Mechanical & Industrial Engineering
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The mission of the Mechanical & Industrial Engineering Department is to serve the State of Montana, the region, and the nation by providing outstanding leadership and contributions in knowledge discovery, student learning, innovation and entrepreneurship, and service to community and profession.
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Item Heat conduction simulation of chondrocyte-embedded agarose gels suggests negligible impact of viscoelastic dissipation on temperature change(Elsevier BV, 2024-09) Myers, Erik; Piazza, Molly; Owkes, Mark; June, Ronald K.Agarose is commonly used for 3D cell culture and to mimic the stiffness of the pericellular matrix of articular chondrocytes. Although it is known that both temperature and mechanical stimulation affect the metabolism of chondrocytes, little is known about the thermal properties of agarose hydrogels. Thermal properties of agarose are needed to analyze potential heat production by chondrocytes induced by various experimental stimuli (carbon source, cyclical compression, etc). Utilizing ASTM C177, a custom-built thermal conductivity measuring device was constructed and used to calculate the thermal conductivity of 4.5 % low gelling temperature agarose hydrogels. Additionally, Differential Scanning Calorimetry was used to calculate the specific heat capacity of the agarose hydrogels. Testing of chondrocyte-embedded agarose hydrogels commonly occurs in Phosphate-Buffered Saline (PBS), and thermal analysis requires the free convection coefficient of PBS. This was calculated using a 2D heat conduction simulation within MATLAB in tandem with experimental data collected for known boundary and initial conditions. The specific heat capacity and thermal conductivity of 4.5 % agarose hydrogels was calculated to be 2.85 J/g°C and 0.121 W/mK, respectively. The free convection coefficient of PBS was calculated to be 1000.1 W/m2K. The values of specific heat capacity and thermal conductivity for agarose are similar to the reported values for articular cartilage, which are 3.20 J/g°C and 0.21 W/mK (Moghadam, et al. 2014). These data show that cyclical loading of hydrogel samples with these thermal properties will result in negligible temperature increases. This suggests that in addition to 4.5 % agarose hydrogels mimicking the physiological stiffness of the cartilage PCM, they can also mimic the thermal properties of articular cartilage for in vitro studies.Item Unraveling sex-specific risks of knee osteoarthritis before menopause: Do sex differences start early in life?(Elsevier BV, 2024-05) Hernandez, Paula A.; Churchill Bradford, John; Brahmachary, Priyanka; Ulman, Sophia; Robinson, Jennifer L.; June, Ronald K.; Cucchiarini, MagaliObjective. Sufficient evidence within the past two decades have shown that osteoarthritis (OA) has a sex-specific component. However, efforts to reveal the biological causes of this disparity have emerged more gradually. In this narrative review, we discuss anatomical differences within the knee, incidence of injuries in youth sports, and metabolic factors that present early in life (childhood and early adulthood) that can contribute to a higher risk of OA in females. Design. We compiled clinical data from multiple tissues within the knee joint—since OA is a whole joint disorder—aiming to reveal relevant factors behind the sex differences from different perspectives. Results. The data gathered in this review indicate that sex differences in articular cartilage, meniscus, and anterior cruciate ligament are detected as early as childhood and are not only explained by sex hormones. Aiming to unveil the biological causes of the uneven sex-specific risks for knee OA, we review the current knowledge of sex differences mostly in young, but also including old populations, from the perspective of (i) human anatomy in both healthy and pathological conditions, (ii) physical activity and response to injury, and (iii) metabolic signatures. Conclusions. We propose that to close the gap in health disparities, and specifically regarding OA, we should address sex-specific anatomic, biologic, and metabolic factors at early stages in life, as a way to prevent the higher severity and incidence of OA in women later in life.Item Evolution and advancements in genomics and epigenomics in OA research: How far we have come(Elsevier BV, 2024-02) Ramos, Yolande F. M.; Rice, Sarah J.; Ali, Shabana Amanda; Pastrello, Chiara; Jurisica, Igor; Farooq Rai, Muhammad; Collins, Kelsey H.; Lang, Annemarie; Maerz, Tristan; Geurts, Jeroen; Ruiz Romero, Cristina; June, Ronald K.; Appleton, C. Thomas; Rockel, Jason S.; Kapoor, MohitObjective. Osteoarthritis (OA) is the most prevalent musculoskeletal disease affecting articulating joint tissues, resulting in local and systemic changes that contribute to increased pain and reduced function. Diverse technological advancements have culminated in the advent of high throughput “omic” technologies, enabling identification of comprehensive changes in molecular mediators associated with the disease. Amongst these technologies, genomics and epigenomics – including methylomics and miRNomics, have emerged as important tools to aid our biological understanding of disease. Design. In this narrative review, we selected articles discussing advancements and applications of these technologies to OA biology and pathology. We discuss how genomics, deoxyribonucleic acid (DNA) methylomics, and miRNomics have uncovered disease-related molecular markers in the local and systemic tissues or fluids of OA patients. Results. Genomics investigations into the genetic links of OA, including using genome-wide association studies, have evolved to identify 100+ genetic susceptibility markers of OA. Epigenomic investigations of gene methylation status have identified the importance of methylation to OA-related catabolic gene expression. Furthermore, miRNomic studies have identified key microRNA signatures in various tissues and fluids related to OA disease. Conclusions. Sharing of standardized, well-annotated omic datasets in curated repositories will be key to enhancing statistical power to detect smaller and targetable changes in the biological signatures underlying OA pathogenesis. Additionally, continued technological developments and analysis methods, including using computational molecular and regulatory networks, are likely to facilitate improved detection of disease-relevant targets, in-turn, supporting precision medicine approaches and new treatment strategies for OA.Item Three Decades of Advancements in Osteoarthritis Research: Insights from Transcriptomic, Proteomic, and Metabolomic Studies(Elsevier BV, 2023-12) Farooq Rai, Muhammad; Collins, Kelsey H.; Lang, Annemarie; Maerz, Tristan; Geurts, Jeroen; Ruiz-Romero, Cristina; June, Ronald K.; Ramos, Yolande; Rice, Sarah J.; Ali, Shabana Amanda; Pastrello, Chiara; Jurisica, Igor; Appleton, C. Thomas; Rockel, Jason S.; Kapoor, MohitObjective. Osteoarthritis (OA) is a complex disease involving contributions from both local joint tissues and systemic sources. Patient characteristics, encompassing sociodemographic and clinical variables, are intricately linked with OA rendering its understanding challenging. Technological advancements have allowed for a comprehensive analysis of transcripts, proteomes and metabolomes in OA tissues/fluids through omic analyses. The objective of this review is to highlight the advancements achieved by omic studies in enhancing our understanding of OA pathogenesis over the last three decades. Design. We conducted an extensive literature search focusing on transcriptomics, proteomics and metabolomics within the context of OA. Specifically, we explore how these technologies have identified individual transcripts, proteins, and metabolites, as well as distinctive endotype signatures from various body tissues or fluids of OA patients, including insights at the single-cell level, to advance our understanding of this highly complex disease. Results. Omic studies reveal the description of numerous individual molecules and molecular patterns within OA-associated tissues and fluids. This includes the identification of specific cell (sub)types and associated pathways that contribute to disease mechanisms. However, there remains a necessity to further advance these technologies to delineate the spatial organization of cellular subtypes and molecular patterns within OA-afflicted tissues. Conclusions. Leveraging a multi-omics approach that integrates datasets from diverse molecular detection technologies, combined with patients’ clinical and sociodemographic features, and molecular and regulatory networks, holds promise for identifying unique patient endophenotypes. This holistic approach can illuminate the heterogeneity among OA patients and, in turn, facilitate the development of tailored therapeutic interventions.Item Germ‐Free C57BL/6 Mice Have Increased Bone Mass and Altered Matrix Properties but Not Decreased Bone Fracture Resistance(Wiley, 2023-08) Vahidi, Ghazal; Moody, Maya; Welhave, Hope D.; Davidson, Leah; Rezaee, Taraneh; Behzad, Ramina; Karim, Lamya; Roggenbeck, Barbara A.; Walk, Seth T.; Martin, Stephen A.; June, Ronald K.; Heveran, Chelsea M.The gut microbiome impacts bone mass, which implies a disruption to bone homeostasis. However, it is not yet clear how the gut microbiome affects the regulation of bone mass and bone quality. We hypothesized that germ-free (GF) mice have increased bone mass and decreased bone toughness compared with conventionally housed mice. We tested this hypothesis using adult (20- to 21-week-old) C57BL/6J GF and conventionally raised female and male mice (n = 6–10/group). Trabecular microarchitecture and cortical geometry were measured from micro–CT of the femur distal metaphysis and cortical midshaft. Whole-femur strength and estimated material properties were measured using three-point bending and notched fracture toughness. Bone matrix properties were measured for the cortical femur by quantitative back-scattered electron imaging and nanoindentation, and, for the humerus, by Raman spectroscopy and fluorescent advanced glycation end product (fAGE) assay. Shifts in cortical tissue metabolism were measured from the contralateral humerus. GF mice had reduced bone resorption, increased trabecular bone microarchitecture, increased tissue strength and decreased whole-bone strength that was not explained by differences in bone size, increased tissue mineralization and fAGEs, and altered collagen structure that did not decrease fracture toughness. We observed several sex differences in GF mice, most notably for bone tissue metabolism. Male GF mice had a greater signature of amino acid metabolism, and female GF mice had a greater signature of lipid metabolism, exceeding the metabolic sex differences of the conventional mice. Together, these data demonstrate that the GF state in C57BL/6J mice alters bone mass and matrix properties but does not decrease bone fracture resistance. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).Item Metabolomic Profiling to Understand Chondrocyte Metabolism(Springer Nature, 2022-11) Brahmachary, Priyanka; Welhaven, Hope D.; June, Ronald K.Metabolism has long been recognized as a critical physiological process necessary to maintain homeostasis in all types of cells including the chondrocytes of articular cartilage. Alterations in metabolism in disease and metabolic adaptation to physiological stimuli such as mechanical loading are increasingly recognized as important for understanding musculoskeletal systems such as synovial joints. Metabolomics is an emerging technique that allows quantitative measurement of thousands of small molecule metabolites that serve as both products and reactants to myriad reactions of cellular biochemistry. This protocol describes procedures to perform metabolomic profiling on chondrocytes and other tissues and fluids within the synovial joint.Item Correlations between metabolites in the synovial fluid and serum: A mouse injury study(Wiley, 2022-03) Wallace, Cameron W.; Hislop, Brady; Hahn, Alyssa K.; Erdogan, Ayten E.; Brahmachary, Priyanka P.; June, Ronald K.Osteoarthritis occurs frequently after joint injury. Currently, osteoarthritis is diagnosed by radiographic changes that are typically found after the disease has progressed to multiple tissues. The primary objective was to compare potential metabolomic biomarkers of joint injury between synovial fluid and serum in a mouse model of posttraumatic osteoarthritis. The secondary objective was to gain insight into the pathophysiology of osteoarthritis by examining metabolomic profiles after joint injury. Twelve-week-old adult female C57BL/6 mice (n = 12) were randomly assigned to control, Day 1, or Day 8 postinjury groups. Randomly selected stifle joints were subjected to a single rapid compression. At Days 1 and 8 postinjury, serum was extracted before mice were euthanized for synovial fluid collection. Metabolomic profiling detected ~2500 metabolites across serum and synovial fluid. Of these, 179 were positively correlated and 51 were negatively correlated between synovial fluid and serum, indicating the potential for the development of metabolomic biomarkers. Synovial fluid captured injury-induced differences in metabolomic profiles at both Days 1 and 8 after injury whereas serum did not. However, synovial fluid and serum were distinct at both time points after injury. In synovial fluid, pathways of interest mapped to amino acid synthesis and degradation, bupropion degradation, and transfer RNA (tRNA) charging. In serum, pathways were amino acid synthesis and degradation, the phospholipase pathway, and nicotine degradation. These results provide a rich picture of the injury response at early time points after joint injury. Furthermore, the correlations between synovial fluid and serum metabolites suggest the potential to gain insight into intra-articular pathophysiology through analysis of serum metabolites.Item A 3-D constitutive model for finite element analyses of agarose with a range of gel concentrations(Elsevier BV, 2020-11) Wang, Xiaogang; June, Ronald K.; Pierce, David M.Hydrogels have seen widespread application across biomedical sciences and there is considerable interest in using hydrogels, including agarose, for creating in vitro three-dimensional environments to grow cells and study mechanobiology and mechanotransduction. Recent advances in the preparation of agarose gels enable successful encapsulation of viable cells at gel concentrations as high as 5%. Agarose with a range of gel concentrations can thus serve as an experimental model mimicking changes in the 3-D microenvironment of cells during disease progression and can facilitate experiments aimed at probing the corresponding mechanobiology, e.g. the evolving mechanobiology of chondrocytes during the progression of osteoarthritis. Importantly, whether stresses (forces) or strains (displacements) drive mechanobiology and mechanotransduction is currently unknown. We can use experiments to quantify mechanical properties of hydrogels, and imaging to estimate microstructure and even strains; however, only computational models can estimate intra-gel stresses in cell-seeded agarose constructs because the required in vitro experiments are currently impossible. Finite element modeling is well-established for (computational) mechanical analyses, but accurate constitutive models for modeling the 3-D mechanical environments of cells within high-stiffness agarose with varying gel concentrations are currently unavailable. In this study we aimed to establish a 3-D constitutive model of high-stiffness agarose with a range of gel concentrations. We applied a multi-step, physics-based optimization approach to separately fit subsets of model parameters and help achieve robust convergence. Our constitutive model, fitted to experimental data on progressive stress-relaxations, was able to predict reaction forces determined from independent experiments on cyclical loading. Our model has broad applications in finite element modeling aimed at interpreting mechanical experiments on agarose specimens seeded with cells, particularly in predicting distributions of intra-gel stresses. Our model and fitted parameters enable more accurate finite element simulations of high-stiffness agarose constructs, and thus better understanding of experiments aimed at mechanobiology, mechanotransduction, or other applications in tissue engineering.Item Metabolomic Profiling to Understand Chondrocyte Metabolism(2021) Brahmachary, Priyanka; Welhaven, Hope D.; June, Ronald K.Metabolism has long been recognized as a critical physiological process necessary to maintain homeostasis in all types of cells including the chondrocytes of articular cartilage. Alterations in metabolism in disease and metabolic adaptation to physiological stimuli such as mechanical loading are increasingly recognized as important for understanding musculoskeletal systems such as synovial joints. Metabolomics is an emerging technique that allows quantitative measurement of thousands of small molecule metabolites that serve as both products and reactants to myriad reactions of cellular biochemistry. This protocol describes procedures to perform metabolomic profiling on chondrocytes and other tissues and fluids within the synovial joint.Item Characterization of synovial fluid metabolomic phenotypes of cartilage morphological changes associated with osteoarthritis(2019-08) Carlson, Alyssa K.; Rawle, Rachel A.; Wallace, Cameron W.; Brooks, Ellen G.; Adams, Erik; Greenwood, Mark C.; Olmer, Merissa; Lotz, Martin K.; Bothner, Brian; June, Ronald K."Objective Osteoarthritis (OA) is a multifactorial disease with etiological heterogeneity. The objective of this study was to classify OA subgroups by generating metabolomic phenotypes from human synovial fluid. Design: Post mortem synovial fluids (n = 75) were analyzed by high performance-liquid chromatography mass spectrometry (LC-MS) to measure changes in the global metabolome. Comparisons of healthy (grade 0), early OA (grades I-II), and late OA (grades III-IV) donor populations were considered to reveal phenotypes throughout disease progression. Results: Global metabolomic profiles in synovial fluid were distinct between healthy, early OA, and late OA donors. Pathways differentially activated among these groups included structural deterioration, glycerophospholipid metabolism, inflammation, central energy metabolism, oxidative stress, and vitamin metabolism. Within disease states (early and late OA), subgroups of donors revealed distinct phenotypes. Synovial fluid metabolomic phenotypes exhibited increased inflammation (early and late OA), oxidative stress (late OA), or structural deterioration (early and late OA) in the synovial fluid. Conclusion: These results revealed distinct metabolic phenotypes in human synovial fluid, provide insight into pathogenesis, represent novel biomarkers, and can move toward developing personalized interventions for subgroups of OA patients.