Next generation sequencing identifies novel CACNA1A gene mutations in Episodic Ataxia type 2

Episodic Ataxia type 2 (EA2) is a rare autosomal dominantly inherited neurological disorder characterized by recurrent disabling imbalance, vertigo and episodes of ataxia lasting minutes to hours. EA2 is caused most often by loss of function mutations of the calcium channel gene CACNA1A. In addition to EA2, mutations in CACNA1A are responsible for two other allelic disorders: familial hemiplegic migraine type1 (FHM1) and spinocerebellar ataxia type 6 (SCA6). Herein, we have utilised Next Generation Sequencing (NGS) to screen the coding sequence, exon-intron boundaries and UTRs of five genes where mutation is known to produce symptoms related to EA2, including CACNA1A. We performed this screening in a group of 31 unrelated patients with EA2 symptoms. Both novel and known mutations were detected through NGS technology, and confirmed through Sanger sequencing. Genetic testing showed in total 15 mutation bearing patients (48%), of which 9 were novel mutations (6 missense and 3 small frameshift deletion mutations) and six known mutations (4 missense and 2 nonsense).These results demonstrate the efficiency of our NGS-panel for detecting known and novel mutations for EA2 in the CACNA1A gene, also identifying a novel missense mutation in ATP1A2 which is not a normal target for EA2 screening.

Data-aware task scheduling for all-to-all comparison problems in heterogeneous distributed systems

Solving large-scale all-to-all comparison problems using distributed computing is increasingly significant for various applications. Previous efforts to implement distributed all-to-all comparison frameworks have treated the two phases of data distribution and comparison task scheduling separately. This leads to high storage demands as well as poor data locality for the comparison tasks, thus creating a need to redistribute the data at runtime. Furthermore, most previous methods have been developed for homogeneous computing environments, so their overall performance is degraded even further when they are used in heterogeneous distributed systems. To tackle these challenges, this paper presents a data-aware task scheduling approach for solving all-to-all comparison problems in heterogeneous distributed systems. The approach formulates the requirements for data distribution and comparison task scheduling simultaneously as a constrained optimization problem. Then, metaheuristic data pre-scheduling and dynamic task scheduling strategies are developed along with an algorithmic implementation to solve the problem. The approach provides perfect data locality for all comparison tasks, avoiding rearrangement of data at runtime. It achieves load balancing among heterogeneous computing nodes, thus enhancing the overall computation time. It also reduces data storage requirements across the network. The effectiveness of the approach is demonstrated through experimental studies.

Place making for knowledge generation and innovation: Planning and branding Brisbane’s knowledge community precincts

Knowledge generation and innovation have been a priority for global city administrators particularly during the last couple of decades. This is mainly due to the growing consensus in identifying knowledge-based urban development as a panacea to the burgeoning economic problems. Place making has become a critical element for success in knowledge-based urban development as planning and branding places is claimed to be an effective marketing tool for attracting investment and talent. This paper aims to investigate the role of planning and branding in place making by assessing the effectiveness of planning and branding strategies in the development of knowledge and innovation milieus. The methodology of the study comprises reviewing the literature thoroughly, developing an analysis framework, and utilizing this framework in analyzing Brisbane’s knowledge community precincts—namely Boggo Road Knowledge Precinct, Kelvin Grove Urban Knowledge Village, and Sippy Downs Knowledge Town. The analysis findings generate invaluable insights in Brisbane’s journey in place making for knowledge and innovation milieus and communities. The results suggest as much as good planning, branding strategies and practice, the requirements of external and internal conditions also need to be met for successful place making in knowledge community precincts.

Training for reduction of design waste

Construction and demolition (C&D) waste have negative impacts on the environment. As a significant proportion of C&D waste is related to the design stage of a project, there is an opportunity for architects to reduce the waste. However, research suggests that many architects often do not understand the impact of their design on waste generation. Training and education are proposed by current researchers to improve architects’ knowledge; however, this has not been adequately validated as a viable approach to solving waste issues. This research investigates architects’ perceptions towards waste management in the design phase, and determines whether they feel they are adequately skilled in reducing C&D waste. Questionnaire surveys were distributed to architects from 98 architectural firms and 25 completed surveys were returned. The results show that while architects are aware of the relationship between design and waste, ‘extra time’ and ‘lack of knowledge’ are the key barriers to implementing waste reduction strategies. In addition, the majority of respondents acknowledge their lack of skill to reduce waste through design evaluation. Therefore, training programmes can be a viable strategy to enable them to address the pressing issue of C&D waste reduction.