang Y., Chen Q., Powder Technol. 2015, 270, 1. [Google Scholar]
  • 5. Kurtz S. M., Devine J. N., Biomaterials 2007, 28, 4845. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Lei H., Zhou Z., Liu L., Gao C., Su Z., Tan Z., Feng P., Liu M., Zhou C., Fan Y., Zhang X., Acta Biomater. 2023, 169, 625. [DOI] [PubMed] [Google Scholar]
  • 7. Shuai C., Yang W., Feng P., Peng S., Pan H., Bioact. Mater. 2021, 6, 490. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Shuai C., Guo W., Wu P., Yang W., Hu S., Xia Y., Feng P., Chem. Eng. J. 2018, 347, 322. [Google Scholar]
  • 9. Feng P., Wu P., Gao C., Yang Y., Guo W., Yang W., Shuai C., Adv. Sci. 2018, 5, 1700817. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Huiskes R., Weinans H., Van R. B., Clin. Orthop. Relat. Res. 1992, 274, 124. [PubMed] [Google Scholar]
  • 11. Yan C., Hao L., Hussein A., Young P., J. Mech. Behav. Biomed. Mater. 2015, 51, 61. [DOI] [PubMed] [Google Scholar]
  • 12. Pei X., Wang L., Zhou C., Wu L., Lei H., Fan S., Zeng Z., Deng Z., Kong Q., Jiang Q., Liang J., Song Y., Fan Y., Gou M., Zhang X., Mater. Des. 2022, 221, 110964. [Google Scholar]
  • 13. Pei X., Wang L., Wu L., Lei H., Feng P., Fan C., Zhou Z., Wang L., Liu M., Zhou C., Kong Q., Fan Y., Compos. Struct. 2023, 323, 117516. [Google Scholar]
  • 14. Husna N., Lee C. C., Norbahiyah S., Sanuddin A. B., Australian J. Basic & Appl. Sci. 2014, 8, 160. [Google Scholar]
  • 15. Bouakaz I., Drouet C., Grossin D., Cobraiville E., Nolens G., Acta Biomater. 2023, 170, 580. [DOI] [PubMed] [Google Scholar]
  • 16. Yanez A., Cuadrado A., Martel O., Afonso H., Monopoli D., Mater. Des. 2018, 140, 21. [Google Scholar]
  • 17. Rati V., Singh N., Rai S., Kumta S., Advances in Computational Methods in Manufacturing, Springer Singapore, Singapore: 2019, pp. 955–966. [Google Scholar]
  • 18. Yoo D. J., Int. J. Precision Eng. Manufactur. 2014, 15, 1657. [Google Scholar]
  • 19. Araya M., Jaskari M., Rautio T., Guillén T., Järvenpää A., J. Sci.: Adv. Mater. Devices 2024, 9, 100663. [Google Scholar]
  • 20. Zhao D., Liang H., Han C., Li J., Liu J., Zhou K., Yang C., Wei Q., Addit. Manuf. 2021, 47, 102223. [Google Scholar]
  • 21. Ali D., Sen S., J. Mech. Behav. Biomed. Mater. 2017, 75, 262. [DOI] [PubMed] [Google Scholar]
  • 22. Wang Z., Liao B., Liu Y., Liao Y., Zhou Y., Li W., J. Biomed. Mater. Res., Part B. 2024, 112, e35337. [DOI] [PubMed] [Google Scholar]
  • 23. Seehanam S., Khrueaduangkham S., Sinthuvanich C., Sae‐Ueng U., Srimaneepong V., Promoppatum P., Heliyon 2024, 10, e26005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Taniguchi N., Fujibayashi S., Takemoto M., Sasaki K., Otsuki B., Nakamura T., Matsushita T., Kokubo T., Matsuda S., Mater. Sci. Eng., C. 2016, 59, 690. [DOI] [PubMed] [Google Scholar]
  • 25. Liu Q., Wei F., Coathup M., Shen W., Wu D., Adv. Healthcare Mater. 2023, 12, 2301111. [DOI] [PubMed] [Google Scholar]
  • 26. Huang C., Fu X., Liu J., Qi Y., Li S., Wang H., Biomaterials 2012, 33, 1791. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Cha B.‐H., Shin S. R., Leijten J., Li Y.‐C., Singh S., Liu J. C., Annabi N., Abdi R., Dokmeci M. R., Vrana N. E., Ghaemmaghami A. M., Khademhosseini A., Adv. Healthcare Mater. 2017, 6, 1700289. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28. Sun F., Li H., Hu Y., Zhang M., Wang W., Chen W., Liu Z., ACS Nano 2023, 17, 18584. [DOI] [PubMed] [Google Scholar]
  • 29. Chen Z., Klein T., Murray R. Z., Crawford R., Chang J., Wu C., Xiao Y., Mater. Today 2016, 19, 304. [Google Scholar]
  • 30. Shapouri‐Moghaddam A., Mohammadian S., Vazini H., Taghadosi M., Esmaeili S. A., Mardani F., Seifi B., Mohammadi A., Afshari J. T., Sahebkar A., J. Cell. Physiol. 2018, 233, 6425. [DOI] [PubMed] [Google Scholar]
  • 31. Isakov E., Weisman‐Shomer P., Benhar M., Bioch. Biophys. Acta. 2014, 1840, 3153. [DOI] [PubMed] [Google Scholar]
  • 32. Mohsen M. A., Afifi A. A., Al‐Bagoury I., Int. J. Osteoporosis & Metabolic Disorders 2012, 5, 13. [Google Scholar]
  • 33. P.‐L. A., Ummarino A., Khan S., Guildford A., Allan I. U., Santin M., Chevallier N., Varaillon E., Kon E., Allavena P., Nanomed.: Nanotechnol. Biol. Med. 2024, 55, 102719. [DOI] [PubMed] [Google Scholar]
  • 34. Chen E., Liu G., Zhou X., Zhang W., Pan Z., FASEB J. 2018, 32, 4917. [DOI] [PubMed] [Google Scholar]
  • 35. Tsai Y. Y., Chang S. W., Int. J. Mech. Sci. 2022, 237, 107795. [Google Scholar]
  • 36. Sikavitsas V. I., Temenoff J. S., Mikos A. G., Biomaterials 2001, 22, 2581. [DOI] [PubMed] [Google Scholar]
  • 37. Yan C., Hao L., Hussein A., Young P., J. Mech. Behav. Biomed. Mater. 2015, 51, 61. [DOI] [PubMed] [Google Scholar]
  • 38. Yan C., Shi Y., Hao L., Hussein A., Wei Q., C. Mater. Biogical Appl. 2017, 75, 1515. [DOI] [PubMed] [Google Scholar]
  • 39. Ataee A., Li Y., Fraser D., Song G., Wen C., Mater. Des. 2018, 137, 345. [Google Scholar]
  • 40. McWhorter F. Y., Wang T., Nguyen P., Chung T., Liu W. F., Proc. Natl. Acad. Sci. USA 2013, 110, 17253. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41. Kurtz S. M., Devine J. N., Biomaterials 2007, 28, 4845. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Shuai C., Shi X., Yang F., Tian H., Feng P., Int. J. Extreme Manufactur. 2024, 6, 015101. [Google Scholar]
  • 43. Prasadam I., van Gennip S., Friis T., Shi W., Crawford R., Xiao Y., Arthritis Rheumatol. 2010, 62, 1349. [DOI] [PubMed] [Google Scholar]
  • 44. Li K., Lv L., Shao D., Xie Y., Cao Y., Zheng X., J. Funct. Biomater. 2022, 13, 31. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45. Yuan J.‐W., Zhang Y.‐N., Liu Y.‐R., Li W., Dou S.‐X., Wei Y., Wang P.‐Y., Li H., Small 2022, 18, 2106498. [Google Scholar]
  • 46. Liu Y., Shao R., Suo T., Zhu J., Liu E., Wang Y., Miao L., Gao X., J. Ethnopharmacol. 2023, 309, 116354. [DOI] [PubMed] [Google Scholar]
  • 47. Zhang S., Qu D., Luo B., Wang L., Li H., Wang H., ACS Appl. Mater. Interfaces 2024, 16, 56801. [DOI] [PubMed] [Google Scholar]
  • 48. Kang H., Wong S. H. D., Pan Q., Li G., Bian L., Nano Lett. 2019, 19, 1963. [DOI] [PubMed] [Google Scholar]
  • 49. Li J., Yang J., Xing R., Wang Y., Aging (Albany NY) 2023, 15, 2554. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50. Brown B. N., Ratner B. D., Goodman S. B., Amar S., Badylak S. F., Biomaterials 2012, 33, 3792. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51. Klopfleisch R., Acta Biomater. 2016, 43, 3. [DOI] [PubMed] [Google Scholar]
  • 52. Arango Duque G., Descoteaux A., Front. Immunol. 2014, 5, 491. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53. Yin Y., He X. T., Wang J., Wu R. X., Chen F. M., Appl. Mater. Today 2019, 18, 100466. [Google Scholar]
  • 54. Shi Y., Shi J., Sun Y., Liu Q., Zhang C., Shao C., Yu K., Ge M., Mi R., Gu J., Adv. Funct. Mater. 2023, 33, 2301099. [Google Scholar]
  • 55. Cheng W., Ding Z., Zheng X., Lu Q., Kong X., Zhou X., Lu G., Kaplan D. L., Biomater. Sci. 2020, 8, 2537. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56. Liang B., Liang J. M., Ding J. N., Xu J., Xu J. G., Chai Y. M., Stem Cell Res. Ther. 2019, 10, 335. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57. Jianfei Z., Wenbin Z., Jiewen D., Xudong W., Steve G., Int. J. Oral Sci. 2019, 1, 45. [Google Scholar]
  • 58. Li Y., Liu Z., Tang Y., Huang W., Cell Death and Disease 2021, 12, 1144. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59. Wang M., Yu Y., Dai K., Ma Z., Liu Y., Wang J., Liu C., Biomater. Sci. 2016, 4, 1574. [DOI] [PubMed] [Google Scholar]
  • 60. Zhang J., Tong D., Song H., Ruan R., Sun Y., Lin Y., Wang J., Hou L., Dai J., Ding J., Yang H., Advanced Materials 2022, 34, 2202044. [DOI] [PubMed] [Google Scholar]
  • 61. Shang L., Liu Z., Ma B., Shao J., Wang B., Ma C., Ge S., Bioact. Mater. 2021, 6, 1175. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62. Li L. Y., Yang Z., Pan X. X., Feng B. X., Yue R., Yu B., Zheng Y. F., Tan J. Y., Yuan G. Y., Pei J., Adv. Funct. Mater. 2022, 32, 2270269. [Google Scholar]
  • 63. Luo Z., Tang Q., Feng Q., Ma S., Song J., Setchi R., Guo F., Zhang Y., Thin‐Wall. Struct. 2023, 192, 111098. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supporting Information

ADHM-14-0-s001.docx (465.8KB, docx)

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.


Articles from Advanced Healthcare Materials are provided here courtesy of Wiley

RESOURCES