A finite element analysis of masticatory stress hypotheses

Understanding how the skull transmits and dissipates forces during feeding provides insights into the selective pressures that may have driven the evolution of primate skull morphology. Traditionally, researchers have interpreted masticatory biomechanics in terms of simple global loading regimes applied to simple shapes (i.e., bending in sagittal and frontal planes, dorsoventral shear, and torsion of beams and cylinders). This study uses finite element analysis to examine the extent to which these geometric models provide accurate strain predictions in the face and evaluate whether simple global loading regimes predict strains that approximate the craniofacial deformation pattern observed during mastication. Loading regimes, including those simulating peak loads during molar chewing and those approximating the global loading regimes, were applied to a previously validated finite element model (FEM) of a macaque (Macaca fascicularis) skull, and the resulting strain patterns were compared. When simple global loading regimes are applied to the FEM, the resulting strains do not match those predicted by simple geometric models, suggesting that these models fail to generate accurate predictions of facial strain. Of the four loading regimes tested, bending in the frontal plane most closely approximates strain patterns in the circumorbital region and lateral face, apparently due to masseter muscle forces acting on the zygomatic arches. However, these results indicate that no single simple global loading regime satisfactorily accounts for the strain pattern found in the validated FEM. Instead, we propose that FE models replace simple cranial models when interpreting bone strain data and formulating hypotheses about craniofacial biomechanics.     

Parametric convergence sensitivity and validation of a finite element model of the human lumbar spine

The primary objective of this study was to generate a finite element model of the human lumbar spine (L1-L5), verify mesh convergence for each tissue constituent and perform an extensive validation using both kinematic/kinetic and stress/strain data. Mesh refinement was accomplished via convergence of strain energy density (SED) predictions for each spinal tissue. The converged model was validated based on range of motion, intradiscal pressure, facet force transmission, anterolateral cortical bone strain and anterior longitudinal ligament deformation predictions. Changes in mesh resolution had the biggest impact on SED predictions under axial rotation loading. Nonlinearity of the moment-rotation curves was accurately simulated and the model predictions on the aforementioned parameters were in good agreement with experimental data. The validated and converged model will be utilised to study the effects of degeneration on the lumbar spine biomechanics, as well as to investigate the mechanical underpinning of the contemporary treatment strategies.     

Parametric convergence sensitivity and validation of a finite element model of the human lumbar spine

The primary objective of this study was to generate a finite element model of the human lumbar spine (L1–L5), verify mesh convergence for each tissue constituent and perform an extensive validation using both kinematic/kinetic and stress/strain data. Mesh refinement was accomplished via convergence of strain energy density (SED) predictions for each spinal tissue. The converged model was validated based on range of motion, intradiscal pressure, facet force transmission, anterolateral cortical bone strain and anterior longitudinal ligament deformation predictions. Changes in mesh resolution had the biggest impact on SED predictions under axial rotation loading. Nonlinearity of the moment-rotation curves was accurately simulated and the model predictions on the aforementioned parameters were in good agreement with experimental data. The validated and converged model will be utilised to study the effects of degeneration on the lumbar spine biomechanics, as well as to investigate the mechanical underpinning of the contemporary treatment strategies.     

Search for critical loading condition of the spine--a meta analysis of a nonlinear viscoelastic finite element model

The relative vulnerability of spinal motion segments to different loading combinations remains unknown. The meta-analysis described here using the results of a validated L2-L3 nonlinear viscoelastic finite element model was designed to investigate the critical loading and its effect on the internal mechanics of the human lumbar spine. A Box-Behnken experimental design was used to design the magnitude of seven independent variables associated with loads, rotations and velocity of motion. Subsequently, an optimization method was used to find the primary and secondary variables that influence spine mechanical output related to facet forces, disc pressure, ligament forces, annulus matrix compressive/shear stresses and anulus fibers strain. The mechanical responses with respect to the two most-relevant variables were then regressed linearly using the response surface quadratic model. Axial force and sagittal rotation were identified as the most-relevant variables for mechanical responses. The procedure developed can be used to find the critical loading for finite element models with multi input variables. The derived meta-models can be used to predict the risk associated with various loading parameters and in setting safer load limits.     

Search for critical loading condition of the spine–A meta analysis of a nonlinear viscoelastic finite element model

The relative vulnerability of spinal motion segments to different loading combinations remains unknown. The meta-analysis described here using the results of a validated L2–L3 nonlinear viscoelastic finite element model was designed to investigate the critical loading and its effect on the internal mechanics of the human lumbar spine. A Box-Behnken experimental design was used to design the magnitude of seven independent variables associated with loads, rotations and velocity of motion. Subsequently, an optimization method was used to find the primary and secondary variables that influence spine mechanical output related to facet forces, disc pressure, ligament forces, annulus matrix compressive/shear stresses and anulus fibers strain. The mechanical responses with respect to the two most-relevant variables were then regressed linearly using the response surface quadratic model. Axial force and sagittal rotation were identified as the most-relevant variables for mechanical responses. The procedure developed can be used to find the critical loading for finite element models with multi input variables. The derived meta-models can be used to predict the risk associated with various loading parameters and in setting safer load limits.     

Application of a fiber-reinforced continuum theory to multiple deformations of the annulus fibrosus.

Accurate tissue stress predictions for the annulus fibrosus are essential for understanding the factors that cause or contribute to disc degeneration and mechanical failure. Current computational models used to predict in vivo disc stresses utilize material laws for annular tissue that are not rigorously validated against experimental data. Consequently, predictions of disc stress resulting from physical activities may be inaccurate and therefore unreliable as a basis for defining mechanical-biologic injury criteria. To address this need we present a model for the annulus as an isotropic ground substance reinforced with two families of collagen fibers, and an approach for determining the material constants by simultaneous consideration of multiple experimental data sets. Two strain energy functions for the annulus are proposed and used in the theory to derive the constitutive equations relating the stress to pure stretch deformations. These equations are applied to four distinct experimental protocols and the material constants are determined from a simultaneous, nonlinear regression analysis. Good agreement between theory and experiment is achieved when the invariants are included within multiple, separate exponentials in the strain energy function.     

Inverse identification of region-specific hyperelastic material parameters for human brain tissue

The identification of material parameters accurately describing the region-dependent mechanical behavior of human brain tissue is crucial for computational models used to assist, e.g., the development of safety equipment like helmets or the planning and execution of brain surgery. While the division of the human brain into different anatomical regions is well established, knowledge about regions with distinct mechanical properties remains limited. Here, we establish an inverse parameter identification scheme using a hyperelastic Ogden model and experimental data from multi-modal testing of tissue from 19 anatomical human brain regions to identify mechanically distinct regions and provide the corresponding material parameters. We assign the 19 anatomical regions to nine governing regions based on similar parameters and microstructures. Statistical analyses confirm differences between the regions and indicate that at least the corpus callosum and the corona radiata should be assigned different material parameters in computational models of the human brain. We provide a total of four parameter sets based on the two initial Poisson’s ratios of 0.45 and 0.49 as well as the pre- and unconditioned experimental responses, respectively. Our results highlight the close interrelation between the Poisson’s ratio and the remaining model parameters. The identified parameters will contribute to more precise computational models enabling spatially resolved predictions of the stress and strain states in human brains under complex mechanical loading conditions.

     

Experimental validation of a finite element model of the proximal femur using digital image correlation and a composite bone model

Computational biomechanical models are useful tools for supporting orthopedic implant design and surgical decision making, but because they are a simplification of the clinical scenario they must be carefully validated to ensure that they are still representative. The goal of this study was to assess the validity of the generation process of a structural finite element model of the proximal femur employing the digital image correlation (DIC) strain measurement technique. A finite element analysis model of the proximal femur subjected to gait loading was generated from a CT scan of an analog composite femur, and its predicted mechanical behavior was compared with an experimental model. Whereas previous studies have employed strain gauging to obtain discreet point data for validation, in this study DIC was used for full field quantified comparison of the predicted and experimentally measured strains. The strain predicted by the computational model was in good agreement with experimental measurements, with R(2) correlation values from 0.83 to 0.92 between the simulation and the tests. The sensitivity and repeatability of the strain measurements were comparable to or better than values reported in the literature for other DIC tests on tissue specimens. The experimental-model correlation was in the same range as values obtained from strain gauging, but the DIC technique produced more detailed, full field data and is potentially easier to use. As such, the findings supported the validity of the model generation process, giving greater confidence in the model's predictions, and digital image correlation was demonstrated as a useful tool for the validation of biomechanical models.     

Dependence of mechanical behavior of the murine tail disc on regional material properties: a parametric finite element study

In vivo rodent tail models are becoming more widely used for exploring the role of mechanical loading on the initiation and progression of intervertebral disc degeneration. Historically, finite element models (FEMs) have been useful for predicting disc mechanics in humans. However, differences in geometry and tissue properties may limit the predictive utility of these models for rodent discs. Clearly, models that are specific for rodent tail discs and accurately simulate the disc's transient mechanical behavior would serve as important tools for clarifying disc mechanics in these animal models. An FEM was developed based on the structure, geometry, and scale of the mouse tail disc. Importantly, two sources of time-dependent mechanical behavior were incorporated: viscoelasticity of the matrix, and fluid permeation. In addition, a novel strain-dependent swelling pressure was implemented through the introduction of a dilatational stress in nuclear elements. The model was then validated against data from quasi-static tension-compression and compressive creep experiments performed previously using mouse tail discs. Finally, sensitivity analyses were performed in which material parameters of each disc subregion were individually varied. During disc compression, matrix consolidation was observed to occur preferentially at the periphery of the nucleus pulposus. Sensitivity analyses revealed that disc mechanics was greatly influenced by changes in nucleus pulposus material properties, but rather insensitive to variations in any of the endplate properties. Moreover, three key features of the model-nuclear swelling pressure, lamellar collagen viscoelasticity, and interstitial fluid permeation-were found to be critical for accurate simulation of disc mechanics. In particular, collagen viscoelasticity dominated the transient behavior of the disc during the initial 2200 s of creep loading, while fluid permeation governed disc deformation thereafter. The FEM developed in this study exhibited excellent agreement with transient creep behavior of intact mouse tail motion segments. Notably, the model was able to produce spatial variations in nucleus pulposus matrix consolidation that are consistent with previous observations in nuclear cell morphology made in mouse discs using confocal microscopy. Results of this study emphasize the need for including nucleus swelling pressure, collagen viscoelasticity, and fluid permeation when simulating transient changes in matrix and fluid stress/strain. Sensitivity analyses suggest that further characterization of nucleus pulposus material properties should be pursued, due to its significance in steady-state and transient disc mechanical response.     

Role of Calcitonin Gene-Related Peptide in Functional Adaptation of the Skeleton

Peptidergic sensory nerve fibers innervating bone and periosteum are rich in calcitonin gene-related peptide (CGRP), an osteoanabolic neurotransmitter. There are two CGRP isoforms, CGRPα and CGRPβ. Sensory fibers are a potential means by which the nervous system may detect and respond to loading events within the skeleton. However, the functional role of the nervous system in the response of bone to mechanical loading is unclear. We used the ulna end-loading model to induce an adaptive modeling response in CGRPα and CGRPβ knockout mouse lines and their respective wildtype controls. For each knockout mouse line, groups of mice were treated with cyclic loading or sham-loading of the right ulna. A third group of mice received brachial plexus anesthesia (BPA) of the loaded limb before mechanical loading. Fluorochrome labels were administered at the time of loading and 7 days later. Ten days after loading, bone responses were quantified morphometrically. We hypothesized that CGRP signaling is required for normal mechanosensing and associated load-induced bone formation. We found that mechanically-induced activation of periosteal mineralizing surface in mice and associated blocking with BPA were eliminated by knockout of CGRPα signaling. This effect was not evident in CGRPβ knockout mice. We also found that mineral apposition responses to mechanical loading and associated BPA blocking were retained with CGRPα deletion. We conclude that activation of periosteal mineralizing surfaces in response to mechanical loading of bone is CGRPα-dependent in vivo. This suggests that release of CGRP from sensory peptidergic fibers in periosteum and bone has a functional role in load-induced bone formation.     

Finite element analysis of blood clots based on the nonlinear visco-hyperelastic model

Mechanical thrombectomy has become the standard treatment for patients with an acute ischemic stroke. In this approach, to remove blood clots, mechanical force is applied using thrombectomy devices, in which the interaction between the clot and the device could significantly affect the clot retrieval performance. It is expected that the finite element method (FEM) could visualize the mechanical interaction by the visualization of the stress transmission from the device to the clot. This research was aimed at verifying the constitutive theory by implementing FEM based on the visco-hyperelastic theory, using a three-dimensional clot model. We used the visco-hyperelastic FEM to reproduce the mechanical behavior of blood clots, as observed in experiments. This study is focused on the mechanical responses of clots under tensile loading and unloading because in mechanical thrombectomy, elongation is assumed to occur locally on the clots during the retrieval process. Several types of cylindrical clots were created by changing the fibrinogen dose. Tensile testing revealed that the stiffness (E_0.45-value) of clots with fibrinogen could be more than three times higher than that of clots without fibrinogen. It was also found that the stiffness was not proportional to the fibrinogen dose. By fitting to the theoretical curve, it was revealed that the Mooney-Rivlin model could reproduce the hyperelastic characteristics of clots well. From the stress-relaxation data, the three-chain Maxwell model could accurately fit the experimental viscoelastic data. FEM, taking the theoretical models into account, was then carried out, and the results matched well with the experimental visco-hyperelastic characteristics of clots under tensile load, reproducing the mechanical hysteresis during unloading, the stress dependence on the strain rate, and the time-dependent stress decrease in the stress-relaxation test.     

A theoretical and non-destructive experimental approach for direct inclusion of measured collagen orientation and recruitment into mechanical models of the artery wall

Gradual collagen recruitment has been hypothesized as the underlying mechanism for the mechanical stiffening with increasing stress in arteries. In this work, we investigated this hypothesis in eight rabbit carotid arteries by directly measuring the distribution of collagen recruitment stretch under increasing circumferential loading using a custom uniaxial (UA) extension device combined with a multi-photon microscope (MPM). This approach allowed simultaneous mechanical testing and imaging of collagen fibers without traditional destructive fixation methods. Fiber recruitment was quantified from 3D rendered MPM images, and fiber orientation was measured in projected stacks of images. Collagen recruitment was observed to initiate at a finite strain, corresponding to a sharp increase in the measured mechanical stiffness, confirming the previous hypothesis and motivating the development of a new constitutive model to capture this response. Previous constitutive equations for the arterial wall have modeled the collagen contribution with either abrupt recruitment at zero strain, abrupt recruitment at finite strain or as gradual recruitment beginning at infinitesimal strain. Based on our experimental data, a new combined constitutive model was presented in which fiber recruitment begins at a finite strain with activation stretch represented by a probability distribution function. By directly including this recruitment data, the collagen contribution was modeled using a simple Neo-Hookean equation. As a result, only two phenomenological material constants were required from the fit to the stress stretch data. Three other models for the arterial wall were then compared with these results. The approach taken here was successful in combining stress-strain analysis with simultaneous microstructural imaging of collagen recruitment and orientation, providing a new approach by which underlying fiber architecture may be quantified and included in constitutive equations.     

Physical activity and bone development during childhood: insights from animal models.

Animal studies illustrate greater structural and material adaptations of growing bone to exercise than in adult bones but do not define effective training regimes to optimize bone strength in children. Controlled loading studies in turkey, rat, or mouse bones have revealed mechanisms of mechanotransduction and loading characteristics that optimize the modeling response to applied strains. Insights from these models reveal that static loads do not play a role in mechanotransduction and that bone formation is threshold driven and dependent on strain rate, amplitude, and partitioning of the load. That is, only a few cycles of loading are required at any time to elicit an adaptive response, and distributed bouts of loading, incorporating rest periods, are more osteogenic than single sessions of long duration. These parameters of loading have been translated into feasible public health interventions that exploit the insights gained from animal experiments to achieve adaptive responses in children and adolescents. Studies manipulating estrogen receptors (ER) in mice also demonstrate that skeletal sensitivity to loading during the peripubertal period is due to a direct regulation of mechanotransduction pathways by ER, and not just a simple enhancement of cell activity already marshaled by the hypothalamic-pituitary axis. Unfortunately, because the rate and timing of growth in small animals are completely different from those in humans, these models can be poor tools to elucidate periods during growth in youths, during which the skeleton is more sensitive to loading. However, there are insights from studies of human growth that can improve the interpretation of data from such studies of growth and development in animals.     

Helmet liner evaluation to mitigate head response from primary blast exposure

Head injury resulting from blast loading, including mild traumatic brain injury, has been identified as an important blast-related injury in modern conflict zones. A study was undertaken to investigate potential protective ballistic helmet liner materials to mitigate primary blast injury using a detailed sagittal plane head finite element model, developed and validated against previous studies of head kinematics resulting from blast exposure. Five measures reflecting the potential for brain injury that were investigated included intracranial pressure, brain tissue strain, head acceleration (linear and rotational) and the head injury criterion. In simulations, these measures provided consistent predictions for typical blast loading scenarios. Considering mitigation, various characteristics of foam material response were investigated and a factor analysis was performed which showed that the four most significant were the interaction effects between modulus and hysteretic response, stress–strain response, damping factor and density. Candidate materials were then identified using the predicted optimal material values. Polymeric foam was found to meet the density and modulus requirements; however, for all significant parameters, higher strength foams, such as aluminum foam, were found to provide the highest reduction in the potential for injury when compared against the unprotected head.     

Mechanical responses of the periodontal ligament based on an exponential hyperelastic model: a combined experimental and finite element method

The V–W exponential hyperelastic model is adopted to describe the instantaneous elastic response of the periodontal ligament (PDL). The general theoretical framework of constitutive modeling is described based on nonlinear continuum mechanics, and the elasticity tensor used to develop UMAT subroutine is formulated. Nanoindentation experiment is performed to characterize mechanical properties of an adult pig PDL specimen. Then the experiment is simulated by using the finite element (FE) analysis. Meanwhile, the optimized material parameters are identified by the inverse FE method. The good agreement between the simulated results and experimental data demonstrates that the V–W model is capable of describing the mechanical behavior of the PDL. Therefore, the model and its implementation into FE code are validated. By using the model, we simulate the tooth movement under orthodontic loading to predict the mechanical responses of the PDL. The results show that local concentrations of stress and strain in the PDL are found.     

Neurogenic adaptation contributes to the afferent response to mechanical stimulation

This study aimed to characterize the effect of mechanical stimuli on mesenteric afferent nerve signaling in the isolated rat jejunum in vitro. This was done to determine the effect of mechanical stresses and strains relative to nonmechanical parameters (neurogenic adaptation). Mechanical stimulations were applied to a segment of jejunum from 15 rats using ramp distension with water at three rates of distension, a relaxation test (volume maintained constant from initial pressure of 20 or 40 mmHg), and a creep test (pressure maintained constant). Circumferential stress and strain and the spike rate increase ratio were calculated for evaluation of afferent nerve activity during the mechanical stimulations. Ramp distension evoked two distinct phases of afferent nerve signaling as a function of circumferential stress or strain. Changing the volume distension rate did not change the stress-strain relationship, but faster distension rate increased the afferent firing rate (P < 0.05). In the stress relaxation test, the spike rate declined faster and to a greater extent than the stress. In the creep test, the spike rate declined, despite a small increase in the strain. Three classes of mechanosensitive single-afferent units (low, wide dynamic range, and high threshold units) showed different response profiles against stress and strain. Low-threshold units exhibited a near linear relationship against the strain (R(2) = 0.8095), whereas high-threshold units exhibited a linear profile against the stress (R(2) = 0.9642). The afferent response is sensitive to the distension speed and to the stress and strain level during distension. However, the afferent nerve response is not a simple function of either stress or strain. Nonmechanical time-dependent adaptive responses other than those related to viscoelasticity also play a role.     

A finite element model of cell-matrix interactions to study the differential effect of scaffold composition on chondrogenic response to mechanical stimulation

Mechanically induced cell deformations have been shown to influence chondrocyte response in 3D culture. However, the relationship between the mechanical stimulation and cell response is not yet fully understood. In this study a finite element model was developed to investigate cell-matrix interactions under unconfined compression conditions, using a tissue engineered encapsulating hydrogel seeded with chondrocytes. Model predictions of stress and strain distributions within the cell and on the cell boundary were shown to exhibit space-dependent responses that varied with scaffold mechanical properties, the presence of a pericellular matrix (PCM), and the cell size. The simulations predicted that when the cells were initially encapsulated into the hydrogel scaffolds, the cell size hardly affected the magnitude of the stresses and strains that were reaching the encapsulated cells. However, with the inclusion of a PCM layer, larger cells experienced enhanced stresses and strains resulting from the mechanical stimulation. It was also noted that the PCM had a stress shielding effect on the cells in that the peak stresses experienced within the cells during loading were significantly reduced. On the other hand, the PCM caused the stresses at the cell-matrix interface to increase. Based on the model predictions, the PCM modified the spatial stress distribution within and around the encapsulated cells by redirecting the maximum stresses from the periphery of the cells to the cell nucleus. In a tissue engineered cartilage exposed to mechanical loading, the formation of a neo-PCM by encapsulated chondrocytes appears to protect them from initially excessive mechanical loading. Predictive models can thus shed important insight into how chondrocytes remodel their local environment in order to redistribute mechanical signals in tissue engineered constructs.     

Experimental validation of a finite element model of a human cadaveric tibia

Finite element (FE) models of long bones are widely used to analyze implant designs. Experimental validation has been used to examine the accuracy of FE models of cadaveric femurs; however, although convergence tests have been carried out, no FE models of an intact and implanted human cadaveric tibia have been validated using a range of experimental loading conditions. The aim of the current study was to create FE models of a human cadaveric tibia, both intact and implanted with a unicompartmental knee replacement, and to validate the models against results obtained from a comprehensive set of experiments. Seventeen strain rosettes were attached to a human cadaveric tibia. Surface strains and displacements were measured under 17 loading conditions, which consisted of axial, torsional, and bending loads. The tibia was tested both before and after implantation of the knee replacement. FE models were created based on computed tomography (CT) scans of the cadaveric tibia. The models consisted of ten-node tetrahedral elements and used 600 material properties derived from the CT scans. The experiments were simulated on the models and the results compared to experimental results. Experimental strain measurements were highly repeatable and the measured stiffnesses compared well to published results. For the intact tibia under axial loading, the regression line through a plot of strains predicted by the FE model versus experimentally measured strains had a slope of 1.15, an intercept of 5.5 microstrain, and an R(2) value of 0.98. For the implanted tibia, the comparable regression line had a slope of 1.25, an intercept of 12.3 microstrain, and an R(2) value of 0.97. The root mean square errors were 6.0% and 8.8% for the intact and implanted models under axial loads, respectively. The model produced by the current study provides a tool for simulating mechanical test conditions on a human tibia. This has considerable value in reducing the costs of physical testing by pre-selecting the most appropriate test conditions or most favorable prosthetic designs for final mechanical testing. It can also be used to gain insight into the results of physical testing, by allowing the prediction of those variables difficult or impossible to measure directly.     

Short-term changes in cell and matrix damage following mechanical injury of articular cartilage explants and modelling of microphysical mediators

The short-term responses of articular cartilage to mechanical injury have important implications for prevention and treatment of degenerative disease. Cell and matrix responses were monitored for 11 days following injurious compression of cartilage in osteochondral explants. Injury was applied as a single ramp compression to 14 MPa peak stress at one of three strain rates: 7 x 10(-1), 7 x 10(-3) or 7 x 10(-5) s(-1). Responses were quantified in terms of the appearance of macroscopic matrix cracks, changes in cell viability, and changes in cartilage wet weights. Loading at the highest strain rate resulted in acute cell death near the superficial zone in association with cracks, followed over the 11 days after compression by a gradual increase in cell death and loss of demarcation between matrix zones containing viable versus nonviable cells. In contrast, loading at the lowest strain rate resulted in more severe, nearly full-depth cell death acutely, but with no apparent worsening over the 11 days following compression. Between days 4 and 11, all mechanically injured explants significantly increased in wet weight, suggesting loss of matrix mechanical integrity independent of compression strain rate. Results demonstrate that short-term responses of cartilage depend upon the biomechanical characteristics of injurious loading, and suggest multiple independent pathways of mechanically-induced cell death and matrix degradation. Modifications to an existing fiber-reinforced poroelastic finite element model were introduced and the model was used for data interpretation and identification of microphysical events involved in cell and matrix injury. The model performed reasonably well at the slower strain rates and exhibited some capacity for anticipating the formation of superficial cracks during injurious loading. However, several improvements appear to be necessary before such a model could reliably be used to draw upon in vitro experimental results for prediction of injurious loading situations in vivo.     

Functional Adaptation in Female Rats: The Role of Estrogen Signaling

Background

Sex steroids have direct effects on the skeleton. Estrogen acts on the skeleton via the classical genomic estrogen receptors alpha and beta (ERα and ERβ), a membrane ER, and the non-genomic G-protein coupled estrogen receptor (GPER). GPER is distributed throughout the nervous system, but little is known about its effects on bone. In male rats, adaptation to loading is neuronally regulated, but this has not been studied in females.

Methodology/Principal Findings

We used the rat ulna end-loading model to induce an adaptive modeling response in ovariectomized (OVX) female Sprague-Dawley rats. Rats were treated with a placebo, estrogen (17β-estradiol), or G-1, a GPER-specific agonist. Fourteen days after OVX, rats underwent unilateral cyclic loading of the right ulna; half of the rats in each group had brachial plexus anesthesia (BPA) of the loaded limb before loading. Ten days after loading, serum estrogen concentrations, dorsal root ganglion (DRG) gene expression of ERα, ERβ, GPER, CGRPα, TRPV1, TRPV4 and TRPA1, and load-induced skeletal responses were quantified. We hypothesized that estrogen and G-1 treatment would influence skeletal responses to cyclic loading through a neuronal mechanism. We found that estrogen suppresses periosteal bone formation in female rats. This physiological effect is not GPER-mediated. We also found that absolute mechanosensitivity in female rats was decreased, when compared with male rats. Blocking of adaptive bone formation by BPA in Placebo OVX females was reduced.

Conclusions

Estrogen acts to decrease periosteal bone formation in female rats in vivo. This effect is not GPER-mediated. Gender differences in absolute bone mechanosensitivity exist in young Sprague-Dawley rats with reduced mechanosensitivity in females, although underlying bone formation rate associated with growth likely influences this observation. In contrast to female and male rats, central neuronal signals had a diminished effect on adaptive bone formation in estrogen-deficient female rats.