Back

Electrical Surface Polarization as a Functionalization Strategy to Improve Bone Regeneration of Apatite-Based Graft Materials

Hrovat, K.; Bergara Muguruza, L.; Hiratai, R.; Alho, A.; Laine, M.; Makela, K.; Yamashita, K.; Nakamura, M.

2026-02-18 bioengineering
10.64898/2026.02.17.705299 bioRxiv
Show abstract

Apatite-based bone graft materials are widely used for bone regeneration; however, their limited bioactivity and slow remodeling often hinder complete replacement by newly formed bone. Electrical surface polarization has emerged as a promising non-chemical strategy to modify biomaterial surface properties without altering bulk characteristics. In this study, we investigated the effects of electrical surface polarization on apatite-based biomaterials using synthesized carbonate apatite (CA) for mechanistic in vitro evaluation and a clinically relevant xenograft material for in vivo validation. Material characterization confirmed the formation of B-type carbonate apatite with bone-like mineral composition. Thermally stimulated depolarization current measurements verified successful induction of surface charges, with polarization intensity dependent on treatment conditions. In vitro studies using human peripheral blood-derived osteoclast precursors demonstrated that electrically polarized CA surfaces significantly enhanced osteoclast differentiation and resorptive activity compared to non-polarized controls, with the strongest effects observed on positively polarized surfaces. Three-dimensional analysis revealed increased resorption pit depth and volume, indicating enhanced osteoclast functionality. In vivo implantation of polarized xenograft materials into rat femoral defects resulted in significantly increased new bone formation and improved implant-bone integration compared to non-polarized materials. Higher polarization conditions promoted more mature bone tissue formation and greater bone-material affinity. These results demonstrate that electrical surface polarization effectively modulates osteoclast-material interactions and enhances bone regeneration, highlighting its potential as a simple and translatable functionalization strategy for apatite-based bone graft materials.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Advanced Healthcare Materials
71 papers in training set
Top 0.1%
22.7%
2
Advanced Functional Materials
41 papers in training set
Top 0.1%
12.6%
3
Bioactive Materials
18 papers in training set
Top 0.1%
6.4%
4
Biomaterials Advances
20 papers in training set
Top 0.1%
6.4%
5
Advanced Science
249 papers in training set
Top 3%
4.9%
50% of probability mass above
6
Advanced Materials
53 papers in training set
Top 0.6%
4.2%
7
Advanced Materials Interfaces
10 papers in training set
Top 0.1%
2.7%
8
ACS Biomaterials Science & Engineering
37 papers in training set
Top 0.3%
2.6%
9
Nature Communications
4913 papers in training set
Top 44%
2.6%
10
ACS Applied Materials & Interfaces
39 papers in training set
Top 0.3%
2.4%
11
Materials Today Bio
18 papers in training set
Top 0.2%
1.9%
12
ACS Applied Bio Materials
21 papers in training set
Top 0.3%
1.7%
13
Biomaterials
78 papers in training set
Top 0.5%
1.7%
14
Acta Biomaterialia
85 papers in training set
Top 0.5%
1.7%
15
Advanced Materials Technologies
27 papers in training set
Top 0.3%
1.7%
16
Scientific Reports
3102 papers in training set
Top 59%
1.7%
17
Nano Letters
63 papers in training set
Top 2%
1.3%
18
Biomaterials Science
21 papers in training set
Top 0.4%
1.3%
19
Small
70 papers in training set
Top 0.7%
1.3%
20
RSC Advances
18 papers in training set
Top 0.8%
1.3%
21
PLOS ONE
4510 papers in training set
Top 60%
1.2%
22
Lab on a Chip
88 papers in training set
Top 1%
0.9%
23
Advanced Biology
29 papers in training set
Top 1.0%
0.8%
24
Journal of Advanced Research
15 papers in training set
Top 0.7%
0.8%
25
Biofabrication
32 papers in training set
Top 0.7%
0.8%
26
Computational and Structural Biotechnology Journal
216 papers in training set
Top 9%
0.8%
27
Chemical Engineering Journal
10 papers in training set
Top 0.6%
0.8%
28
ACS Nano
99 papers in training set
Top 4%
0.6%
29
Nanoscale Advances
13 papers in training set
Top 0.8%
0.5%