The complex and highly organized environment in which cells reside consists primarily of the extracellular matrix (ECM) that delivers biological signals and physical stimuli to resident cells. In the native myocardium, the ECM contributes to both heart compliance and cardiomyocyte maturation and function. Thus, myocardium regeneration cannot be accomplished if cardiac ECM is not restored. We hypothesize that decellularized human skin might make an easily accessible and viable alternate biological scaffold for cardiac tissue engineering (CTE). To test our hypothesis, we decellularized specimens of both human skin and human myocardium and analyzed and compared their composition by histological methods and quantitative assays. Decellularized dermal matrix was then cut into 600-μm-thick sections and either tested by uniaxial tensile stretching to characterize its mechanical behavior or used as three-dimensional scaffold to assess its capability to support regeneration by resident cardiac progenitor cells (hCPCs) in vitro. Histological and quantitative analyses of the dermal matrix provided evidence of both effective decellularization with preserved tissue architecture and retention of ECM proteins and growth factors typical of cardiac matrix. Further, the elastic modulus of the dermal matrix resulted comparable with that reported in literature for the human myocardium and, when tested in vitro, dermal matrix resulted a comfortable and protective substrate promoting and supporting hCPC engraftment, survival and cardiomyogenic potential. Our study provides compelling evidence that dermal matrix holds promise as a fully autologous and cost-effective biological scaffold for CTE.

Osteoporotic fracture incidence represents a major social and economic concern in the modern society, where the progressive graying of the population involves an highly increased fracture occurrence. Although the gold standard to diagnose osteoporosis is represented by the T-score measurement, estimated from the Bone Mineral Density (BMD) using Dual-energy X-ray Absorptiometry (DXA), the identification of the subjects at high risk of fracture still remains an issue. From this perspective, the purpose of this work is to investigate the role that DXA-based two-dimensional patient-specific finite element (FE) models of the proximal femur, in combination with T-score, could play in enhancing the risk of fracture estimation. With this aim, 2D FE models were built from DXA images of the 28 post-menopausal female subjects involved. A sideways fall condition was reproduced and a Risk of Fracture ($\widehat{\text{RF}}$) was computed on the basis of principal strains criteria. The identified $\widehat{\text{RF}}$ was then compared to that derived from the CT-based models developed in a previous study. The 2D and 3D $\widehat{\text{RF}}$ turned out to be significantly correlated (Spearman's ρ = 0.66, p < 0.001), highlighting the same patients as those at higher risk. Moreover, the 2D $\widehat{\text{RF}}$ resulted significantly correlated with the T-score (Spearman's ρ = −0.69, p < 0.001), and managed to better differentiate osteopenic patients, drawing the attention to some of them. The Hip Structural Analysis (HSA) variables explaining the majority of the variance of the 2D and 3D fracture risk were the same as well, i.e., neck-shaft angle and narrow neck buckling ratio. In conclusion, DXA-based FE models, developable from currently available clinical data, appear promising in supporting and integrating the present diagnostic procedure.

At present, the current gold-standard for osteoporosis diagnosis is based on bone mineral density (BMD) measurement, which, however, has been demonstrated to poorly estimate fracture risk. Further parameters in the hands of the clinicians are represented by the hip structural analysis (HSA) variables, which include geometric information of the proximal femur cross section. The purpose of this study was to investigate the suitability of HSA parameters as additional hip fracture risk predictors. With this aim, twenty-eight three-dimensional patient-specific models of the proximal femur were built from computed tomography (CT) images and a sideways fall condition was reproduced by finite element (FE) analyses. A tensile or compressive predominance based on minimum and maximum principal strains was determined at each volume element and a risk factor (RF) was calculated. The power of HSA variables combinations to predict the maximum superficial RF values was assessed by multivariate linear regression analysis. The optimal regression model, identified through the Akaike information criterion (AIC), only comprises two variables: the buckling ratio (BR) and the neck-shaft angle (NSA). In order to validate the study, the model was tested on two additional patients who suffered a hip fracture after a fall. The results classified the patients in the high risk level, confirming the prediction power of the adopted model.

Principal components analysis is a powerful technique which can be used to reduce data dimensionality. With reference to three-dimensional bone shape models, it can be used to generate an unlimited number of models, defined by thousands of nodes, from a limited (less than twenty) number of scalars. The full procedure has been here described in detail and tested. Two databases were used as input data: the first database comprised 40 mandibles, while the second one comprised 98 proximal femurs. The “average shape” and principal components that were required to cover at least 90% of the whole variance were identified for both bones, as well as the statistical distributions of the respective principal components weights. Fifteen principal components sufficed to describe the mandibular shape, while nine components sufficed to describe the proximal femur morphology. A routine has been set up to generate any number of mandible or proximal femur geometries, according to the actual statistical shape distributions. The set-up procedure can be generalized to any bone shape given a sufficiently large database of the respective 3D shapes.

Summary: Background: Double pelvic osteotomy (DPO) planning is usually performed by hip palpation, and on radiographic images which give a poor representation of the complex three-dimensional manoeuvre required during surgery. Furthermore, bone strains which play a crucial role cannot be foreseen.Objective: To support surgeons and designers with biomechanical guidelines through a virtual model that would provide bone stress and strain, required moments, and three-dimensional measurements.Methods: A multibody numerical model for kinematic analyses has been coupled to a finite element model for stress/strain analysis on deformable bodies. The model was parametrized by the fixation plate angle, the iliac osteotomy angle, and the plate offset in ventro-dorsal direction. Model outputs were: acetabular ventro-version (VV) and lateralization (L), Norberg (NA) and dorsal acetabular rim (DAR) angles, the percentage of acetabular coverage (PC), the peak bone stress, and moments required to deform the pelvis.Results: Over 150 combinations of cited parameters and their respective outcome were analysed. Curves reporting NA and PC versus VV were traced for the given patient. The optimal VV range in relation to NA and PC limits was established. The 25° DPO plate results were the most similar to 20° TPO. The output L grew for positive iliac osteotomy inclinations. The 15° DPO plate was critical in relation to DAR, while very large VV could lead to bone failure.Clinical significance: Structural models can be a support to the study and optimization of DPO as they allow for foreseeing geometrical and structural outcomes of surgical choices.ORCID iDALA: http://orcid.org/0000-0002-4877-3630AV: http://orcid.org/0000-0003-2837-7822CB: http://orcid.org/0000-0002-7065-2552EZ: http://orcid.org/0000-0003-4121-6126MT: http://orcid.org/0000-0002-5699-6009