Current advances concerning the most cited metal ions doped bioceramics and silicate-based bioactive glasses for bone tissue engineering

Studies related to biomaterials that stimulate the repair of living tissue have increased considerably, improving the quality of many people's lives that require surgery due to traumatic accidents, bone diseases, bone defects, and reconstructions. Among these biomaterials, bioceramics and bioactive glasses (BGs) have proved to be suitable for coating materials, cement, scaffolds, and nanoparticles, once they present good biocompatibility and degradability, able to generate osteoconduction on the surrounding tissue. However, the role of biomaterials in hard tissue engineering is not restricted to a structural replacement or for guiding tissue regeneration. Nowadays, it is expected that biomaterials develop a multifunctional role when implanted, orchestrating the process of tissue regeneration and providing to the body the capacity to heal itself. In this way, the incorporation of specific metal ions in bioceramics and BGs structure, including magnesium, silver, strontium, lithium, copper, iron, zinc, cobalt, and manganese are currently receiving enhanced interest as biomaterials for biomedical applications. When an ion is incorporated into the bioceramic structure, a new category of material is created, which has several unique properties that overcome the disadvantages of primitive material and favors its use in different biomedical applications. The doping can enhance handling properties, angiogenic and osteogenic performance, and antimicrobial activity. Therefore, this review aims to summarize the effect of selected metal ion dopants into bioceramics and silicate-based BGs in bone tissue engineering. Furthermore, new applications for doped bioceramics and BGs are highlighted, including cancer treatment and drug delivery.     

A pragmatic approach to hierarchical categorization of research expertise in the presence of scarce information

International Journal on Digital Libraries - Throughout the history of science, different knowledge areas have collaborated to overcome major research challenges. The task of associating a...     

Electrospray ionization mass spectrometry fingerprinting of Brazilian cacha?as produced in copper alembic and in stainless-steel column stills

Brazilian cacha?a can be produced in two different ways: distilled in stainless steel column or in copper alembic stills. We evaluated 36 samples of commercial non-aged cacha?as: 18 samples of sweetened cacha?as distilled in stainless steel column, and 18 samples distilled in copper alembic stills. Fingerprints were obtained through electrospray ionization mass spectrometry by recording the intensity of the 15 most abundant ions. Principal component analysis was applied to the data and separated the samples in two groups. However, after sample standardization with sugar (20?g?L^?1), it was not possible to group them by type of distillation. The results showed that the technique applied did not allow differentiation of cacha?as based on the distillation system, but for the presence or absence of sugar in them.     

Ensembles of ARTMAP-based neural networks: an experimental study

ARTMAP-based models are neural networks which use a match-based learning procedure. The main advantage of ARTMAP-based models over error-based models, such as Multi-Layer Perceptron, is the learning time, which is considered as significantly fast. This feature is extremely important in complex systems that require the use of several models, such as ensembles or committees, since they produce robust and fast classifiers. Subsequently, some extensions of the ARTMAP model have been proposed, such as: ARTMAP-IC, RePART, among others. Aiming to add an extra contribution to ARTMAP context, this paper presents an analysis of ARTMAP-based models in ensemble systems. As a result of this analysis, two main goals are aimed, which are: to analyze the influence of the RePART model in ensemble systems and to detect any relation between diversity and accuracy in ensemble systems in order to use this relation in the design of these systems.     

Digital current regulator for proportional electro-hydraulic valves with unknown disturbance rejection

Solenoid current regulation is well-known and standard in any proportional electro-hydraulic valve. The goal is to provide a wide-band transfer function from the reference to the measured current, thus making the solenoid a fast and ideal force actuator within the limits of the power supplier. The power supplier is usually a Pulse Width Modulation (PWM) amplifier fixing the voltage bound and the Nyquist frequency of the regulator. Typical analog regulators include three main terms: a feedforward channel, a proportional feedback channel and the electromotive force compensation. The latter compensation may be accomplished by integrative feedback. Here the problem is faced through a model-based design (Embedded Model Control), on the basis of a wide-band embedded model of the solenoid which includes the effect of eddy currents. To this end model parameters must be identified. The embedded model includes a stochastic disturbance dynamics capable of estimating and correcting the electromotive contribution together with parametric uncertainty, variability and state dependence. The embedded model which is fed by the measured current and the supplied voltage becomes a state predictor of the controllable and disturbance dynamics. The control law combines reference generator, state feedback and disturbance rejection to dispatch the PWM amplifier with the appropriate duty cycle. Modeling, identification and control design are outlined together with experimental result. Comparison with an existing analog regulator is also provided.     

CLA Reduces Inflammatory Mediators from A427 Human Lung Cancer Cells and A427 Conditioned Medium Promotes Differentiation of C2C12 Murine Muscle Cells

Conjugated linoleic acid (CLA) is thought to have anti-proliferative and anti-inflammatory properties, but its effect on cancer cachexia is unknown. Two effects were here investigated: that of CLA on inflammatory mediator production in human lung cancer cells, and that of reduced mediators on the myogenic differentiation of murine muscle C2C12 cells. The latter cells were grown in medium conditioned by human lung cancer A427 cells, with or without CLA, to mimic only the effect of molecules released from the tumor “in vivo”, excluding the effect of host-produced cachectic factors. The results obtained show that CLA was found to reduce the production of tumor necrosis factor-α, interleukin (IL)-1β and prostaglandin E2 (PGE2), but had no effect on IL-6 production. The mechanisms underlying the effect of CLA on cytokine or PGE2 release in A427 cells are probably mediated by activation of peroxisome proliferator-activated receptor (PPAR)α, which increased at 24 h CLA treatment. In turn, the reduced content of inflammatory mediators in medium conditioned by A427 cells, in the presence of CLA, allowed muscle cells to proliferate, again by inducing PPAR. The involvement of PPARα was demonstrated by treatment with the antagonist MK-886. The findings demonstrate the anti-inflammatory and myogenic action of CLA and point to its possible application as a novel dietary supplement and therapeutic agent in inflammatory disease states, such as cachexia.     

Intelligent agents for the management of complexity in multimodal biometrics

Current approaches to personal identity authentication using a single biometric technology are limited, principally because no single biometric is generally considered both sufficiently accurate and user-acceptable for universal application. Multimodal biometrics can provide a more adaptable solution to the security and convenience requirements of many applications. However, such an approach can also lead to additional complexity in the design and management of authentication systems. Additionally, complex hierarchies of security levels and interacting user/provider requirements demand that authentication systems are adaptive and flexible in configuration. In this paper we consider the integration of multimodal biometrics using intelligent agents to address issues of complexity management. The work reported here is part of a major project designated IAMBIC (Intelligent Agents for Multimodal Biometric Identification and Control), aimed at exploring the application of the intelligent agent metaphor to the field of biometric authentication. The paper provides an introduction to a first-level architecture for such a system, and demonstrates how this architecture can provide a framework for the effective control and management of access to data and systems where issues of privacy, confidentiality and trust are of primary concern. Novel approaches to software agent design and agent implementation strategies required for this architecture are also highlighted. The paper further shows how such a structure can define a fundamental paradigm to support the realisation of universal access in situations where data integrity and confidentiality must be robustly and reliably protected .     

Investigating fusion approaches in multi-biometric cancellable recognition

Cancellable biometrics has recently been introduced in order to overcome some privacy issues about the management of biometric data, aiming to transform a biometric trait into a new but revocable representation for enrolment and identification (verification). Therefore, a new representation of original biometric data can be generated in case of being compromised. Additionally, the use multi-biometric systems are increasingly being deployed in various biometric-based applications since the limitations imposed by a single biometric model can be overcome by these multi-biometric recognition systems. In this paper, we specifically investigate the performance of different fusion approaches in the context of multi-biometrics cancellable recognition. In this investigation, we adjust the ensemble structure to be used for a biometric system and we use as examples two different biometric modalities (voice and iris data) in a multi-biometrics context, adapting three cancellable transformations for each biometric modality.