Prisons Memory Archive

Between 2006 and 2007, the Prisons Memory Archive (PMA) filmed participants, including former prisoners, prison staff, teachers, chaplains, visitors, solicitors and welfare workers back inside the Maze/Long Kesh Prison and Armagh Gaol. They shared the memory of the time spent in these prisons during the period of political violence from 1970 - 2000 in Northern Ireland, commonly known as the Troubles. Underpinning the overall methodology is co-ownership of the material, which gives participants the right to veto as well as to participate in the processes of editing and exhibiting their stories, so prioritising the value of co-authorship of their stories. The PMA adopted life-story interviewing techniques with the empty sites stimulating participants’ memory while they walked and talked their way around the empty sites. A third feature is inclusivity: the archive holds stories from across the full spectrum of the prison experience. A selection of the material, with accompanying context and links is available online www.prisonsmemoryarchive.com

Further Information:

The protocols of inclusivity, co-ownership and life-story telling make this collection significant as an initiative that engages with contemporary problems of how to negotiate narratives about a conflicted past in a society emerging out of violence. Inclusivity means that prison staff, prisoners, governors, chaplains, tutors and visitors have participated, relating their individual and collective experiences, which sit side by side on the PMA website. Co-ownership addresses the issues of ethics and sensitivity, allowing key constituencies to be involved. Life-story telling, based on oral history methodologies allows participants to be the authors of their own stories, crucial when dealing with sensitive issues from a violent past. The website hosts a selection of excerpts, e.g. the Armagh Stories page shows excerpts from 15 participants, while the Maze and Long Kesh Prison page offers interactive access to 24 participants from that prison. Using an interactive documentary structure, the site offers users opportunities to navigate their own way through the material and encourages them to hear and see the ‘other’, central to attempts at encouraging dialogue in a divided society. Further, public discussions have been held after screening of excerpts with community groups in the following locations - Belfast, Newtownabbey, Derry, Armagh, Enniskillen, London, Cork, Maynooth, Clones, and Monaghan. Extracts have been screened at international academic conferences in Valencia, Australia, Tartu, Estonia, Prague, and York. A dataset of the content, with description and links, is available for REF purposes.

Valuing the talk of young people: are we nearly there yet?

This paper examines reasons why young people’s talk about themselves and their educational experiences do not seem to be valued in public discourse about education. Drawing on a national dataset of student focus groups, it illustrates how students talk about themselves in educational contexts in a way that is entirely different and more complex than how they are conceptualised by an adult audience and symbolic elites. It demonstrates, contrary to dominant adult perceptions, the critical, communicative and creative use of language offered by young people when asked about their educational experiences, and highlights the potential innovation being missed by not listening.

Genetic variants influencing human aging from late-onset Alzheimer's disease (LOAD) genome-wide association studies (GWAS)

Genetics plays a crucial role in human aging with up to 30% of those living to the mid-80s being determined by genetic variation. Survival to older ages likely entails an even greater genetic contribution. There is increasing evidence that genes implicated in age-related diseases, such as cancer and neuronal disease, play a role in affecting human life span. We have selected the 10 most promising late-onset Alzheimer's disease (LOAD) susceptibility genes identified through several recent large genome-wide association studies (GWAS). These 10 LOAD genes (APOE, CLU, PICALM, CR1, BIN1, ABCA7, MS4A6A, CD33, CD2AP, and EPHA1) have been tested for association with human aging in our dataset (1385 samples with documented age at death [AAD], age range: 58-108 years; mean age at death: 80.2) using the most significant single nucleotide polymorphisms (SNPs) found in the previous studies. Apart from the APOE locus (rs2075650) which showed compelling evidence of association with risk on human life span (p = 5.27 × 10(-4)), none of the other LOAD gene loci demonstrated significant evidence of association. In addition to examining the known LOAD genes, we carried out analyses using age at death as a quantitative trait. No genome-wide significant SNPs were discovered. Increasing sample size and statistical power will be imperative to detect genuine aging-associated variants in the future. In this report, we also discuss issues relating to the analysis of genome-wide association studies data from different centers and the bioinformatic approach required to distinguish spurious genome-wide significant signals from real SNP associations.

A multi-center study of ACE and the risk of late-onset Alzheimer's disease

A key pathological feature of late-onset Alzheimer's disease (LOAD) is the abnormal extracellular accumulation of the amyloid-ß (Aß) peptide. Thus, altered Aß degradation could be a major contributor to the development of LOAD. Variants in the gene encoding the Aß-degrading enzyme, angiotensin-1 converting enzyme (ACE) therefore represent plausible candidates for association with LOAD pathology and risk. Following Alzgene meta-analyses of all published case-control studies, the ACE variants rs4291 and rs1800764 showed significant association with LOAD risk. Furthermore ACE haplotypes are associated with both plasma ACE levels and LOAD risk. We tested three ACE variants (rs4291, rs4343, and rs1800764) for association with LOAD in ten Caucasian case-control populations (n = 8,212). No association was found using multiple logistic models (all p > 0.09). We found no population heterogeneity (all p > 0.38) or evidence for association with LOAD risk following meta-analysis of the ten populations for rs4343 (OR = 1.00), rs4291 (OR = 0.97), or rs1800764 (OR = 0.99). Although we found no haplotypic association in our complete dataset (p = 0.51), a significant global haplotypic p-value was observed in one population (p = 0.007) due to an association of the H3 haplotype (OR = 0.72, p = 0.02) and a trend towards an association of H4 (OR = 1.38, p = 0.09) and H7 (OR = 2.07, p = 0.08) although these did not survive Bonferroni correction. Previously reported associations of ACE variants with LOAD will be diminished following this study. At best, ACE variants have modest effect sizes, which are likely part of a complex interaction between genetic, phenotypic and pharmacological effects that would be undetected in traditional case-control studies.

Trends in product recalls within the agri-food industry:Empirical evidence from the USA, UK and the Republic of Ireland

The increasing frequency of product recalls within the agri-food industry has led many to question food safety. Research studies also often focus on biological hazards without considering how past, present and emerging risks change over time. We undertake a systematic review of the different biological, operational and chemical hazards within the agri-food industry using a dataset of 2070 registered food recalls in the USA, UK and Republic of Ireland between 2004 and 2010. We show product recalls have become more frequent over time and operational hazards, rather than biological and chemical hazards, are the most frequent recall type within the agri-food industry. © 2012 Elsevier Ltd. All rights reserved.

A genome-wide association study provides evidence for association of chromosome 8p23 (MYP10) and 10q21.1 (MYP15) with high myopia in the French population.

PURPOSE. Myopia is a complex trait affected by both genetic and environmental factors. High myopia is associated with increased risk of sight-threatening eye disorders such as retinal detachment. The purpose of this genome-wide association study was to identify susceptibility genes contributing to high myopia in the French population. METHODS. High myopic cases were genotyped using Affymetrix SNP 6.0 chips and population controls were selected from the GABRIEL French dataset in which samples were genotyped by Illumina Human610 quad array. The association study was conducted using 152,234 single nucleotide polymorphisms that were present on both manufacturers' chips in 192 high myopic cases and 1064 controls to identify associated regions. Imputation was performed on peak regions. RESULTS. Associations were found at known myopia locus MYP10 on chromosome 8p23 and MYP15 on chromosome 10q21.1. Rs189798 (8p23) and rs10825992 (10q21.1) showed the strongest associations in these regions (P=6.32x10-7 and P=2.17x10-5, respectively). The imputed results at 8p23 showed 2 peaks of interest. The first spanned 30kb including rs189798 between MIR4660 and PPP1R3B with the most significant association at rs17155227 (P=1.07x10-10). The second novel peak was 4kb in length, encompassing MIR124-1 and the MSRA gene, with the strongest association at rs55864141 (P=1.30x10-7). The peak of imputed data at 10q21.1 was 70kb in length between ZWINT and MIR3924, with rs3107503 having the lowest P value (P=1.54x10-7). CONCLUSION. We provide evidence for the association of MYP10 at 8p23 and MYP15 at 10p21.1 with high myopia in the French population and refine these regions of association.

Palaeoglacial and palaeoclimatic conditions in the NW Pacific, as revealed by a morphometric analysis of cirques upon the Kamchatka Peninsula

The distribution of glacial cirques upon the Kamchatka peninsula, Far Eastern Russia, is systematically mapped from satellite images and digital elevation model data. A total of 3,758 cirques are identified, 238 of which are occupied by active glaciers. The morphometry of the remaining 3,520 cirques is analysed. These cirques are found to show a very strong N bias in their azimuth (orientation), likely resulting from aspect-related variations in insolation. The strength of this N bias is considered to indicate that former glaciation upon the peninsula was often ‘marginal’, and mainly of cirque-type, with peaks extending little above regional equilibrium-line altitudes. This is supported by the fact that S and SE-facing cirques are the highest in the dataset, suggesting that glacier-cover was rarely sufficient to allow S and SE-facing glaciers to develop at low altitudes. The strength of these azimuth-related variations in cirque altitude is thought to reflect comparatively cloud-free conditions during former periods of glaciation. It is suggested that these characteristics, of marginal glaciation and comparatively cloud-free conditions, reflect the region’s former aridity, which was likely intensified at the global Last Glacial Maximum, and during earlier periods of ice advance, as a result of the development of negative pressure anomalies over the North Pacific (driven by the growth of the Laurentide Ice Sheet), combined with other factors, including an increase in the extent and duration of sea ice, a reduction in global sea levels, cooler sea surface temperatures, and the localised growth of mountain glaciers. There is published evidence to suggest extensive glaciation of the Kamchatka Peninsula at times during the Late Quaternary, yet the data presented here appears to suggest that such phases were comparatively short-lived, and that smaller cirque-type glaciers were generally more characteristic of the period.

Exploring the Transcriptome of Atlantic Salmon (Salmo salar) Skin, a Major Defense Organ

The skin of fish is the first line of defense against pathogens and parasites. The skin transcriptome of the Atlantic salmon is poorly characterized, and currently only 2,089 expressed sequence tags (ESTs) out of a total of half a million sequences are generated from skin-derived cDNA libraries. The primary aim of this study was to enhance the transcriptomic knowledge of salmon skin by using next-generation sequencing (NGS) technology, namely the Roche-454 platform. An equimolar mixture of high-quality RNA from skin and epidermal samples of salmon reared in either freshwater or seawater was used for 454-sequencing. This technique yielded over 600,000 reads, which were assembled into 34,696 isotigs using Newbler. Of these isotigs, 12 % had not been sequenced in Atlantic salmon, hence representing previously unreported salmon mRNAs that can potentially be skin-specific. Many full-length genes have been acquired, representing numerous biological processes. Mucin proteins are the main structural component of mucus and we examined in greater detail the sequences we obtained for these genes. Several isotigs exhibited homology to mammalian mucins (MUC2, MUC5AC and MUC5B). Mucin mRNAs are generally > 10 kbp and contain large repetitive units, which pose a challenge towards full-length sequence discovery. To date, we have not unearthed any full-length salmon mucin genes with this dataset, but have both N- and C-terminal regions of a mucin type 5. This highlights the fact that, while NGS is indeed a formidable tool for sequence data mining of non-model species, it must be complemented with additional experimental and bioinformatic work to characterize some mRNA sequences with complex features.

Assessing reproducibility of data obtained with instruments based on continuous measurements

Data obtained with any research tool must be reproducible, a concept referred to as reliability. Three techniques are often used to evaluate reliability of tools using continuous data in aging research: intraclass correlation coefficients (ICC), Pearson correlations, and paired t tests. These are often construed as equivalent when applied to reliability. This is not correct, and may lead researchers to select instruments based on statistics that may not reflect actual reliability. The purpose of this paper is to compare the reliability estimates produced by these three techniques and determine the preferable technique. A hypothetical dataset was produced to evaluate the reliability estimates obtained with ICC, Pearson correlations, and paired t tests in three different situations. For each situation two sets of 20 observations were created to simulate an intrarater or inter-rater paradigm, based on 20 participants with two observations per participant. Situations were designed to demonstrate good agreement, systematic bias, or substantial random measurement error. In the situation demonstrating good agreement, all three techniques supported the conclusion that the data were reliable. In the situation demonstrating systematic bias, the ICC and t test suggested the data were not reliable, whereas the Pearson correlation suggested high reliability despite the systematic discrepancy. In the situation representing substantial random measurement error where low reliability was expected, the ICC and Pearson coefficient accurately illustrated this. The t test suggested the data were reliable. The ICC is the preferred technique to measure reliability. Although there are some limitations associated with the use of this technique, they can be overcome.

Human pose tracking in low dimensional space enhanced by limb correction

This paper proposes a two-level 3D human pose tracking method for a specific action captured by several cameras. The generation of pose estimates relies on fitting a 3D articulated model on a Visual Hull generated from the input images. First, an initial pose estimate is constrained by a low dimensional manifold learnt by Temporal Laplacian Eigenmaps. Then, an improved global pose is calculated by refining individual limb poses. The validation of our method uses a public standard dataset and demonstrates its accurate and computational efficiency. © 2011 IEEE.

Online Multiperson Tracking With Occlusion Reasoning and Unsupervised Track Motion Model

We address the problem of multi-target tracking in realistic crowded conditions by introducing a novel dual-stage online tracking algorithm. The problem of data-association between tracks and detections, based on appearance, is often complicated by partial occlusion. In the first stage, we address the issue of occlusion with a novel method of robust data-association, that can be used to compute the appearance similarity between tracks and detections without the need for explicit knowledge of the occluded regions. In the second stage, broken tracks are linked based on motion and appearance, using an online-learned linking model. The online-learned motion-model for track linking uses the confident tracks from the first stage tracker as training examples. The new approach has been tested on the town centre dataset and has performance comparable with the present state-of-the-art

Robust Multimodal Person Identification With Limited Training Data

This paper presents a novel method of audio-visual feature-level fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there are limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new multimodal feature representation and a modified cosine similarity are introduced to combine and compare bimodal features with limited training data, as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal dataset created from the SPIDRE speaker recognition database and AR face recognition database with variable noise corruption of speech and occlusion in the face images. The system's speaker identification performance on the SPIDRE database, and facial identification performance on the AR database, is comparable with the literature. Combining both modalities using the new method of multimodal fusion leads to significantly improved accuracy over the unimodal systems, even when both modalities have been corrupted. The new method also shows improved identification accuracy compared with the bimodal systems based on multicondition model training or missing-feature decoding alone.

An Examination of Transformation Techniques to Investigate and Interpret Multivariate Geochemical Data Analysis: Tellus Case Study

This research aims to use the multivariate geochemical dataset, generated by the Tellus project, to investigate the appropriate use of transformation methods to maintain the integrity of geochemical data and inherent constrained behaviour in multivariate relationships. The widely used normal score transform is compared with the use of a stepwise conditional transform technique. The Tellus Project, managed by GSNI and funded by the Department of Enterprise Trade and Development and the EU’s Building Sustainable Prosperity Fund, involves the most comprehensive geological mapping project ever undertaken in Northern Ireland. Previous study has demonstrated spatial variability in the Tellus data but geostatistical analysis and interpretation of the datasets requires use of an appropriate methodology that reproduces the inherently complex multivariate relations. Previous investigation of the Tellus geochemical data has included use of Gaussian-based techniques. However, earth science variables are rarely Gaussian, hence transformation of data is integral to the approach. The multivariate geochemical dataset generated by the Tellus project provides an opportunity to investigate the appropriate use of transformation methods, as required for Gaussian-based geostatistical analysis. In particular, the stepwise conditional transform is investigated and developed for the geochemical datasets obtained as part of the Tellus project. The transform is applied to four variables in a bivariate nested fashion due to the limited availability of data. Simulation of these transformed variables is then carried out, along with a corresponding back transformation to original units. Results show that the stepwise transform is successful in reproducing both univariate statistics and the complex bivariate relations exhibited by the data. Greater fidelity to multivariate relationships will improve uncertainty models, which are required for consequent geological, environmental and economic inferences.

Haplotype association analysis of genes within the WNT signalling pathways in diabetic nephropathy

Background: Renal interstitial fibrosis and glomerular sclerosis are hallmarks of diabetic nephropathy (DN) and several studies have implicated members of the WNT pathways in these pathological processes. This study comprehensively examined common genetic variation within the WNT pathway for association with DN.

Methods: Genes within the WNT pathways were selected on the basis of nominal significance and consistent direction of effect in the GENIE meta-analysis dataset. Common SNPs and common haplotypes were examined within the selected WNT pathway genes in a white population with type 1 diabetes, discordant for DN (cases: n = 718; controls: n = 749). SNPs were genotyped using Sequenom or Taqman assays. Association analyses were performed using PLINK, to compare allele and haplotype frequencies in cases and controls. Correction for multiple testing was performed by either permutation testing or using false discovery rate.

Results: A logistic regression model including collection centre, duration of diabetes, and average HbA1c as covariates highlighted three SNPs in GSK3B (rs17810235, rs17471, rs334543), two in DAAM1 (rs1253192, rs1252906) and one in NFAT5 (rs17297207) as being significantly (P< 0.05) associated with DN, however these SNPs did not remain significant after correction for multiple testing. Logistic regression of haplotypes, with ESRD as the outcome, and pairwise interaction analyses did not yield any significant results after correction for multiple testing.

Conclusions: These results indicate that both common SNPs and common haplotypes of WNT pathway genes are not strongly associated with DN. However, this does not completely exclude these or the WNT pathways from association with DN, as unidentified rare genetic or copy number variants could still contribute towards the genetic architecture of DN.© 2013 Kavanagh et al.; licensee BioMed Central Ltd.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. © 2013 McArt et al.