Browsing by Subject "mechanical loading"
Now showing 1 - 6 of 6
Results Per Page
Sort Options
Item Exercise Alters Mineral and Matrix Composition in the Absence of Adding New Bone(2008-12) Kohn, David H.; Sahar, Nadder D.; Wallace, Joseph M.; Golcuk, Kurtulus; Morris, Michael D.The mechanical properties of bone are dictated by its amount, distribution and ‘quality’. The composition of the mineral and matrix phases is integral to defining ‘bone quality’. Exercise can potentially increase resistance to fracture, yet the effects of exercise on skeletal fragility, and how alterations in fragility are modulated by the amount, distribution and composition of bone, are unknown. In this investigation, the effects of exercise on the size, composition, mechanical properties and damage resistance of bones from mice of various ages, background strains and genetic makeup were assessed, as a means of testing the hypothesis that mechanical loading can improve skeletal fragility via compositional alterations. C57BL/6 mice (4-month-old males) ran on a treadmill for 21 days. Tibiae from exercised and control mice were analyzed for cross-sectional geometry, mechanical properties, microdamage and composition. Exercise significantly increased strength without increasing cross-sectional properties, suggesting that mechanical stimulation led to changes in the bone matrix, and these changes led to the improvements in mechanical properties. Consistent with this interpretation, the mineral/matrix ratio was significantly increased in exercised bones. The number of fatigue-induced microcracks was significantly lower in exercised bones, providing evidence that exercise modulates fatigue resistance. The ratio of nonreducible/reducible cross-links mirrored the damage data. Similar trends (exercise induced increases in mechanical properties without increases in cross-sectional properties, but with compositional changes) were also observed in 2-month-old biglycan-deficient and wild-type mice bred on a C57BL/6x129 genetic background.Item Finite Element Analysis of an Electro-Mechanical Knee Loading Device(ASME, 2016-11) Prabhala, Sai Krishna; Anwar, Sohel; Yokota, Hiroki; Chien, Stanley; Mechanical Engineering, School of Engineering and TechnologyThe mechanical loading of knee is an effective regimen for treatment of bone related ailments like fractures, osteoarthritis, and osteoporosis [1–2]. Efficacy of knee loading is evident from the previous studies done on rodents and other small animals [3]. In order to test this loading concept on human subjects, a prototype of a portable and compact device was designed previously. In this study, the prototype device was re-designed with a modified slider crank mechanism. Since this device has multiple moving parts, durability of the parts under stress is a key factor for its success. Thus, this paper focuses on its mechanical characteristics using finite element analysis (FEA). In particular, structural deformities and modal frequency characteristics are analyzed. The FEA analysis is performed on a CAD model of the device. The static structural and modal analyses are performed on two different configurations, in which different materials were used for selected components. Individual parts were meshed and solved extensively to obtain useful results under maximum loading conditions, such as total deformation, Von Mises stress, and modal frequencies. The analysis results show that ABS plastic based design provides an optimal solution in terms weight, cost, and usability.Item Finite Element Analysis of the Mouse Proximal Ulna in Response to Elbow Loading(Springer, 2018) Jiang, Feifei; Jalali, Aydin; Deguchi, Chie; Chen, Andy; Liu, Shengzhi; Kondo, Rika; Minami, Kazumasa; Horiuchi, Takashi; Li, Bai-Yan; Robling, Alexander G.; Chen, Jie; Yokota, Hiroki; Mechanical and Energy Engineering, School of Engineering and TechnologyBone is a mechano-sensitive tissue that alters its structure and properties in response to mechanical loading. We have previously shown that application of lateral dynamic loads to a synovial joint, such as the knee and elbow, suppresses degradation of cartilage and prevents bone loss in arthritis and postmenopausal mouse models, respectively. While loading effects on pathophysiology have been reported, mechanical effects on the loaded joint are not fully understood. Because the direction of joint loading is non-axial, not commonly observed in daily activities, strain distributions in the laterally loaded joint are of great interest. Using elbow loading, we herein characterized mechanical responses in the loaded ulna focusing on the distribution of compressive strain. In response to 1-N peak-to-peak loads, which elevate bone mineral density and bone volume in the proximal ulna in vivo, we conducted finite-element analysis and evaluated strain magnitude in three loading conditions. The results revealed that strain of ~ 1000 μstrain (equivalent to 0.1% compression) or above was observed in the limited region near the loading site, indicating that the minimum effective strain for bone formation is smaller with elbow loading than axial loading. Calcein staining indicated that elbow loading increased bone formation in the regions predicted to undergo higher strain.Item In vivo axial loading of the mouse tibia(Springer, 2015) Melville, Katherine M.; Robling, Alexander G.; van der Meulen, Marjolein C. H.; Department of Anatomy and Cell Biology, IU School of MedicineNoninvasive methods to apply controlled, cyclic loads to the living skeleton are used as anabolic procedures to stimulate new bone formation in adults and enhance bone mass accrual in growing animals. These methods are also invaluable for understanding bone signaling pathways. Our focus here is on a particular loading model: in vivo axial compression of the mouse tibia. An advantage of loading the tibia is that changes are present in both the cancellous envelope of the proximal tibia and the cortical bone of the tibial diaphysis. To load the tibia of the mouse axially in vivo, a cyclic compressive load is applied up to five times a week to a single tibia per mouse for a duration lasting from 1 day to 6 weeks. With the contralateral limb as an internal control, the anabolic response of the skeleton to mechanical stimuli can be studied in a pairwise experimental design. Here, we describe the key parameters that must be considered before beginning an in vivo mouse tibial loading experiment, including methods for in vivo strain gauging of the tibial midshaft, and then we describe general methods for loading the mouse tibia for an experiment lasting multiple days.Item Model-based Comparative Prediction of Transcription-Factor Binding Motifs in Anabolic Responses in Bone.(Elsevier, 2007) Chen, Andy B.; Hamamura, Kazunori; Wang, Guohua; Xing, Weirong; Mohan, Subburaman; Yokota, Hiroki; Liu, Yunlong; Department of Biomedical Engineering, School of Engineering and TechnologyUnderstanding the regulatory mechanism that controls the alteration of global gene expression patterns continues to be a challenging task in computational biology. We previously developed an ant algorithm, a biologically-inspired computational technique for microarray data, and predicted putative transcription-factor binding motifs (TFBMs) through mimicking interactive behaviors of natural ants. Here we extended the algorithm into a set of web-based software, Ant Modeler, and applied it to investigate the transcriptional mechanism underlying bone formation. Mechanical loading and administration of bone morphogenic proteins (BMPs) are two known treatments to strengthen bone. We addressed a question: Is there any TFBM that stimulates both “anabolic responses of mechanical loading” and “BMP-mediated osteogenic signaling”? Although there is no significant overlap among genes in the two responses, a comparative model-based analysis suggests that the two independent osteogenic processes employ common TFBMs, such as a stress responsive element and a motif for peroxisome proliferator-activated receptor (PPAR). The post-modeling in vitro analysis using mouse osteoblast cells supported involvements of the predicted TFBMs such as PPAR, Ikaros 3, and LMO2 in response to mechanical loading. Taken together, the results would be useful to derive a set of testable hypotheses and examine the role of specific regulators in complex transcriptional control of bone formation.Item Physical Weight Loading Induces Expression of Tryptophan Hydroxylase 2 in the Brain Stem(2014-01) Shim, Joon W.; Dodge, Todd R.; Hammond, Max A.; Wallace, Joseph M.; Zhou, Feng C.; Yokota, HirokiSustaining brain serotonin is essential in mental health. Physical activities can attenuate mental problems by enhancing serotonin signaling. However, such activity is not always possible in disabled individuals or patients with dementia. Knee loading, a form of physical activity, has been found to mimic effects of voluntary exercise. Focusing on serotonergic signaling, we addressed a question: Does local mechanical loading to the skeleton elevate expression of tryptophan hydroxylase 2 (tph2) that is a rate-limiting enzyme for brain serotonin? A 5 min knee loading was applied to mice using 1 N force at 5 Hz for 1,500 cycles. A 5-min treadmill running was used as an exercise (positive) control, and a 90-min tail suspension was used as a stress (negative) control. Expression of tph2 was determined 30 min – 2 h in three brain regions ––frontal cortex (FC), ventromedial hypothalamus (VMH), and brain stem (BS). We demonstrated for the first time that knee loading and treadmill exercise upregulated the mRNA level of tph2 in the BS, while tail suspension downregulated it. The protein level of tph2 in the BS was also upregulated by knee loading and downregulated by tail suspension. Furthermore, the downregulation of tph2 mRNA by tail suspension can be partially suppressed by pre-application of knee loading. The expression of tph2 in the FC and VMH was not significantly altered with knee loading. In this study we provided evidence that peripheral mechanical loading can activate central tph2 expression, suggesting that physical cues may mediate tph2-cathalyzed serotonergic signaling in the brain.