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BACKGROUND AND OBJECTIVE: Aging is associated with a reduction in muscle performance, but muscle weakness is characterized by a much greater loss of force loss compared to mass loss. The aim of this work is to assess the contribution of the extracellular matrix (ECM) to the lateral transmission of force in humans and the loss of transmitted force due to age-related modifications. METHODS: Finite element models of muscle bundles are developed for young and elderly human subjects, by considering a few fibers connected through an ECM layer. Bundles of young and elderly subjects are assumed to differ in terms of ECM thickness, as observed experimentally. A three-element-based Hill model is adopted to describe the active behavior of muscle fibers, while the ECM is modeled assuming an isotropic hyperelastic neo-Hookean constitutive formulation. Numerical analyses are carried out by mimicking, at the scale of a bundle, two experimental protocols from the literature. RESULTS: When comparing numerical results obtained for bundles of young and elderly subjects, a greater reduction in the total transmitted force is observed in the latter. The loss of transmitted force is 22 % for the elderly subjects, while it is limited to 7.5 % for the young subjects. The result for the elderly subjects is in line with literature studies on animal models, showing a reduction in the range of 20-34 %. This can be explained by an alteration in the mechanism of lateral force transmission due to the lower shear stiffness of the ECM in elderly subjects, related to its higher thickness. CONCLUSIONS: Computational modeling allows to evaluate at the bundle level how the age-related increase of the ECM amount between fibers affects the lateral transmission of force. The results suggest that the observed increase in ECM thickness in aging alone can explain the reduction of the total transmitted force, due to the impaired lateral transmission of force of each fiber.

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Polyvinyl alcohol (PVA) hydrogels are extensively used as scaffolds for tissue engineering, although their biodegradation properties have not been optimized yet. To overcome this limitation, partially oxidized PVA has been developed by means of different oxidizing agents, obtaining scaffolds with improved biodegradability. The oxidation reaction also allows tuning the mechanical properties, which are essential for effective use in vivo. In this work, the compressive mechanical behavior of native and partially oxidized PVA hydrogels is investigated, to evaluate the effect of different oxidizing agents, i.e., potassium permanganate, bromine, and iodine. For this purpose, PVA hydrogels are tested by means of indentation tests, also considering the time-dependent mechanical response. Indentation results show that the oxidation reduces the compressive stiffness from about 2.3 N/mm for native PVA to 1.1 ÷ 1.4 N/mm for oxidized PVA. During the consolidation, PVA hydrogels exhibit a force reduction of about 40% and this behavior is unaffected by the oxidizing treatment. A poroviscoelastic constitutive model is developed to describe the time-dependent mechanical response, accounting for the viscoelastic polymer matrix properties and the flow of water molecules within the matrix during long-term compression. This model allows to estimate the long-term Young's modulus of PVA hydrogels in drained conditions (66 kPa for native PVA and 34-42 kPa for oxidized PVA) and can be exploited to evaluate their performances under compressive stress in vivo, as in the case of cartilage tissue engineering.

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BACKGROUND AND OBJECTIVE: In the last few decades, several studies have been performed to investigate traumatic brain injuries (TBIs) and to understand the biomechanical response of brain tissues, by using experimental and computational approaches. As part of computational approaches, human head finite element (FE) models show to be important tools in the analysis of TBIs, making it possible to estimate local mechanical effects on brain tissue for different accident scenarios. The present study aims to contribute to the computational approach by means of the development of three advanced FE head models for accurately describing the head tissue dynamics, the first step to predict TBIs. METHODS: We have developed three detailed FE models of human heads from magnetic resonance images of three volunteers: an adult female (32 yrs), an adult male (35 yrs), and a young male (16 yrs). These models have been validated against experimental data of post mortem human subjects (PMHS) tests available in the literature. Brain tissue displacements relative to the skull, hydrostatic intracranial pressure, and head acceleration have been used as the parameters to compare the model response with the experimental response for validation. The software CORAplus (CORrelation and Analysis) has been adopted to evaluate the bio-fidelity level of FE models. RESULTS: Numerical results from the three models agree with experimental data. FE models presented in this study show a good bio-fidelity for hydrostatic pressure (CORA score of 0.776) and a fair bio-fidelity brain tissue displacements relative to the skull (CORA score of 0.443 and 0.535). The comparison among numerical simulations carried out with the three models shows negligible differences in the mechanical state of brain tissue due to the different morphometry of the heads, when the same acceleration history is considered. CONCLUSIONS: The three FE models, thanks to their accurate description of anatomical morphology and to their bio-fidelity, can be useful tools to investigate brain mechanics due to different impact scenarios. Therefore, they can be used for different purposes, such as the investigation of the correlation between head acceleration and tissue damage, or the effectiveness of helmet designs. This work does not address the issue to define injury thresholds for the proposed models.

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