Translating Data from the Laboratory into Simulation: A Computational Framework for Subject-Specific Finite Element Musculoskeletal Simulation

Computational modeling is a powerful tool which has been used to inform decisions made by engineers, scientists, and clinicians for decades. Musculoskeletal modeling has emerged as a computational modeling technique used to understand the interaction between the body and its surroundings. There are several common approaches used for musculoskeletal modeling which take advantage of different model formulations to obtain information of interest. Unfortunately, models with different joint formulations inherit disparities in representations of ligament, muscle, and cartilage at joints of interest. These differences affect the way the joint functions and limit the insight it provides through computational analysis. Musculoskeletal models with high fidelity joint representations in a finite element framework have become increasingly viable in recent years, but three challenges limit progression: model personalization, modeling infrastructure, and computational efficiency. The goal of musculoskeletal modeling is almost entirely to understand the motion of the body, the mechanics of the joints, and the strain on the tissues in subjects performing various activities. These interests require models that act as the subject’s body would – a very complex task. Improving on methods in model personalization for calibrating joint strength, soft tissue response, and modeling geometry will continue to drive this work toward true subject specificity. Previously, software has been released which provides a modeling infrastructure for musculoskeletal modeling using rigid body dynamics. No such framework exists to build and perform musculoskeletal modeling with high fidelity joint representations in a finite element environment. A computational framework which provides methods to scale models and estimate joint kinematics and muscle forces directly from laboratory data would improve the accessibility and usability of these complex techniques. Developing tools which promote computational efficiency and manage effective parallelization of simulation and optimization will help improve the usability of musculoskeletal finite element modeling. The purpose of this work was to improve upon methods in musculoskeletal finite element modeling by developing novel techniques to evolve the current state-of-the-art in this area of research. Specifically, the first study calibrated the knee strength response of a musculoskeletal model of the lower limb to healthy data collected from subjects. The model was then used in the second study to perform concurrent estimation of muscle forces and tissue strain in subjects performing two activities. The third study considered markerbased motion and compared it to kinematics obtained from stereo radiography-based bone tracking. As part of this study a new set of polynomial splines describing the motion in 5 degrees of freedom at the knee were provided. Lastly, a computational framework was developed which served to scale a generic musculoskeletal finite element model and perform estimations of joint kinematics and muscle forces directly from laboratory data. The goal of this dissertation was to increase the accessibility of a powerful modeling approach to researchers around the globe by developing and advancing techniques which improve the usability of these methods

Histopathologic alterations associated with the transplanted homologous dog liver

Homotransplanted livers in dogs developed mononuclear, lymphocytic and plasmacytic infiltration and hepatic cell degeneration roughly paralleling survival time. Extensive histologic alterations of host reticuloendothelial structures occurred. Proliferation and infiltration of mononuclear cells, principally plasmacytes, were noted in lung, kidney, perirenal supportive tissue, bone marrow, and lymph nodes. Lymph nodes, in addition, were characterized by cortical and follicular depletion. These changes were considered to represent extensive host reticuloendothelial mobilization coincident to liver homotransplant rejection. The relation between these alterations and those found in other hypersensitivity states is discussed. © 1962

An Automated Process for 2D and 3D Finite Element Overclosure and Gap Adjustment using Radial Basis Function Networks

In biomechanics, geometries representing complicated organic structures are consistently segmented from sparse volumetric data or morphed from template geometries resulting in initial overclosure between adjacent geometries. In FEA, these overclosures result in numerical instability and inaccuracy as part of contact analysis. Several techniques exist to fix overclosures, but most suffer from several drawbacks. This work introduces a novel automated algorithm in an iterative process to remove overclosure and create a desired minimum gap for 2D and 3D finite element models. The RBF Network algorithm was introduced by its four major steps to remove the initial overclosure. Additionally, the algorithm was validated using two test cases against conventional nodal adjustment. The first case compared the ability of each algorithm to remove differing levels of overclosure between two deformable muscles and the effects on mesh quality. The second case used a non-deformable femur and deformable distal femoral cartilage geometry with initial overclosure to test both algorithms and observe the effects on the resulting contact FEA. The RBF Network in the first case study was successfully able to remove all overclosures. In the second case, the nodal adjustment method failed to create a usable FEA model, while the RBF Network had no such issue. This work proposed an algorithm to remove initial overclosures prior to FEA that has improved performance over conventional nodal adjustment, especially in complicated situations and those involving 3D elements. The work can be included in existing FEA modeling workflows to improve FEA results in situations involving sparse volumetric segmentation and mesh morphing. This algorithm has been implemented in MATLAB, and the source code is publicly available to download at the following GitHub repository: https://github.com/thor-andreassen/femorsComment: 26 Pages, 5 Figures, 2 Table

Integration of Neural Architecture within a Finite Element Framework for Improved Neuromusculoskeletal Modeling

Neuromusculoskeletal (NMS) models can aid in studying the impacts of the nervous and musculoskeletal systems on one another. These computational models facilitate studies investigating mechanisms and treatment of musculoskeletal and neurodegenerative conditions. In this study, we present a predictive NMS model that uses an embedded neural architecture within a finite element (FE) framework to simulate muscle activation. A previously developed neuromuscular model of a motor neuron was embedded into a simple FE musculoskeletal model. Input stimulation profiles from literature were simulated in the FE NMS model to verify effective integration of the software platforms. Motor unit recruitment and rate coding capabilities of the model were evaluated. The integrated model reproduced previously published output muscle forces with an average error of 0.0435 N. The integrated model effectively demonstrated motor unit recruitment and rate coding in the physiological range based upon motor unit discharge rates and muscle force output. The combined capability of a predictive NMS model within a FE framework can aid in improving our understanding of how the nervous and musculoskeletal systems work together. While this study focused on a simple FE application, the framework presented here easily accommodates increased complexity in the neuromuscular model, the FE simulation, or both

Reproducibility in modeling and simulation of the knee:Academic, industry, and regulatory perspectives

Stakeholders in the modeling and simulation (M&amp;S) community organized a workshop at the 2019 Annual Meeting of the Orthopaedic Research Society (ORS) entitled “Reproducibility in Modeling and Simulation of the Knee: Academic, Industry, and Regulatory Perspectives.” The goal was to discuss efforts among these stakeholders to address irreproducibility in M&amp;S focusing on the knee joint. An academic representative from a leading orthopedic hospital in the United States described a multi-institutional, open effort funded by the National Institutes of Health to assess model reproducibility in computational knee biomechanics. A regulatory representative from the United States Food and Drug Administration indicated the necessity of standards for reproducibility to increase utility of M&amp;S in the regulatory setting. An industry representative from a major orthopedic implant company emphasized improving reproducibility by addressing indeterminacy in personalized modeling through sensitivity analyses, thereby enhancing preclinical evaluation of joint replacement technology. Thought leaders in the M&amp;S community stressed the importance of data sharing to minimize duplication of efforts. A survey comprised 103 attendees revealed strong support for the workshop and for increasing emphasis on computational modeling at future ORS meetings. Nearly all survey respondents (97%) considered reproducibility to be an important issue. Almost half of respondents (45%) tried and failed to reproduce the work of others. Two-thirds of respondents (67%) declared that individual laboratories are most responsible for ensuring reproducible research whereas 44% thought that journals are most responsible. Thought leaders and survey respondents emphasized that computational models must be reproducible and credible to advance knee M&amp;S.</p

Peritoneal macrophage heterogeneity is associated with different peritoneal dialysis outcomes

Peritonitis remains the major obstacle for the maintenance of long-term peritoneal dialysis and dysregulated host peritoneal immune responses may compromise local anti-infectious defense, leading to treatment failure. Whilst, tissue mononuclear phagocytes, comprising macrophages and dendritic cells, are central to a host response to pathogens and the development of adaptive immune responses, they are poorly characterized in the human peritoneum. Combining flow cytometry with global transcriptome analysis, the phenotypic features and lineage identity of the major CD14+ macrophage and CD1c+ dendritic cell subsets in dialysis effluent were defined. Their functional specialization was reflected in cytokine generation, phagocytosis, and antigen processing/presentation. By analyzing acute bacterial peritonitis, stable (infection-free) and new-starter patients receiving peritoneal dialysis, we identified a skewed distribution of macrophage to dendritic cell subsets (increasing ratio) that associated with adverse peritonitis outcomes, history of multiple peritonitis episodes, and early catheter failure, respectively. Intriguingly, we also noted significant alterations of macrophage heterogeneity, indicative of different maturation and activation states that were associated with different peritoneal dialysis outcomes. Thus, our studies delineate peritoneal dendritic cells from macrophages within dialysate, and define cellular characteristics associated with peritoneal dialysis treatment failure. These are the first steps to unravelling the detrimental adaptive immune responses occurring as a consequence of peritonitis

Enabling and Enhancing Science Exploration Across the Solar System: Aerocapture Technology for SmallSat to Flagship Missions

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Viral Mimicry of Cdc2/Cyclin-Dependent Kinase 1 Mediates Disruption of Nuclear Lamina during Human Cytomegalovirus Nuclear Egress

The nuclear lamina is a major obstacle encountered by herpesvirus nucleocapsids in their passage from the nucleus to the cytoplasm (nuclear egress). We found that the human cytomegalovirus (HCMV)-encoded protein kinase UL97, which is required for efficient nuclear egress, phosphorylates the nuclear lamina component lamin A/C in vitro on sites targeted by Cdc2/cyclin-dependent kinase 1, the enzyme that is responsible for breaking down the nuclear lamina during mitosis. Quantitative mass spectrometry analyses, comparing lamin A/C isolated from cells infected with viruses either expressing or lacking UL97 activity, revealed UL97-dependent phosphorylation of lamin A/C on the serine at residue 22 (Ser22). Transient treatment of HCMV-infected cells with maribavir, an inhibitor of UL97 kinase activity, reduced lamin A/C phosphorylation by approximately 50%, consistent with UL97 directly phosphorylating lamin A/C during HCMV replication. Phosphorylation of lamin A/C during viral replication was accompanied by changes in the shape of the nucleus, as well as thinning, invaginations, and discrete breaks in the nuclear lamina, all of which required UL97 activity. As Ser22 is a phosphorylation site of particularly strong relevance for lamin A/C disassembly, our data support a model wherein viral mimicry of a mitotic host cell kinase activity promotes nuclear egress while accommodating viral arrest of the cell cycle

Oncogenic Properties of Apoptotic Tumor Cells in Aggressive B Cell Lymphoma

BACKGROUND: Cells undergoing apoptosis are known to modulate their tissue microenvironments. By acting on phagocytes, notably macrophages, apoptotic cells inhibit immunological and inflammatory responses and promote trophic signaling pathways. Paradoxically, because of their potential to cause death of tumor cells and thereby militate against malignant disease progression, both apoptosis and tumor-associated macrophages (TAMs) are often associated with poor prognosis in cancer. We hypothesized that, in progression of malignant disease, constitutive loss of a fraction of the tumor cell population through apoptosis could yield tumor-promoting effects. RESULTS: Here, we demonstrate that apoptotic tumor cells promote coordinated tumor growth, angiogenesis, and accumulation of TAMs in aggressive B cell lymphomas. Through unbiased "in situ transcriptomics" analysis-gene expression profiling of laser-captured TAMs to establish their activation signature in situ-we show that these cells are activated to signal via multiple tumor-promoting reparatory, trophic, angiogenic, tissue remodeling, and anti-inflammatory pathways. Our results also suggest that apoptotic lymphoma cells help drive this signature. Furthermore, we demonstrate that, upon induction of apoptosis, lymphoma cells not only activate expression of the tumor-promoting matrix metalloproteinases MMP2 and MMP12 in macrophages but also express and process these MMPs directly. Finally, using a model of malignant melanoma, we show that the oncogenic potential of apoptotic tumor cells extends beyond lymphoma. CONCLUSIONS: In addition to its profound tumor-suppressive role, apoptosis can potentiate cancer progression. These results have important implications for understanding the fundamental biology of cell death, its roles in malignant disease, and the broader consequences of apoptosis-inducing anti-cancer therapy