Automated tumor analysis for molecular profiling in lung cancer

The discovery and clinical application of molecular biomarkers in solid tumors, increasingly relies on nucleic acid extraction from FFPE tissue sections and subsequent molecular profiling. This in turn requires the pathological review of haematoxylin & eosin (H&E) stained slides, to ensure sample quality, tumor DNA sufficiency by visually estimating the percentage tumor nuclei and tumor annotation for manual macrodissection. In this study on NSCLC, we demonstrate considerable variation in tumor nuclei percentage between pathologists, potentially undermining the precision of NSCLC molecular evaluation and emphasising the need for quantitative tumor evaluation. We subsequently describe the development and validation of a system called TissueMark for automated tumor annotation and percentage tumor nuclei measurement in NSCLC using computerized image analysis. Evaluation of 245 NSCLC slides showed precise automated tumor annotation of cases using Tissuemark, strong concordance with manually drawn boundaries and identical EGFR mutational status, following manual macrodissection from the image analysis generated tumor boundaries. Automated analysis of cell counts for % tumor measurements by Tissuemark showed reduced variability and significant correlation (p < 0.001) with benchmark tumor cell counts. This study demonstrates a robust image analysis technology that can facilitate the automated quantitative analysis of tissue samples for molecular profiling in discovery and diagnostics.

Knowledge Transfer in Quadruple Helix Ecosystems: An Absorptive Capacity Perspective

Increased understanding of knowledge transfer (KT) from universities to the wider regional knowledge ecosystem offers opportunities for increased regional innovation and commercialisation. The aim of this article is to improve the understanding of the KT phenomena in an open innovation context where multiple diverse quadruple helix stakeholders are interacting. An absorptive capacity-based conceptual framework is proposed, using a priori constructs which portrays the multidimensional process of KT between universities and its constituent stakeholders in pursuit of open innovation and commercialisation. Given the lack of overarching theory in the field, an exploratory, inductive theory building methodology was adopted using semi-structured interviews, document analysis and longitudinal observation data over a three-year period. The findings identify five factors, namely human centric factors, organisational factors, knowledge characteristics, power relationships and network characteristics, which mediate both the ability of stakeholders to engage in KT and the effectiveness of knowledge acquisition, assimilation, transformation and exploitation. This research has implications for policy makers and practitioners by identifying the need to implement interventions to overcome the barriers to KT effectiveness between regional quadruple helix stakeholders within an open innovation ecosystem.

Genomic Resources Notes Accepted 1 June 2015 - 31 July 2015

This article documents the public availability of (i) microbiomes in diet and gut of larvae from the dipteran Dilophus febrilis using massive parallel sequencing, (ii) SNP and SSR discovery and characterization in the transcriptome of the Atlantic mackerel (Scomber scombrus, L) and (iii) assembled transcriptome for an endangered, endemic Iberian cyprinid fish (Squalius pyrenaicus).

A primer for the Environmental Impact Assessment of mining at seafloor massive sulfide deposits

Seafloor massive sulfides (SMS) contain commercially viable quantities of high grade ores, making them attractive prospect sites for marine mining. SMS deposits may also contain hydrothermal vent ecosystems populated by high conservation value vent-endemic species. Responsible environmental management of these resources is best achieved by the adoption of a precautionary approach. Part of this precautionary approach involves the Environmental Impact Assessment (EIA) of exploration and exploitative activities at SMS deposits. The VentBase 2012 workshop provided a forum for stakeholders and scientists to discuss issues surrounding SMS exploration and exploitation. This forum recognised the requirement for a primer which would relate concepts underpinning EIA at SMS deposits. The purpose of this primer is to inform policy makers about EIA at SMS deposits in order to aid management decisions. The primer offers a basic introduction to SMS deposits and their associated ecology, and the basic requirements for EIA at SMS deposits; including initial data and information scoping, environmental survey, and ecological risk assessment. © 2013 Elsevier Ltd.

A Hybrid Swarm Based Approach in Addressing University Timetabling Problems

This paper is concerned with the application of an automated hybrid approach in addressing the university timetabling problem. The approach described is based on the nature-inspired artificial bee colony (ABC) algorithm. An ABC algorithm is a biologically-inspired optimization approach, which has been widely implemented in solving a range of optimization problems in recent years such as job shop scheduling and machine timetabling problems. Although the approach has proven to be robust across a range of problems, it is acknowledged within the literature that there currently exist a number of inefficiencies regarding the exploration and exploitation abilities. These inefficiencies can often lead to a slow convergence speed within the search process. Hence, this paper introduces a variant of the algorithm which utilizes a global best model inspired from particle swarm optimization to enhance the global exploration ability while hybridizing with the great deluge (GD) algorithm in order to improve the local exploitation ability. Using this approach, an effective balance between exploration and exploitation is attained. In addition, a traditional local search approach is incorporated within the GD algorithm with the aim of further enhancing the performance of the overall hybrid method. To evaluate the performance of the proposed approach, two diverse university timetabling datasets are investigated, i.e., Carter's examination timetabling and Socha course timetabling datasets. It should be noted that both problems have differing complexity and different solution landscapes. Experimental results demonstrate that the proposed method is capable of producing high quality solutions across both these benchmark problems, showing a good degree of generality in the approach. Moreover, the proposed method produces best results on some instances as compared with other approaches presented in the literature.

A Hybrid Imperialist Approach in Solving University Timetabling Problems. Information Sciences. Vol. 283, 1-21

Generating timetables for an institution is a challenging and time consuming task due to different demands on the overall structure of the timetable. In this paper, a new hybrid method which is a combination of a great deluge and artificial bee colony algorithm (INMGD-ABC) is proposed to address the university timetabling problem. Artificial bee colony algorithm (ABC) is a population based method that has been introduced in recent years and has proven successful in solving various optimization problems effectively. However, as with many search based approaches, there exist weaknesses in the exploration and exploitation abilities which tend to induce slow convergence of the overall search process. Therefore, hybridization is proposed to compensate for the identified weaknesses of the ABC. Also, inspired from imperialist competitive algorithms, an assimilation policy is implemented in order to improve the global exploration ability of the ABC algorithm. In addition, Nelder–Mead simplex search method is incorporated within the great deluge algorithm (NMGD) with the aim of enhancing the exploitation ability of the hybrid method in fine-tuning the problem search region. The proposed method is tested on two differing benchmark datasets i.e. examination and course timetabling datasets. A statistical analysis t-test has been conducted and shows the performance of the proposed approach as significantly better than basic ABC algorithm. Finally, the experimental results are compared against state-of-the art methods in the literature, with results obtained that are competitive and in certain cases achieving some of the current best results to those in the literature.