The purpose of this study is to develop a novel scaffold, derived from fish scales, as an alternative functional material with sufficient mechanical strength for corneal regenerative applications. Fish scales, which are usually considered as marine wastes, were acellularized, decalcified and fabricated into collagen scaffolds. The microstructure of the acellularized scaffold was imaged by scanning electron microscopy (SEM). The acellularization and decalcification treatments did not affect the naturally 3-dimentional, highly centrally-oriented micropatterned structure of the material. To assess the cytocompatibility of the scaffold with corneal cells, rabbit corneal cells were cultured on the scaffold and examined under SEM and confocal microscopy at different time periods. Rapid cell proliferation and migration on the scaffold were observed under SEM and confocal microscopy. The highly centrallyoriented micropatterned structure of the scaffold was beneficial for efficient nutrient and oxygen supply to the cells cultured in the three-dimensional matrices, and therefore it is useful for high-density cell seeding and spreading. Collectively, we demonstrate the superior cellular conductivity of the newly developed material. We provide evidences for the feasibility of the scaffold as a template for corneal cells growth and migration, and thus the fish scale-derived scaffold can be developed as a promising material for tissue-engineering of cornea.
Several modifications of the induced membrane technique (IMT) have been reported, but there is no consensus regarding their results and prognosis. Moreover, most studies have focused on tibial defects; no meta‐analysis of the treatment of femoral defects using the IMT has been reported. This systematic review and meta‐analysis aimed to identify the potential risk factors of post‐procedural complications following the treatment of segmental femoral defects using the IMT. A comprehensive search was performed on the Cochrane Library, EBSCO, EMBASE, Ovid, PubMed, Scopus, and Web of Science databases, using the keywords “femur,” “Masquelet technique,” and “induced membrane technique.” Original articles composed in English, having accessible individual patient data, and reporting more than two cases of bony defect or nonunion of femur or more than five cases of any body part were included. Post‐procedural bone graft infections, final union status, and union time after second‐stage operation were analyzed. Fourteen reports, including 90 patients, were used in this study. External fixation in second‐stage surgery had an odds ratio of 9.267 for post‐procedural bone graft infection (p = 0.047). The odds ratio of post‐procedural bone graft infection and age >65 years for final non‐union status was 51.05 (p = 0.003) and 9.18 (p = 0.042). Shorter union time was related to impregnated antibiotics in the spacer (p = 0.005), transplanting all‐autologous grafts (p = 0.042), and the application of intramedullary nails as the second‐stage fixation method (p = 0.050). The IMT appears to be reasonable and reproducible for femoral segmental bone defects. Several preoperative and surgical factors may affect post‐procedural complications and union time.
Natural bone is comprised of nanosized blade-like crystals of hydroxyapatite grown in close contact with collagen (Col) fibers. Characteristics of artificial bone tissue differ considerably with those of natural ones, mainly from the unusual self-organizing interaction between the apatite crystals and the proteic components. Nanoparticle spheres of hydroxyapatite (n-HA), dispersed in reconstituted fibrous Col, were prepared in three weight ratios of 75:25, 65:35, and 50:50 (n-HA:Col). Bone marrow mesenchymal stem cells (MSCs) from rabbits were seeded and cultured on the n-HA/Col microbeads and characterized. n-HA were evenly distributed throughout the Col matrix and aggregated to microbeads as determined by scanning electron microscopy. Electron and confocal microscopy showed that the MSCs spread and attached to microbeads via focal adhesions, while staining for F-actin and DNA revealed the presence of stress fibers. The phenotype of the MSCs in the flow cytometry was identified as CD11a-, CD44+, and CD90.1+. The optimal weight ratio is 65:35 for the normalized alkaline phosphatase activities. The transduced MSCs, engineered by replication-defective adenovirus to express the BMP-2 gene, demonstrated synergic osteogenic effects in the microbeads. MSCs are capable of proliferating and differentiating in appropriate combinations of n-HA/Col. Thus it is a promising composite for future clinical applications.
In the past, the liver tumors were reported manually in an unstructured format. There actually exists much valuable knowledge in these reports for further disease risk assessment, disease recognition and treatment recommendation. Yet, it is not easy to read and mine knowledge from the unstructured reports. Hence, how to extract the knowledge from these biomedical reports effectively and efficiently has been a challenging issue in the past decades. Although a set of Natural Language Processing techniques were proposed for Bio-medical information retrieval, few related works were made on transforming the unstructured CT liver-tumor reports into structured ones. To aim at this issue, in this paper, we propose a two-stage report structuring method by integrating effective Natural Language Processing (NLP) and interpretable machine learning. For the first stage, the candidate keywords in unstructured reports are extracted. Next, the feature keywords are determined by the feature-selection technique. For the second stage, the well-known multi-classifiers are performed, and finally the reports are labeled in a refined structure format. Further, the factor keywords in the classification model are filtered to interpret the performance. In overall, the proposed report structuring method generates a hierarchical data structure, including the common features and refined features in the 1 st and 2 nd levels/stages, respectively. To reveal the performance of proposed method, a set of evaluations were conducted and the results show that, the proposed method is more promising than the fashion neural networks such as Bert (Bidirectional Encoder Representations from Transformers) in terms of effectiveness and efficiency.
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