146 resultados para Neural stimulation.


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Objectives: People with Parkinson’s disease (PD) are at higher risk of malnutrition due to PD symptoms and pharmacotherapy side effects. When pharmacotherapy is no longer effective for symptom control, deep-brain stimulation (DBS) surgery may be considered. The aim of this study was to assess the nutritional status of people with PD who may be at higher risk of malnutrition related to unsatisfactory symptom management with optimised medical therapy. Design: This was an observational study using a convenience sample. Setting: Participants were seen during their hospital admission for their deep brain stimulation surgery. Participants: People with PD scheduled for DBS surgery were recruited from a Brisbane neurological clinic (n=15). Measurements: The Patient-Generated Subjective Global Assessment (PG-SGA), weight, height and body composition were assessed to determine nutritional status. Results: Six participants (40%) were classified as moderately malnourished (SGA-B). Eight participants (53%) reported previous unintentional weight loss (average loss of 13.3%). On average, participants classified as well-nourished (SGA-A) were younger, had shorter disease durations, lower PG-SGA scores, higher body mass (BMI) and fat free mass indices (FFMI) when compared to malnourished participants (SGA-B). Five participants had previously received dietetic advice but only one in relation to unintentional weight loss. Conclusion: Malnutrition remains unrecognised and untreated in this group despite unintentional weight loss and presence of nutrition impact symptoms. Improving nutritional status prior to surgery may improve surgical outcomes.

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Because of the limited availability of donor cartilage for resurfacing defects in articular surfaces, there is tremendous interest in the in vitro bioengineering of cartilage replacements for clinical applications. However, attaining mechanical properties in engineered cartilaginous constructs that approach those of native cartilage has not been previously achieved when constructs are cultured under free-swelling conditions. One approach toward stimulating the development of constructs that are mechanically more robust is to expose them to physical environments that are similar, in certain ways, to those encountered by native cartilage. This is a strategy motivated by observations in numerous short-term experiments that certain mechanical signals are potent stimulators of cartilage metabolism. On the other hand, excess mechanical loading can have a deleterious effect on cartilage. Culture conditions that include a physical stimulation component are made possible by the use of specialized bioreactors. This chapter addresses some of the issues involved in using bioreactors as integral components of cartilage tissue engineering and in studying the physical regulation of cartilage. We first consider the generation of cartilaginous constructs in vitro. Next we describe the rationale and design of bioreactors that can impart either mechanical deformation or fluid-induced mechanical signals.

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This paper presents a nonlinear gust-attenuation controller based on constrained neural-network (NN) theory. The controller aims to achieve sufficient stability and handling quality for a fixed-wing unmanned aerial system (UAS) in a gusty environment when control inputs are subjected to constraints. Constraints in inputs emulate situations where aircraft actuators fail requiring the aircraft to be operated with fail-safe capability. The proposed controller enables gust-attenuation property and stabilizes the aircraft dynamics in a gusty environment. The proposed flight controller is obtained by solving the Hamilton-Jacobi-Isaacs (HJI) equations based on an policy iteration (PI) approach. Performance of the controller is evaluated using a high-fidelity six degree-of-freedom Shadow UAS model. Simulations show that our controller demonstrates great performance improvement in a gusty environment, especially in angle-of-attack (AOA), pitch and pitch rate. Comparative studies are conducted with the proportional-integral-derivative (PID) controllers, justifying the efficiency of our controller and verifying its suitability for integration into the design of flight control systems for forced landing of UASs.

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This thesis investigated the viability of using Frequency Response Functions in combination with Artificial Neural Network technique in damage assessment of building structures. The proposed approach can help overcome some of limitations associated with previously developed vibration based methods and assist in delivering more accurate and robust damage identification results. Excellent results are obtained for damage identification of the case studies proving that the proposed approach has been developed successfully.

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The application of different EMS current thresholds on muscle activates not only the muscle but also peripheral sensory axons that send proprioceptive and pain signals to the cerebral cortex. A 32-channel time-domain fNIRS instrument was employed to map regional cortical activities under varied EMS current intensities applied on the right wrist extensor muscle. Eight healthy volunteers underwent four EMS at different current thresholds based on their individual maximal tolerated intensity (MTI), i.e., 10 % < 50 % < 100 % < over 100 % MTI. Time courses of the absolute oxygenated and deoxygenated hemoglobin concentrations primarily over the bilateral sensorimotor cortical (SMC) regions were extrapolated, and cortical activation maps were determined by general linear model using the NIRS-SPM software. The stimulation-induced wrist extension paradigm significantly increased activation of the contralateral SMC region according to the EMS intensities, while the ipsilateral SMC region showed no significant changes. This could be due in part to a nociceptive response to the higher EMS current intensities and result also from increased sensorimotor integration in these cortical regions.

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Over the past few decades, biodiesel produced from oilseed crops and animal fat is receiving much attention as a renewable and sustainable alternative for automobile engine fuels, and particularly petroleum diesel. However, current biodiesel production is heavily dependent on edible oil feedstocks which are unlikely to be sustainable in the longer term due to the rising food prices and the concerns about automobile engine durability. Therefore, there is an urgent need for researchers to identify and develop sustainable biodiesel feedstocks which overcome the disadvantages of current ones. On the other hand, artificial neural network (ANN) modeling has been successfully used in recent years to gain new knowledge in various disciplines. The main goal of this article is to review recent literatures and assess the state of the art on the use of ANN as a modeling tool for future generation biodiesel feedstocks. Biodiesel feedstocks, production processes, chemical compositions, standards, physio-chemical properties and in-use performance are discussed. Limitations of current biodiesel feedstocks over future generation biodiesel feedstock have been identified. The application of ANN in modeling key biodiesel quality parameters and combustion performance in automobile engines is also discussed. This review has determined that ANN modeling has a high potential to contribute to the development of renewable energy systems by accelerating biodiesel research.

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Background Matrix metalloproteinases (MMPs) are central to degradation of the extracellular matrix and basement membrane during both normal and carcinogenic tissue remodeling. MT1-MMP (MMP-14) and stromelysin-3 (MMP-11) are two members of the MMP family of proteolytic enzymes that have been specifically implicated in breast cancer progression. Expressed in stromal fibroblasts adjacent to epithelial tumour cells, the mechanism of MT1-MMP and MMP-11 induction remains unknown. Methods To investigate possible mechanisms of induction, we examined the effects of a number of plausible regulatory agents and treatments that may physiologically influence MMP expression during tumour progression. Thus NIH3T3 and primary mouse embryonic fibroblasts (MEFs) were: a) treated with the cytokines IL-1β, IL-2, IL-6, IL-8 and TGF-β for 3, 6, 12, 24, and 48 hours; b) grown on collagens I, IV and V; c) treated with fibronectin, con-A and matrigel; and d) co-cultured with a range of HBC (human breast cancer) cell lines of varied invasive and metastatic potential. Results Competitive quantitative RT-PCR indicated that MMP-11 expression was stimulated to a level greater than 100%, by 48 hour treatments of IL-1β, IL-2, TGF-β, fibronectin and collagen V. No other substantial changes in expression of MMP-11 or MT1-MMP in either tested fibroblast culture, under any treatment conditions, were observed. Conclusion We have demonstrated significant MMP-11 stimulation in mouse fibroblasts using cytokines, matrix constituents and HBC cell lines, and also some inhibition of MT1-MMP. Our data suggest that the regulation of these genes in the complex stromal-epithelial interactions that occur in human breast carcinoma, is influenced by several mechanisms.

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Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the a mission should be aborted due to mechanical or other failure. On-board cameras provide information that can be used in the determination of potential landing sites, which are continually updated and ranked to prevent injury and minimize damage. Pulse Coupled Neural Networks have been used for the detection of features in images that assist in the classification of vegetation and can be used to minimize damage to the aerial vehicle. However, a significant drawback in the use of PCNNs is that they are computationally expensive and have been more suited to off-line applications on conventional computing architectures. As heterogeneous computing architectures are becoming more common, an OpenCL implementation of a PCNN feature generator is presented and its performance is compared across OpenCL kernels designed for CPU, GPU and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images obtained during unmanned aerial vehicle trials to determine the plausibility for real-time feature detection.

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Compromised angiogenesis appears to be a major limitation in various suboptimal bone healing situations. Appropriate mechanical stimuli support blood vessel formation in vivo and improve healing outcomes. However, the mechanisms responsible for this association are unclear. To address this question, the paracrine angiogenic potential of early human fracture haematoma and its responsiveness to mechanical loading, as well as angiogenic growth factors involved, were investigated in vitro. Human haematomas were collected from healthy patients undergoing surgery within 72. h after bone fracture. The haematomas were embedded in a fibrin matrix, and cultured in a bioreactor resembling the in vivo conditions of the early phase of bone healing (20 compression, 1. Hz) over 3. days. Conditioned medium (CM) from the bioreactor was then analyzed. The matrices were also incubated in fresh medium for a further 24. h to evaluate the persistence of the effects. Growth factor (GF) concentrations were measured in the CM by ELISAs. In vitro tube formation assays were conducted on Matrigel with the HMEC-1 cell line, with or without inhibition of vascular endothelial growth factor receptor 2 (VEGFR2). Cell numbers were quantified using an MTS test. In vitro endothelial tube formation was enhanced by CM from haematomas, compared to fibrin controls. The angiogenesis regulators, vascular endothelial growth factor (VEGF) and transforming growth factor β1 (TGF-β1), were released into the haematoma CM, but not angiopoietins 1 or 2 (Ang1, 2), basic fibroblast growth factor (bFGF) or platelet-derived growth factor (PDGF). Mechanical stimulation of haematomas, but not fibrin controls, further increased the induction of tube formation by their CM. The mechanically stimulated haematoma matrices retained their elevated pro-angiogenic capacity for 24. h. The pro-angiogenic effect was cancelled by inhibition of VEGFR2 signalling. VEGF concentrations in CM tended to be elevated by mechanical stimulation; this was significant in haematomas from younger, but not from older patients. Other GFs were not mechanically regulated. In conclusion, the paracrine pro-angiogenic capacity of early human haematomas is enhanced by mechanical stimulation. This effect lasts even after removing the mechanical stimulus and appears to be VEGFR2-dependent.

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Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

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Olfactory ensheathing cells, the glial cells of the olfactory nervous system, exhibit unique growth-promoting and migratory properties that make them interesting candidates for cell therapies targeting neuronal injuries such as spinal cord injury. Transplantation of olfactory cells is feasible and safe in humans; however, functional outcomes are highly variable with some studies showing dramatic improvements and some no improvements at all. We propose that the reason for this is that the identity and purity of the cells is different in each individual study. We have shown that olfactory ensheathing cells are not a uniform cell population and that individual subpopulations of OECs are present in different regions of the olfactory nervous system, with strikingly different behaviors. Furthermore, the presence of fibroblasts and other cell types in the transplant can dramatically alter the behavior of the transplanted glial cells. Thus, a thorough characterization of the differences between olfactory ensheathing cell subpopulations and how the behavior of these cells is affected by the presence of other cell types is highly warranted.

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Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the mission should be aborted due to mechanical or other failure. This article presents a pulse-coupled neural network (PCNN) to assist in the vegetation classification in a vision-based landing site detection system for an unmanned aircraft. We propose a heterogeneous computing architecture and an OpenCL implementation of a PCNN feature generator. Its performance is compared across OpenCL kernels designed for CPU, GPU, and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images to determine the plausibility for real-time feature detection.

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Along with the tri-lineage of bone, cartilage and fat, human mesenchymal stem cells (hMSCs) retain neural lineage potential. Multiple factors have been described that influence lineage fate of hMSCs including the extracellular microenvironment or niche. The niche includes the extracellular matrix (ECM) providing structural composition, as well as other associated proteins and growth factors, which collectively influence hMSC stemness and lineage specification. As such, lineage specific differentiation of MSCs is mediated through interactions including cell–cell and cell–matrix, as well as through specific signalling pathways triggering downstream events. Proteoglycans (PGs) are ubiquitous within this microenvironment and can be localised to the cell surface or embedded within the ECM. In addition, the heparan sulfate (HS) and chondroitin sulfate (CS) families of PGs interact directly with a number of growth factors, signalling pathways and ECM components including FGFs, Wnts and fibronectin. With evidence supporting a role for HSPGs and CSPGs in the specification of hMSCs down the osteogenic, chondrogenic and adipogenic lineages, along with the localisation of PGs in development and regeneration, it is conceivable that these important proteins may also play a role in the differentiation of hMSCs toward the neuronal lineage. Here we summarise the current literature and highlight the potential for HSPG directed neural lineage fate specification in hMSCs, which may provide a new model for brain damage repair.

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Background Directed cell migration is essential for normal development. In most of the migratory cell populations that have been analysed in detail to date, all of the cells migrate as a collective from one location to another. However, there are also migratory cell populations that must populate the areas through which they migrate, and thus some cells get left behind while others advance. Very little is known about how individual cells behave to achieve concomitant directional migration and population of the migratory route. We examined the behavior of enteric neural crest-derived cells (ENCCs), which must both advance caudally to reach the anal end and populate each gut region. Results The behaviour of individual ENCCs was examined using live imaging and mice in which ENCCs express a photoconvertible protein. We show that individual ENCCs exhibit very variable directionalities and speed; as the migratory wavefront of ENCCs advances caudally, each gut region is populated primarily by some ENCCs migrating non-directionally. After populating each region, ENCCs remain migratory for at least 24 hours. Endothelin receptor type B (EDNRB) signaling is known to be essential for the normal advance of the ENCC population. We now show that perturbation of EDNRB principally affects individual ENCC speed rather than directionality. The trajectories of solitary ENCCs, which occur transiently at the wavefront, were consistent with an unbiased random walk and so cell-cell contact is essential for directional migration. ENCCs migrate in close association with neurites. We showed that although ENCCs often use neurites as substrates, ENCCs lead the way, neurites are not required for chain formation and neurite growth is more directional than the migration of ENCCs as a whole. Conclusions Each gut region is initially populated by sub-populations of ENCCs migrating non-directionally, rather than stopping. This might provide a mechanism for ensuring a uniform density of ENCCs along the growing gut.

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Polymer biomaterials have been widely used for bone replacement/regeneration because of their unique mechanical properties and workability. Their inherent low bioactivity makes them lack osseointegration with host bone tissue. For this reason, bioactive inorganic particles have been always incorporated into the matrix of polymers to improve their bioactivity. However, mixing inorganic particles with polymers always results in inhomogeneity of particle distribution in polymer matrix with limited bioactivity. This study sets out to apply the pulsed laser deposition (PLD) technique to prepare uniform akermanite (Ca2MgSi2O7, AKT) glass nanocoatings on the surface of two polymers (non-degradable polysulfone (PSU) and degradable polylactic acid (PDLLA)) in order to improve their surface osteogenic and angiogenic activity. The results show that a uniform nanolayer composed of amorphous AKT particles (∼30nm) of thickness 130nm forms on the surface of both PSU and PDLLA films with the PLD technique. The prepared AKT-PSU and AKT-PDLLA films significantly improved the surface roughness, hydrophilicity, hardness and apatite mineralization, compared with pure PSU and PDLLA, respectively. The prepared AKT nanocoatings distinctively enhance the alkaline phosphate (ALP) activity and bone-related gene expression (ALP, OCN, OPN and Col I) of bone-forming cells on both PSU and PDLLA films. Furthermore, AKT nanocoatings on two polymers improve the attachment, proliferation, VEGF secretion and expression of proangiogenic factors and their receptors of human umbilical vein endothelial cells (HUVEC). The results suggest that PLD-prepared bioceramic nanocoatings are very useful for enhancing the physicochemical, osteogenic and angiogenic properties of both degradable and non-degradable polymers for application in bone replacement/regeneration.