Strategy in developing cell based therapy for large bone

Regeneration of osseous defects by tissue-engineering approach provides a novel means of treatment utilizing cell biology, materials science, and molecular biology. The concept of in vitro cultured osteoblasts having an ability to induce new bone formation has been demonstrated in the critical size defects using small animal models. The bone derived cells can be incorporated into bioengineered scaffolds and synthesize bone matrix, which on implantation can induce new bone formation. In search of optimal cell delivery materials, the extracellular matrix as cell carriers for the repair and regeneration of tissues is receiving increased attention. We have investigated extracellular matrix formed by osteoblasts in vitro as a scaffold for osteoblasts transplantation and found a mineralized matrix, formed by human osteoblasts in vitro, can initiate bone formation by activating endogenous mesenchymal cells. To repair the large bone defects, osteogenic or stem cells need to be prefabricated in a large three dimensional scaffold usually made of synthetic biomaterials, which have inadequate interaction with cells and lead to in vivo foreign body reactions. The interstitial extracellular matrix has been applied to modify biomaterials surface and identified vitronectin, which binds the heparin domain and RGD (Arg-Gly-Asp) sequence can modulate cell spreading, migration and matrix formation on biomaterials. We also synthesized a tri-block copolymer, methoxy-terminated poly(ethylene glycol)(MPEG)-polyL-lactide(PLLA)-polylysine(PLL) for human osteoblasts delivery. We identified osteogenic activity can be regulated by the molecular weight and composition of the triblock copolymers. Due to the sequential loss of lineage differentiation potential during the culture of bone marrow stromal cells that hinderers their potential clinical application, we have developed a clonal culture system and established several stem cell clones with fast growing and multi-differentiation properties. Using proteomics and subtractive immunization, several differential proteins have been identified and verified their potential application in stem cell characterization and tissue regeneration

Bioactive SrO–SiO2 glass with well-ordered mesopores : characterization, physiochemistry and biological properties

For a biomaterial to be considered suitable for bone repair it should ideally be both bioactive and have a capacity for controllable drug delivery; as such, mesoporous SiO2 glass has been proposed as a new class of bone regeneration material by virtue of its high drug-loading ability and generally good biocompatibility. It does, however, have less than optimum bioactivity and controllable drug delivery properties. In this study, we incorporated strontium (Sr) into mesoporous SiO2 in an effort to develop a bioactive mesoporous SrO–SiO2 (Sr–Si) glass with the capacity to deliver Sr2+ ions, as well as a drug, at a controlled rate, thereby producing a material better suited for bone repair. The effects of Sr2+ on the structure, physiochemistry, drug delivery and biological properties of mesoporous Sr–Si glass were investigated. The prepared mesoporous Sr–Si glass was found to have an excellent release profile of bioactive Sr2+ ions and dexamethasone, and the incorporation of Sr2+ improved structural properties, such as mesopore size, pore volume and specific surface area, as well as rate of dissolution and protein adsorption. The mesoporous Sr–Si glass had no cytotoxic effects and its release of Sr2+ and SiO44− ions enhanced alkaline phosphatase activity – a marker of osteogenic cell differentiation – in human bone mesenchymal stem cells. Mesoporous Sr–Si glasses can be prepared to porous scaffolds which show a more sustained drug release. This study suggests that incorporating Sr2+ into mesoporous SiO2 glass produces a material with a more optimal drug delivery profile coupled with improved bioactivity, making it an excellent material for bone repair applications. Keywords: Mesoporous Sr–Si glass; Drug delivery; Bioactivity; Bone repair; Scaffolds

The effects of bioactive akermanite on physiochemical, drug-delivery and biological properties of poly (lactide-co-glycolide) beads

Poly(lactide-co-glycolide) (PLGA) beads have been widely studied as a potential drug/protein carrier. The main shortcomings of PLGA beads are that they lack bioactivity and controllable drug-delivery ability, and their acidic degradation by-products can lead to pH decrease in the vicinity of the implants. Akermanite (AK) (Ca(2) MgSi(2) O(7) ) is a novel bioactive ceramic which has shown excellent bioactivity and degradation in vivo. This study aimed to incorporate AK to PLGA beads to improve the physiochemical, drug-delivery, and biological properties of PLGA beads. The microstructure of beads was characterized by SEM. The effect of AK incorporating into PLGA beads on the mechanical strength, apatite-formation ability, the loading and release of BSA, and the proliferation, and differentiation of bone marrow stromal cells (BMSCs) was investigated. The results showed that the incorporation of AK into PLGA beads altered the anisotropic microporous structure into homogenous one and improved their compressive strength and apatite-formation ability in simulated body fluids (SBF). AK neutralized the acidic products from PLGA beads, leading to stable pH value of 7.4 in biological environment. AK led to a sustainable and controllable release of bovine serum albumin (BSA) in PLGA beads. The incorporation of AK into PLGA beads enhanced the proliferation and alkaline phosphatase activity of BMSCs. This study implies that the incorporation of AK into PLGA beads is a promising method to enhance their physiochemical and biological property. AK/PLGA composite beads are a potential bioactive drug-delivery system for bone tissue repair.

Three-dimensional printing of hierarchical and tough mesoporous bioactive glass scaffolds with a controllable pore architecture, excellent mechanical strength and mineralization ability

New-generation biomaterials for bone regenerations should be highly bioactive, resorbable and mechanically strong. Mesoporous bioactive glass (MBG), as a novel bioactive material, has been used for the study of bone regeneration due to its excellent bioactivity, degradation and drug-delivery ability; however, how to construct a 3D MBG scaffold (including other bioactive inorganic scaffolds) for bone regeneration still maintains a significant challenge due to its/their inherit brittleness and low strength. In this brief communication, we reported a new facile method to prepare hierarchical and multifunctional MBG scaffolds with controllable pore architecture, excellent mechanical strength and mineralization ability for bone regeneration application by a modified 3D-printing technique using polyvinylalcohol (PVA), as a binder. The method provides a new way to solve the commonly existing issues for inorganic scaffold materials, for example, uncontrollable pore architecture, low strength, high brittleness and the requirement for the second sintering at high temperature. The obtained 3D-printing MBG scaffolds possess a high mechanical strength which is about 200 times for that of traditional polyurethane foam template-resulted MBG scaffolds. They have highly controllable pore architecture, excellent apatite-mineralization ability and sustained drug-delivery property. Our study indicates that the 3D-printed MBG scaffolds may be an excellent candidate for bone regeneration.

Developing trust networks based on user tagging information for recommendation making

Recommender systems are one of the recent inventions to deal with ever growing information overload. Collaborative filtering seems to be the most popular technique in recommender systems. With sufficient background information of item ratings, its performance is promising enough. But research shows that it performs very poor in a cold start situation where previous rating data is sparse. As an alternative, trust can be used for neighbor formation to generate automated recommendation. User assigned explicit trust rating such as how much they trust each other is used for this purpose. However, reliable explicit trust data is not always available. In this paper we propose a new method of developing trust networks based on user’s interest similarity in the absence of explicit trust data. To identify the interest similarity, we have used user’s personalized tagging information. This trust network can be used to find the neighbors to make automated recommendations. Our experiment result shows that the proposed trust based method outperforms the traditional collaborative filtering approach which uses users rating data. Its performance improves even further when we utilize trust propagation techniques to broaden the range of neighborhood.

Trust and reputation management in web-based social network

know personally. They also communicate with other members of the network who are the friends of their friends and may be friends of their friend’s network. They share their experiences and opinions within the social network about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Opinions, reputations and ecommendations will influence users' choice and usage of online resources. Recommendations may be received through a chain of friends of friends, so the problem for the user is to be able to evaluate various types of trust recommendations and reputations. This opinion or ecommendation has a great influence to choose to use or enjoy the item by the other user of the community. Users share information on the level of trust they explicitly assign to other users. This trust can be used to determine while taking decision based on any recommendation. In case of the absence of direct connection of the recommender user, propagated trust could be useful.

Hylaluronan-based heparin-incorporated hydrogels for generation of axially vascularized bioartificial bone tissues : in vitro and in vivo evaluation in a PLDLLA-TCP-PCL-composite system

Smart matrices are required in bone tissueengineered grafts that provide an optimal environment for cells and retain osteo-inductive factors for sustained biological activity. We hypothesized that a slow-degrading heparin-incorporated hyaluronan (HA) hydrogel can preserve BMP-2; while an arterio–venous (A–V) loop can support axial vascularization to provide nutrition for a bioartificial bone graft. HA was evaluated for osteoblast growth and BMP-2 release. Porous PLDLLA–TCP–PCL scaffolds were produced by rapid prototyping technology and applied in vivo along with HA-hydrogel, loaded with either primary osteoblasts or BMP-2. A microsurgically created A–V loop was placed around the scaffold, encased in an isolation chamber in Lewis rats. HA-hydrogel supported growth of osteoblasts over 8 weeks and allowed sustained release of BMP-2 over 35 days. The A–V loop provided an angiogenic stimulus with the formation of vascularized tissue in the scaffolds. Bone-specific genes were detected by real time RT-PCR after 8 weeks. However, no significant amount of bone was observed histologically. The heterotopic isolation chamber in combination with absent biomechanical stimulation might explain the insufficient bone formation despite adequate expression of bone-related genes. Optimization of the interplay of osteogenic cells and osteo-inductive factors might eventually generate sufficient amounts of axially vascularized bone grafts for reconstructive surgery.

A methodology for object identification and tracking in construction based on spatial modeling and image matching techniques

Understanding the motion characteristics of on-site objects is desirable for the analysis of construction work zones, especially in problems related to safety and productivity studies. This article presents a methodology for rapid object identification and tracking. The proposed methodology contains algorithms for spatial modeling and image matching. A high-frame-rate range sensor was utilized for spatial data acquisition. The experimental results indicated that an occupancy grid spatial modeling algorithm could quickly build a suitable work zone model from the acquired data. The results also showed that an image matching algorithm is able to find the most similar object from a model database and from spatial models obtained from previous scans. It is then possible to use the matched information to successfully identify and track objects.

Object identification based on 3D spatial models of construction sites

On obstacle-cluttered construction sites, understanding the motion characteristics of objects is important for anticipating collisions and preventing accidents. This study investigates algorithms for object identification applications that can be used by heavy equipment operators to effectively monitor congested local environment. The proposed framework contains algorithms for three-dimensional spatial modeling and image matching that are based on 3D images scanned by a high-frame rate range sensor. The preliminary results show that an occupancy grid spatial modeling algorithm can successfully build the most pertinent spatial information, and that an image matching algorithm is best able to identify which objects are in the scanned scene.

Modeling object identification and tracking errors on image-based safety assessment of earthmoving operations

Object identification and tracking have become critical for automated on-site construction safety assessment. The primary objective of this paper is to present the development of a testbed to analyze the impact of object identification and tracking errors caused by data collection devices and algorithms used for safety assessment. The testbed models workspaces for earthmoving operations and simulates safety-related violations, including speed limit violations, access violations to dangerous areas, and close proximity violations between heavy machinery. Three different cases were analyzed based on actual earthmoving operations conducted at a limestone quarry. Using the testbed, the impacts of device and algorithm errors were investigated for safety planning purposes.

Investigating the process of teaching and learning principles through practice : a case study on collegiate action by media practitioners and teachers, designing a skills-based learning program

This paper in the journalism education field reports on the construction of a new subject as part of a postgraduate coursework degree. The subject, or unit1 will offer both Journalism students and other students an introductory experience of creating media, using common ‘new media’ tools, with exercises that will model the learning of communication principles through practice. It has been named ‘Fundamental Media Skills for the Workplace’. The conceptualisation and teaching of it will be characteristic of the Journalism academic discipline that uses the ‘inside perspective’—understanding mass media by observing from within. Proposers for the unit within the Journalism discipline have sought to extend the common teaching approach, based on training to produce start-ready recruits for media jobs, backed by a study of contexts, e.g. journalistic ethics, or media audiences. In this proposal, students would then examine the process to elicit additional knowledge about their learning. The paper draws on literature of journalism and its pedagogy, and on communication generally. It also documents a ‘community of practice’ exercise conducted among practitioners as teachers for the subject, developing exercises and models of media work. A preliminary conclusion from that exercise is that it has taken a step towards enhancing skills-based learning for media work, as a portal to more generalised knowledge.

Fast content-based file type identification

Digital forensic examiners often need to identify the type of a file or file fragment based only on the content of the file. Content-based file type identification schemes typically use a byte frequency distribution with statistical machine learning to classify file types. Most algorithms analyze the entire file content to obtain the byte frequency distribution, a technique that is inefficient and time consuming. This paper proposes two techniques for reducing the classification time. The first technique selects a subset of features based on the frequency of occurrence. The second speeds classification by sampling several blocks from the file. Experimental results demonstrate that up to a fifteen-fold reduction in file size analysis time can be achieved with limited impact on accuracy.

Fragment-based version management for repositories of business process models

As organizations reach higher levels of Business Process Management maturity, they tend to accumulate large collections of process models. These repositories may contain thousands of activities and be managed by different stakeholders with varying skills and responsibilities. However, while being of great value, these repositories induce high management costs. Thus, it becomes essential to keep track of the various model versions as they may mutually overlap, supersede one another and evolve over time. We propose an innovative versioning model, and associated storage structure, specifically designed to maximize sharing across process models and process model versions, reduce conflicts in concurrent edits and automatically handle controlled change propagation. The focal point of this technique is to version single process model fragments, rather than entire process models. Indeed empirical evidence shows that real-life process model repositories have numerous duplicate fragments. Experiments on two industrial datasets confirm the usefulness of our technique.

Loculus : an ontology-based information management framework for the motion picture industry

"How do you film a punch?" This question can be posed by actors, make-up artists, directors and cameramen. Though they can all ask the same question, they are not all seeking the same answer. Within a given domain, based on the roles they play, agents of the domain have different perspectives and they want the answers to their question from their perspective. In this example, an actor wants to know how to act when filming a scene involving a punch. A make-up artist is interested in how to do the make-up of the actor to show bruises that may result from the punch. Likewise, a director wants to know how to direct such a scene and a cameraman is seeking guidance on how best to film such a scene. This role-based difference in perspective is the underpinning of the Loculus framework for information management for the Motion Picture Industry. The Loculus framework exploits the perspective of agent for information extraction and classification within a given domain. The framework uses the positioning of the agent’s role within the domain ontology and its relatedness to other concepts in the ontology to determine the perspective of the agent. Domain ontology had to be developed for the motion picture industry as the domain lacked one. A rule-based relatedness score was developed to calculate the relative relatedness of concepts with the ontology, which were then used in the Loculus system for information exploitation and classification. The evaluation undertaken to date have yielded promising results and have indicated that exploiting perspective can lead to novel methods of information extraction and classifications.

A new family of Marx generators based on commutation circuits

This paper presents a novel topology for the generation of high voltage pulses that uses both slow and fast solid-state power switches. This topology includes diode-capacitor units in parallel with commutation circuits connected to a positive buck-boost converter. This enables the generation of a range of high output voltages with a given number of capacitors. The advantages of this topology are the use of slow switches and a reduced number of diodes in comparison with conventional Marx generator. Simulations performed for single and repetitive pulse generation and experimental tests of a prototype hardware verify the proposed topology.