Effects of surgical joint destabilization on load sharing between ligamentous structures in the thoracic spine : a finite element investigation

Background: In vitro investigations have demonstrated the importance of the ribcage in stabilising the thoracic spine. Surgical alterations of the ribcage may change load-sharing patterns in the thoracic spine. Computer models are used in this study to explore the effect of surgical disruption of the rib-vertebrae connections on ligament load-sharing in the thoracic spine. Methods: A finite element model of a T7-8 motion segment, including the T8 rib, was developed using CT-derived spinal anatomy for the Visible Woman. Both the intact motion segment and the motion segment with four successive stages of destabilization (discectomy and removal of right costovertebral joint, right costotransverse joint and left costovertebral joint) were analysed for a 2000Nmm moment in flexion/extension, lateral bending and axial rotation. Joint rotational moments were compared with existing in vitro data and a detailed investigation of the load sharing between the posterior ligaments carried out. Findings: The simulated motion segment demonstrated acceptable agreement with in vitro data at all stages of destabilization. Under lateral bending and axial rotation, the costovertebral joints were of critical importance in resisting applied moments. In comparison to the intact joint, anterior destabilization increases the total moment contributed by the posterior ligaments. Interpretation: Surgical removal of the costovertebral joints may lead to excessive rotational motion in a spinal joint, increasing the risk of overload and damage to the remaining ligaments. The findings of this study are particularly relevant for surgical procedures involving rib head resection, such as some techniques for scoliosis deformity correction.

Fuzzy methods for analysis of microarrays and networks

Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

On IT governance structures and their effectiveness in collaborative organizational structures

Organizations today engage in various forms of alliances to manage their existing business processes or to diversify into new processes to sustain their competitive positions. Many of today’s alliances use the IT resources as their backbone. The results of these alliances are collaborative organizational structures with little or no ownership stakes between the parties. The emergence of Web 2.0 tools is having a profound effect on the nature and form of these alliance structures. These alliances heavily depend on and make radical use of the IT resources in a collaborative environment. This situation requires a deeper understanding of the governance of these IT resources to ensure the sustainability of the collaborative organizational structures. This study first suggests the types of IT governance structures required for collaborative organizational structures. Semi-structured interviews with senior executives who operate in such alliances reveal that co-created IT governance structures are necessary. Such structures include co-created IT-steering committees, co-created operational committees, and inter-organizational performance management and communication systems. The findings paved the way for the development of a model for understanding approaches to governing IT and evaluating the effectiveness for such governance mechanisms in today’s IT dependent alliances. This study presents a sustainable IT-related capabilities approach to assessing the effectiveness of suggested IT governance structures for collaborative alliances. The findings indicate a favourable association between organizations IT governance efforts and their ability to sustain their capabilities to leverage their IT resources. These IT-related capabilities also relate to measures business value at the process and firm level. This makes it possible to infer that collaborative organizations’ IT governance efforts contribute to business value.

US Federal Government entrepreneurship : new enterprise structures

Purpose: The purpose of this paper is to guide the formation and to determine the structure of new governmental entrepreneurial ventures based on the nature of the public goods and the need for an entrepreneurial orientation. Design/methodology/research: This paper is conceptual and is based on reviews of appropriate organizational structure and entrepreneurship, cases studies, and the authors' experiences. Findings: Public or quasi-public entities may need to change their organizational structure in order to act more entrepreneurially and to be more effective in accomplishing their missions. Propositions are raised to guide the development of new public or private enterprises and provide the basis for future research. Research limitations/implications: This paper is conceptual and needs to be tested empirically. Though other levels of government and countries were included, a major focus is on the US federal government. Originality/value: This is the first published research on the topic of new enterprise government structures based on the nature of the goods and the requisite entrepreneurial orientation. It will help governmental and quasi-governmental organizations in developing efficient and effective organizational structures.

IT governance in collaborative organizational structures

Organizations today engage in various forms of alliances to manage their existing business processes or to diversify into new processes to sustain their competitive positions. Many of today’s alliances use the IT resources as their backbone. The results of these alliances are collaborative organizational structures with little or no ownership stakes between the parties. The emergence of Web 2.0 tools is having a profound effect on the nature and form of these alliance structures. These alliances heavily depend on and make radical use of the IT resources in a collaborative environment. This situation requires a deeper understanding of the governance of these IT resources to ensure the sustainability of the collaborative organizational structures. This study reports on the first stage of this initiative. It suggest the types of IT governance structures required for collaborative organizational structures. Semi-structured interviews with senior executives who operate in such alliances reveal that co-created IT governance structures are necessary. Such structures include co-created IT-steering committees, cocreated operational committees, and inter-organizational performance management and communication systems. The findings pave the way for the development of a model for understanding approaches to governing IT and evaluating the effectiveness for such governance mechanisms in today’s IT dependent alliances.

VAMP3 regulates podosome organisation in macrophages and together with Stx4/SNAP23 mediates adhesion, cell spreading and persistent migration

The ability of cells to adhere, spread and migrate is essential to many physiological processes, particularly in the immune system where cells must traffic to sites of inflammation and injury. By altering the levels of individual components of the VAMP3/Stx4/SNAP23 complex we show here that this SNARE complex regulates efficient macrophage adhesion, spreading and migration on fibronectin. During cell spreading this complex mediates the polarised exocytosis of VAMP3- positive recycling endosome membrane into areas of membrane expansion, where VAMP3's surface partner Q-SNARE complex Stx4/SNAP23 was found to accumulate. Lowering the levels of VAMP3 in spreading cells resulted in a more rounded cell morphology and most cells were found to be devoid of the typical ring-like podosome superstructures seen normally in spreading cells. In migrating cells lowering VAMP3 levels disrupted the polarised localisation of podosome clusters. The reduced trafficking of recycling endosome membrane to sites of cell spreading and the disorganised podosome localisation in migrating macrophages greatly reduced their ability to persistently migrate on fibronectin. Thus, this important SNARE complex facilitates macrophage adhesion, spreading, and persistent macrophage migration on fibronectin through the delivery of VAMP3-positive membrane with its cargo to expand the plasma membrane and to participate in organising adhesive podosome structures.

The FAM deubiquitylating enzyme localizes to multiple points of protein trafficking in epithelia, where it associates with E-cadherin and β-catenin

Ubiquitylation is a necessary step in the endocytosis and lysosomal trafficking of many plasma membrane proteins and can also influence protein trafficking in the biosynthetic pathway. Although a molecular understanding of ubiquitylation in these processes is beginning to emerge, very little is known about the role deubiquitylation may play. Fat Facets in mouse (FAM) is substrate-specific deubiquitylating enzyme highly expressed in epithelia where it interacts with its substrate, β-catenin. Here we show, in the polarized intestinal epithelial cell line T84, FAM localized to multiple points of protein trafficking. FAM interacted with β-catenin and E-cadherin in T84 cells but only in subconfluent cultures. FAM extensively colocalized with β-catenin in cytoplasmic puncta but not at sites of cell-cell contact as well as immunoprecipitating with β-catenin and E-cadherin from a higher molecular weight complex (~500 kDa). At confluence FAM neither colocalized with, nor immunoprecipitated, β-catenin or E-cadherin, which were predominantly in a larger molecular weight complex (~2 MDa) at the cell surface. Overexpression of FAM in MCF-7 epithelial cells resulted in increased β-catenin levels, which localized to the plasma membrane. Expression of E-cadherin in L-cell fibroblasts resulted in the relocalization of FAM from the Golgi to cytoplasmic puncta. These data strongly suggest that FAM associates with E-cadherin and β-catenin during trafficking to the plasma membrane.

Tinamous and moa flock together : mitochondrial genome sequence analysis reveals independent losses of flight among ratites

Ratites are large, flightless birds and include the ostrich, rheas, kiwi, emu, and cassowaries, along with extinct members, such as moa and elephant birds. Previous phylogenetic analyses of complete mitochondrial genome sequences have reinforced the traditional belief that ratites are monophyletic and tinamous are their sister group. However, in these studies ratite monophyly was enforced in the analyses that modeled rate heterogeneity among variable sites. Relaxing this topological constraint results in strong support for the tinamous (which fly) nesting within ratites. Furthermore, upon reducing base compositional bias and partitioning models of sequence evolution among protein codon positions and RNA structures, the tinamou–moa clade grouped with kiwi, emu, and cassowaries to the exclusion of the successively more divergent rheas and ostrich. These relationships are consistent with recent results from a large nuclear data set, whereas our strongly supported finding of a tinamou–moa grouping further resolves palaeognath phylogeny. We infer flight to have been lost among ratites multiple times in temporally close association with the Cretaceous–Tertiary extinction event. This circumvents requirements for transient microcontinents and island chains to explain discordance between ratite phylogeny and patterns of continental breakup. Ostriches may have dispersed to Africa from Eurasia, putting in question the status of ratites as an iconic Gondwanan relict taxon. [Base composition; flightless; Gondwana; mitochondrial genome; Palaeognathae; phylogeny; ratites.]

Collaborative organisational structures : implications for the accounting profession

The IT systems drive the financial reporting processes in modern business environments. The result is an integrative system of initialing, authorizing, recording, and processing of financial transactions. This IT-related change inextricably links to the overall financial reporting process, requiring a deeper level of understanding and commitment. Firm’s IT governance initiatives provide this commitment by enforcing controls to IT components to ensure compliance to overall financial reporting requirements. The IT governance institute (ITGI) and other authorities have developed a number of frameworks and guidelines (e.g., COBIT) to help management in managing IT-intensive processes.

Performance characteristics of compound curved sandwich shell structures

Sandwich shells have recently emerged as aesthetically pleasing, efficient and economical structural systems, with a number of applications. They combine the advantages of sandwich layer technology together with those of shell action. With different materials and thicknesses used in the sandwich layers, their performance characteristics largely remain un-quantified and there are no guidelines at present for their design. This research paper provides verification, through finite element modeling and testing, for the application of this technology to dome styled dwellings with research currently being conducted into the further application to roofing and floor structures.

Cellular settings mediating Src Substrate switching between Focal Adhesion Kinase Tyrosine 861 and CUB-domain-containing protein 1 (CDCP1) Tyrosine 734

Reciprocal interactions between Src family kinases (SFKs) and focal adhesion kinase (FAK) are critical during changes in cell attachment. Recently it has been recognized that another SFK substrate, CUB-domain-containing protein 1 (CDCP1), is differentially phosphorylated during these events. However, the molecular processes underlying SFK-mediated phosphorylation of CDCP1 are poorly understood. Here we identify a novel mechanism in which FAK tyrosine 861 and CDCP1-Tyr-734 compete as SFK substrates and demonstrate cellular settings in which SFKs switch between these sites. Our results show that stable CDCP1 expression induces robust SFK-mediated phosphorylation of CDCP1-Tyr-734 with concomitant loss of p-FAK-Tyr-861 in adherent HeLa cells. SFK substrate switching in these cells is dependent on the level of expression of CDCP1 and is also dependent on CDCP1-Tyr-734 but is independent of CDCP1-Tyr-743 and -Tyr-762. In HeLa CDCP1 cells, engagement of SFKs with CDCP1 is accompanied by an increase in phosphorylation of Src-Tyr-416 and a change in cell morphology to a fibroblastic appearance dependent on CDCP1-Tyr-734. SFK switching between FAK-Tyr-861 and CDCP1-Tyr-734 also occurs during changes in adhesion of colorectal cancer cell lines endogenously expressing these two proteins. Consistently, increased p-FAK-Tyr-861 levels and a more epithelial morphology are seen in colon cancer SW480 cells silenced for CDCP1. Unlike protein kinase Cδ, FAK does not appear to form a trimeric complex with Src and CDCP1. These data demonstrate novel aspects of the dynamics of SFK-mediated cell signaling that may be relevant during cancer progression.

The Impact of gender identity-conscious HR structures on performance : mediating effects of gender diversity

Gender identity-conscious HR structures signal an organization’s perspective on gender diversity. The signal produces perceptions that the organization values gender diversity leading to a gender diverse workforce. In turn, a gender diverse workforce provides a firm with a competitive advantage which should result in higher performance. This paper tests the mediating effects of gender diversity (at non-management and management levels) in the relationship between gender identity-conscious HR structures and performance. The findings indicate that non-management gender diversity partially mediates the relationship between HR structures and productivity, and management gender diversity partially mediates the relationship between HR structures and perceived market performance.