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A theoretical numerical model is proposed to predict patient dependent osteoporotic bone degradation. The model parameters are identified through a particle swarm optimization algorithm and based on individual patient high resolution peripherical quantitative computer tomography (HRpQCT) scan data. The degradation model is based on cellular activity initiated by the elastic strain energy developed in the bone microstructure through patient's body weight. The macro (organ scale) and meso (trabecular scale) scale analyses are carried out and predicted bone volume fraction and microstructure evolution are compared with in-vivo experimental bone degradation for four elderly women over a period of 10 years. A significant correlation (r > 0.9) is observed between the model predictions and in-vivo experiments in all cases with an average deviation error of 1.46%. The model can easily be extended to other patients and provide good predictions for different population categories such as ethnicity, gender, age, etc., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Recent studies demonstrate that bisphosphonates suppress bone resorption by leading to apoptosis of the osteoclast and inhibiting the differentiation to mature osteoclasts. The influence of bisphosphonates on bone formation is unknown, although it has been hypothesized that bisphosphonates inhibit osteoblast apoptosis and stimulate osteoblast proliferation and differentiation in vitro, leading to increased bone formation. The purpose of this study was to investigate the effect of bisphosphonates on bone formation. We administered risedronate at 0.05, 0.5 or 5.0 microg/kg/day or alendronate at 0.1, 1.0 or 10 microg/kg/day subcutaneously for 17 days to 6-month-old female Sprague-Dawley rats. Control rats were given a daily subcutaneous injection of saline. Following sacrifice, the femoral and tibial mid-diaphyses were harvested and mineralizing surface (MS/BS), mineral apposition rate (MAR) and bone formation rate (BFR/BS) were measured on periosteal and endocortical surfaces. In the femur, periosteal MAR was significantly lower in all treatment groups (22-29% for risedronate, 26-36% for alendronate) than in control. In the tibia, periosteal MAR and BFR of all treatment groups were significantly lower (41-50% for risedronate, 43-52% for alendronate) than in the control group. Because the periosteal surfaces of these bones are only undergoing bone formation in modeling mode, our results show that bisphosphonates suppress bone formation independently of bone resorption. Because this effect is seen on periosteal MAR rather than on periosteal MS/BS, we hypothesize that bisphosphonates affect the activity of individual osteoblasts at the cell level. This may help to explain the reason that the anabolic effects of teriparatide are blunted when administered concurrently with or following a course of bisphosphonates in humans.

The article focuses on the impact of the intra tibial injection of phosphate-buffered saline (PBS) on mechanical properties of the tibia. Topics discussed include determining the impact of the injection on mice tibia, performing Wilcoxon and Mann-Whitney test; and analyzing degradation in mechanical properties of the bone by intra-tibial injection.

A finite element analysis based on Micro-Quantitative Computed Tomography (µQCT) is a method with high potential to improve fracture risk prediction. However, the segmentation process and model generation are generally not automatized in their entirety. Even with a rigorous protocol, the operator might add uncertainties during the creation of the model. The aim of this study was to evaluate a µQCT-based model of mice tumoral and sham tibias in terms of the variabilities induced by the operator and sensitivity to operator-dependent variables (such as model orientation or length). Two different operators generated finite element (FE) models from µCT images of 8 female Balb/c nude mice tibias aged 10 weeks old with bone tumors induced in the right tibia and with sham injection in the left. From these models, predicted failure load was determined for two different boundary conditions: fixed support and spherical joints. The difference between the predicted and experimental failure load of both operators was large (-122% to 93%). The difference in the predicted failure load between operators was less for the spherical joints boundary conditions (9.8%) than for the fixed support (58.3%), p < 0.001, whereas varying the orientation of bone tibia caused more variability for the fixed support boundary condition (44.7%) than for the spherical joints (9.1%), p < 0.002. Varying tibia length had no significant effect, regardless of boundary conditions (<4%). When using the same mesh and same orientation, the difference between operators is non-significant (<6%) for each model. This study showed that the operator influences the failure load assessed by a µQCT-based finite element model of the tumoral and sham mice tibias. The results suggest that automation is needed for better reproducibility. [ABSTRACT FROM AUTHOR]