Correlation-based damage detection for complicated truss bridges using multi-layer genetic algorithms

The study presents a multi-layer genetic algorithm (GA) approach using correlation-based methods to facilitate damage determination for through-truss bridge structures. To begin, the structure’s damage-suspicious elements are divided into several groups. In the first GA layer, the damage is initially optimised for all groups using correlation objective function. In the second layer, the groups are combined to larger groups and the optimisation starts over at the normalised point of the first layer result. Then the identification process repeats until reaching the final layer where one group includes all structural elements and only minor optimisations are required to fine tune the final result. Several damage scenarios on a complicated through-truss bridge example are nominated to address the proposed approach’s effectiveness. Structural modal strain energy has been employed as the variable vector in the correlation function for damage determination. Simulations and comparison with the traditional single-layer optimisation shows that the proposed approach is efficient and feasible for complicated truss bridge structures when the measurement noise is taken into account.

Application of a human bone engineering platform to an in vitro and in vivo breast cancer metastasis model

Breast cancer in its advanced stage has a high predilection to the skeleton. Currently, treatment options of breast cancer-related bone metastasis are restricted to only palliative therapeutic modalities. This is due to the fact that mechanisms regarding the breast cancer celI-bone colonisation as well as the interactions of breast cancer cells with the bone microenvironment are not fully understood, yet. This might be explained through a lack of appropriate in vitro and in vivo models that are currently addressing the above mentioned issue. Hence the hypothesis that the translation of a bone tissue engineering platform could lead to improved and more physiological in vitro and in vivo model systems in order to investigate breast cancer related bone colonisation was embraced in this PhD thesis. Therefore the first objective was to develop an in vitro model system that mimics human mineralised bone matrix to the highest possible extent to examine the specific biological question, how the human bone matrix influences breast cancer cell behaviour. Thus, primary human osteoblasts were isolated from human bone and cultured under osteogenic conditions. Upon ammonium hydroxide treatment, a cell-free intact mineralised human bone matrix was left behind. Analyses revealed a similar protein and mineral composition of the decellularised osteoblast matrix to human bone. Seeding of a panel of breast cancer cells onto the bone mimicking matrix as well as reference substrates like standard tissue culture plastic and collagen coated tissue culture plastic revealed substrate specific differences of cellular behaviour. Analyses of attachment, alignment, migration, proliferation, invasion, as well as downstream signalling pathways showed that these cellular properties were influenced through the osteoblast matrix. The second objective of this PhD project was the development of a human ectopic bone model in NOD/SCID mice using medical grade polycaprolactone tricalcium phosphate (mPCL-TCP) scaffold. Human osteoblasts and mesenchymal stem cells were seeded onto an mPCL-TCP scaffold, fabricated using a fused deposition modelling technique. After subcutaneous implantation in conjunction with the bone morphogenetic protein 7, limited bone formation was observed due to the mechanical properties of the applied scaffold and restricted integration into the soft tissue of flank of NOD/SCID mice. Thus, a different scaffold fabrication technique was chosen using the same polymer. Electrospun tubular scaffolds were seeded with human osteoblasts, as they showed previously the highest amount of bone formation and implanted into the flanks of NOD/SCID mice. Ectopic bone formation with sufficient vascularisation could be observed. After implantation of breast cancer cells using a polyethylene glycol hydrogel in close proximity to the newly formed bone, macroscopic communication between the newly formed bone and the tumour could be observed. Taken together, this PhD project showed that bone tissue engineering platforms could be used to develop an in vitro and in vivo model system to study cancer cell colonisation in the bone microenvironment.

Spatial inequalities in colorectal and breast cancer survival : premature deaths and associated factors

This study examines the influence of cancer stage, distance to treatment facilities and area disadvantage on breast and colorectal cancer spatial survival inequalities. We also estimate the number of premature deaths after adjusting for cancer stage to quantify the impact of spatial survival inequalities. Population-based descriptive study of residents aged <90 years in Queensland, Australia diagnosed with primary invasive breast (25,202 females) or colorectal (14,690 males, 11,700 females) cancers during 1996-2007. Bayesian hierarchical models explored relative survival inequalities across 478 regions. Cancer stage and disadvantage explained the spatial inequalities in breast cancer survival, however spatial inequalities in colorectal cancer survival persisted after adjustment. Of the 6,019 colorectal cancer deaths within 5 years of diagnosis, 470 (8%) were associated with spatial inequalities in non-diagnostic factors, i.e. factors beyond cancer stage at diagnosis. For breast cancers, of 2,412 deaths, 170 (7%) were related to spatial inequalities in non-diagnostic factors. Quantifying premature deaths can increase incentive for action to reduce these spatial inequalities.

Global flash multifocal electroretinogram : early detection of local functional changes and its correlations with optical coherence tomography and visual field loss in diabetic eyes

Purpose: To investigate the correlations of the global flash multifocal electroretinogram (MOFO mfERG) with common clinical visual assessments – Humphrey perimetry and Stratus circumpapillary retinal nerve fiber layer (RNFL) thickness measurement in type II diabetic patients. Methods: Forty-two diabetic patients participated in the study: ten were free from diabetic retinopathy (DR) while the remainder suffered from mild to moderate non-proliferative diabetic retinopathy (NPDR). Fourteen age-matched controls were recruited for comparison. MOFO mfERG measurements were made under high and low contrast conditions. Humphrey central 30-2 perimetry and Stratus OCT circumpapillary RNFL thickness measurements were also performed. Correlations between local values of implicit time and amplitude of the mfERG components (direct component (DC) and induced component (IC)), and perimetric sensitivity and RNFL thickness were evaluated by mapping the localized responses for the three subject groups. Results: MOFO mfERG was superior to perimetry and RNFL assessments in showing differences between the diabetic groups (with and without DR) and the controls. All the MOFO mfERG amplitudes (except IC amplitude at high contrast) correlated better with perimetry findings (Pearson’s r ranged from 0.23 to 0.36, p<0.01) than did the mfERG implicit time at both high and low contrasts across all subject groups. No consistent correlation was found between the mfERG and RNFL assessments for any group or contrast conditions. The responses of the local MOFO mfERG correlated with local perimetric sensitivity but not with RNFL thickness. Conclusion: Early functional changes in the diabetic retina seem to occur before morphological changes in the RNFL.

Neural network-based detection of virtual environment anomalies

The increasingly widespread use of large-scale 3D virtual environments has translated into an increasing effort required from designers, developers and testers. While considerable research has been conducted into assisting the design of virtual world content and mechanics, to date, only limited contributions have been made regarding the automatic testing of the underpinning graphics software and hardware. In the work presented in this paper, two novel neural network-based approaches are presented to predict the correct visualization of 3D content. Multilayer perceptrons and self-organizing maps are trained to learn the normal geometric and color appearance of objects from validated frames and then used to detect novel or anomalous renderings in new images. Our approach is general, for the appearance of the object is learned rather than explicitly represented. Experiments were conducted on a game engine to determine the applicability and effectiveness of our algorithms. The results show that the neural network technology can be effectively used to address the problem of automatic and reliable visual testing of 3D virtual environments.

Prevalence of breast cancer treatment sequelae over 6 years of follow-up

Background: There is a need to better describe and understand the prevalence of breast cancer treatment-related adverse effects amenable to physical therapy and rehabilitative exercise. Prior studies have been limited to single issues and lacked long term follow-up. The Pulling Through Study provides data on prevalence of adverse effects in breast cancer survivors followed over six years. Methods: A population-based sample of Australian women (n=287) diagnosed with invasive, unilateral breast cancer was followed for a median of 6.6 years and prospectively assessed for treatment-related complications at 6, 12, 18 months, and 6 years post-diagnosis. Assessments included post-surgical complications, skin or tissue reaction to radiation therapy, upper-body symptoms, lymphedema, 10% weight gain, fatigue, and upper-quadrant function. The proportion of women with positive indication for each complication and one or more complication was estimated using all available data at each time point. Women were only considered to have a specific complication if they reported the highest two levels of the Likert scale for self-reported issues. Results: At six years post-diagnosis over 60% of women experienced one or more side effects amenable to rehabilitative intervention. The proportion of women experiencing 3 or more side effects decreased throughout follow-up, while the proportion experiencing no side effects remained stable around 40% from 12 months to six years. Weight gain was the only complication to increase in prevalence over time. Conclusion: These data support the development of a multi-disciplinary prospective surveillance approach for the purposes of managing and treating adverse effects in breast cancer survivors.

Prognostic significance of IGF and ECM induced signalling proteins in breast cancer patients

Breast cancer is a leading contributor to the burden of disease in Australia. Fortunately, the recent introduction of diverse therapeutic strategies have improved the survival outcome for many women. Despite this, the clinical management of breast cancer remains problematic as not all approaches are sufficiently sophisticated to take into account the heterogeneity of this disease and are unable to predict disease progression, in particular, metastasis. As such, women with good prognostic outcomes are exposed to the side effects of therapies without added benefit. Furthermore, women with aggressive disease for whom these advanced treatments would deliver benefit cannot be distinguished and opportunities for more intensive or novel treatment are lost. This study is designed to identify novel factors associated with disease progression, and the potential to inform disease prognosis. Frequently overlooked, yet common mediators of disease are the interactions that take place between the insulin-like growth factor (IGF) system and the extracellular matrix (ECM). Our laboratory has previously demonstrated that multiprotein insulin-like growth factor-I (IGF-I): insulin-like growth factor binding protein (IGFBP): vitronectin (VN) complexes stimulate migration of breast cancer cells in vitro, via the cooperative involvement of the insulin-like growth factor type I receptor (IGF-IR) and VN-binding integrins. However, the effects of IGF and ECM protein interactions on the dissemination and progression of breast cancer in vivo are unknown. It was hypothesised that interactions between proteins required for IGF induced signalling events and those within the ECM contribute to breast cancer metastasis and are prognostic and predictive indicators of patient outcome. To address this hypothesis, semiquantitative immunohistochemistry (IHC) analyses were performed to compare the extracellular and subcellular distribution of IGF and ECM induced signalling proteins between matched normal, primary cancer, and metastatic cancer among archival formalin-fixed paraffin-embedded (FFPE) breast tissue samples collected from women attending the Princess Alexandra Hospital, Brisbane. Multivariate Cox proportional hazards (PH) regression survival models in conjunction with a modified „purposeful selection of covariates. method were applied to determine the prognostic potential of these proteins. This study provides the first in-depth, compartmentalised analysis of the distribution of IGF and ECM induced signalling proteins. As protein function and protein localisation are closely correlated, these findings provide novel insights into IGF signalling and ECM protein function during breast cancer development and progression. Distinct IGF signalling and ECM protein immunoreactivity was observed in the stroma and/or in subcellular locations in normal breast, primary cancer and metastatic cancer tissues. Analysis of the presence and location of stratifin (SFN) suggested a causal relationship in ECM remodelling events during breast cancer development and progression. The results of this study have also suggested that fibronectin (FN) and ¥â1 integrin are important for the formation of invadopodia and epithelial-to-mesenchymal transition (EMT) events. Our data also highlighted the importance of the temporal and spatial distribution of IGF induced signalling proteins in breast cancer metastasis; in particular, SFN, enhancer-of-split and hairy-related protein 2 (SHARP-2), total-akt/protein kinase B 1 (Total-AKT1), phosphorylated-akt/protein kinase B (P-AKT), extracellular signal-related kinase-1 and extracellular signal-related kinase-2 (ERK1/2) and phosphorylated-extracellular signal-related kinase-1 and extracellular signal-related kinase-2 (P-ERK1/2). Multivariate survival models were created from the immunohistochemical data. These models were found to fit well with these data with very high statistical confidence. Numerous prognostic confounding effects and effect modifications were identified among elements of the ECM and IGF signalling cascade and corroborate the survival models. This finding provides further evidence for the prognostic potential of IGF and ECM induced signalling proteins. In addition, the adjusted measures of associations obtained in this study have strengthened the validity and utility of the resulting models. The findings from this study provide insights into the biological interactions that occur during the development of breast tissue and contribute to disease progression. Importantly, these multivariate survival models could provide important prognostic and predictive indicators that assist the clinical management of breast disease, namely in the early identification of cancers with a propensity to metastasise, and/or recur following adjuvant therapy. The outcomes of this study further inform the development of new therapeutics to aid patient recovery. The findings from this study have widespread clinical application in the diagnosis of disease and prognosis of disease progression, and inform the most appropriate clinical management of individuals with breast cancer.

Factors influencing health behaviours of younger women after menopause-inducing cancer treatment

Objective To investigate the health promotion and risk reduction behaviors of younger women previously treated for cancer. Design and Sample Guided by the Precede-Proceed framework, a mixed-method descriptive investigation of the health behaviors of younger women with cancer treatment-induced menopause in one health jurisdiction in Australia was undertaken. Measures This article reports the results of the qualitative interview component of the study. Results Of the 85 women who responded to surveys that quantified their health behaviors, 22 consented to interviews that explored how and why these behaviors might occur. Conclusions Several predisposing, enabling and reinforcing factors that influenced participants will or ability to engage with health-promoting behaviors after cancer treatment were identified in the interviews. These include entrenched precancer diagnosis health behaviors, the disabilities resulting from cancer treatments, perceptions of risk, focused intervention by health professionals and the nature of participants social support. The results indicate a need for flexibility when planning public health initiatives to prepare this cohort for a healthy life after cancer, which accounts for their developmental, knowledge and posttreatment needs.

Phenotypic Characterization of Prostate Cancer LNCaP Cells Cultured within a Bioengineered Microenvironment

Biophysical and biochemical properties of the microenvironment regulate cellular responses such as growth, differentiation, morphogenesis and migration in normal and cancer cells. Since two-dimensional (2D) cultures lack the essential characteristics of the native cellular microenvironment, three-dimensional (3D) cultures have been developed to better mimic the natural extracellular matrix. To date, 3D culture systems have relied mostly on collagen and Matrigel™ hydrogels, allowing only limited control over matrix stiffness, proteolytic degradability, and ligand density. In contrast, bioengineered hydrogels allow us to independently tune and systematically investigate the influence of these parameters on cell growth and differentiation. In this study, polyethylene glycol (PEG) hydrogels, functionalized with the Arginine-glycine-aspartic acid (RGD) motifs, common cell-binding motifs in extracellular matrix proteins, and matrix metalloproteinase (MMP) cleavage sites, were characterized regarding their stiffness, diffusive properties, and ability to support growth of androgen-dependent LNCaP prostate cancer cells. We found that the mechanical properties modulated the growth kinetics of LNCaP cells in the PEG hydrogel. At culture periods of 28 days, LNCaP cells underwent morphogenic changes, forming tumor-like structures in 3D culture, with hypoxic and apoptotic cores. We further compared protein and gene expression levels between 3D and 2D cultures upon stimulation with the synthetic androgen R1881. Interestingly, the kinetics of R1881 stimulated androgen receptor (AR) nuclear translocation differed between 2D and 3D cultures when observed by immunofluorescent staining. Furthermore, microarray studies revealed that changes in expression levels of androgen responsive genes upon R1881 treatment differed greatly between 2D and 3D cultures. Taken together, culturing LNCaP cells in the tunable PEG hydrogels reveals differences in the cellular responses to androgen stimulation between the 2D and 3D environments. Therefore, we suggest that the presented 3D culture system represents a powerful tool for high throughput prostate cancer drug testing that recapitulates tumor microenvironment. © 2012 Sieh et al.

Fast power line detection and localization using steerable filter for active UAV guidance

In this paper we present a fast power line detection and localisation algorithm as well as propose a high-level guidance architecture for active vision-based Unmanned Aerial Vehicle (UAV) guidance. The detection stage is based on steerable filters for edge ridge detection, followed by a line fitting algorithm to refine candidate power lines in images. The guidance architecture assumes an UAV with an onboard Gimbal camera. We first control the position of the Gimbal such that the power line is in the field of view of the camera. Then its pose is used to generate the appropriate control commands such that the aircraft moves and flies above the lines. We present initial experimental results for the detection stage which shows that the proposed algorithm outperforms two state-of-the-art line detection algorithms for power line detection from aerial imagery.

Detection of tissue plasminogen activator (t-PA) and plasminogen activator inhibitor 2(PAI-2) in gingival crevicular fluid from healthy, gingivitis and periodontitis patients

Background: The regulation of plasminogen activation is a key element in controlling proteolytic events in the extracellular matrix. Our previous studies had demonstrated that in inflamed gingival tissues, tissue-type plasminogen activator (t-PA) is significantly increased in the extracellular matrix of the connective tissue and that interleukin 1β (IL-1β) can up regulate the level of t-PA and plasminogen activator inhibitor-2 (PAI-2) synthesis by human gingival fibroblasts. Method: In the present study, the levels of t-PA and PAI-2 in gingival crevicular fluid (GCF) were measured from healthy, gingivitis and periodontitis sites and compared before and after periodontal treatment. Crevicular fluid from106 periodontal sites in 33 patients were collected. 24 sites from 11 periodontitis patients received periodontal treatment after the first sample collection and post-treatment samples were collected 14 days after treatment. All samples were analyzed by enzyme-linked immunosorbent assay (ELISA) for t-PA and PAI-2. Results: The results showed that significantly high levels of t-PA and PAI-2 in GCF were found in the gingivitis and periodontitis sites. Periodontal treatment led to significant decreases of PAI-2, but not t-PA, after 14 days. A significant positive linear correlation was found between t-PA and PAI-2 in GCF (r=0.80, p<0.01). In the healthy group, different sites from within the same subject showed little variation of t-PA and PAI-2 in GCF. However, the gingivitis and periodontitis sites showed large variation. These results suggest a good correlation between t-PA and PAI-2 with the severity of periodontal conditions. Conclusion: This study indicates that t-PA and PAI-2 may play a significant rôle in the periodontal tissue destruction and tissue remodeling and that t-PA and PAI-2 in GCF may be used as clinical markers to evaluate the periodontal diseases and assess treatment.

Fibroblast growth factor receptor inhibition synergizes with paclitaxel and doxorubicin in endometrial cancer cells

OBJECTIVE: The fibroblast growth factor (FGF) family of signaling molecules has been associated with chemoresistance and poor prognosis in a number of cancer types, including lung, breast, ovarian, prostate, and head and neck carcinomas. Given the identification of activating mutations in the FGF receptor 2 (FGFR2) receptor tyrosine kinase in a subset of endometrial tumors, agents with activity against FGFRs are currently being tested in clinical trials for recurrent and progressive endometrial cancer. Here, we evaluated the effect of FGFR inhibition on the in vitro efficacy of chemotherapy in endometrial cancer cell lines. METHODS: Human endometrial cancer cell lines with wild-type or activating FGFR2 mutations were used to determine any synergism with concurrent use of the pan-FGFR inhibitor, PD173074, and the chemotherapeutics, doxorubicin and paclitaxel, on cell proliferation and apoptosis. RESULTS: FGFR2 mutation status did not alter sensitivity to either chemotherapeutic agent alone. The combination of PD173074 with paclitaxel or doxorubicin showed synergistic activity in the 3 FGFR2 mutant cell lines evaluated. In addition, although nonmutant cell lines were resistant to FGFR inhibition alone, the addition of PD173074 potentiated the cytostatic effect of paclitaxel and doxorubicin in a subset of FGFR2 wild-type endometrial cancer cell lines. CONCLUSIONS: Together these data suggest a potential therapeutic benefit to combining an FGFR inhibitor with standard chemotherapeutic agents in endometrial cancer therapy particularly in patients with FGFR2 mutation positive tumors.

Many paths lead to discovery : analogical retrieval of cancer therapies

This paper addresses the issue of analogical inference, and its potential role as the mediator of new therapeutic discoveries, by using disjunction operators based on quantum connectives to combine many potential reasoning pathways into a single search expression. In it, we extend our previous work in which we developed an approach to analogical retrieval using the Predication-based Semantic Indexing (PSI) model, which encodes both concepts and the relationships between them in high-dimensional vector space. As in our previous work, we leverage the ability of PSI to infer predicate pathways connecting two example concepts, in this case comprising of known therapeutic relationships. For example, given that drug x TREATS disease z, we might infer the predicate pathway drug x INTERACTS WITH gene y ASSOCIATED WITH disease z, and use this pathway to search for drugs related to another disease in similar ways. As biological systems tend to be characterized by networks of relationships, we evaluate the ability of quantum-inspired operators to mediate inference and retrieval across multiple relations, by testing the ability of different approaches to recover known therapeutic relationships. In addition, we introduce a novel complex vector based implementation of PSI, based on Plate’s Circular Holographic Reduced Representations, which we utilize for all experiments in addition to the binary vector based approach we have applied in our previous research.

Automatic region-of-interest detection and prioritisation for visually optimised coding of low bit rate videos

The increasing popularity of video consumption from mobile devices requires an effective video coding strategy. To overcome diverse communication networks, video services often need to maintain sustainable quality when the available bandwidth is limited. One of the strategy for a visually-optimised video adaptation is by implementing a region-of-interest (ROI) based scalability, whereby important regions can be encoded at a higher quality while maintaining sufficient quality for the rest of the frame. The result is an improved perceived quality at the same bit rate as normal encoding, which is particularly obvious at the range of lower bit rate. However, because of the difficulties of predicting region-of-interest (ROI) accurately, there is a limited research and development of ROI-based video coding for general videos. In this paper, the phase spectrum quaternion of Fourier Transform (PQFT) method is adopted to determine the ROI. To improve the results of ROI detection, the saliency map from the PQFT is augmented with maps created from high level knowledge of factors that are known to attract human attention. Hence, maps that locate faces and emphasise the centre of the screen are used in combination with the saliency map to determine the ROI. The contribution of this paper lies on the automatic ROI detection technique for coding a low bit rate videos which include the ROI prioritisation technique to give different level of encoding qualities for multiple ROIs, and the evaluation of the proposed automatic ROI detection that is shown to have a close performance to human ROI, based on the eye fixation data.

Determining the detection capabilities of existing real time measurement techniques for different engineered nanoparticles

The application of nanotechnology products has increased significantly in recent years. With their broad range of applications, including electronics, food and agriculture, power and energy, scientific instruments, clothing, cosmetics, buildings, biomedical and health, etc (Catanzariti, 2008), nanomaterials are an indispensible part of human life.