The binding of nuclear factors to the as-1 element in the CaMV 35S promoter is affected by cytosine methylation in vitro

Transcriptional gene silencing (TCS) is often associated with an increased level of cytosine methylation in the affected promoters. The effect of methylation of the cauliflower mosaic virus (CaMV) 35S promoter sequence on its binding to factors present in the nuclei was analyzed by electrophoretic mobility shift assays using extracts of petunia flowers. Specific DNA-protein interactions were detected in the region of the CaMV 35S promoter that contains the as-1 element and the region between -345 and -208. The binding of protein factor(s) to the as-1 element was influenced by cytosine methylation, whereas the binding to the region between -345 and -208 was unaffected. The results suggest that cytosine methylation of the as-1 element potentially affects the activity of the CaMV 35S promoter. © Georg Thieme Verlag KG Stuttgart.

The construction of social identity in newly recruited nuclear engineering staff : a longitudinal study

This study examines the process by which newly recruited nuclear engineering and technical staff came to understand, define, think, feel and behave within a distinct group that has a direct contribution to the organization's overall emphasis on a culture of reliability and system safety. In the field of organizational behavior the interactive model of social identity formation has been recently proposed to explain the process by which the internalization of shared norms and values occurs, an element critical in identity formation. Using this rich model of organizational behavior we analyzed multiple sources of data from nine new hires over a period of three years. This was done from the time they were employed to investigate the construction of social identity by new entrants entering into a complex organizational setting reflected in the context of a nuclear facility. Informed by our data analyses, we found support for the interactive model of social identity development and report the unexpected finding that a newly appointed member's age and level of experience appears to influence the manner in which they adapt, and assimilate into their surroundings. This study represents an important contribution to the safety and reliability literature as it provides a rich insight into the way newly recruited employees enact the process by which their identities are formed and hence act, particularly under conditions of duress or significant organizational disruption in complex organizational settings.

The orphan nuclear receptor LRH-1 promotes breast cancer motility and invasion

The orphan nuclear receptor liver receptor homologue-1 (LRH-1) has roles in the development, cholesterol and bile acid homeostasis, and steroidogenesis. It also enhances proliferation and cell cycle progression of cancer cells. In breast cancer, LRH-1 expression is associated with invasive breast cancer; positively correlates with ERα status and aromatase activity; and promotes oestrogen-dependent cell proliferation. However, the mechanism of action of LRH-1 in breast cancer epithelial cells is still not clear. By silencing or over-expressing LRH-1 in ER-positive MCF-7 and ER-negative MDA-MB-231 breast cancer cells, we have demonstrated that LRH-1 promotes motility and cell invasiveness. Similar effects were observed in the non-tumourigenic mammary epithelial cell line, MCF-10A. Remodelling of the actin cytoskeleton and E-cadherin cleavage was observed with LRH-1 over-expression, contributing to increased migratory and invasive properties. Additionally, in LRH-1 over-expressing cells, the truncation of the 120 kDa E-cadherin to the inactive 97 kDa form was observed. These post-translational modifications in E-cadherin may be associated with LRH-1-dependent changes to matrix metalloproteinase 9 expression. These findings suggest a new role of LRH-1 in promoting migration and invasion in breast cancer, independent of oestrogen sensitivity. Therefore, LRH-1 may represent a new target for breast cancer therapeutics.

Biological performance of a polycaprolactone-based scaffold plus recombinant human morphogenetic protein-2 (rhBMP-2) in an ovine thoracic interbody fusion model

PURPOSE. We develop a sheep thoracic spine interbody fusion model to study the suitability of polycaprolactone-based scaffold and recombinant human bone morphogenetic protein-2 (rhBMP-2) as a bone graft substitute within the thoracic spine. The surgical approach is a mini- open thoracotomy with relevance to minimally invasive deformity correction surgery for adolescent idiopathic scoliosis. To date there are no studies examining the use of this biodegradable implant in combination with biologics in a sheep thoracic spine model. METHODS. In the present study, six sheep underwent a 3-level (T6/7, T8/9 and T10/11) discectomy with randomly allocated implantation of a different graft substitute at each of the three levels; (i) calcium phosphate (CaP) coated polycaprolactone-based scaffold plus 0.54μg rhBMP-2, (ii) CaP coated PCL- based scaffold alone or (iii) autograft (mulched rib head). Fusion was assessed at six months post-surgery. RESULTS. Computed Tomographic scanning demonstrated higher fusion grades in the rhBMP-2 plus PCL- based scaffold group in comparison to either PCL-based scaffold alone or autograft. These results were supported by histological evaluations of the respective groups. Biomechanical testing revealed significantly higher stiffness for the rhBMP-2 plus PCL- based scaffold group in all loading directions in comparison to the other two groups. CONCLUSION. The results of this study demonstrate that rhBMP-2 plus PCL- based scaffold is a viable bone graft substitute, providing an optimal environment for thoracic interbody spinal fusion in a large animal model.

6 versus 12 month performance of polycaprolactone-based scaffold plus recombinant human morphogenetic protein-2 (rhBMP-2) in an ovine thoracic interbody fusion model

Introduction Well-designed biodegradable scaffolds in combination with bone growth factors offer a valuable alternative to the current gold standard autograft in spinal fusion surgery Yong et al. (2013). Here we report on 6- vs 12- month data set evaluating the longitudinal performance of a CaP coated polycaprolactone (PCL) scaffold loaded with recombinant human bone morphogenetic protein-2 (rhBMP-2) as a bone graft substitute within a large preclinical animal model. Methods Twelve sheep underwent a 3-level (T6/7, T8/9 and T10/11) discectomy with randomly allocated implantation of a different graft substitute at each of the three levels; (i) calcium phosphate (CaP) coated polycaprolactone based scaffold plus 0.54µg rhBMP-2, (ii) CaP coated PCL- based scaffold alone or (iii) autograft (mulched rib head). Fusion assessments were performed via high resolution clinical computed tomography and histological evaluation were undertaken at six (n=6) and twelve (n=6) months post-surgery using the Sucato grading system (Sucato et al. 2004). Results The computed tomography fusion grades of the 6- and 12- months in the rhBMP-2 plus PCL- based scaffold group were 1.9 and 2.1 respectively, in the autograft group 1.9 and 1.3 respectively, and in the scaffold alone group 0.9 and 1.17 respectively. There were no statistically significant differences in the fusion scores between 6- and 12- month for the rhBMP plus PCL- based scaffold or PCL – based scaffold alone group however there was a significant reduction in scores in the autograft group. These scores were seen to correlate with histological evaluations of the respective groups. Conclusions The results of this study demonstrate the efficacy of scaffold-based delivery of rhBMP-2 in promoting higher fusion grades at 6- and 12- months in comparison to the scaffold alone or autograft group within the same time frame. Fusion grades achieved at six months using PCL+rhBMP-2 are not significantly increased at twelve months post-surgery.

Robust multiple-sensing-modality data fusion using Gaussian Process Implicit Surfaces

The ability to build high-fidelity 3D representations of the environment from sensor data is critical for autonomous robots. Multi-sensor data fusion allows for more complete and accurate representations. Furthermore, using distinct sensing modalities (i.e. sensors using a different physical process and/or operating at different electromagnetic frequencies) usually leads to more reliable perception, especially in challenging environments, as modalities may complement each other. However, they may react differently to certain materials or environmental conditions, leading to catastrophic fusion. In this paper, we propose a new method to reliably fuse data from multiple sensing modalities, including in situations where they detect different targets. We first compute distinct continuous surface representations for each sensing modality, with uncertainty, using Gaussian Process Implicit Surfaces (GPIS). Second, we perform a local consistency test between these representations, to separate consistent data (i.e. data corresponding to the detection of the same target by the sensors) from inconsistent data. The consistent data can then be fused together, using another GPIS process, and the rest of the data can be combined as appropriate. The approach is first validated using synthetic data. We then demonstrate its benefit using a mobile robot, equipped with a laser scanner and a radar, which operates in an outdoor environment in the presence of large clouds of airborne dust and smoke.

Managing identity transitions during radical change in nuclear engineering organizations

This study reports the construction and reconstruction of identities of new and existing employees during a significant transition phase of a nuclear engineering organization. We followed a group of new and existing employees over the period of three years, during which the organization constructed a greenfield nuclear facility with new generational technologies whilst in parallel, decommissioned the older reactor. This change led to the transfer and integration of existing trade-based employees with the newly recruited, primarily university educated graduates in the new site. Three waves of interview data were collected, in conjunction with the cognitive mapping of social grouping and photo elicitation portrayed the stories of different group of employees who either succeeded or failed at embracing their new professional identity. In contrast with the new recruits who constructed new identities as they join this organization, we identify and report on the number of enabling and disabling factors that influence the process of professional identity construction and reconstruction during gamma change.

Data fusion and tracking with multiple UAVs

This chapter describes decentralized data fusion algorithms for a team of multiple autonomous platforms. Decentralized data fusion (DDF) provides a useful basis with which to build upon for cooperative information gathering tasks for robotic teams operating in outdoor environments. Through the DDF algorithms, each platform can maintain a consistent global solution from which decisions may then be made. Comparisons will be made between the implementation of DDF using two probabilistic representations. The first, Gaussian estimates and the second Gaussian mixtures are compared using a common data set. The overall system design is detailed, providing insight into the overall complexity of implementing a robust DDF system for use in information gathering tasks in outdoor UAV applications.

KRAB zinc-finger proteins localise to novel KAP1-containing foci that are adjacent to PML nuclear bodies

The KRAB-zinc finger proteins (KRAB-ZFPs) represent a very large, but poorly understood, family of transcriptional regulators in mammals. They are thought to repress transcription via their interaction with KRAB-associated protein 1 (KAP1), which then assembles a complex of chromatin modifiers to lay down histone marks that are associated with inactive chromatin. Studies of KRAB-ZFP/KAP1-mediated gene silencing, using reporter constructs and ectopically expressed proteins, have shown colocalisation of both KAP1 and repressed reporter target genes to domains of constitutive heterochromatin in the nucleus. However, we show here that although KAP1 does indeed become recruited to pericentric heterochromatin during differentiation of mouse embryonic stem (ES) cells, endogenous KRAB-ZFPs do not. Rather, KRAB-ZFPs and KAP1 relocalise to novel nucleoplasmic foci that we have termed KRAB- and KAP1-associated (KAKA) foci. HP1s can also concentrate in these foci and there is a close spatial relationship between KAKA nuclear foci and PML nuclear bodies. Finally, we reveal differential requirements for the recruitment of KAP1 to pericentric heterochromatin and KAKA foci, and suggest that KAKA foci may contain sumoylated KAP1 - the form of the protein that is active in transcriptional repression.

Score-level multibiometric fusion based on Dempster-Shafer theory incorporating uncertainty factors

While existing multi-biometic Dempster-Shafer the- ory fusion approaches have demonstrated promising perfor- mance, they do not model the uncertainty appropriately, sug- gesting that further improvement can be achieved. This research seeks to develop a unified framework for multimodal biometric fusion to take advantage of the uncertainty concept of Dempster- Shafer theory, improving the performance of multi-biometric authentication systems. Modeling uncertainty as a function of uncertainty factors affecting the recognition performance of the biometric systems helps to address the uncertainty of the data and the confidence of the fusion outcome. A weighted combination of quality measures and classifiers performance (Equal Error Rate) are proposed to encode the uncertainty concept to improve the fusion. We also found that quality measures contribute unequally to the recognition performance, thus selecting only significant factors and fusing them with a Dempster-Shafer approach to generate an overall quality score play an important role in the success of uncertainty modeling. The proposed approach achieved a competitive performance (approximate 1% EER) in comparison with other Dempster-Shafer based approaches and other conventional fusion approaches.

Fusion of worlds : consumers’ self-narrative in a hybrid physical/digital world

As the Internet becomes deeply embedded into consumers’ daily life, the digital virtual world brings significant influence to consumers’ self and narrative. Prior studies look at consumer self from either from a certain online space or comparing consumers’ physical and digital virtual selves but not the integration of the physical/digital world. This paper aims to explore the meanings of the digital virtual space on consumers’ narrative as a whole (their interests, dreams, or subjectivity). We utilise a postmodern concept of the cyborg to understand the cultural complexity, subjective meanings of, and the extent to which the digital virtual space plays a role in consumers’ self-narrative. We conducted in-depth interviews and gathered three consumer narratives. Our findings indicate that consumers’ narrative contains important fragments from both physical and digital virtual worlds and their physical and digital virtual selves form a feedback loop that strengthen their overall narrative.

Preparation, Analysis and Use of an Affinity Adsorbent for the Purification of GST Fusion Protein

Methods are presented for the preparation, ligand density analysis and use of an affinity adsorbent for the purification of a glutathione S-transferase (GST) fusion protein in packed and expanded bed chromatographic processes. The protein is composed of GST fused to a zinc finger transcription factor (ZnF). Glutathione, the affinity ligand for GST purification, is covalently immobilized to a solid-phase adsorbent (Streamline™). The GST–ZnF fusion protein displays a dissociation constant of 0.6 x10-6 M to glutathione immobilized to Streamline™. Ligand density optimization, fusion protein elution conditions (pH and glutathione concentration) and ligand orientation are briefly discussed.

A multidimensional collaborative filtering fusion approach with dimensionality reduction

Multidimensional data are getting increasing attention from researchers for creating better recommender systems in recent years. Additional metadata provides algorithms with more details for better understanding the interaction between users and items. While neighbourhood-based Collaborative Filtering (CF) approaches and latent factor models tackle this task in various ways effectively, they only utilize different partial structures of data. In this paper, we seek to delve into different types of relations in data and to understand the interaction between users and items more holistically. We propose a generic multidimensional CF fusion approach for top-N item recommendations. The proposed approach is capable of incorporating not only localized relations of user-user and item-item but also latent interaction between all dimensions of the data. Experimental results show significant improvements by the proposed approach in terms of recommendation accuracy.