Managing Research Data: Mechanical testing and modelling of bone-implant constructs

Presentation by Dr Caroline Grant, Science & Engineering Faculty, IHBI, at Managing your research data seminar, 2012

Managing Research Data at QUT

Presentation by Paula Callan, eResearch Access Coordinator, at Managing your research data seminar, 2012

Research Data Management Update on National Programs: New infrastructure and opportunities

Presentation by Dr Joe Young, ITS-HPC and Research Support, Managing your research data seminar, 2012

The importance of accurate beam data measurement for SRT/SRS treatment planning

Introduction This study investigated the sensitivity of calculated stereotactic radiotherapy and radiosurgery doses to the accuracy of the beam data used by the treatment planning system. Methods Two sets of field output factors were acquired using fields smaller than approximately 1 cm2, for inclusion in beam data used by the iPlan treatment planning system (Brainlab, Feldkirchen, Germany). One set of output factors were measured using an Exradin A16 ion chamber (Standard Imaging, Middleton, USA). Although this chamber has a relatively small collecting volume (0.007 cm3), measurements made in small fields using this chamber are subject to the effects of volume averaging, electronic disequilibrium and chamber perturbations. The second, more accurate, set of measurements were obtained by applying perturbation correction factors, calculated using Monte Carlo simulations according to a method recommended by Cranmer-Sargison et al. [1] to measurements made using a 60017 unshielded electron diode (PTW, Freiburg, Germany). A series of 12 sample patient treatments were used to investigate the effects of beam data accuracy on resulting planned dose. These treatments, which involved 135 fields, were planned for delivery via static conformal arcs and 3DCRT techniques, to targets ranging from prostates (up to 8 cm across) to meningiomas (usually more than 2 cm across) to arterioveinous malformations, acoustic neuromas and brain metastases (often less than 2 cm across). Isocentre doses were calculated for all of these fields using iPlan, and the results of using the two different sets of beam data were evaluated. Results While the isocentre doses for many fields are identical (difference = 0.0 %), there is a general trend for the doses calculated using the data obtained from corrected diode measurements to exceed the doses calculated using the less-accurate Exradin ion chamber measurements (difference\0.0 %). There are several alarming outliers (circled in the Fig. 1) where doses differ by more than 3 %, in beams from sample treatments planned for volumes up to 2 cm across. Discussion and conclusions These results demonstrate that treatment planning dose calculations for SRT/SRS treatments can be substantially affected when beam data for fields smaller than approximately 1 cm2 are measured inaccurately, even when treatment volumes are up to 2 cm across.

CTCombine : rotating and combining CT data with an accurate detector model to simulate radiotherapy portal imaging at non-zero beam angles

Established Monte Carlo user codes BEAMnrc and DOSXYZnrc permit the accurate and straightforward simulation of radiotherapy experiments and treatments delivered from multiple beam angles. However, when an electronic portal imaging detector (EPID) is included in these simulations, treatment delivery from non-zero beam angles becomes problematic. This study introduces CTCombine, a purpose-built code for rotating selected CT data volumes, converting CT numbers to mass densities, combining the results with model EPIDs and writing output in a form which can easily be read and used by the dose calculation code DOSXYZnrc...

The big data lottery

Big data is certainly the buzz term in executive networking circles at the moment. Heralded by management consultancies and research organisations alike as the next big thing in business efficiency, it is shooting up the Gartner hype cycle to the giddy heights of the peak of inflated expectations before it tumbles down in to the trough of disillusionment

Accelerometer data reduction : a comparison of four reduction algorithms on select outcome variables

Purpose Accelerometers are recognized as a valid and objective tool to assess free-living physical activity. Despite the widespread use of accelerometers, there is no standardized way to process and summarize data from them, which limits our ability to compare results across studies. This paper a) reviews decision rules researchers have used in the past, b) compares the impact of using different decision rules on a common data set, and c) identifies issues to consider for accelerometer data reduction. Methods The methods sections of studies published in 2003 and 2004 were reviewed to determine what decision rules previous researchers have used to identify wearing period, minimal wear requirement for a valid day, spurious data, number of days used to calculate the outcome variables, and extract bouts of moderate to vigorous physical activity (MVPA). For this study, four data reduction algorithms that employ different decision rules were used to analyze the same data set. Results The review showed that among studies that reported their decision rules, much variability was observed. Overall, the analyses suggested that using different algorithms impacted several important outcome variables. The most stringent algorithm yielded significantly lower wearing time, the lowest activity counts per minute and counts per day, and fewer minutes of MVPA per day. An exploratory sensitivity analysis revealed that the most stringent inclusion criterion had an impact on sample size and wearing time, which in turn affected many outcome variables. Conclusions These findings suggest that the decision rules employed to process accelerometer data have a significant impact on important outcome variables. Until guidelines are developed, it will remain difficult to compare findings across studies

Physical activity recognition from accelerometer data using a multi-scale ensemble method

Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.

Comparison of 3 accelerometer data reduction approaches, step counts, and 2 self-report measures for estimating physical activity in free-living adults

Background Accelerometers have become one of the most common methods of measuring physical activity (PA). Thus, validity of accelerometer data reduction approaches remains an important research area. Yet, few studies directly compare data reduction approaches and other PA measures in free-living samples. Objective To compare PA estimates provided by 3 accelerometer data reduction approaches, steps, and 2 self-reported estimates: Crouter's 2-regression model, Crouter's refined 2-regression model, the weighted cut-point method adopted in the National Health and Nutrition Examination Survey (NHANES; 2003-2004 and 2005-2006 cycles), steps, IPAQ, and 7-day PA recall. Methods A worksite sample (N = 87) completed online-surveys and wore ActiGraph GT1M accelerometers and pedometers (SW-200) during waking hours for 7 consecutive days. Daily time spent in sedentary, light, moderate, and vigorous intensity activity and percentage of participants meeting PA recommendations were calculated and compared. Results Crouter's 2-regression (161.8 +/- 52.3 minutes/day) and refined 2-regression (137.6 +/- 40.3 minutes/day) models provided significantly higher estimates of moderate and vigorous PA and proportions of those meeting PA recommendations (91% and 92%, respectively) as compared with the NHANES weighted cut-point method (39.5 +/- 20.2 minutes/day, 18%). Differences between other measures were also significant. Conclusions When comparing 3 accelerometer cut-point methods, steps, and self-report measures, estimates of PA participation vary substantially.

Design of a garment for data collection of toddler language and physical activity

Design process phases of development, evaluation and implementation were used to create a garment to simultaneously collect reliable data of speech production and intensity of movement of toddlers (18-36 months). A series of prototypes were developed and evaluated that housed accelerometer-based motion sensors and a digital transmitter with microphone. The approved test garment was a top constructed from loop-faced fabric with interior pockets to house devices. Extended side panels allowed for sizing. In total, 56 toddlers (28 male; 28 female; 16-36 months of age) participated in the study providing pilot and baseline data. The test garment was effective in collecting data as evaluated for accuracy and reliability using ANOVA for accelerometer data, transcription of video for type of movement, and number and length of utterances for speech production. The data collection garment has been implemented in various studies across disciplines.

Hormonal carcinogenesis in breast cancer : cellular and molecular studies of malignant progression

We have established and characterized a series of variant cell lines in which to identify the critical factors associated with E2-induced malignant progression, and the acquisition to tamoxifen resistance in human breast cancer. Sublines of the hormone-dependent MCF-7 cell line (MCF7/MIII and MCF7/LCC1) form stable, invasive, estrogen independent tumors in the mammary fat pads of ovariectomized athymic nude mice. These cells retain expression of both estrogen (ER) and progesterone receptors (PGR), but retain sensitivity to each of the major structural classes of antiestrogens. The tamoxifen-resistant MCF7/LCC2 cells retain sensitivity to the inhibitory effects of the steroidal antiestrogen ICI 182780. By comparing the parental hormone-dependent and variant hormone-independent cells, we have demonstrated an altered expression of some estrogen regulated genes (PGR, pS2, cathepsin D) in the hormone-independent variants. Other genes remain normally estrogen regulated (ER, laminin receptor, EGF-receptor). These data strongly implicate the altered regulation of a specific subset or network of estrogen regulated genes in the malignant progression of human breast cancer. Some of the primary response genes in this network may exhibit dose-response and induction kinetics similar to pS2, which is constitutively upregulated in the MCF7/MIII, MCF7/LCC1 and MCF7/LCC2 cells.

Bluetooth and Wi-Fi MAC address based crowd data collection and monitoring : benefits, challenges and enhancement

This paper firstly presents the benefits and critical challenges on the use of Bluetooth and Wi-Fi for crowd data collection and monitoring. The major challenges include antenna characteristics, environment’s complexity and scanning features. Wi-Fi and Bluetooth are compared in this paper in terms of architecture, discovery time, popularity of use and signal strength. Type of antennas used and the environment’s complexity such as trees for outdoor and partitions for indoor spaces highly affect the scanning range. The aforementioned challenges are empirically evaluated by “real” experiments using Bluetooth and Wi-Fi Scanners. The issues related to the antenna characteristics are also highlighted by experimenting with different antenna types. Novel scanning approaches including Overlapped Zones and Single Point Multi-Range detection methods will be then presented and verified by real-world tests. These novel techniques will be applied for location identification of the MAC IDs captured that can extract more information about people movement dynamics.

Loss of epithelial markers and acquisition of vimentin expression in adriamycin- and vinblastine-resistant human breast cancer cell lines

We have previously observed that breast cancer cell lines could exhibit either epithelial or fibroblastic phenotypes as reflected by their morphologies and intermediate filament protein expression (C. L. Sommers, D. Walker-Jones, S. E. Heckford, P. Worland, E. Valverius, R. Clark, M. Stampfer, and E. P. Gelmann, Cancer Res., 49: 4258-4263, 1989). Fibroblastoid, vimentin-expressing breast cancer cell lines are more invasive in vitro and in vivo (E. W. Thompson, S. Paik, N. Brunner, C. L. Sommers, G. Zugmaier, R. Clarke, T. B. Shima, J. Torri, S. Donahue, M. E. Lippman, G. R. Martin, and R. B. Dickson, J. Cell. Physiol., 150: 534-544, 1992). We hypothesized that a breast cancer cell with an epithelial phenotype could undergo a transition to a fibroblastic phenotype, possibly resulting in more invasive capacity. We now show that two Adriamycin-resistant MCF-7 cell lines and a vinblastine-resistant ZR-75-B cell line have undergone such a transition. Adriamycin-resistant MCF-7 cells express vimentin, have diminished keratin 19 expression, have lost cell adhesion molecule uvomorulin expression, and have reduced formation of desmosomes and tight junctions as determined by reduced immunodetection of their components desmoplakins I and II and zonula occludens (ZO)-1. Other MCF-7 cell lines selected for resistance to vinblastine and to Adriamycin and verapamil did not have these characteristics, indicating that drug selection does not invariably cause these phenotypic changes. In addition, to determine if vimentin expression in MCF-7 cells alone could manifest a fibroblastic phenotype, we transfected the full-length human vimentin complementary DNA into MCF-7 cells. Although vimentin expression was achieved in MCF-7 cells, it did not affect the phenotype of the cells in terms of the distribution of keratins, desmoplakins I and II, ZO-1, or uvomorulin or in terms of in vitro invasiveness. We conclude that vimentin expression is a marker for a fibroblastic and invasive phenotype in breast cancer cells but does not by itself give rise to this phenotype.

Matrix metalloproteinase 13-deficient mice are resistant to osteoarthritic cartilage erosion but not chondrocyte hypertrophy or osteophyte development

Objective To investigate the role of matrix metalloproteinase 13 (MMP-13; collagenase 3) in osteoarthritis (OA). Methods OA was surgically induced in the knees of MMP-13-knockout mice and wild-type mice, and mice were compared. Histologic scoring of femoral and tibial cartilage aggrecan loss (0-3 scale), erosion (0-7 scale), and chondrocyte hypertrophy (0-1 scale), as well as osteophyte size (0-3 scale) and maturity (0-3 scale) was performed. Serial sections were stained for type X collagen and the MMP-generated aggrecan neoepitope DIPEN. Results Following surgery, aggrecan loss and cartilage erosion were more severe in the tibia than femur (P < 0.01) and tibial cartilage erosion increased with time (P < 0.05) in wild-type mice. Cartilaginous osteophytes were present at 4 weeks and underwent ossification, with size and maturity increasing by 8 weeks (P < 0.01). There was no difference between genotypes in aggrecan loss or cartilage erosion at 4 weeks. There was less tibial cartilage erosion in knockout mice than in wild-type mice at 8 weeks (P < 0.02). Cartilaginous osteophytes were larger in knockout mice at 4 weeks (P < 0.01), but by 8 weeks osteophyte maturity and size were no different from those in wild-type mice. Articular chondrocyte hypertrophy with positive type X collagen and DIPEN staining occurred in both wild-type and knockout mouse joints. Conclusion Our findings indicate that structural cartilage damage in a mouse model of OA is dependent on MMP-13 activity. Chondrocyte hypertrophy is not regulated by MMP-13 activity in this model and does not in itself lead to cartilage erosion. MMP-13 deficiency can inhibit cartilage erosion in the presence of aggrecan depletion, supporting the potential for therapeutic intervention in established OA with MMP-13 inhibitors.

Hunting and gathering : new imperatives in mapping and collecting student learning data to assure quality outcomes

Assurance of learning (AOL) is a quality enhancement and quality assurance process used in higher education. It involves a process of determining programme learning outcomes and standards, and systematically gathering evidence to measure students' performance on these. The systematic assessment of whole-of-programme outcomes provides a basis for curriculum development and management, continuous improvement, and accreditation. To better understand how AOL processes operate, a national study of university practices across one discipline area, business and management, was undertaken. To solicit data on AOL practice, interviews were undertaken with a sample of business school representatives (n = 25). Two key processes emerged: (1) mapping of graduate attributes and (2) collection of assurance data. External drivers such as professional accreditation and government legislation were the primary reasons for undertaking AOL outcomes but intrinsic motivators in relation to continuous improvement were also evident. The facilitation of academic commitment was achieved through an embedded approach to AOL by the majority of universities in the study. A sustainable and inclusive process of AOL was seen to support wider stakeholder engagement in the development of higher education learning outcomes.