A poly(D,L-lactide) resin for the preparation of tissue engineering scaffolds by stereolithography

Porous polylactide constructs were prepared by stereolithography, for the first time without the use of reactive diluents. Star-shaped poly(D,L-lactide) oligomers with 2, 3 and 6 arms were synthesised, end-functionalised with methacryloyl chloride and photocrosslinked in the presence of ethyl lactate as a non-reactive diluent. The molecular weights of the arms of the macromers were 0.2, 0.6, 1.1 and 5 kg/mol, allowing variation of the crosslink density of the resulting networks. Networks prepared from macromers of which the molecular weight per arm was 0.6 kg/mol or higher had good mechanical properties, similar to linear high molecular weight poly(D,L-lactide). A resin based on a 2-armed poly(D,L-lactide) macromer with a molecular weight of 0.6 kg/mol per arm (75 wt%), ethyl lactate (19 wt%), photo-initiator (6 wt%), inhibitor and dye was prepared. Using this resin, films and computer-designed porous constructs were accurately fabricated by stereolithography. Pre-osteoblasts showed good adherence to these photocrosslinked networks. The proliferation rate on these materials was comparable to that on high molecular weight poly(D,L-lactide) and tissue culture polystyrene.

Development of a PDLLA-based stereolithography resin for making tissue engineering scaffolds

The use of porous structures as tissue engineering scaffolds imposes high demands on the pore architecture. Stereolithography is a rapid prototyping method based on photo-polymerisation, that can be utilised to make 3D constructs with high spatial control. In this study, biodegradable resins were developed that can find application in stereolithography. Poly(D,L-lactide) (PDLLA) oligomers were synthesised and functionalised with methacrylate end-groups. By mixing the resulting macromers with a diluent, photo-initiator and inhibitor, lowviscosity resins were obtained that were photocrosslinked to yield stiff and strong degradable poly(lactide) networks. Also, porous scaffolds were fabricated on a stereolithography apparatus (SLA) from a nondegradable resin.

Properties of porous structures prepared by stereolithography using a polylactide resin

Rapid prototyping techniques such as stereolithography allow for building designed tissue engineering scaffolds with high accuracy. In this work, a stereolithography resin based on poly(D,L-lactide) was developed. Biodegradable scaffolds with varying porosity were built from this resin. The scaffolds were analysed by μCT-scanning and compression testing. The porous structures showed excellent mechanical properties in the range of trabecular bone.

Utilising semantic tags in XML clustering

This paper presents an overview of the experiments conducted using Hybrid Clustering of XML documents using Constraints (HCXC) method for the clustering task in the INEX 2009 XML Mining track. This technique utilises frequent subtrees generated from the structure to extract the content for clustering the XML documents. It also presents the experimental study using several data representations such as the structure-only, content-only and using both the structure and the content of XML documents for the purpose of clustering them. Unlike previous years, this year the XML documents were marked up using the Wiki tags and contains categories derived by using the YAGO ontology. This paper also presents the results of studying the effect of these tags on XML clustering using the HCXC method.

Connecting users and items with weighted tags for personalized item recommendations

Social tags are an important information source in Web 2.0. They can be used to describe users’ topic preferences as well as the content of items to make personalized recommendations. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. To eliminate the noise of tags, in this paper we propose to use the multiple relationships among users, items and tags to find the semantic meaning of each tag for each user individually. With the proposed approach, the relevant tags of each item and the tag preferences of each user are determined. In addition, the user and item-based collaborative filtering combined with the content filtering approach are explored. The effectiveness of the proposed approaches is demonstrated in the experiments conducted on real world datasets collected from Amazon.com and citeULike website.

A hybrid recommender systems based on weighted tags

Social tags in web 2.0 are becoming another important information source to describe the content of items as well as to profile users’ topic preferences. However, as arbitrary words given by users, tags contains a lot of noise such as tag synonym and semantic ambiguity a large number personal tags that only used by one user, which brings challenges to effectively use tags to make item recommendations. To solve these problems, this paper proposes to use a set of related tags along with their weights to represent semantic meaning of each tag for each user individually. A hybrid recommendation generation approaches that based on the weighted tags are proposed. We have conducted experiments using the real world dataset obtained from Amazon.com. The experimental results show that the proposed approaches outperform the other state of the art approaches.

Massively parallel sequencing and analysis of expressed sequence tags in a successful invasive plant

Background Invasive species pose a significant threat to global economies, agriculture and biodiversity. Despite progress towards understanding the ecological factors associated with plant invasions, limited genomic resources have made it difficult to elucidate the evolutionary and genetic factors responsible for invasiveness. This study presents the first expressed sequence tag (EST) collection for Senecio madagascariensis, a globally invasive plant species. Methods We used pyrosequencing of one normalized and two subtractive libraries, derived from one native and one invasive population, to generate an EST collection. ESTs were assembled into contigs, annotated by BLAST comparison with the NCBI non-redundant protein database and assigned gene ontology (GO) terms from the Plant GO Slim ontologies. Key Results Assembly of the 221 746 sequence reads resulted in 12 442 contigs. Over 50 % (6183) of 12 442 contigs showed significant homology to proteins in the NCBI database, representing approx. 4800 independent transcripts. The molecular transducer GO term was significantly over-represented in the native (South African) subtractive library compared with the invasive (Australian) library. Based on NCBI BLAST hits and literature searches, 40 % of the molecular transducer genes identified in the South African subtractive library are likely to be involved in response to biotic stimuli, such as fungal, bacterial and viral pathogens. Conclusions This EST collection is the first representation of the S. madagascariensis transcriptome and provides an important resource for the discovery of candidate genes associated with plant invasiveness. The over-representation of molecular transducer genes associated with defence responses in the native subtractive library provides preliminary support for aspects of the enemy release and evolution of increased competitive ability hypotheses in this successful invasive. This study highlights the contribution of next-generation sequencing to better understanding the molecular mechanisms underlying ecological hypotheses that are important in successful plant invasions.

Mobile banking customization via user-defined tags

In this paper, we describe on-going work on mobile banking customization, particularly in the Australian context. The use of user-defined tags to facilitate personalized interactions in the mobile context is explored. The aim of this research is to find ways to improve mobile banking interaction. Customization is more significant in the mobile context than online due to factors such as smaller screen sizes and limited software and hardware capabilities, placing an increased emphasis on usability. This paper explains how user-defined tags can aid different types of customization at the interaction level. A preliminary prototype has been developed to demonstrate the mechanics of the proposed approach. Potential implications, design decisions and limitations are discussed with an outline of future work.

Personalized recommender systems integrating tags and item taxonomy

The social tags in Web 2.0 are becoming another important information source to profile users' interests and preferences to make personalized recommendations. To solve the problem of low information sharing caused by the free-style vocabulary of tags and the long tails of the distribution of tags and items, this paper proposes an approach to integrate the social tags given by users and the item taxonomy with standard vocabulary and hierarchical structure provided by experts to make personalized recommendations. The experimental results show that the proposed approach can effectively improve the information sharing and recommendation accuracy.

Cyanoacrylate glue as an alternative mounting medium for resin-embedded semithin sections

Commercially available generic Superglue (cyanoacrylate glue) can be used as an alternative mounting medium for stained resin-embedded semithin sections. It is colourless and contains a volatile, quick-setting solvent that produces permanent mounts of semithin sections for immediate inspection under the light microscope. Here, we compare the use of cyanoacrylate glue for mounting semithin sections with classical dibutyl phthalate xylene (DPX) in terms of practical usefulness, effectiveness and the quality of the final microscopic image.

Social tagging, guppy effect and the role of interference : a quantum-inspired model for tags combination

Social tagging systems are shown to evidence a well known cognitive heuristic, the guppy effect, which arises from the combination of different concepts. We present some empirical evidence of this effect, drawn from a popular social tagging Web service. The guppy effect is then described using a quantum inspired formalism that has been already successfully applied to model conjunction fallacy and probability judgement errors. Key to the formalism is the concept of interference, which is able to capture and quantify the strength of the guppy effect.