Effects of Long-Term Sclerostin Deficiency on Trabecular Bone Mass and Adaption to Limb Loading Differ in Male and Female Mice.

A new therapeutic option to treat osteoporosis is focused on Wnt signaling and its inhibitor sclerostin, a product of the Sost gene. In this work, we study the effect of sclerostin deficiency on trabecular bone formation and resorption in male and female mice and whether it affects mechano-responsiveness. Male and female 10- and 26-week-old Sost knockout (KO) and littermate controls (LCs) were subjected to in vivo mechanical loading of the left tibia for 2 weeks. The right tibia served as internal control. The mice were imaged using in vivo micro-computed tomography at days 0, 5, 10, and 15 and tibiae were collected for histomorphometric analyses after euthanasia. Histomorphometry and micro-CT-based 3D time-lapse morphometry revealed an anabolic and anti-catabolic effect of Sost deficiency although increased trabecular bone resorption accompanied by diminished trabecular bone formation occurred with age. Loading led to diminished resorption in adult female but not in male mice. A net gain in bone volume could be achieved with mechanical loading in Sost KO adult female mice, which occurred through a further reduction in resorbed bone volume. Our data show that sclerostin deficiency has a particularly positive effect in adult female mice. Sclerostin antibodies are approved to treat postmenopausal women with high risk of osteoporotic fractures. Further studies are required to clarify whether both sexes benefit equally from sclerostin inhibition.

Tomography-Based Quantification of Regional Differences in Cortical Bone Surface Remodeling and Mechano-Response.

Bone has an adaptive capacity to maintain structural integrity. However, there seems to be a heterogeneous cortical (re)modeling response to loading at different regions within the same bone, which may lead to inconsistent findings since most studies analyze only one region. It remains unclear if the local mechanical environment is responsible for this heterogeneous response and whether both formation and resorption are affected. Thus, we compared the formation and resorptive response to in vivo loading and the strain environment at two commonly analyzed regions in the mouse tibia, the mid-diaphysis and proximal metaphysis. We quantified cortical surface (re)modeling by tracking changes between geometrically aligned consecutive in vivo micro-tomography images (time lapse 15 days). We investigated the local mechanical strain environment using finite element analyses. The relationship between mechanical stimuli and surface (re)modeling was examined by sub-dividing the mid-diaphysis and proximal metaphysis into 32 sub-regions. In response to loading, metaphyseal cortical bone (re)modeled predominantly at the periosteal surface, whereas diaphyseal (re)modeling was more pronounced at the endocortical surface. Furthermore, different set points and slopes of the relationship between engendered strains and remodeling response were found for the endosteal and periosteal surfaces at the metaphyseal and diaphyseal regions. Resorption was correlated with strain at the endocortical, but not the periosteal surfaces, whereas, formation correlated with strain at all surfaces, except at the metaphyseal periosteal surface. Therefore, besides mechanical stimuli, other non-mechanical factors are likely driving regional differences in adaptation. Studies investigating adaptation to loading or other treatments should consider region-specific (re)modeling differences.

Decoding rejuvenating effects of mechanical loading on skeletal aging using in vivo µCT imaging and deep learning.

Throughout the process of aging, dynamic changes of bone material, micro- and macro-architecture result in a loss of strength and therefore in an increased likelihood of fragility fractures. To date, precise contributions of age-related changes in bone (re)modeling and (de)mineralization dynamics to this fragility increase are not completely understood. Here, we present an image-based deep learning approach to quantitatively describe the effects of short-term aging and adaptive response to cyclic loading applied to proximal mouse tibiae and fibulae. Our approach allowed us to perform an end-to-end age prediction based on µCT imaging to determine the dynamic biological process of aging during a two week period, therefore permitting short-term bone aging analysis with 95% accuracy in predicting time points. In a second application, our deep learning analysis reveals that two weeks of in vivo mechanical loading are associated with an underlying rejuvenating effect of 5 days. Additionally, by quantitatively analyzing the learning process, we could, for the first time, identify the localization of the age-relevant encoded information and demonstrate 89% load-induced similarity of these locations in the loaded tibia with younger control bones. These data therefore suggest that our method enables identifying a general prognostic phenotype of a certain skeletal age as well as a temporal and localized loading-treatment effect on this apparent skeletal age for the studied mouse tibia and fibula. Future translational applications of this method may provide an improved decision-support method for osteoporosis treatment at relatively low cost. STATEMENT OF SIGNIFICANCE: Bone is a highly complex and dynamic structure that undergoes changes during the course of aging as well as in response to external stimuli, such as loading. Automatic assessment of "age" and "state" of the bone may lead to early prognosis of deceases such as osteoporosis and enables evaluating the effects of certain treatments. Here, we present an artificial intelligence-based method capable of automatically predicting the skeletal age from µCT images with 95% accuracy. Additionally, we utilize it to demonstrate the rejuvenation effects of in-vivo loading treatment on bones. We further, for the first time, break down aging-related local changes in bone by quantitatively analyzing "what the age assessment model has learned" and use this information to investigate the structural details of rejuvenation process.

A NanoFE simulation-based surrogate machine learning model to predict mechanical functionality of protein networks from live confocal imaging.

Sub-cellular mechanics plays a crucial role in a variety of biological functions and dysfunctions. Due to the strong structure-function relationship in cytoskeletal protein networks, light can be shed on their mechanical functionality by investigating their structures. Here, we present a data-driven approach employing a combination of confocal live imaging of fluorescent tagged protein networks, in silico mechanical experiments and machine learning to investigate this relationship. Our designed image processing and nanoFE mechanical simulation framework resolves the structure and mechanical behaviour of cytoskeletal networks and the developed gradient boosting surrogate models linking network structure to its functionality. In this study, for the first time, we perform mechanical simulations of Filamentous Temperature Sensitive Z (FtsZ) complex protein networks with realistic network geometry depicting its skeletal functionality inside organelles (here, chloroplasts) of the moss Physcomitrella patens. Training on synthetically produced simulation data enables predicting the mechanical characteristics of FtsZ network purely based on its structural features ( R 2 ⩾ 0.93 ), therefore allowing to extract structural principles enabling specific mechanical traits of FtsZ, such as load bearing and resistance to buckling failure in case of large network deformation.

Computational 3D imaging to quantify structural components and assembly of protein networks.

Traditionally, protein structures have been described by the secondary structure architecture and fold arrangement. However, the relatively novel method of 3D confocal microscopy of fluorescent-protein-tagged networks in living cells allows resolving the detailed spatial organization of these networks. This provides new possibilities to predict network functionality, as structure and function seem to be linked at various scales. Here, we propose a quantitative approach using 3D confocal microscopy image data to describe protein networks based on their nano-structural characteristics. This analysis is constructed in four steps: (i) Segmentation of the microscopic raw data into a volume model and extraction of a spatial graph representing the protein network. (ii) Quantifying protein network gross morphology using the volume model. (iii) Quantifying protein network components using the spatial graph. (iv) Linking these two scales to obtain insights into network assembly. Here, we quantitatively describe the filamentous temperature sensitive Z protein network of the moss Physcomitrella patens and elucidate relations between network size and assembly details. Future applications will link network structure and functionality by tracking dynamic structural changes over time and comparing different states or types of networks, possibly allowing more precise identification of (mal) functions or the design of protein-engineered biomaterials for applications in regenerative medicine. STATEMENT OF SIGNIFICANCE: Protein networks are highly complex and dynamic structures that play various roles in biological environments. Analyzing the detailed spatial structure of these networks may lead to new insight into biological functions and malfunctions. Here, we propose a tool set that extracts structural information at two scales of the protein network and allows therefore to address questions such as "how is the network built?" or "how networks grow?".

Cytological analysis and structural quantification of FtsZ1-2 and FtsZ2-1 network characteristics in Physcomitrella patens.

Although the concept of the cytoskeleton as a cell-shape-determining scaffold is well established, it remains enigmatic how eukaryotic organelles adopt and maintain a specific morphology. The Filamentous Temperature Sensitive Z (FtsZ) protein family, an ancient tubulin, generates complex polymer networks, with striking similarity to the cytoskeleton, in the chloroplasts of the moss Physcomitrella patens. Certain members of this protein family are essential for structural integrity and shaping of chloroplasts, while others are not, illustrating the functional diversity within the FtsZ protein family. Here, we apply a combination of confocal laser scanning microscopy and a self-developed semi-automatic computational image analysis method for the quantitative characterisation and comparison of network morphologies and connectivity features for two selected, functionally dissimilar FtsZ isoforms, FtsZ1-2 and FtsZ2-1. We show that FtsZ1-2 and FtsZ2-1 networks are significantly different for 8 out of 25 structural descriptors. Therefore, our results demonstrate that different FtsZ isoforms are capable of generating polymer networks with distinctive morphological and connectivity features which might be linked to the functional differences between the two isoforms. To our knowledge, this is the first study to employ computational algorithms in the quantitative comparison of different classes of protein networks in living cells.

Sost deficiency led to a greater cortical bone formation response to mechanical loading and altered gene expression.

Bone adaptation optimizes mass and structure, but the mechano-response is already reduced at maturation. Downregulation of sclerostin was believed to be a mandatory step in mechano-adaptation, but in young mice it was shown that load-induced formation can occur independent of sclerostin, a product of the Sost gene. We hypothesized that the bone formation and resorption response to loading is not affected by Sost deficiency, but is age-specific. Our findings indicate that the anabolic response to in vivo tibial loading was reduced at maturation in Sost Knockout (KO) and littermate control (LC) mice. Age affected all anabolic and catabolic parameters and altered Sost and Wnt target gene expression. While load-induced cortical resorption was similar between genotypes, loading-induced gains in mineralizing surface was enhanced in Sost KO compared to LC mice. Loading led to a downregulation in expression of the Wnt inhibitor Dkk1. Expression of Dkk1 was greater in both control and loaded limbs of Sost KO compared to LC mice suggesting a compensatory role in the absence of Sost. These data suggest physical activity could enhance bone mass concurrently with sclerostin-neutralizing antibodies, but treatment strategies should consider the influence of age on ultimate load-induced bone mass gains.

The Periosteal Bone Surface is Less Mechano-Responsive than the Endocortical.

Dynamic processes modify bone micro-structure to adapt to external loading and avoid mechanical failure. Age-related cortical bone loss is thought to occur because of increased endocortical resorption and reduced periosteal formation. Differences in the (re)modeling response to loading on both surfaces, however, are poorly understood. Combining in-vivo tibial loading, in-vivo micro-tomography and finite element analysis, remodeling in C57Bl/6J mice of three ages (10, 26, 78 week old) was analyzed to identify differences in mechano-responsiveness and its age-related change on the two cortical surfaces. Mechanical stimulation enhanced endocortical and periosteal formation and reduced endocortical resorption; a reduction in periosteal resorption was hardly possible since it was low, even without additional loading. Endocortically a greater mechano-responsiveness was identified, evident by a larger bone-forming surface and enhanced thickness of formed bone packets, which was not detected periosteally. Endocortical mechano-responsiveness was better conserved with age, since here adaptive response declined continuously with aging, whereas periosteally the main decay in formation response occurred already before adulthood. Higher endocortical mechano-responsiveness is not due to higher endocortical strains. Although it is clear structural adaptation varies between different bones in the skeleton, this study demonstrates that adaptation varies even at different sites within the same bone.

Aging Leads to a Dysregulation in Mechanically Driven Bone Formation and Resorption.

Physical activity is essential to maintain skeletal mass and structure, but its effect seems to diminish with age. To test the hypothesis that bone becomes less sensitive to mechanical strain with age, we used a combined in vivo/in silico approach. We investigated how maturation and aging influence the mechanical regulation of bone formation and resorption to 2 weeks of noninvasive in vivo controlled loading in mice. Using 3D in vivo morphometrical assessment of longitudinal microcomputed tomography images, we quantified sites in the mouse tibia where bone was deposited or resorbed in response to controlled in vivo loading. We compared the (re)modeling events (formation/resorption/quiescent) to the mechanical strains induced at these sites (predicted using finite element analysis). Mice of all age groups (young, adult, and elderly) responded to loading with increased formation and decreased resorption, preferentially at high strains. Low strains were associated with no anabolic response in adult and elderly mice, whereas young animals showed a strong response. Adult animals showed a clear separation between strain ranges where formation and resorption occurred but without an intermediate quiescent "lazy zone". This strain threshold disappeared in elderly mice, as mechanically induced (re)modeling became dysregulated, apparent in an inability to inhibit resorption or initiate formation. Contrary to what is generally believed until now, aging does not shift the mechanical threshold required to initiate formation or resorption, but rather blurs its specificity. These data suggest that pharmaceutical strategies augmenting physical exercise should consider this dysfunction in the mechanical regulation of bone (re)modeling to more effectively combat age-related bone loss.

Monitoring in vivo (re)modeling: a computational approach using 4D microCT data to quantify bone surface movements.

Bone undergoes continual damage repair and structural adaptation to changing external loads with the aim of maintaining skeletal integrity throughout life. The ability to monitor bone (re)modeling would allow for a better understanding in how various pathologies and interventions affect bone turnover and subsequent bone strength. To date, however, current methods to monitor bone (re)modeling over time and in space are limited. We propose a novel method to visualize and quantify bone turnover, based on in vivo microCT imaging and a 4D computational approach. By in vivo tracking of spatially correlated formation and resorption sites over time it classifies bone restructuring into (re)modeling sequences, the spatially and temporally linked sequences of formation, resorption and quiescent periods on the bone surface. The microCT based method was validated using experimental data from an in vivo mouse tibial loading model and ex vivo data of the mouse tibia. In this application, the method allows the visualization of time-resolved cortical (re)modeling and the quantification of short-term and long-term modeling on the endocortical and periosteal surface at the mid-diaphysis of loaded and control mice tibiae. Both short-term and long-term modeling processes, independent formation and resorption events, could be monitored and modeling (spatially not correlated formation and resorption) and remodeling (resorption followed by new formation at the same site) could be distinguished on the bone surface. This novel method that combines in vivo microCT with a computational approach is a powerful tool to monitor bone turnover in animal models now and is waiting to be applied to human patients in the near future.

Skeletal maturity leads to a reduction in the strain magnitudes induced within the bone: a murine tibia study.

Bone adapts to changes in the local mechanical environment (e.g. strains) through formation and resorption processes. However, the bone adaptation response is significantly reduced with increasing age. The mechanical strains induced within the bone by external loading are determined by bone morphology and tissue material properties. Although it is known that changes in bone mass, architecture and bone tissue quality occur with age, to what extent they contribute to the altered bone adaptation response remains to be determined. This study investigated alterations in strains induced in the tibia of different aged female C57Bl/6J mice (young, 10-week-old; adult, 26-week-old; and elderly, 78-week-old) subjected to in vivo compressive loading. Using a combined in vivo/in silico approach, the strains in the bones were assessed by both strain gauging and finite element modeling experiments. In cortical bone, strain magnitudes induced at the mid-diaphysis decreased by 20% from young to adult mice and by 15% from adult to elderly mice. In the cancellous bone (at the proximal metaphysis), induced strains were 70% higher in young compared with adult and elderly mice. Taking into account previous studies showing a reduced bone adaptation response to mechanical loading in adulthood, these results suggest that the diminished adaptive response is in part due to a reduction in the strains induced within the bone.

The influence of age on adaptive bone formation and bone resorption.

Bone is a tissue with enormous adaptive capacity, balancing resorption and formation processes. It is known that mechanical loading shifts this balance towards an increased formation, leading to enhanced bone mass and mechanical performance. What is not known is how this adaptive response to mechanical loading changes with age. Using dynamic micro-tomography, we show that structural adaptive changes of trabecular bone within the tibia of living mice subjected to two weeks of in vivo cyclic loading are altered by aging. Comparisons of 10, 26 and 78 weeks old animals reveal that the adaptive capacity diminishes. Strikingly, adaptation was asymmetric in that loading increases formation more than it reduces resorption. This asymmetry further shifts the (re)modeling balance towards a net bone loss with age. Loading results in a major increase in the surface area of mineralizing bone. Interestingly, the resorption thickness is independent of loading in trabecular bone in all age groups. This data suggests that during youth, mechanical stimulation induces the recruitment of bone modeling cells whereas in old age, only bone forming cells are affected. These findings provide mechanistic insights into the processes that guide skeletal aging in mice as well as in other mammals.

Mineralizing surface is the main target of mechanical stimulation independent of age: 3D dynamic in vivo morphometry.

Mechanical loading can increase cortical bone mass by shifting the balance between bone formation and resorption towards increased formation. With advancing age resorption outpaces formation resulting in a net loss in cortical bone mass. How cortical bone (re)modeling - especially resorption - responds to mechanical loading with aging remains unclear. In this study, we investigated age-related changes in the modulation of cortical bone formation and resorption sites by mechanical loading. Using in vivo microCT we determined the kinetics of three dimensional formation and resorption parameters. To analyze age-associated adaptation, the left tibiae of young, adult and elderly female C57BL/6 mice were cyclically loaded for 2weeks. Our data showed that in the nonloaded limbs, cortical bone loss with age is the result of an imbalance of resorption to formation thickness, while the surface of resorption is comparable to formation. Loading has a much stronger effect on formation than on resorption; more specifically this effect is due to an increase in formation surface with mechanical stimulation. This is the only effect of loading which is conserved into old age. The resorption thickness is independent of loading in all age groups. Using this novel image analysis technique, we were able for the first time to quantify age-related changes in cortical (re)modeling and the adaptive capacity to mechanics. Most likely a therapy against age-related bone loss combining physical exercise and pharmaceuticals is most efficient if they each act on different parameters of the (re)modeling process. Despite some differences in skeletal aging between mice and humans, our results would suggest that physical exercise in old individuals can positively influence only the formation side of (re) modeling.

Diminished response to in vivo mechanical loading in trabecular and not cortical bone in adulthood of female C57Bl/6 mice coincides with a reduction in deformation to load.

Bone loss occurs during adulthood in both women and men and affects trabecular bone more than cortical bone. The mechanism responsible for trabecular bone loss during adulthood remains unexplained, but may be due at least in part to a reduced mechanoresponsiveness. We hypothesized that trabecular and cortical bone would respond anabolically to loading and that the bone response to mechanical loading would be reduced and the onset delayed in adult compared to postpubescent mice. We evaluated the longitudinal adaptive response of trabecular and cortical bone in postpubescent, young (10 week old) and adult (26 week old) female C57Bl/6J mice to axial tibial compression using in vivo microCT (days 0, 5, 10, and 15) and dynamic histomorphometry (day 15). Loading elicited an anabolic response in both trabecular and cortical bone in young and adult mice. As hypothesized, trabecular bone in adult mice exhibited a reduced and delayed response to loading compared to the young mice, apparent in trabecular bone volume fraction and architecture after 10 days. No difference in mechanoresponsiveness of the cortical bone was observed between young and adult mice. Finite element analysis showed that load-induced strain was reduced with age. Our results suggest that trabecular bone loss that occurs in adulthood may in part be due to a reduced mechanoresponsiveness in this tissue and/or a reduction in the induced tissue deformation which occurs during habitual loading. Therapeutic approaches that address the mechanoresponsiveness of the bone tissue may be a promising and alternate strategy to maintain trabecular bone mass during aging.