We have previously reported that an osteopontin-derived SVVYGLR peptide exhibited potent angiogenic activity in vitro and in vivo. In the present study, the focus points were on the in vitro effect of SVVYGLR on bone marrow stromal cell proliferation, as well as its in vivo effect on bone tissue formation when grafts made of CO3 Ap-collagen sponge -as a scaffold biomaterial containing the SVVYGLR motif -were implanted. SVVYGLR peptide promoted bone marrow stromal cell proliferation. When a CO3 Ap-collagen sponge containing SVVYGLR peptide was implanted as a graft into a tissue defect created in rat tibia, the migration of numerous vascular endothelial cells -as well as prominent angiogenesis -inside the graft could be detected after one week. These results thus suggested that our scaffold biomaterials including the peptide could be useful for bone tissue regeneration.

The purpose of this study is to investigate the feasibility of pure titanium to the metal-porcelain system. Pure titanium has the intermediate mechanical properties between gold and nickel-chromium alloys and higher sag resistance than these alloys.

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Atactic and syndiotactic-rich poly(vinyl alcohol) fibers were prepared by gel spinning using ethylene glycol as a solvent. The mechanical properties of the fibers were independent of the degree of polymerization, although they were dependent on syndiotacticity. The amounts of tie molecules and the difference between the amounts of hydrogen bonds and microvoids determine the mechanical properties. The mechanical properties depended on the orientation of the segments in the amorphous parts. The entangled segments produced in the amorphous parts as a consequence of the difficulty of drawing were considered to form the voids and cracks, which grow to a banded structure.

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Cellulose nanofiber (CNF) has been accepted as a valid nanofiller that can improve the mechanical properties of composite materials by mechanical and chemical methods. The purpose of this work is to numerically and experimentally evaluate the mechanical behavior of CNF-reinforced polymer composites under tensile loading. Finite element analysis (FEA) was conducted using a model for the representative volume element of CNF/epoxy composites to determine the effective Young's modulus and the stress state within the composites. The possible random orientation of the CNFs was considered in the finite element model. Tensile tests were also conducted on the CNF/epoxy composites to identify the effect of CNFs on their tensile behavior. The numerical findings were then correlated with the test results. The present randomly oriented CNF/epoxy composite model provides a means for exploring the property interactions across different length scales.

To develop a machine learning (ML) model that predicts disease groups or autoantibodies in patients with idiopathic inflammatory myopathies (IIMs) using muscle MRI radiomics features. Twenty-two patients with dermatomyositis (DM), 14 with amyopathic dermatomyositis (ADM), 19 with polymyositis (PM) and 19 with non-IIM were enrolled. Using 2D manual segmentation, 93 original features as well as 93 local binary pattern (LBP) features were extracted from MRI (short-tau inversion recovery [STIR] imaging) of proximal limb muscles. To construct and compare ML models that predict disease groups using each set of features, dimensional reductions were performed using a reproducibility analysis by inter-reader and intra-reader correlation coefficients, collinearity analysis, and the sequential feature selection (SFS) algorithm. Models were created using the linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), support vector machine (SVM), k-nearest neighbors (k-NN), random forest (RF) and multi-layer perceptron (MLP) classifiers, and validated using tenfold cross-validation repeated 100 times. We also investigated whether it was possible to construct models predicting autoantibody status. Our ML-based MRI radiomics models showed the potential to distinguish between PM, DM, and ADM. Models using LBP features provided better results, with macro-average AUC values of 0.767 and 0.714, accuracy of 61.2 and 61.4%, and macro-average recall of 61.9 and 59.8%, in the LDA and k-NN classifiers, respectively. In contrast, the accuracies of radiomics models distinguishing between non-IIM and IIM disease groups were low. A subgroup analysis showed that classification models for anti-Jo-1 and anti-ARS antibodies provided AUC values of 0.646–0.853 and 0.692–0.792, with accuracy of 71.5–81.0 and 65.8–78.3%, respectively. ML-based TA of muscle MRI may be used to predict disease groups or the autoantibody status in patients with IIM and is useful in non-invasive assessments of disease mechanisms.

A 60-year-old man with direct carotid cavernous fistula (CCF) due to a motor vehicle accident underwent internal carotid artery trapping following high-flow external carotid to internal carotid artery bypass (EC-IC bypass). Follow-up angiography revealed ipsilateral complex indirect cavernous arteriovenous fistula. Although the traumatic indirect CCF angioarchitecture differs from cavernous-sinus dural arteriovenous fistula (CS-DAVF), the present indirect fistula was similar to the latter. Complex indirect CCF can occur after treatment of direct CCF caused by severe head injury.