Predicting altered bone biomechanics in juvenile mice: insights from microgravity simulation, loading interventions, and Raman Spectroscopy

Author:

Berteau J. P.ORCID

Abstract

Abstract Background Microgravity, a condition experienced in a spatial environment, poses unique challenges to the skeletal system, particularly in juvenile organisms. This study aimed to investigate alterations in bone biomechanics of juvenile mice due to unloading – that simulates microgravity in the laboratory—and the effects of a bone-loading intervention. We compared bone compositional and mechanical properties between 21-six-week-old C57Bl/6 from a control group (wild type) and a group that underwent a tail-suspension unloading protocol to mimic microgravity (MG). The second group (MG) experienced additional in vivo loading protocol (MG + LDG) on the right hind leg, where dynamic compressive loading was applied to the right knee using a custom-built loading device. Results Our results show that after two weeks, we successfully induced bone alterations by (i) decreasing the energy dissipated before fracture and (ii) decreasing the yield and maximum stress. In addition, we showed that Mineral to matrix component [ν1PO4/Amide I], Carbonate to Amide [CO3/Amide I], and Crystallinity [1/FWHM(ν1PO4)] are strongly linked in physiological bone but not in microgravity even after loading intervention. While Crystallinity is very sensitive to bone deformation (strain) alterations coming from simulated microgravity, we show that Carbonate to Amide [CO3/Amide I] – a common marker of turnover rate/remodeling activity—is a specific predictor of bone deformation for bone after simulated microgravity. Our results also invalidate the current parameters of the loading intervention to prevent bone alterations entirely in juvenile mice. Conclusions Our study successfully induced bone alterations in juvenile mice by using an unloading protocol to simulate microgravity, and we provided a new Raman Spectroscopy (RS) dataset of juvenile mice that contributes to the prediction of cortical bone mechanical properties, where the degree of interrelationship for RS data for physiological bone is improved compared to the most recent evidence.

Publisher

Springer Science and Business Media LLC

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