Electrospun silk-elastin-like fiber mats for tissue engineering applications

Protein-based polymers are present in a wide variety of organisms fulfilling structural and mechanical roles. Advances in protein engineering and recombinant DNA technology allow the design and production of recombinant protein-based polymers (rPBPs) with an absolute control of its composition. Although the application of recombinant proteins as biomaterials is still an emerging technology, the possibilities are limitless and far superior to natural or synthetic materials, as the complexity of the structural design can be fully customized. In this work, we report the electrospinning of two new genetically engineered silk-elastin-like proteins (SELPs) consisting of alternate silk- and elastin-like blocks. Electrospinning was performed with formic acid and aqueous solutions at different concentrations without addition of further agents. The size and morphology of the electrospun structures was characterized by scanning electron microscopy showing to be dependent of concentration and solvent used. Treatment with air saturated with methanol was employed to stabilize the structure and promote water insolubility through a time-dependent conversion of random coils into β-sheets (FTIR). The resultant methanol-treated electrospun mats were characterized for swelling degree (570-720%), water vapour transmission rate (1083 g/m2/day) and mechanical properties (modulus of elasticity of ~126 MPa). Furthermore, the methanol-treated SELP fiber mats showed no cytotoxicity and were able to support adhesion and proliferation of normal human skin fibroblasts. Adhesion was characterized by a filopodia-mediated mechanism. These results demonstrate that SELP fiber mats can provide promising solutions for the development of novel biomaterials suitable for tissue engineering applications.

Vitória da Alemanha constitucional e de direito social!

O poder judicial é hoje independente na RFA, sendo ainda o direito baseado no direito romano, com algumas referências germânicas. O Tribunal Federal Constitucional é uma instituição sagrada que prima pela reverência absoluta ao Estado de Direito social e controla a constitucionalidade. Existe ainda o Tribunal de Justiça Federal e os Tribunais Federais do Trabalho, o Social Federal, o Federal das Finanças e o Administrativo Federal. O sistema penal alemão é destinado à recuperação do criminoso. O Völkerstrafgesetzbuch/“Código Penal Internacional” dá aos tribunais alemães jurisdição universal caso a acusação por um tribunal do país onde o crime foi praticado, ou por um tribunal internacional, não for possível. Abstract: The judiciary is independent today in the Germany, still being the right based on Roman law with some Germanic references. The Federal Constitutional Court is a sacred institution that excels in absolute reverence for the rule of law and social controls constitutionality. There is also the Federal Court of Justice and the Federal Courts of Labor, the Federal Social, the Federal Finance Administration and the Federal. The German penal system is aimed at the criminal recovery. The Völkerstrafgesetzbuch / "International Criminal Code" gives German courts universal jurisdiction if prosecution by a court of the country where the crime was committed, or by an international court, is not possible.

Computer-aided recognition of dental implants in X-ray images

Dental implant recognition in patients without available records is a time-consuming and not straightforward task. The traditional method is a complete user-dependent process, where the expert compares a 2D X-ray image of the dental implant with a generic database. Due to the high number of implants available and the similarity between them, automatic/semi-automatic frameworks to aide implant model detection are essential. In this study, a novel computer-aided framework for dental implant recognition is suggested. The proposed method relies on image processing concepts, namely: (i) a segmentation strategy for semi-automatic implant delineation; and (ii) a machine learning approach for implant model recognition. Although the segmentation technique is the main focus of the current study, preliminary details of the machine learning approach are also reported. Two different scenarios are used to validate the framework: (1) comparison of the semi-automatic contours against implant’s manual contours of 125 X-ray images; and (2) classification of 11 known implants using a large reference database of 601 implants. Regarding experiment 1, 0.97±0.01, 2.24±0.85 pixels and 11.12±6 pixels of dice metric, mean absolute distance and Hausdorff distance were obtained, respectively. In experiment 2, 91% of the implants were successfully recognized while reducing the reference database to 5% of its original size. Overall, the segmentation technique achieved accurate implant contours. Although the preliminary classification results prove the concept of the current work, more features and an extended database should be used in a future work.