In vitro mechanical fatigue behavior of poly-ε-caprolactone macroporous scaffolds for cartilage tissue engineering: Influence of pore filling by a poly(vinyl alcohol) gel

Polymeric scaffolds used in regenerative therapies are implanted in the damaged tissue and subjected to repeated loading cycles. In the case of articular cartilage engineering, an implanted scaffold is typically subjected to long term dynamic compression. The evolution of the mechanical properties of the scaffold during bioresorption has been deeply studied in the past, but the possibility of failure due to mechanical fatigue has not been properly addressed. Nevertheless, the macroporous scaffold is susceptible to failure after repeated loading-unloading cycles. In this work fatigue studies of polycaprolactone scaffolds were carried by subjecting the scaffold to repeated compression cycles in conditions simulating the scaffold implanted in the articular cartilage. The behaviour of the polycaprolactone sponge with the pores filled with a poly(vinyl alcohol) gel simulating the new formed tissue within the pores was compared with that of the material immersed in water. Results were analyzed with Morrow’s criteria for failure and accurate fittings are obtained just up to 200 loading cycles. It is also shown that the presence of poly(vinyl alcohol) increases the elastic modulus of the scaffolds, the effect being more pronounced with increasing the number of freeze/thawing cycles.

Prognostics health management: perspectives in engineering systems reliability prognostics

The Prognostic Health Management (PHM) has been asserting itself as the most promising methodology to enhance the effective reliability and availability of a product or system during its life-cycle conditions by detecting current and approaching failures, thus, providing mitigation of the system risks with reduced logistics and support costs. However, PHM is at an early stage of development, it also expresses some concerns about possible shortcomings of its methods, tools, metrics and standardization. These factors have been severely restricting the applicability of PHM and its adoption by the industry. This paper presents a comprehensive literature review about the PHM main general weaknesses. Exploring the research opportunities present in some recent publications, are discussed and outlined the general guide-lines for finding the answer to these issues.

Extracting kinetic information from literature with KineticRE

To better understand the dynamic behavior of metabolic networks in a wide variety of conditions, the field of Systems Biology has increased its interest in the use of kinetic models. The different databases, available these days, do not contain enough data regarding this topic. Given that a significant part of the relevant information for the development of such models is still wide spread in the literature, it becomes essential to develop specific and powerful text mining tools to collect these data. In this context, this work has as main objective the development of a text mining tool to extract, from scientific literature, kinetic parameters, their respective values and their relations with enzymes and metabolites. The approach proposed integrates the development of a novel plug-in over the text mining framework @Note2. In the end, the pipeline developed was validated with a case study on Kluyveromyces lactis, spanning the analysis and results of 20 full text documents.

Reconstructing transcriptional regulatory networks using data integration and text mining

Transcriptional Regulatory Networks (TRNs) are powerful tool for representing several interactions that occur within a cell. Recent studies have provided information to help researchers in the tasks of building and understanding these networks. One of the major sources of information to build TRNs is biomedical literature. However, due to the rapidly increasing number of scientific papers, it is quite difficult to analyse the large amount of papers that have been published about this subject. This fact has heightened the importance of Biomedical Text Mining approaches in this task. Also, owing to the lack of adequate standards, as the number of databases increases, several inconsistencies concerning gene and protein names and identifiers are common. In this work, we developed an integrated approach for the reconstruction of TRNs that retrieve the relevant information from important biological databases and insert it into a unique repository, named KREN. Also, we applied text mining techniques over this integrated repository to build TRNs. However, was necessary to create a dictionary of names and synonyms associated with these entities and also develop an approach that retrieves all the abstracts from the related scientific papers stored on PubMed, in order to create a corpora of data about genes. Furthermore, these tasks were integrated into @Note, a software system that allows to use some methods from the Biomedical Text Mining field, including an algorithms for Named Entity Recognition (NER), extraction of all relevant terms from publication abstracts, extraction relationships between biological entities (genes, proteins and transcription factors). And finally, extended this tool to allow the reconstruction Transcriptional Regulatory Networks through using scientific literature.

A firefly dynamic penalty approach for solving engineering design problems

Firefly Algorithm is a recent swarm intelligence method, inspired by the social behavior of fireflies, based on their flashing and attraction characteristics [1, 2]. In this paper, we analyze the implementation of a dynamic penalty approach combined with the Firefly algorithm for solving constrained global optimization problems. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.

A new perspective of students allocation satisfaction in engineering courses in Portugal

Publicado em "AIP Conference Proceedings" Vol. 1648

Análise de dados e aplicação de modelos estatísticos para apoio à decisão de contratação na Petróleo Brasileiro

Dissertação de mestrado em Engenharia Industrial

Poker learner: modelação de jogadores através de data mining

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Proving the suitability of magnetoelectric stimuli for tissue engineering applications

A novel approach for tissue engineering applications based on the use of magnetoelectric materials is presented. This work proves that magnetoelectric Terfenol-D/poly(vinylidene fluoride-co-trifluoroethylene) composites are able to provide mechanical and electrical stimuli to MC3T3-E1 pre-osteoblast cells and that those stimuli can be remotely triggered by an applied magnetic field. Cell proliferation is enhanced up to 25% when cells are cultured under mechanical (up to 110 ppm) and electrical stimulation (up to 0.115 mV), showing that magnetoelectric cell stimulation is a novel and suitable approach for tissue engineering allowing magnetic, mechanical and electrical stimuli.

Modelling tyre-road noise with data mining techniques

The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and uneven- ness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors.

The Data Mining applied for the prediction of highway roughness due to overloaded trucks

Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks

Geotechnical engineering for sustainable transportation infrastructure

This paper highlights how transportation geotechnics can interact with transportation infrastructures and how through the planning, design, construction and maintenance can contribute to ensure solutions more safe, reliable and resilient in the future. In this context sustainable concepts are discussed and applied as best practices to preserve natural resources and assuring socio-economic and environment benefits for the society

Gellan gum-coated gold nanorods: an intracellular nanosystem for bone tissue engineering

Gold nanorods (AuNRs) have emerged as an exceptional nanotool for a myriad of applications ranging from cancer therapy to tissue engineering. However, their surface modification with biocompatible and stabilizing biomaterials is crucial to allow their use in a biological environment. Herein, low-acyl gellan gum (GG) was used to coat AuNRs surface, taking advantage of its stabilizing, biocompatible and gelling features. The layer-by-layer based strategy implied the successive deposition of poly(acrylic acid), poly(allylamine hydrochloride) and GG, which allowed the formation of a GG hydrogel-like shell with 7 nm thickness around individual AuNRs. Stability studies in a wide range of pH and salt concentrations showed that the polysaccharide coating can prevent AuNRs aggregation. Moreover, a reversible pH-responsive feature of the nanoparticles was observed. Cytocompatibility and osteogenic ability of GG-coated AuNRs was also addressed. After 14 days of culturing within SaOS-2, an osteoblast-like cell line, in vitro studies revealed that AuNRs-GG exhibit no cytotoxicity, were internalized by the cells and localized inside lysosomes. AuNRs-GG combined with osteogenic media enhanced the mineralization capacity two-fold, as compared to cells exposed to osteogenic media alone. The proposed system has shown interesting features for osteogenesis, and further insights might be relevant for drug delivery, tissue engineering and regenerative medicine.

Highly functional and biodegradable nanofibrous scaffolds combined with stem cells for bone and cartilage tissue engineering

Among the various possible embodiements of Advanced Therapies and in particular of Tissue Engineering the use of temporary scaffolds to regenerate tissue defects is one of the key issues. The scaffolds should be specifically designed to create environments that promote tissue development and not merely to support the maintenance of communities of cells. To achieve that goal, highly functional scaffolds may combine specific morphologies and surface chemistry with the local release of bioactive agents. Many biomaterials have been proposed to produce scaffolds aiming the regeneration of a wealth of human tissues. We have a particular interest in developing systems based in nanofibrous biodegradable polymers1,2. Those demanding applications require a combination of mechanical properties, processability, cell-friendly surfaces and tunable biodegradability that need to be tailored for the specific application envisioned. Those biomaterials are usually processed by different routes into devices with wide range of morphologies such as biodegradable fibers and meshes, films or particles and adaptable to different biomedical applications. In our approach, we combine the temporary scaffolds populated with therapeutically relevant communities of cells to generate a hybrid implant. For that we have explored different sources of adult and also embryonic stem cells. We are exploring the use of adult MSCs3, namely obtained from the bone marrow for the development autologous-based therapies. We also develop strategies based in extra-embryonic tissues, such as amniotic fluid (AF) and the perivascular region of the umbilical cord4 (Whartonâ s Jelly, WJ). Those tissues offer many advantages over both embryonic and other adult stem cell sourcess. These tissues are frequently discarded at parturition and its extracorporeal nature facilitates tissue donation by the patients. The comparatively large volume of tissue and ease of physical manipulation facilitates the isolation of larger numbers of stem cells. The fetal stem cells appear to have more pronounced immunomodulatory properties than adult MSCs. This allogeneic escape mechanism may be of therapeutic value, because the transplantation of readily available allogeneic human MSCs would be preferable as opposed to the required expansion stage (involving both time and logistic effort) of autologous cells. Topics to be covered: This talk will review our latest developments of nanostructured-based biomaterials and scaffolds in combination with stem cells for bone and cartilage tissue engineering.