Physical exercise impacts bone remodeling around bio-resorbable magnesium implants
Source abstract
Abstract
Physical exercise has been shown to induce positive reactions in bone healing but next to nothing is known about how it affects the nanostructure, in particular around implants. In this study, we established this link by using small-angle X-ray scattering tensor tomography (SASTT) to investigate nanostructural parameters in 3D such as mineral particle orientation and thickness. As a model system, rat femoral bone with a bio-resorbable implant (ultra-high purity magnesium) was used. One-half of the rats underwent treadmill exercise while the other half were moving freely in a cage. At two- and six-weeks post-surgery, rats were sacrificed, and samples were taken. Our results point to an earlier start and stronger remodeling when physical exercise is applied and to a stronger reorientation of the mineralized collagen fibers around the implant. This study reveals the nanostructural response of bone with bio-resorbable implants to physical exercise. Understanding this response is very important for designing post-surgery treatments. STATEMENT OF SIGNIFICANCE: Physical exercise is known to have beneficial effects on the human body and is often incorporated into the recovery process following orthopedic surgeries. While the response of bone to physical exercise is well-documented, the structural response of bone to early exercise after implant placement, particularly its impact on the nanostructure, has not been extensively studied. In this study, we identify the effects of physical exercise on the bone nanostructure and the remodeling process around a bioresorbable implant. These findings could help develop tailored physical exercise strategies for post-surgery recovery in patients.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Bone Tissue Engineering Materials · Magnesium Alloys: Properties and Applications · Bone health and osteoporosis research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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