Mechanobiological osteocyte feedback drives mechanostat regulation of bone in a multiscale computational model

Martin, Madge; Sansalone, V.; Cooper, David M.L.; Forwood, Mark R.; Pivonka, Peter

doi:10.1007/s10237-019-01158-w

Cited by 36 publications

(43 citation statements)

References 62 publications

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“…bone-forming cells) and osteoclasts (i.e. bone-resorbing cells) [82][83][84] where the mechanical stimulus exceeds, or is lower, than its homeostatic value [85,86]. Typically based on animal studies [87][88][89], these models can be used for determining the amount of bone deposited, or resorbed, as a function of exercise, individual metabolism, diet and pharmacological treatment [90, 91•, 92] for different anatomical locations and bone types [87][88][89].…”

Section: A Perspective Toward Personalized Exercise Prescriptionmentioning

confidence: 99%

Modelling Human Locomotion to Inform Exercise Prescription for Osteoporosis

Martelli

Beck

Saxby

et al. 2020

Curr Osteoporos Rep

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Purpose of Review We review the literature on hip fracture mechanics and models of hip strain during exercise to postulate the exercise regimen for best promoting hip strength. Recent Findings The superior neck is a common location for hip fracture and a relevant exercise target for osteoporosis. Current modelling studies showed that fast walking and stair ambulation, but not necessarily running, optimally load the femoral neck and therefore theoretically would mitigate the natural age-related bone decline, being easily integrated into routine daily activity. High intensity jumps and hopping have been shown to promote anabolic response by inducing high strain in the superior anterior neck. Multidirectional exercises may cause beneficial non-habitual strain patterns across the entire femoral neck. Resistance knee flexion and hip extension exercises can induce high strain in the superior neck when performed using maximal resistance loadings in the average population. Summary Exercise can stimulate an anabolic response of the femoral neck either by causing higher than normal bone strain over the entire hip region or by causing bending of the neck and localized strain in the superior cortex. Digital technologies have enabled studying interdependences between anatomy, bone distribution, exercise, strain and metabolism and may soon enable personalized prescription of exercise for optimal hip strength.

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Section: A Perspective Toward Personalized Exercise Prescriptionmentioning

confidence: 99%

Modelling Human Locomotion to Inform Exercise Prescription for Osteoporosis

Martelli

Beck

Saxby

et al. 2020

Curr Osteoporos Rep

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“…As in previous models, the RANK-RANKL-OPG pathway, together with the action of several regulatory factors on bone cells, including TGF-β, PTH, and mechanobiological feedback is given (for details on original models see Pivonka et al, 2008Pivonka et al, , 2010Scheiner et al, 2013;Pivonka et al, 2012;Martínez-Reina and Pivonka, 2019). The new model has been designed following the structure of the original model, adding the population of osteocytes, as done in Martin et al (2019), slightly modifying the mechanoregulation feedback and adding new features relevant to the formulation of damage, the last two modifications being dealt with in subsections 2.3 and 2.4, respectively.…”

Section: Model Of Bone Cell Interactions In Bone Adaptationmentioning

confidence: 99%

“…(1) act is a function of the mechanical stimulus that regulates the anabolic part of the mechanobiological feedback in the proliferation term and will be addressed in section 2.3. Finally, η is the concentration of osteocytes in bone matrix, which is assumed constant as in Martin et al (2019), thus leading to proportional variations of osteocytes population and fraction of bone matrix volume per total volume, f bm (Equation 4). The variation of f bm over time is precisely one of the main outcomes to be derived from the set of cell population equations and is defined through the balance between resorbed and formed tissue:…”

Section: Model Of Bone Cell Interactions In Bone Adaptationmentioning

confidence: 99%

“…β RANKL is the production rate of endogenous RANKL on the surface of osteoblasts precursors and osteocytes. We have assumed that RANKL is expressed by those cells, following experimental evidence (Nakashima et al, 2011;Xiong and O'Brien, 2012) and a previous model (Martin et al, 2019). So, RANKL eff is the total effective carrying capacity of those cells that controls the maximum expression of RANKL:…”

Section: Denosumab Action On Rank-rankl-opg: Competitive Bindingmentioning

confidence: 99%

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Combined Effects of Exercise and Denosumab Treatment on Local Failure in Post-menopausal Osteoporosis–Insights from Bone Remodelling Simulations Accounting for Mineralisation and Damage

Martínez-Reina

Calvo-Gallego

Pivonka

2021

Front. Bioeng. Biotechnol.

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Denosumab has been shown to increase bone mineral density (BMD) and reduce the fracture risk in patients with post-menopausal osteoporosis (PMO). Increase in BMD is linked with an increase in bone matrix mineralisation due to suppression of bone remodelling. However, denosumab anti-resorptive action also leads to an increase in fatigue microdamage, which may ultimately lead to an increased fracture risk. A novel mechanobiological model of bone remodelling was developed to investigate how these counter-acting mechanisms are affected both by exercise and long-term denosumab treatment. This model incorporates Frost's mechanostat feedback, a bone mineralisation algorithm and an evolution law for microdamage accumulation. Mechanical disuse and microdamage were assumed to stimulate RANKL production, which modulates activation frequency of basic multicellular units in bone remodelling. This mechanical feedback mechanism controls removal of excess bone mass and microdamage. Furthermore, a novel measure of bone local failure due to instantaneous overloading was developed. Numerical simulations indicate that trabecular bone volume fraction and bone matrix damage are determined by the respective bone turnover and homeostatic loading conditions. PMO patients treated with the currently WHO-approved dose of denosumab (60 mg administrated every 6 months) exhibit increased BMD, increased bone ash fraction and damage. In untreated patients, BMD will significantly decrease, as will ash fraction; while damage will increase. The model predicted that, depending on the time elapsed between the onset of PMO and the beginning of treatment, BMD slowly converges to the same steady-state value, while damage is low in patients treated soon after the onset of the disease and high in patients having PMO for a longer period. The simulations show that late treatment PMO patients have a significantly higher risk of local failure compared to patients that are treated soon after the onset of the disease. Furthermore, overloading resulted in an increase of BMD, but also in a faster increase of damage, which may consequently promote the risk of fracture, specially in late treatment scenarios. In case of mechanical disuse, the model predicted reduced BMD gains due to denosumab, while no significant change in damage occurred, thus leading to an increased risk of local failure compared to habitual loading.

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“…Recently, mechano-chemo-biological models, which derive from the ODE models previously mentioned, have appeared. Very few articles have considered this type of models in their investigations (Klika et al, 2013;Avval et al, 2014;Lerebours et al, 2016;Pastrama et al, 2018;Martin et al, 2019;Ashrafi et al, 2020). Nevertheless, we think that they are very promising as they englobe each of mechanical, biological, and biochemical features of bone.…”

Section: Mathematical Models Of Bone Remodelingmentioning

confidence: 99%

Toward a Mathematical Modeling of Diseases’ Impact on Bone Remodeling: Technical Review

Oumghar

Barkaoui

Chabrand

2020

Front. Bioeng. Biotechnol.

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A wide variety of bone diseases have hitherto been discovered, such as osteoporosis, Paget's disease, osteopetrosis, and metastatic bone disease, which are not well defined in terms of changes in biochemical and mechanobiological regulatory factors. Some of these diseases are secondary to other pathologies, including cancer, or to some clinical treatments. To better understand bone behavior and prevent its deterioration, bone biomechanics have been the subject of mathematical modeling that exponentially increased over the last years. These models are becoming increasingly complex. The current paper provides a timely and critical analysis of previously developed bone remodeling mathematical models, particularly those addressing bone diseases. Besides, mechanistic pharmacokinetic/pharmacodynamic (PK/PD) models, which englobe bone disease and its treatment's effect on bone health. Therefore, the review starts by presenting bone remodeling cycle and mathematical models describing this process, followed by introducing some bone diseases and discussing models of pathological mechanisms affecting bone, and concludes with exhibiting the available bone treatment procedures considered in the PK/PD models.

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Mechanobiological osteocyte feedback drives mechanostat regulation of bone in a multiscale computational model

Cited by 36 publications

References 62 publications

Modelling Human Locomotion to Inform Exercise Prescription for Osteoporosis

Modelling Human Locomotion to Inform Exercise Prescription for Osteoporosis

Combined Effects of Exercise and Denosumab Treatment on Local Failure in Post-menopausal Osteoporosis–Insights from Bone Remodelling Simulations Accounting for Mineralisation and Damage

Toward a Mathematical Modeling of Diseases’ Impact on Bone Remodeling: Technical Review

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