Impact of extracellular matrix derived from osteoarthritis subchondral bone osteoblasts on osteocytes : role of integrinβ1 and focal adhesion kinase signaling cues

INTRODUCTION: Our recent study indicated that subchondral bone pathogenesis in osteoarthritis (OA) is associated with osteocyte morphology and phenotypic abnormalities. However, the mechanism underlying this abnormality needs to be identified. In this study we investigated the effect of extracellular matrix (ECM) produced from normal and OA bone on osteocytic cells function. METHODS: De-cellularized matrices, resembling the bone provisional ECM secreted from primary human subchondral bone osteoblasts (SBOs) of normal and OA patients were used as a model to study the effect on osteocytic cells. Osteocytic cells (MLOY4 osteocyte cell line) cultured on normal and OA derived ECMs were analyzed by confocal microscopy, scanning electron microscopy (SEM), cell attachment assays, zymography, apoptosis assays, qRT-PCR and western blotting. The role of integrinβ1 and focal adhesion kinase (FAK) signaling pathways during these interactions were monitored using appropriate blocking antibodies. RESULTS: The ECM produced by OA SBOs contained less mineral content, showed altered organization of matrix proteins and matrix structure compared with the matrices produced by normal SBOs. Culture of osteocytic cells on these defective OA ECM resulted in a decrease of integrinβ1 expression and the de-activation of FAK cell signaling pathway, which subsequently affected the initial osteocytic cell's attachment and functions including morphological abnormalities of cytoskeletal structures, focal adhesions, increased apoptosis, altered osteocyte specific gene expression and increased Matrix metalloproteinases (MMP-2) and -9 expression. CONCLUSION: This study provides new insights in understanding how altered OA bone matrix can lead to the abnormal osteocyte phenotypic changes, which is typical in OA pathogenesis.

Gifted students with a reading disability : the impact of lived experience

Gifted students who have a reading disability have learning characteristics that set them apart from their peers. The ability to read impacts upon all areas of the formal curriculum in which print-based texts are common. Therefore, the full intellectual development of gifted students with a reading disability can be repressed because their access to learning opportunities is reduced. When the different learning needs caused by concomitant giftedness and reading disability are not met, it can have serious implications for both academic achievement and the social-emotional wellbeing of these students. In order to develop a deeper understanding of this vulnerable group of students, this study investigated the learning characteristics of gifted students with a reading disability. Furthermore, it investigated how the learning characteristics of these students impact upon their lived experiences. Since achievement and motivation have been shown to be closely linked to self-efficacy, self-efficacy theory underpinned the conceptual framework of the study. The study used a descriptive case study approach to document the lived experiences of gifted students with a reading disability. Nine participants aged between 11 and 18, who were formally identified as gifted with a reading disability, took part in the study. Data sources in the case study database included: cognitive assessments, such as WISC assessments, Stanford Binet 5, or the Raven's Standard Progressive Matrices; the WIAT II reading assessment; the Reader Self-Perception Scale; document reviews; parent and teacher checklists designed to gain information about the students' learning characteristics; and semi-structured interviews with students. The study showed that gifted students with a reading disability display a complex profile of learning strengths and weaknesses. As a result, they face a daily struggle of trying to reconcile the confusion of being able to complete some tasks to a high level, while struggling to read. The study sheds light on the myriad of issues faced by the students at school. It revealed that when the particular learning characteristics and needs of gifted students with a reading disability are recognised and met, these students can experience academic success, and avoid the serious social-emotional complications cited in previous studies. Indeed, rather than suffering from depression, disengagement from learning, and demotivation, these students were described as resilient, independent, determined, goal oriented and motivated to learn and persevere. Notably, the students in the study had developed effective coping strategies for dealing with the daily challenges they faced. These strategies are outlined in the thesis together with the advice students offered for helping other gifted students with a reading disability to succeed. Their advice is significant for all teachers who wish to nurture the potential of those students who face the challenge of being gifted with a reading disability, and for the parents of these students. This research advances knowledge pertaining to the theory of self-efficacy, and self-efficacy in reading specifically, by showing that although gifted students with a reading disability have low self-efficacy, the level is not the same for all aspects of reading. Furthermore, despite low self-efficacy in reading these students remained motivated. The study also enhances existing knowledge in the areas of gifted education and special education because it documents the lived experience of gifted students with a specific learning disability in reading from the students' perspectives. Based on a synthesis of the literature and research findings, an Inclusive Pathway Model is proposed that describes a framework to support gifted students with a reading disability so that they might achieve, and remain socially and emotionally well-adjusted. The study highlights the importance of clear identification protocols (such as the use of a range of assessment sources, discussions with students and parents, and an awareness of the characteristics of gifted students with a reading disability) and support mechanisms for assisting students (for example, differentiated reading instruction and the use of assistive technology).

Ergodic capacity and outage performance of amplify-and-forward protocols

This thesis analyses the performance bounds of amplify-and-forward relay channels which are becoming increasingly popular in wireless communication applications. The statistics of cascaded Nakagami-m fading model which is a major obstacle in evaluating the outage of wireless networks is analysed using Mellin transform. Furthermore, the upper and the lower bounds for the ergodic capacity of the slotted amplify-and-forward relay channel, for finite and infinite number of relays are derived using random matrix theory. The results obtained will enable wireless network designers to optimize the network resources, benefiting the consumers.

Advance transit oriented development typology : case study in Brisbane, Australia

Internationally, transit oriented development (TOD) is characterised by moderate to high density development with diverse land use patterns and well connected street networks centred around high frequency transit stops (bus and rail). Although different TOD typologies have been developed in different contexts, they are based on subjective evaluation criteria derived from the context in which they are built and typically lack a validation measure. Arguably there exist sets of TOD characteristics that perform better in certain contexts, and being able to optimise TOD effectiveness would facilitate planning and supporting policy development. This research utilises data from census collection districts (CCDs) in Brisbane with different sets of TOD attributes measured across six objectively quantified built environmental indicators: net employment density, net residential density, land use diversity, intersection density, cul-de-sac density, and public transport accessibility. Using these measures, a Two Step Cluster Analysis was conducted to identify natural groupings of the CCDs with similar profiles, resulting in four unique TOD clusters: (a) residential TODs, (b) activity centre TODs, (c) potential TODs, and; (d) TOD non-suitability. The typologies are validated by estimating a multinomial logistic regression model in order to understand the mode choice behaviour of 10,013 individuals living in these areas. Results indicate that in comparison to people living in areas classified as residential TODs, people who reside in non-TOD clusters were significantly less likely to use public transport (PT) (1.4 times), and active transport (4 times) compared to the car. People living in areas classified as potential TODs were 1.3 times less likely to use PT, and 2.5 times less likely to use active transport compared to using the car. Only a little difference in mode choice behaviour was evident between people living in areas classified as residential TODs and activity centre TODs. The results suggest that: (a) two types of TODs may be suitable for classification and effect mode choice in Brisbane; (b) TOD typology should be developed based on their TOD profile and performance matrices; (c) both bus stop and train station based TODs are suitable for development in Brisbane.

Design, implementation and multisite evaluation of a system suitability protocol for the quantitative assessment of instrument performance in liquid chromatography-multiple reaction monitoring-MS (LC-MRM-MS)

Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities.

C. elegans RNA-dependent RNA polymerases rrf-1 and ego-1 silence Drosophila transgenes by differing mechanisms

Drosophila possesses the core gene silencing machinery but, like all insects, lacks the canonical RNA-dependent RNA polymerases (RdRps) that in C. elegans either trigger or enhance two major small RNA-dependent gene silencing pathways. Introduction of two different nematode RdRps into Drosophila showed them to be functional, resulting in differing silencing activities. While RRF-1 enhanced transitive dsRNA-dependent silencing, EGO-1 triggered dsRNA-independent silencing, specifically of transgenes. The strain w; da-Gal4; UAST-ego-1, constitutively expressing ego-1, is capable of silencing transgene including dsRNA hairpin upon a single cross, which created a powerful tool for research in Drosophila. In C. elegans, EGO-1 is involved in transcriptional gene silencing (TGS) of chromosome regions that are unpaired during meiosis. There was no opportunity for meiotic interactions involving EGO-1 in Drosophila that would explain the observed transgene silencing. Transgene DNA is, however, unpaired during the pairing of chromosomes in embryonic mitosis that is an unusual characteristic of Diptera, suggesting that in Drosophila, EGO-1 triggers transcriptional silencing of unpaired DNA during embryonic mitosis. © 2012 Springer Basel.

A methodology for effective implementation of lean strategies and its performance evaluation in manufacturing organizations

Purpose – The purpose of this paper is to develop an effective methodology for implementing lean manufacturing strategies and a leanness evaluation metric using continuous performance measurement (CPM). Design/methodology/approach – Based on five lean principles, a systematic lean implementation methodology for manufacturing organizations has been proposed. A simplified leanness evaluation metric consisting of both efficiency and effectiveness attributes of manufacturing performance has been developed for continuous evaluation of lean implementation. A case study to validate the proposed methodology has been conducted and proposed CPM metric has been used to assess the manufacturing leanness. Findings – Proposed methodology is able to systematically identify manufacturing wastes, select appropriate lean tools, identify relevant performance indicators, achieve significant performance improvement and establish lean culture in the organization. Continuous performance measurement matrices in terms of efficiency and effectiveness are proved to be appropriate methods for continuous evaluation of lean performance. Research limitations/implications – Effectiveness of the method developed has been demonstrated by applying it in a real life assembly process. However, more tests/applications will be necessary to generalize the findings. Practical implications – Results show that applying the methods developed, managers can successfully identify and remove manufacturing wastes from their production processes. By improving process efficiency, they can optimize their resource allocations. Manufacturers now have a validated step by step methodology for successfully implementing lean strategies. Originality/value – According to the authors’ best knowledge, this is the first known study that proposed a systematic lean implementation methodology based on lean principles and continuous improvement techniques. Evaluation of performance improvement by lean strategies is a critical issue. This study develops a simplified leanness evaluation metric considering both efficiency and effectiveness attributes and integrates it with the lean implementation methodology.

Local stress-strain distribution and load transfer across cartilage matrix at micro-scale using combined microscopy-based finite element method

Articular cartilage is the load-bearing tissue that consists of proteoglycan macromolecules entrapped between collagen fibrils in a three-dimensional architecture. To date, the drudgery of searching for mathematical models to represent the biomechanics of such a system continues without providing a fitting description of its functional response to load at micro-scale level. We believe that the major complication arose when cartilage was first envisaged as a multiphasic model with distinguishable components and that quantifying those and searching for the laws that govern their interaction is inadequate. To the thesis of this paper, cartilage as a bulk is as much continuum as is the response of its components to the external stimuli. For this reason, we framed the fundamental question as to what would be the mechano-structural functionality of such a system in the total absence of one of its key constituents-proteoglycans. To answer this, hydrated normal and proteoglycan depleted samples were tested under confined compression while finite element models were reproduced, for the first time, based on the structural microarchitecture of the cross-sectional profile of the matrices. These micro-porous in silico models served as virtual transducers to produce an internal noninvasive probing mechanism beyond experimental capabilities to render the matrices micromechanics and several others properties like permeability, orientation etc. The results demonstrated that load transfer was closely related to the microarchitecture of the hyperelastic models that represent solid skeleton stress and fluid response based on the state of the collagen network with and without the swollen proteoglycans. In other words, the stress gradient during deformation was a function of the structural pattern of the network and acted in concert with the position-dependent compositional state of the matrix. This reveals that the interaction between indistinguishable components in real cartilage is superimposed by its microarchitectural state which directly influences macromechanical behavior.

Delineating breast cancer cell interactions with engineered bone microenvironments

The mechanisms leading to colonization of metastatic breast cancer cells (BCa) in the skeleton are still not fully understood. Here, we demonstrate that mineralized extracellular matrices secreted by primary human osteoblasts (hOBM) modulate cellular processes associated with BCa colonization of bone. A panel of four BCa cell lines of different bone-metastatic potential (T47D, SUM1315, MDA-MB-231, and the bone-seeking subline MDA-MB-231BO) was cultured on hOBM. After 3 days, the metastatic BCa cells had undergone morphological changes on hOBM and were aligned along the hOBM's collagen type I fibrils that were decorated with bone-specific proteins. In contrast, nonmetastatic BCa cells showed a random orientation on hOBM. Atomic force microscopy-based single-cell force spectroscopy revealed that the metastatic cell lines adhered more strongly to hOBM compared with nonmetastatic cells. Function-blocking experiments indicated that β1-integrins mediated cell adhesion to hOBM. In addition, metastatic BCa cells migrated directionally and invaded hOBM, which was accompanied by enhanced MMP-2 and -9 secretion. Furthermore, we observed gene expression changes associated with osteomimickry in BCa cultured on hOBM. As such, osteopontin mRNA levels were significantly increased in SUM1315 and MDA-MB-231BO cells in a β1-integrin-dependent manner after growing for 3 days on hOBM compared with tissue culture plastic. In conclusion, our results show that extracellular matrices derived from human osteoblasts represent a powerful experimental platform to dissect mechanisms underlying critical steps in the development of bone metastases.

A bioengineered 3D ovarian cancer model for the assessment of peptidase-mediated enhancement of spheroid growth and intraperitoneal spread

Cancer-associated proteases promote peritoneal dissemination and chemoresistance in malignant progression. In this study, kallikrein-related peptidases 4, 5, 6, and 7 (KLK4-7)-cotransfected OV-MZ-6 ovarian cancer cells were embedded in a bioengineered three-dimensional (3D) microenvironment that contains RGD motifs for integrin engagement to analyze their spheroid growth and survival after chemotreatment. KLK4-7-cotransfected cells formed larger spheroids and proliferated more than controls in 3D, particularly within RGD-functionalized matrices, which was reduced upon integrin inhibition. In contrast, KLK4-7-expressing cell monolayers proliferated less than controls, emphasizing the relevance of the 3D microenvironment and integrin engagement. In a spheroid-based animal model, KLK4-7-overexpression induced tumor growth after 4 weeks and intraperitoneal spread after 8 weeks. Upon paclitaxel administration, KLK4-7-expressing tumors declined in size by 91% (controls: 87%) and showed 90% less metastatic outgrowth (controls: 33%, P<0.001). KLK4-7-expressing spheroids showed 53% survival upon paclitaxel treatment (controls: 51%), accompanied by enhanced chemoresistance-related factors, and their survival was further reduced by combination treatment of paclitaxel with KLK4/5/7 (22%, P=0.007) or MAPK (6%, P=0.006) inhibition. The concomitant presence of KLK4-7 in ovarian cancer cells together with integrin activation drives spheroid formation and proliferation. Combinatorial approaches of paclitaxel and KLK/MAPK inhibition may be more efficient for late-stage disease than chemotherapeutics alone as these inhibitory regimens reduced cancer spheroid growth to a greater extent than paclitaxel alone.

Mechanical stimulation of the pro-angiogenic capacity of human fracture haematoma: Involvement of VEGF mechano-regulation

Compromised angiogenesis appears to be a major limitation in various suboptimal bone healing situations. Appropriate mechanical stimuli support blood vessel formation in vivo and improve healing outcomes. However, the mechanisms responsible for this association are unclear. To address this question, the paracrine angiogenic potential of early human fracture haematoma and its responsiveness to mechanical loading, as well as angiogenic growth factors involved, were investigated in vitro. Human haematomas were collected from healthy patients undergoing surgery within 72. h after bone fracture. The haematomas were embedded in a fibrin matrix, and cultured in a bioreactor resembling the in vivo conditions of the early phase of bone healing (20 compression, 1. Hz) over 3. days. Conditioned medium (CM) from the bioreactor was then analyzed. The matrices were also incubated in fresh medium for a further 24. h to evaluate the persistence of the effects. Growth factor (GF) concentrations were measured in the CM by ELISAs. In vitro tube formation assays were conducted on Matrigel with the HMEC-1 cell line, with or without inhibition of vascular endothelial growth factor receptor 2 (VEGFR2). Cell numbers were quantified using an MTS test. In vitro endothelial tube formation was enhanced by CM from haematomas, compared to fibrin controls. The angiogenesis regulators, vascular endothelial growth factor (VEGF) and transforming growth factor β1 (TGF-β1), were released into the haematoma CM, but not angiopoietins 1 or 2 (Ang1, 2), basic fibroblast growth factor (bFGF) or platelet-derived growth factor (PDGF). Mechanical stimulation of haematomas, but not fibrin controls, further increased the induction of tube formation by their CM. The mechanically stimulated haematoma matrices retained their elevated pro-angiogenic capacity for 24. h. The pro-angiogenic effect was cancelled by inhibition of VEGFR2 signalling. VEGF concentrations in CM tended to be elevated by mechanical stimulation; this was significant in haematomas from younger, but not from older patients. Other GFs were not mechanically regulated. In conclusion, the paracrine pro-angiogenic capacity of early human haematomas is enhanced by mechanical stimulation. This effect lasts even after removing the mechanical stimulus and appears to be VEGFR2-dependent.

Laser-radar data fusion with Gaussian Process Implicit Surfaces

This work considers the problem of building high-fidelity 3D representations of the environment from sensor data acquired by mobile robots. Multi-sensor data fusion allows for more complete and accurate representations, and for more reliable perception, especially when different sensing modalities are used. In this paper, we propose a thorough experimental analysis of the performance of 3D surface reconstruction from laser and mm-wave radar data using Gaussian Process Implicit Surfaces (GPIS), in a realistic field robotics scenario. We first analyse the performance of GPIS using raw laser data alone and raw radar data alone, respectively, with different choices of covariance matrices and different resolutions of the input data. We then evaluate and compare the performance of two different GPIS fusion approaches. The first, state-of-the-art approach directly fuses raw data from laser and radar. The alternative approach proposed in this paper first computes an initial estimate of the surface from each single source of data, and then fuses these two estimates. We show that this method outperforms the state of the art, especially in situations where the sensors react differently to the targets they perceive.

Learning detectors quickly with stationary statistics

Computer vision is increasingly becoming interested in the rapid estimation of object detectors. The canonical strategy of using Hard Negative Mining to train a Support Vector Machine is slow, since the large negative set must be traversed at least once per detector. Recent work has demonstrated that, with an assumption of signal stationarity, Linear Discriminant Analysis is able to learn comparable detectors without ever revisiting the negative set. Even with this insight, the time to learn a detector can still be on the order of minutes. Correlation filters, on the other hand, can produce a detector in under a second. However, this involves the unnatural assumption that the statistics are periodic, and requires the negative set to be re-sampled per detector size. These two methods differ chie y in the structure which they impose on the co- variance matrix of all examples. This paper is a comparative study which develops techniques (i) to assume periodic statistics without needing to revisit the negative set and (ii) to accelerate the estimation of detectors with aperiodic statistics. It is experimentally verified that periodicity is detrimental.

Consensus σ70 promoter prediction using hadoop

MapReduce frameworks such as Hadoop are well suited to handling large sets of data which can be processed separately and independently, with canonical applications in information retrieval and sales record analysis. Rapid advances in sequencing technology have ensured an explosion in the availability of genomic data, with a consequent rise in the importance of large scale comparative genomics, often involving operations and data relationships which deviate from the classical Map Reduce structure. This work examines the application of Hadoop to patterns of this nature, using as our focus a wellestablished workflow for identifying promoters - binding sites for regulatory proteins - Across multiple gene regions and organisms, coupled with the unifying step of assembling these results into a consensus sequence. Our approach demonstrates the utility of Hadoop for problems of this nature, showing how the tyranny of the "dominant decomposition" can be at least partially overcome. It also demonstrates how load balance and the granularity of parallelism can be optimized by pre-processing that splits and reorganizes input files, allowing a wide range of related problems to be brought under the same computational umbrella.

Observability analysis of electric networks considering branch impedance

This paper presents an analytical method to analyze the effect of X to R ratio as well as impedance value of branches on observability of a network based on un-decoupled formulation of state estimation (SE) and null space of matrices. The results showed that the X to R ratio of branches had no effect on the observability of networks. In addition, it was shown that observability of some networks was affected by impedance values while some others were not affected. In addition, for branch observability analysis of radial network, a simple and quick method is developed. Illustrative examples of the network under transmission and distribution voltages demonstrate the effectiveness of the proposed methods.