The validity of a latent class typology of adolescent drinking patterns

Objectives: This study examined the validity of a latent class typology of adolescent drinking based on four alcohol dimensions; frequency of drinking, quantity consumed, frequency of binge drinking and the number of alcohol related problems encountered. Method: Data used were from the 1970 British Cohort Study sixteen-year-old follow-up. Partial or complete responses to the selected alcohol measures were provided by 6,516 cohort members. The data were collected via a series of postal questionnaires. Results: A five class LCA typology was constructed. Around 12% of the sample were classified as �hazardous drinkers� reporting frequent drinking, high levels of alcohol consumed, frequent binge drinking and multiple alcohol related problems. Multinomial logistic regression, with multiple imputation for missing data, was used to assess the covariates of adolescent drinking patterns. Hazardous drinking was associated with being white, being male, having heavy drinking parents (in particular fathers), smoking, illicit drug use, and minor and violent offending behaviour. Non-significant associations were found between drinking patterns and general mental health and attention deficient disorder. Conclusion: The latent class typology exhibited concurrent validity in terms of its ability to distinguish respondents across a number of alcohol and non-alcohol indicators. Notwithstanding a number of limitations, latent class analysis offers an alternative data reduction method for the construction of drinking typologies that addresses known weaknesses inherent in more tradition classification methods.

A novel GUCY2D mutation, V933A, causes central areolar choroidal dystrophy

Purpose: To identify the genetic cause of central areolar choroidal dystrophy (CACD) in a large Northern Irish family.
Methods: We previously reported linkage of the locus for CACD in this family to an interval of approximately 5 cM on chromosome 17p13 flanked by polymorphic markers D17S1810 and CHLC GATA7B03. We undertook sequence capture, massively-parallel sequencing and computational alignment, base-calling and annotation to identify a causative mutation. Conventional sequencing was used to confirm the results.
Results: Deep sequencing identified a single-base substitution in guanylate cyclase 2D, membrane (retina-specific) (GUCY2D). The novel mutation segregated with the disease phenotype and resulted in substitution of valine by alanine at position 933, within the catalytic domain of the protein. It altered a motif that is strongly conserved in a large number of distantly related proteins across several species, and was predicted to have a damaging effect on protein activity.
Conclusion: Mutations in GUCY2D have previously been associated with dominant cone rod dystrophies (CORD6) and recessive forms of Leber's congenital amaurosis (LCA). This is the first report of GUCY2D mutation causing CACD and adds to our understanding of genotype-phenotype correlation in this heterogeneous group of choroidoretinal dystrophies.

A streamlined life-cycle assessment and decision tool for used tyres recycling

In order to achieve progress towards sustainable resource management, it is essential to evaluate options for the reuse and recycling of secondary raw materials, in order to provide a robust evidence base for decision makers. This paper presents the research undertaken in the development of a web-based decision-support tool (the used tyres resource efficiency tool) to compare three processing routes for used tyres compared to their existing primary alternatives. Primary data on the energy and material flows for the three routes, and their alternatives were collected and analysed. The methodology used was a streamlined life-cycle assessment (sLCA) approach. Processes included were: car tyre baling against aggregate gabions; car tyre retreading against new car tyres; and car tyre shred used in landfill engineering against primary aggregates. The outputs of the assessment, and web-based tool, were estimates of raw materials used, carbon dioxide emissions and costs. The paper discusses the benefits of carrying out a streamlined LCA and using the outputs of this analysis to develop a decision-support tool. The strengths and weakness of this approach are discussed and future research priorities identified which could facilitate the use of life cycle approaches by designers and practitioners.

Life Cycle Assessment guidelines for the sustainable production and recycling of aggregates:The Sustainable Aggregates Resource Management project (SARMa)

The mining/quarrying industry is a sector of industry where there are very few Life Cycle Assessment (LCA) tools, and where the role of LCA has been poorly investigated. A key issue is the integration of three inter-dependent life cycles: Project, Asset and Product. Given the unique features of mining LCAs, this Note from the Field presents a common methodology implemented within the Sustainable Aggregates Resource Management (SARMa) Project (www.sarmaproject.eu) in order to boost adoption of LCA in the aggregate industry in South Eastern Europe. The proposed methodology emphasises the importance of resource efficiency and recycling in the context of a Sustainable Supply Mix of aggregates for the construction industry. Through its adoption, aggregate producers, recyclers, and governmental planners would gain confidence with LCA tools and conduct consistent and meaningful life cycle analyses of natural and recycled aggregates. © 2011 Elsevier Ltd. All rights reserved.

On The Energy-Efficiency of Byte-Addressable Non-Volatile Memory

Non-Volatile Memory (NVM) technology holds promise to replace SRAM and DRAM at various levels of the memory hierarchy. The interest in NVM is motivated by the difficulty faced in scaling DRAM beyond 22 nm and, long-term, lower cost per bit. While offering higher density and negligible static power (leakage and refresh), NVM suffers increased latency and energy per memory access. This paper develops energy and performance models of memory systems and applies them to understand the energy-efficiency of replacing or complementing DRAM with NVM. Our analysis focusses on the application of NVM in main memory. We demonstrate that NVM such as STT-RAM and RRAM is energy-efficient for memory sizes commonly employed in servers and high-end workstations, but PCM is not. Furthermore, the model is well suited to quickly evaluate the impact of changes to the model parameters, which may be achieved through optimization of the memory architecture, and to determine the key parameters that impact system-level energy and performance.

VDR and MEK-ERK dependent induction of the antimicrobial peptide cathelicidin in keratinocytes by lithocholic acid

Cathelicidin is an antimicrobial peptide (AMP) and signaling molecule in innate immunity and a direct target of 1,25-dihydroxyvitamin D3 (1,25D3) in primary human keratinocytes (NHEK). The expression of cathelicidin is dysregulated in various skin diseases and its regulation differs depending on the epithelial cell type. The secondary bile acid lithocholic acid (LCA) is a ligand of the vitamin D receptor (VDR) and can carry out in vivo functions of vitamin D3. Therefore we analyzed cathelicidin mRNA- and peptide expression levels in NHEK and colonic epithelial cells (Caco-2) after stimulation with LCA. We found increased expression of cathelicidin mRNA and peptide in NHEK, in Caco-2 colon cells no effect was observed after LCA stimulation. The VDR as well as MEK-ERK signaled the upregulation of cathelicidin in NHEK induced by LCA. Collectively, our data indicate that cathelicidin induction upon LCA treatment differs in keratinocytes and colonic epithelial cells. Based on these observations LCA-like molecules targeting cathelicidin could be designed for the treatment of cutaneous diseases that are characterized by disturbed cathelicidin expression.

Understanding aerospace composite components' supply chain carbon emissions

This paper examines a large structural component and its supply chain. The component is representative of that used in the production of civil transport aircraft and is manufactured from carbon fibre epoxy resin prepreg, using traditional hand layup and autoclave cure. Life cycle assessment (LCA) is used to predict the component’s production carbon emissions. The results determine the distribution of carbon emissions within the supply chain, identifying the dominant production processes as carbon fibre manufacture and composite part manufacture. The elevated temperature processes of material and part creation, and the associated electricity usage, have a significant impact on the overall production emissions footprint. The paper also demonstrates the calculation of emissions footprint sensitivity to the geographic location and associated energy sources of the supply chain. The results verify that the proposed methodology is capable of quantitatively linking component and supply chain specifics to manufacturing processes and thus identifying the design drivers for carbon emissions in the manufacturing life of the component.