Heparan sulfate mediates the proliferation and differentiation of rat mesenchymal stem cells

The growth and differentiation of mesenchymal stem cells is controlled by various growth factors, the activities of which can be modulated by heparan sulfates. We have previously underscored the necessity of sulfated glycosaminoglycans for the FGF-2-stimulated differentiation of osteoprogenitor cells. Here we show that exogenous application of heparan sulfate to cultures of primary rat MSCs stimulates their proliferation leading to increased expression of osteogenic markers and enhanced bone nodule formation. FGF-2 can also increase the proliferation and osteogenic differentiation of rMSCs when applied exogenously during their linear growth. However, as opposed to exogenous HS, the continuous use of FGF-2 during in vitro differentiation completely blocked rMSC mineralization. Furthermore, we show that the effects of both FGF-2 and HS are mediated through FGF receptor 1 (FGFR1) and that inhibition of signaling through this receptor arrests cell growth resulting in the cells being unable to reach the critical density necessary to induce differentiation. Interestingly, blocking FGFR1 signaling in post-confluent osteogenic cultures significantly increased calcium deposition. Taken together our data clearly suggests that FGFR1 signaling plays an important role during osteogenic differentiation, firstly by stimulating cell growth that is closely followed by an inhibitory affect once the cells have reached confluence. It also underlines the importance of HS as a co-receptor for the signaling of endogenous FGF-2 and suggests that purified glycosaminoglycans may be attractive alternatives to growth factors for improved ex vivo growth and differentiation of MSCs.

Combining electrospun scaffolds with electrosprayed hydrogels leads to three-dimensional cellularization of hybrid constructs

A common problem in the design of tissue engineered scaffolds using electrospun scaffolds is the poor cellular infiltration into the structure. To tackle this issue, three approaches to scaffold design using electrospinning were investigated: selective leaching of a water-soluble fiber phase (poly ethylene oxide (PEO) or gelatin), the use of micron-sized fibers as the scaffold, and a combination of micron-sized fibers with codeposition of a hyaluronic acid-derivative hydrogel, Heprasil. These designs were achieved by modifying a conventional electrospinning system with two charged capillaries and a rotating mandrel collector. Three types of scaffolds were fabricated: medical grade poly(epsilon-caprolactone)/collagen (mPCL/Col) cospun with PEO or gelatin, mPCL/Col meshes with micron-sized fibers, and mPCL/Col microfibers cosprayed with Heprasil. All three scaffold types supported attachment and proliferation of human fetal osteoblasts. However, selective leaching only marginally improved cellular infiltration when compared to meshes obtained by conventional electrospinning. Better cell penetration was seen in mPCL/Col microfibers, and this effect was more pronounced when Heprasil regions were present in the structure. Thus, such techniques could be further exploited for the design of cell permeable fibrous meshes for tissue engineering applications.

Simulation and enhancement of a cardiovascular device test rig

Cardiovascular assist devices are tested in mock circulation loops (MCLs) prior to animal and clinical testing. These MCLs rely on characteristics such as pneumatic parameters to create pressure and flow, and pipe dimensions to replicate the resistance, compliance and fluid inertia of the natural cardiovascular system. A mathematical simulation was developed in SIMULINK to simulate an existing MCL. Model validation was achieved by applying the physical MCL characteristics to the simulation and comparing the resulting pressure traces. These characteristics were subsequently altered to improve and thus predict the performance of a more accurate physical system. The simulation was successful in simulating the physical mock circulation loop, and proved to be a useful tool in the development of improved cardiovascular device test rigs.

Best basis-based intelligent machine fault diagnosis

The wavelet packet transform decomposes a signal into a set of bases for time–frequency analysis. This decomposition creates an opportunity for implementing distributed data mining where features are extracted from different wavelet packet bases and served as feature vectors for applications. This paper presents a novel approach for integrated machine fault diagnosis based on localised wavelet packet bases of vibration signals. The best basis is firstly determined according to its classification capability. Data mining is then applied to extract features and local decisions are drawn using Bayesian inference. A final conclusion is reached using a weighted average method in data fusion. A case study on rolling element bearing diagnosis shows that this approach can greatly improve the accuracy ofdiagno sis.

Characterisation of mesenchymal cells from osteophytes in osteoarthritis

Osteophytes form through the process of chondroid metamorphosis of fibrous tissue followed by endochondral ossification. Osteophytes have been found to consist of three different mesenchymal tissue regions including endochondral bone formation within cartilage residues, intra-membranous bone formation within fibrous tissue and bone formation within bone marrow spaces. All these features provide evidence of mesenchymal stem cells (MSC) involvement in osteophyte formation; nevertheless, it remains to be characterised. MSC from numerous mesenchymal tissues have been isolated but bone marrow remains the “ideal” due to the ease of ex vivo expansion and multilineage potential. However, the bone marrow stroma has a relatively low number of MSC, something that necessitates the need for long-term culture and extensive population doublings in order to obtain a sufficient number of cells for therapeutic applications. MSC in vitro have limited proliferative capacity and extensive passaging compromises differentiation potential. To overcome this barrier, tissue derived MSC are of strong interest for extensive study and characterisation, with a focus on their potential application in therapeutic tissue regeneration. To date, no MSC type cell has been isolated from osteophyte tissue, despite this tissue exhibiting all the hallmark features of a regenerative tissue. Therefore, this study aimed to isolate and characterise cells from osteophyte tissues in relation to their phenotype, differentiation potential, immuno-modulatory properties, proliferation, cellular ageing, longevity and chondrogenesis in in vitro defect model in comparison to patient matched bone marrow stromal cells (bMSC). Osteophyte derived cells were isolated from osteophyte tissue samples collected during knee replacement surgery. These cells were characterised by the expression of cell surface antigens, differentiation potential into mesenchymal lineages, growth kinetics and modulation of allo-immune responses. Multipotential stem cells were identified from all osteophyte samples namely osteophyte derived mesenchymal stem cells (oMSC). Extensively expanded cell cultures (passage 4 and 9 respectively) were used to confirm cytogenetic stability and study signs of cellular aging, telomere length and telomerase activity. Cultured cells at passage 4 were used to determine 84 pathway focused stem cell related gene expression profile. Micro mass pellets were cultured in chondrogenic differentiation media for 21 days for phenotypic and chondrogenic related gene expression. Secondly, cell pellets differentiated overnight were placed into articular cartilage defects and cultured for further 21 days in control medium and chondrogenic medium to study chondrogenesis and cell behaviour. The surface antigen expression of oMSC was consistent with that of mesenchymal stem cells, such as lacking the haematopoietic and common leukocyte markers (CD34, CD45) while expressing those related to adhesion (CD29, CD166, CD44) and stem cells (CD90, CD105, CD73). The proliferation capacity of oMSC in culture was superior to that of bMSC, and they readily differentiated into tissues of the mesenchymal lineages. oMSC also demonstrated the ability to suppress allogeneic T-cell proliferation, which was associated with the expression of tryptophan degrading enzyme indoleamine 2,3 dioxygenase (IDO). Cellular aging was more prominent in late passage bMSC than in oMSC. oMSC had longer telomere length in late passages compared with bMSC, although there was no significant difference in telomere lengths in the early passages in either cell type. Telomerase activity was detectable only in early passage oMSC and not in bMSC. In osteophyte tissues telomerase positive cells were found to be located peri vascularly and were Stro-1 positive. Eighty-four pathway-focused genes were investigated and only five genes (APC, CCND2, GJB2, NCAM and BMP2) were differentially expressed between bMSC and oMSC. Chondrogenically induced micro mass pellets of oMSC showed higher staining intensity for proteoglycans, aggrecan and collagen II. Differential expression of chondrogenic related genes showed up regulation of Aggrecan and Sox 9 in oMSC and collagen II in bMSC. The in vitro defect models of oMSC in control medium showed rounded and aggregated cells staining positively for proteoglycan and presence of some extracellular matrix. In contrast, defects with bMSC showed fragmentation and loss of cells, fibroblast-like cell morphology staining positively for proteoglycans. For defects maintained in chondrogenic medium, rounded, aggregated and proteoglycan positive cells were found in both oMSC and bMSC cultures. Extracellular matrix and cellular integration into newly formed matrix was evident only in oMSC defects. For analysis of chondrocyte hypertrophy, strong expression of type X collagen could be noticed in the pellet cultures and transplanted bMSC. In summary, this study demonstrated that osteophyte derived cells had similar properties to mesenchymal stem cells in the expression of antigen phenotype, differential potential and suppression of allo-immune response. Furthermore, when compared to bMSC, oMSC maintained a higher proliferative capacity due to a retained level of telomerase activity in vitro, which may account for the relatively longer telomeres delaying growth arrest by replicative senescence compared with bMSC. oMSC behaviour in defects supported chondrogenesis which implies that cells derived from regenerative tissue can be an alternative source of stem cells and have a potential clinical application for therapeutic stem cell based tissue regeneration.

Composite load model decomposition : induction motor contribution

In this thesis, a new technique has been developed for determining the composition of a collection of loads including induction motors. The application would be to provide a representation of the dynamic electrical load of Brisbane so that the ability of the power system to survive a given fault can be predicted. Most of the work on load modelling to date has been on post disturbance analysis, not on continuous on-line models for loads. The post disturbance methods are unsuitable for load modelling where the aim is to determine the control action or a safety margin for a specific disturbance. This thesis is based on on-line load models. Dr. Tania Parveen considers 10 induction motors with different power ratings, inertia and torque damping constants to validate the approach, and their composite models are developed with different percentage contributions for each motor. This thesis also shows how measurements of a composite load respond to normal power system variations and this information can be used to continuously decompose the load continuously and to characterize regarding the load into different sizes and amounts of motor loads.

Robust real time multi-layer foreground segmentation

Many surveillance applications (object tracking, abandoned object detection) rely on detecting changes in a scene. Foreground segmentation is an effective way to extract the foreground from the scene, but these techniques cannot discriminate between objects that have temporarily stopped and those that are moving. We propose a series of modifications to an existing foreground segmentation system\cite{Butler2003} so that the foreground is further segmented into two or more layers. This yields an active layer of objects currently in motion and a passive layer of objects that have temporarily ceased motion which can itself be decomposed into multiple static layers. We also propose a variable threshold to cope with variable illumination, a feedback mechanism that allows an external process (i.e. surveillance system) to alter the motion detectors state, and a lighting compensation process and a shadow detector to reduce errors caused by lighting inconsistencies. The technique is demonstrated using outdoor surveillance footage, and is shown to be able to effectively deal with real world lighting conditions and overlapping objects.

Abandoned object detection using multi-layer motion detection

Abandoned object detection (AOD) systems are required to run in high traffic situations, with high levels of occlusion. Systems rely on background segmentation techniques to locate abandoned objects, by detecting areas of motion that have stopped. This is often achieved by using a medium term motion detection routine to detect long term changes in the background. When AOD systems are integrated into person tracking system, this often results in two separate motion detectors being used to handle the different requirements. We propose a motion detection system that is capable of detecting medium term motion as well as regular motion. Multiple layers of medium term (static) motion can be detected and segmented. We demonstrate the performance of this motion detection system and as part of an abandoned object detection system.

Multi-sensor tracking using a scalable condensation filter

Surveillance and tracking systems typically use a single colour modality for their input. These systems work well in controlled conditions but often fail with low lighting, shadowing, smoke, dust, unstable backgrounds or when the foreground object is of similar colouring to the background. With advances in technology and manufacturing techniques, sensors that allow us to see into the thermal infrared spectrum are becoming more affordable. By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using visible light only for surveillance and tracking. Thermal images are not affected by lighting or shadowing and are not overtly affected by smoke, dust or unstable backgrounds. We propose and evaluate three approaches for fusing visual and thermal images for person tracking. We also propose a modified condensation filter to track and aid in the fusion of the modalities. We compare the proposed fusion schemes with using the visual and thermal domains on their own, and demonstrate that significant improvements can be achieved by using multiple modalities.

Object tracking using multiple motion modalities

This paper presents an object tracking system that utilises a hybrid multi-layer motion segmentation and optical flow algorithm. While many tracking systems seek to combine multiple modalities such as motion and depth or multiple inputs within a fusion system to improve tracking robustness, current systems have avoided the combination of motion and optical flow. This combination allows the use of multiple modes within the object detection stage. Consequently, different categories of objects, within motion or stationary, can be effectively detected utilising either optical flow, static foreground or active foreground information. The proposed system is evaluated using the ETISEO database and evaluation metrics and compared to a baseline system utilising a single mode foreground segmentation technique. Results demonstrate a significant improvement in tracking results can be made through the incorporation of the additional motion information.

Scene invariant crowd counting for real-time surveillance

Automated crowd counting allows excessive crowding to be detected immediately, without the need for constant human surveillance. Current crowd counting systems are location specific, and for these systems to function properly they must be trained on a large amount of data specific to the target location. As such, configuring multiple systems to use is a tedious and time consuming exercise. We propose a scene invariant crowd counting system which can easily be deployed at a different location to where it was trained. This is achieved using a global scaling factor to relate crowd sizes from one scene to another. We demonstrate that a crowd counting system trained at one viewpoint can achieve a correct classification rate of 90% at a different viewpoint.

Improved simultaneous computation of motion detection and optical flow for object tracking

Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Whilst optical flow allows multiple moving targets to be separated based on their individual velocities, optical flow techniques are prone to errors caused by changing lighting and occlusions, both common in a surveillance environment. Motion segmentation techniques are more robust to fluctuating lighting and occlusions, but don't provide information on the direction of the motion. In this paper we propose a combined motion segmentation/optical flow algorithm for use in object tracking. The proposed algorithm uses the motion segmentation results to inform the optical flow calculations and ensure that optical flow is only calculated in regions of motion, and improve the performance of the optical flow around the edge of moving objects. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects. The algorithm is evaluated by attempting to extract a moving target within the flow images, given expected horizontal and vertical movement (i.e. the algorithms intended use for object tracking). Results show that the proposed algorithm outperforms other widely used optical flow techniques for this surveillance application.

Soft-biometrics : unconstrained authentication in a surveillance environment

Soft biometrics are characteristics that can be used to describe, but not uniquely identify an individual. These include traits such as height, weight, gender, hair, skin and clothing colour. Unlike traditional biometrics (i.e. face, voice) which require cooperation from the subject, soft biometrics can be acquired by surveillance cameras at range without any user cooperation. Whilst these traits cannot provide robust authentication, they can be used to provide coarse authentication or identification at long range, locate a subject who has been previously seen or who matches a description, as well as aid in object tracking. In this paper we propose three part (head, torso, legs) height and colour soft biometric models, and demonstrate their verification performance on a subset of the PETS 2006 database. We show that these models, whilst not as accurate as traditional biometrics, can still achieve acceptable rates of accuracy in situations where traditional biometrics cannot be applied.

FPGA implementation of dual-microphone delay-and-sum beamforming for in-car speech enhancement and recognition

In an automotive environment, the performance of a speech recognition system is affected by environmental noise if the speech signal is acquired directly from a microphone. Speech enhancement techniques are therefore necessary to improve the speech recognition performance. In this paper, a field-programmable gate array (FPGA) implementation of dual-microphone delay-and-sum beamforming (DASB) for speech enhancement is presented. As the first step towards a cost-effective solution, the implementation described in this paper uses a relatively high-end FPGA device to facilitate the verification of various design strategies and parameters. Experimental results show that the proposed design can produce output waveforms close to those generated by a theoretical (floating-point) model with modest usage of FPGA resources. Speech recognition experiments are also conducted on enhanced in-car speech waveforms produced by the FPGA in order to compare recognition performance with the floating-point representation running on a PC.

Bayes factor based speaker clustering for speaker diarization

This paper proposes the use of the Bayes Factor to replace the Bayesian Information Criterion (BIC) as a criterion for speaker clustering within a speaker diarization system. The BIC is one of the most popular decision criteria used in speaker diarization systems today. However, it will be shown in this paper that the BIC is only an approximation to the Bayes factor of marginal likelihoods of the data given each hypothesis. This paper uses the Bayes factor directly as a decision criterion for speaker clustering, thus removing the error introduced by the BIC approximation. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, leading to a 14.7% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.