Properties of porous structures prepared by stereolithography using a polylactide resin

Rapid prototyping techniques such as stereolithography allow for building designed tissue engineering scaffolds with high accuracy. In this work, a stereolithography resin based on poly(D,L-lactide) was developed. Biodegradable scaffolds with varying porosity were built from this resin. The scaffolds were analysed by μCT-scanning and compression testing. The porous structures showed excellent mechanical properties in the range of trabecular bone.

Properties of photo-cured poly(D,L-lactide) networks

Poly(D,L-lactide) is a degradable polymer with a long history of use in medical applications. It is strong and stiff and degrades over the course of months into lactic acid, a body-own substance. In the field of tissue engineering it is commonly used to fabricate scaffolds. Stereolithography is a high resolution rapid prototyping technique by which designed 3D objects can be built using photo-initiated radical polymerisations. Poly(D,Llactide) (PDLLA) networks can be obtained by photopolymerisation of oligomers functionalised with unsaturated groups. In this work, PDLLA oligomers of varying architectures (arm lengths, numbers of arms) were synthesised and end-functionalised with methacrylate groups. These macromers were photo-crosslinked in solution to yield PDLLA networks of different architectures. The influence of the network architecture on its physical properties was studied.

Mechanical properties of advanced tissue engineering scaffold architectures

In tissue engineering, porous scaffolds are used as a temporal support for tissue regeneration through cell adhesion, proliferation and differentiation. Besides applying a suitable material that is both biocompatible and biodegradable, the architectural design of the porous scaffold can be of essential for successful tissue regeneration. The architecture is of great influence on mechanical properties and transport properties of nutrients and metabolites1.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

The effects of muscle fatigue on knee function during landing

The human knee acts as a sophisticated shock absorber during landing movements. The ability of the knee to perform this function in the real world is remarkable given that the context of the landing movement may vary widely between performances. For this reason, humans must be capable of rapidly adjusting the mechanical properties of the knee under impact load in order to satisfy many competing demands. However, the processes involved in regulating these properties in response to changing constraints remain poorly understood. In particular, the effects of muscle fatigue on knee function during step landing are yet to be fully explored. Fatigue of the knee muscles is significant for 2 reasons. First, it is thought to have detrimental effects on the ability of the knee to act as a shock absorber and is considered a risk factor for knee injury. Second, fatigue of knee muscles provides a unique opportunity to examine the mechanisms by which healthy individuals alter knee function. A review of the literature revealed that the effect of fatigue on knee function during landing has been assessed by comparing pre and postfatigue measurements, with fatigue induced by a voluntary exercise protocol. The information is limited by inconsistent results with key measures, such as knee stiffness, showing varying results following fatigue, including increased stiffness, decreased stiffness or failure to detect any change in some experiments. Further consideration of the literature questions the validity of the models used to induce and measure fatigue, as well as the pre-post study design, which may explain the lack of consensus in the results. These limitations cast doubt on the usefulness of the available information and identify a need to investigate alternative approaches. Based on the results of this review, the aims of this thesis were to: • evaluate the methodological procedures used in validation of a fatigue model • investigate the adaptation and regulation of post-impact knee mechanics during repeated step landings • use this new information to test the effects of fatigue on knee function during a step-landing task. To address the aims of the thesis, 3 related experiments were conducted that collected kinetic, kinematic and electromyographic data from 3 separate samples of healthy male participants. The methodologies involved optoelectronic motion capture (VICON), isokinetic dynamometry (System3 Pro, BIODEX) and wireless surface electromyography (Zerowire, Aurion, Italy). Fatigue indicators and knee function measures used in each experiment were derived from the data. Study 1 compared the validity and reliability of repetitive stepping and isokinetic contractions with respect to fatigue of the quadriceps and hamstrings. Fifteen participants performed 50 repetitions of each exercise twice in randomised order, over 4 sessions. Sessions were separated by a minimum of 1 week’s rest, to ensure full recovery. Validity and reliability depended on a complex interaction between the exercise protocol, the fatigue indicator, the individual and the muscle of interest. Nevertheless, differences between exercise protocols indicated that stepping was less effective in eliciting valid and reliable changes in peak power and spectral compression, compared with isokinetic exercise. A key finding was that fatigue progressed in a biphasic pattern during both exercises. The point separating the 2 phases, known as the transition point, demonstrated superior between-test reliability during the isokinetic protocol, compared with stepping. However, a correction factor should be used to accurately apply this technique to the study of fatigue during landing. Study 2 examined alterations in knee function during repeated landings, with a different sample (N =12) performing 60 consecutive step landing trials. Each landing trial was separated by 1-minute rest periods. The results provided new information in relation to the pre-post study design in the context of detecting adjustments in knee function during landing. First, participants significantly increased or decreased pre-impact muscle activity or post-impact mechanics despite environmental and task constraints remaining unchanged. This is the 1st study to demonstrate this effect in healthy individuals without external feedback on performance. Second, single-subject analysis was more effective in detecting alterations in knee function compared to group-level analysis. Finally, repeated landing trials did not reduce inter-trial variability of knee function in some participants, contrary to assumptions underpinning previous studies. The results of studies 1 and 2 were used to modify the design of Study 3 relative to previous research. These alterations included a modified isokinetic fatigue protocol, multiple pre-fatigue measurements and singlesubject analysis to detect fatigue-related changes in knee function. The study design incorporated new analytical approaches to investigate fatiguerelated alterations in knee function during landing. Participants (N = 16) were measured during multiple pre-fatigue baseline trial blocks prior to the fatigue model. A final block of landing trials was recorded once the participant met the operational fatigue definition that was identified in Study 1. The analysis revealed that the effects of fatigue in this context are heavily dependent on the compensatory response of the individual. A continuum of responses was observed within the sample for each knee function measure. Overall, preimpact preparation and post-impact mechanics of the knee were altered with highly individualised patterns. Moreover, participants used a range of active or passive pre-impact strategies to adapt post-impact mechanics in response to quadriceps fatigue. The unique patterns identified in the data represented an optimisation of knee function based on priorities of the individual. The findings of these studies explain the lack of consensus within the literature regarding the effects of fatigue on knee function during landing. First, functional fatigue protocols lack validity in inducing fatigue-related changes in mechanical output and spectral compression of surface electromyography (sEMG) signals, compared with isokinetic exercise. Second, fatigue-related changes in knee function during landing are confounded by inter-individual variation, which limits the sensitivity of group-level analysis. By addressing these limitations, the 3rd study demonstrated the efficacies of new experimental and analytical approaches to observe fatigue-related alterations in knee function during landing. Consequently, this thesis provides new perspectives into the effects of fatigue in knee function during landing. In conclusion: • The effects of fatigue on knee function during landing depend on the response of the individual, with considerable variation present between study participants, despite similar physical characteristics. • In healthy males, adaptation of pre-impact muscle activity and postimpact knee mechanics is unique to the individual and reflects their own optimisation of demands such as energy expenditure, joint stability, sensory information and loading of knee structures. • The results of these studies should guide future exploration of adaptations in knee function to fatigue. However, research in this area should continue with reduced emphasis on the directional response of the population and a greater focus on individual adaptations of knee function.

Purification and Properties of Closteroviruslike Particles Associated with Grapevine Corky Bark Disease

Closteroviruslike particles, designated as grapevine corky bark-associated virus (GCBaV), were purified from mature leaves and stem phloem tissue of a corky bark-affected grapevine that had indexed negative for other grapevine viruses. Electron microscopy of purified preparations revealed the presence of flexuous rod-shaped viruslike particles that were about 13 nm in diameter and between 1,400 and 2,000 nm long, with a helical pitch of 3.4 nm. In purified preparations, the GCBaV particles degraded within a few weeks, unlike grapevine leafroll associated virus (GLRaV), which was stable for more than 1 mo under the same storage condition. The molecular weight of the coat protein of GCBaV was 24,000. A large dsRNA molecule (about 15.3 kbp), along with lower molecular weight species, was detected in tissues of corky bark-diseased grapevines, but not in healthy grapevines. Polyclonal antisera were produced in rabbits against purified or partially purified virus preparations. In direct enzyme-linked immunosorbent assay (ELISA), antisera to GCBaV did not react to the serologically distinct types (II and III) of the long closteroviruses associated with grapevine leafroll disease and grapevine virus A (GVA), and vice versa. This antiserum also reacted in ELISA with other corky bark-affected grapevines. Our data suggest that closteroviruslike particles, designated as GCBaV, may be the causal agent of corky bark disease. However, definitive proof is still lacking. The inclusion of GCBaV in the group of closteroviruses with citrus tristeza virus is proposed.

Effect of thermal treatment on adsorption-desorption of ammonia and sulfur dioxide on palygorskite : change of surface acid-alkali properties

Thermally activated Palygorskite (Pg) has been found to be a good adsorbent material for ammonia (NH3) and sulfur dioxide (SO2). This research investigated the effect of thermal treatment on pore structure and surface acid-alkali properties of Pg through the adsorption-desorption of NH3 and SO2. The results showed that, up to 200 °C, the adsorption of NH3 on Pg was significantly higher than SO2. This was due to NH3 being adsorbed in the internal surface of Pg and forming hydrogen bonds (H-bonds) with coordinated water. The increase in thermal treatment temp. from 150 to 550 °C, showed a gradual decrease in the no. of surface acid sites, while the no. of surface alk. sites increased from 200 to 400 °C. The change of surface acidity-alk. sites is due to the collapse of internal channels of Pg and desorption of different types of hydroxyls assocd. with the Pg structure.

A probability-based approach for assessing the relationship between crash accidents and pavement properties

Skid resistance is a condition parameter characterising the contribution that a road makes to the friction between a road surface and a vehicle tyre. Studies of traffic crash histories around the world have consistently found that a disproportionate number of crashes occur where the road surface has a low level of surface friction and/or surface texture, particularly when the road surface is wet. Various research results have been published over many years and have tried to quantify the influence of skid resistance on accident occurrence and to characterise a correlation between skid resistance and accident frequency. Most of the research studies used simple statistical correlation methods in analysing skid resistance and crash data.----- ------ Preliminary findings of a systematic and extensive literature search conclude that there is rarely a single causation factor in a crash. Findings from research projects do affirm various levels of correlation between skid resistance and accident occurrence. Studies indicate that the level of skid resistance at critical places such as intersections, curves, roundabouts, ramps and approaches to pedestrian crossings needs to be well maintained.----- ----- Management of risk is an integral aspect of the Queensland Department of Main Roads (QDMR) strategy for managing its infrastructure assets. The risk-based approach has been used in many areas of infrastructure engineering. However, very limited information is reported on using risk-based approach to mitigate crash rates related to road surface. Low skid resistance and surface texture may increase the risk of traffic crashes.----- ----- The objectives of this paper are to explore current issues of skid resistance in relation to crashes, to provide a framework of probability-based approach to be adopted by QDMR in assessing the relationship between crash accidents and pavement properties, and to explain why the probability-based approach is a suitable tool for QDMR in order to reduce accident rates due to skid resistance.

A biologically inspired object spectral-texture descriptor and its application to vegetation classification in power-line corridors

The use of appropriate features to represent an output class or object is critical for all classification problems. In this paper, we propose a biologically inspired object descriptor to represent the spectral-texture patterns of image-objects. The proposed feature descriptor is generated from the pulse spectral frequencies (PSF) of a pulse coupled neural network (PCNN), which is invariant to rotation, translation and small scale changes. The proposed method is first evaluated in a rotation and scale invariant texture classification using USC-SIPI texture database. It is further evaluated in an application of vegetation species classification in power line corridor monitoring using airborne multi-spectral aerial imagery. The results from the two experiments demonstrate that the PSF feature is effective to represent spectral-texture patterns of objects and it shows better results than classic color histogram and texture features.

Spatial and temporal variations of mechanical properties and mineral content of the external callus during bone healing

After bone fracture, various cellular activities lead to the formation of different tissue types, which form the basis for the process of secondary bone healing. Although these tissues have been quantified by histology, their material properties are not well understood. Thus, the aim of this study is to correlate the spatial and temporal variations in the mineral content and the nanoindentation modulus of the callus formed via intramembranous ossification over the course of bone healing. Midshaft tibial samples from a sheep osteotomy model at time points of 2, 3, 6 and 9 weeks were employed. PMMA embedded blocks were used for quantitative back scattered electron imaging and nanoindentation of the newly formed periosteal callus near the cortex. The resulting indentation modulus maps show the heterogeneity in the modulus in the selected regions of the callus. The indentation modulus of the embedded callus is about 6 GPa at the early stage. At later stages of mineralization, the average indentation modulus reaches 14 GPa. There is a slight decrease in average indentation modulus in regions distant to the cortex, probably due to remodelling of the peripheral callus. The spatial and temporal distribution of mineral content in the callus tissue also illustrates the ongoing remodelling process observed from histological analysis. Most interestingly the average indentation modulus, even at 9 weeks, remains as low as 13 GPa, which is roughly 60% of that for cortical sheep bone. The decreased indentation modulus in the callus compared to cortex is due to the lower average mineral content and may be perhaps also due to the properties of the organic matrix which might be different from normal bone.

Bioactive SrO–SiO2 glass with well-ordered mesopores : characterization, physiochemistry and biological properties

For a biomaterial to be considered suitable for bone repair it should ideally be both bioactive and have a capacity for controllable drug delivery; as such, mesoporous SiO2 glass has been proposed as a new class of bone regeneration material by virtue of its high drug-loading ability and generally good biocompatibility. It does, however, have less than optimum bioactivity and controllable drug delivery properties. In this study, we incorporated strontium (Sr) into mesoporous SiO2 in an effort to develop a bioactive mesoporous SrO–SiO2 (Sr–Si) glass with the capacity to deliver Sr2+ ions, as well as a drug, at a controlled rate, thereby producing a material better suited for bone repair. The effects of Sr2+ on the structure, physiochemistry, drug delivery and biological properties of mesoporous Sr–Si glass were investigated. The prepared mesoporous Sr–Si glass was found to have an excellent release profile of bioactive Sr2+ ions and dexamethasone, and the incorporation of Sr2+ improved structural properties, such as mesopore size, pore volume and specific surface area, as well as rate of dissolution and protein adsorption. The mesoporous Sr–Si glass had no cytotoxic effects and its release of Sr2+ and SiO44− ions enhanced alkaline phosphatase activity – a marker of osteogenic cell differentiation – in human bone mesenchymal stem cells. Mesoporous Sr–Si glasses can be prepared to porous scaffolds which show a more sustained drug release. This study suggests that incorporating Sr2+ into mesoporous SiO2 glass produces a material with a more optimal drug delivery profile coupled with improved bioactivity, making it an excellent material for bone repair applications. Keywords: Mesoporous Sr–Si glass; Drug delivery; Bioactivity; Bone repair; Scaffolds

The effects of bioactive akermanite on physiochemical, drug-delivery and biological properties of poly (lactide-co-glycolide) beads

Poly(lactide-co-glycolide) (PLGA) beads have been widely studied as a potential drug/protein carrier. The main shortcomings of PLGA beads are that they lack bioactivity and controllable drug-delivery ability, and their acidic degradation by-products can lead to pH decrease in the vicinity of the implants. Akermanite (AK) (Ca(2) MgSi(2) O(7) ) is a novel bioactive ceramic which has shown excellent bioactivity and degradation in vivo. This study aimed to incorporate AK to PLGA beads to improve the physiochemical, drug-delivery, and biological properties of PLGA beads. The microstructure of beads was characterized by SEM. The effect of AK incorporating into PLGA beads on the mechanical strength, apatite-formation ability, the loading and release of BSA, and the proliferation, and differentiation of bone marrow stromal cells (BMSCs) was investigated. The results showed that the incorporation of AK into PLGA beads altered the anisotropic microporous structure into homogenous one and improved their compressive strength and apatite-formation ability in simulated body fluids (SBF). AK neutralized the acidic products from PLGA beads, leading to stable pH value of 7.4 in biological environment. AK led to a sustainable and controllable release of bovine serum albumin (BSA) in PLGA beads. The incorporation of AK into PLGA beads enhanced the proliferation and alkaline phosphatase activity of BMSCs. This study implies that the incorporation of AK into PLGA beads is a promising method to enhance their physiochemical and biological property. AK/PLGA composite beads are a potential bioactive drug-delivery system for bone tissue repair.

Long-term effects of hydrogel properties on human chondrocyte behavior

Hydrogels provide a 3-dimensional network for embedded cells and offer promise for cartilage tissue engineering applications. Nature-derived hydrogels, including alginate, have been shown to enhance the chondrocyte phenotype but are variable and not entirely controllable. Synthetic hydrogels, including polyethylene glycol (PEG)-based matrices, have the advantage of repeatability and modularity; mechanical stiffness, cell adhesion, and degradability can be altered independently. In this study, we compared the long-term in vitro effects of different hydrogels (alginate and Factor XIIIa-cross-linked MMP-sensitive PEG at two stiffness levels) on the behavior of expanded human chondrocytes and the development of construct properties. Monolayer-expanded human chondrocytes remained viable throughout culture, but morphology varied greatly in different hydrogels. Chondrocytes were characteristically round in alginate but mostly spread in PEG gels at both concentrations. Chondrogenic gene (COL2A1, aggrecan) expression increased in all hydrogels, but alginate constructs had much higher expression levels of these genes (up to 90-fold for COL2A1), as well as proteoglycan 4, a functional marker of the superficial zone. Also, chondrocytes expressed COL1A1 and COL10A1, indicative of de-differentiation and hypertrophy. After 12 weeks, constructs with lower polymer content were stiffer than similar constructs with higher polymer content, with the highest compressive modulus measured in 2.5% PEG gels. Different materials and polymer concentrations have markedly different potency to affect chondrocyte behavior. While synthetic hydrogels offer many advantages over natural materials such as alginate, they must be further optimized to elicit desired chondrocyte responses for use as cartilage models and for development of functional tissue-engineered articular cartilage.