Implication of 3D culture system for study of prostate cancer (CaP) mediated bone metastasis

Introduction : For the past decade, three dimensional (3D) culture has served as a foundation for regenerative medicine study. With an increasing awareness of the importance of cell-cell and cell-extracellular matrix interactions which are lacking in 2D culture system, 3D culture system has been employed for many other applications namely cancer research. Through development of various biomaterials and utilization of tissue engineering technology, many in vivo physiological responses are now better understood. The cellular and molecular communication of cancer cells and their microenvironment, for instance can be studied in vitro in 3D culture system without relying on animal models alone. Predilection of prostate cancer (CaP) to bone remains obscure due to the complexity of the mechanisms and lack of proper model for the studies. In this study, we aim to investigate the interaction between CaP cells and osteoblasts simulating the natural bone metastasis. We also further investigate the invasiveness of CaP cells and response of androgen sensitve CaP cells, LNCaP to synthetic androgen.----- Method : Human osteoblast (hOB) scaffolds were prepared by seeding hOB on medical grade polycaprolactone-tricalcium phosphate (mPLC-TCP) scaffolds and induced to produce bone matrix. CaP cell lines namely wild type PC3 (PC3-N), overexpressed prostate specific antigen PC3 (PC3k3s5) and LNCaP were seeded on hOB scaffolds as co-cultures. Morphology of cells was examined by Phalloidin-DAPI and SEM imaging. Gelatin zymography was performed on the 48 hours conditioned media (CM) from co-cultures to determine matrix metalloproteinase (MMP) activity. Gene expression of hOB/LNCaP co-cultures which were treated for 48 hours with 1nM synthetic androgen R1881 were analysed by quantitative real time PCR (qRT-PCR).----- Results : Co-culture of PCC/hOB revealed that the morphology of PCCs on the tissue engineered bone matrix varied from homogenous to heterogenous clusters. Enzymatically inactive pro-MMP2 was detected in CM from hOBs and PCCs cultured on scaffolds. Elevation in MMP9 activity was found only in hOB/PC3N co-culture. hOB/LNCaP co-culture showed increase in expression of key enzymes associated with steroid production which also corresponded to an increase in prostate specific antigen (PSA) and MMP9.----- Conclusions : Upregulation of MMP9 indicates involvement of ECM degradation during cancer invasion and bone metastases. Expression of enzymes involved in CaP progression, PSA, which is not expressed in osteoblasts, demonstrates that crosstalk between PCCs and osteoblasts may play a part in the aggressiveness of CaP. The presence of steroidogenic enzymes, particularly, RDH5, in osteoblasts and stimulated expression in co-culture, may indicate osteoblast production of potent androgens, fuelling cancer cell proliferation. Based on these results, this practical 3D culture system may provide greater understanding into CaP mediated bone metastasis. This allows the role of the CaP/hOB interaction with regards to invasive property and steroidogenesis to be further explored.

Demonstration of Software Agents Prototype System : [AIMM] Agents for Improving Maintenance Management

This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. • Refining the development of a multi agent system for data mining in virtual environments (Active Worlds) by developing and implementing a filtering agent on the results obtained from applying data mining techniques on the maintenance data. • Integrating the filtering agent within the multi agents system in an interactive networked multi-user 3D virtual environment. • Populating maintenance data and discovering new rules of knowledge.

Model Based Estimating System for Civil Concrete Structures

An earlier CRC-CI project on ‘automatic estimating’ (AE) has shown the key benefit of model-based design methodologies in building design and construction to be the provision of timely quantitative cost evaluations. Furthermore, using AE during design improves design options, and results in improved design turn-around times, better design quality and/or lower costs. However, AEs for civil engineering structures do not exist; and research partners in the CRC-CI expressed interest in exploring the development of such a process. This document reports on these investigations. The central objective of the study was to evaluate the benefits and costs of developing an AE for concrete civil engineering works. By studying existing documents and through interviews with design engineers, contractors and estimators, we have established that current civil engineering practices (mainly roads/bridges) do not use model-based planning/design. Drawings are executed in 2D and only completed at the end of lengthy planning/design project management lifecycle stages. We have also determined that estimating plays two important, but different roles. The first is part of project management (which we have called macro level estimating). Estimating in this domain sets project budgets, controls quality delivery and contains costs. The second role is estimating during planning/design (micro level estimating). The difference between the two roles is that the former is performed at the end of various lifecycle stages, whereas the latter is performed at any suitable time during planning/design.

The knowledge advantage (K-Adv): unleashing creativity and innovation

The K-Adv has been developed around the concept that it comprises an ICT enabling infrastructure that encompasses ICT hardware and software infrastructure facilities together with an enabling ICT support system; a leadership infrastructure support system that provides the vision for its implementation and the realisation capacity for the vision to be realised; and the necessary people infrastructure that includes the people capabilities and capacities supported by organisational processes that facilitates this resource to be mobilised.

Brite innovation survey : executive summary

This report summarises the fi ndings of an innovation survey of the Australian construction industry undertaken by the BRITE Project of the CRC for Construction Innovation in 2004. The BRITE Innovation Survey can be viewed in full at www.brite.crcci.info.The objective of the BRITE project is to improve the incidence and quality of innovation in the Australian construction industry. Many stakeholders in the industry are sceptical about the potential for innovation and its likely benefi ts. Many also lack the linkages and capabilities required for successful innovation. The BRITE Project is redressing this situation through demonstration and benchmarking activities. The term ‘innovation’ is defi ned as a new or signifi cantly improved technology or advanced business practice. Innovation may be technological or organisational, and it may be new to the world, or just new to the industry or business concerned. The defi nition includes the adoption of existing advancements developed outside a particular business. The survey sample was drawn from 3,500 businesses in the road/bridge and commercial building sectors in New South Wales, Victoria and Queensland, covering main contractors, trade contractors, consultants, suppliers and clients. Onethird of this population was sampled and a response rate of almost 30% was achieved. The survey collected information about respondents’ perceptions of innovation determinants in the industry, comprising various aspects of business strategy and business environment.

Influences on construction innovation : a brief overview of recent literature

This report reviews the most recent literature on construction innovation with the aim of highlighting the primary influences on innovation in the building and construction industry.

Final Report : learning system for life prediction of infrastructure

The project has further developed two programs for the industry partners related to service life prediction and salt deposition. The program for Queensland Department of Main Roads which predicts salt deposition on different bridge structures at any point in Queensland has been further refined by looking at more variables. It was found that the height of the bridge significantly affects the salt deposition levels only when very close to the coast. However the effect of natural cleaning of salt by rainfall was incorporated into the program. The user interface allows selection of a location in Queensland, followed by a bridge component. The program then predicts the annual salt deposition rate and rates the likely severity of the environment. The service life prediction program for the Queensland Department of Public Works has been expanded to include 10 common building components, in a variety of environments. Data mining procedures have been used to develop the program and increase the usefulness of the application. A Query Based Learning System (QBLS) has been developed which is based on a data-centric model with extensions to provide support for user interaction. The program is based on number of sources of information about the service life of building components. These include the Delphi survey, the CSIRO Holistic model and a school survey. During the project, the Holistic model was modified for each building component and databases generated for the locations of all Queensland schools. Experiments were carried out to verify and provide parameters for the modelling. These included instrumentation of a downpipe, measurements on pH and chloride levels in leaf litter, EIS measurements and chromate leaching from Colorbond materials and dose tests to measure corrosion rates of new materials. A further database was also generated for inclusion in the program through a large school survey. Over 30 schools in a range of environments from tropical coastal to temperate inland were visited and the condition of the building components rated on a scale of 0-5. The data was analysed and used to calculate an average service life for each component/material combination in the environments, where sufficient examples were available.

The user query based learning system for lifetime prediction of metallic components

Real-World Data Mining Applications generally do not end up with the creation of the models. The use of the model is the final purpose especially in prediction tasks. The problem arises when the model is built based on much more information than that the user can provide in using the model. As a result, the performance of model reduces drastically due to many missing attributes values. This paper develops a new learning system framework, called as User Query Based Learning System (UQBLS), for building data mining models best suitable for users use. We demonstrate its deployment in a real-world application of the lifetime prediction of metallic components in buildings

A user driven data mining process model and learning system

This paper deals with the problem of using the data mining models in a real-world situation where the user can not provide all the inputs with which the predictive model is built. A learning system framework, Query Based Learning System (QBLS), is developed for improving the performance of the predictive models in practice where not all inputs are available for querying to the system. The automatic feature selection algorithm called Query Based Feature Selection (QBFS) is developed for selecting features to obtain a balance between the relative minimum subset of features and the relative maximum classification accuracy. Performance of the QBLS system and the QBFS algorithm is successfully demonstrated with a real-world application

HVAC system size – getting it right

There is evidence that many heating, ventilating & air conditioning (HVAC) systems, installed in larger buildings, have more capacity than is ever required to keep the occupants comfortable. This paper explores the reasons why this can occur, by examining a typical brief/design/documentation process. Over-sized HVAC systems cost more to install and operate and may not be able to control thermal comfort as well as a “right-sized” system. These impacts are evaluated, where data exists. Finally, some suggestions are developed to minimise both the extent of, and the negative impacts of, HVAC system over-sizing, for example: • Challenge “rules of thumb” and/or brief requirements which may be out of date. • Conduct an accurate load estimate, using AIRAH design data, specific to project location, and then resist the temptation to apply “safety factors • Use a load estimation program that accounts for thermal storage and diversification of peak loads for each zone and air handling system. • Select chiller sizes and staged or variable speed pumps and fans to ensure good part load performance. • Allow for unknown future tenancies by designing flexibility into the system, not by over-sizing. For example, generous sizing of distribution pipework and ductwork will allow available capacity to be redistributed. • Provide an auxiliary tenant condenser water loop to handle high load areas. • Consider using an Integrated Design Process, build an integrated load and energy use simulation model and test different operational scenarios • Use comprehensive Life Cycle Cost analysis for selection of the most optimal design solutions. This paper is an interim report on the findings of CRC-CI project 2002-051-B, Right-Sizing HVAC Systems, which is due for completion in January 2006.

Fusion of in-vehicle sensor data to develop Intelligent Driver Training System (IDTS)

The over represented number of novice drivers involved in crashes is alarming. Driver training is one of the interventions aimed at mitigating the number of crashes that involve young drivers. To our knowledge, Advanced Driver Assistance Systems (ADAS) have never been comprehensively used in designing an intelligent driver training system. Currently, there is a need to develop and evaluate ADAS that could assess driving competencies. The aim is to develop an unsupervised system called Intelligent Driver Training System (IDTS) that analyzes crash risks in a given driving situation. In order to design a comprehensive IDTS, data is collected from the Driver, Vehicle and Environment (DVE), synchronized and analyzed. The first implementation phase of this intelligent driver training system deals with synchronizing multiple variables acquired from DVE. RTMaps is used to collect and synchronize data like GPS, vehicle dynamics and driver head movement. After the data synchronization, maneuvers are segmented out as right turn, left turn and overtake. Each maneuver is composed of several individual tasks that are necessary to be performed in a sequential manner. This paper focuses on turn maneuvers. Some of the tasks required in the analysis of ‘turn’ maneuver are: detect the start and end of the turn, detect the indicator status change, check if the indicator was turned on within a safe distance and check the lane keeping during the turn maneuver. This paper proposes a fusion and analysis of heterogeneous data, mainly involved in driving, to determine the risk factor of particular maneuvers within the drive. It also explains the segmentation and risk analysis of the turn maneuver in a drive.