Numerical simulation on mass transfer in the bone lacunar-canalicular system under different gravity fields

Abstract

The bone lacunar-canalicular system (LCS) is a unique complex 3D microscopic tubular network structure within the osteon that contains interstitial fluid flow to ensure the efficient transport of signaling molecules, nutrients, and wastes to guarantee the normal physiological activities of bone tissue. The mass transfer laws in the LCS under microgravity and hypergravity are still unclear. In this paper, a multi-scale 3D osteon model was established to mimic the cortical osteon, and a finite element method was used to numerically analyze the mass transfer in the LCS under hypergravity, normal gravity and microgravity and combined with high-intensity exercise conditions. It was shown that hypergravity promoted mass transfer in the LCS to the deep lacunae, and the number of particles in lacunae increased more significantly from normal gravity to hypergravity the further away from the Haversian canal. The microgravity environment inhibited particles transport in the LCS to deep lacunae. Under normal gravity and microgravity, the number of particles in lacunae increased greatly when doing high-intensity exercise compared to stationary standing. This paper presents the first simulation of mass transfer within the LCS with different gravity fields combined with high-intensity exercise using the finite element method. The research suggested that hypergravity can greatly promote mass transfer in the LCS to deep lacunae, and microgravity strongly inhibited this mass transfer; high-intensity exercise increased the mass transfer rate in the LCS. This study provided a new strategy to combat and treat microgravity-induced osteoporosis.

Keywords:

• Lacunar-canalicular system
• particle tracing
• microgravity
• osteoporosis
• numerical simulation

Disclosure statement

All authors have read and approved the manuscript to be submitted, and there is no ethical problem or conflict of interest in the manuscript.

Additional information

Funding

The work was supported by the [National Natural Science Foundation of China] under Grant [number 12072235]; [National Natural Science Foundation of China] under Grant [number 12002388]; and [Tianjin Natural Science Foundation] under Grant [numbers 21JCYBJC00910].