The selection of search sources influences the findings of a systematic review of people’s views: a case study in public health

Background For systematic reviews providing evidence for policy decisions in specific geographical regions, there is a need to minimise regional bias when seeking out relevant research studies. Studies on people’s views tend to be dispersed across a range of bibliographic databases and other search sources. It is recognised that a comprehensive literature search can provide unique evidence not found from a focused search; however, the geographical focus of databases as a potential source of bias on the findings of a research review is less clear. This case study describes search source selection for research about people’s views and how supplementary searches designed to redress geographical bias influenced the findings of a systematic review. Our research questions are: a) what was the impact of search methods employed to redress potential database selection bias on the overall findings of the review? and b) how did each search source contribute to the identification of all the research studies included in the review? Methods The contribution of 25 search sources in locating 28 studies included within a systematic review on UK children’s views of body size, shape and weight was analysed retrospectively. The impact of utilising seven search sources chosen to identify UK-based literature on the review’s findings was assessed. Results Over a sixth (5 out of 28) of the studies were located only through supplementary searches of three sources. These five studies were of a disproportionally high quality compared with the other studies in the review. The retrieval of these studies added direction, detail and strength to the overall findings of the review. All studies in the review were located within 21 search sources. Precision for 21 sources ranged from 0.21% to 1.64%. Conclusions For reducing geographical bias and increasing the coverage and context-specificity of systematic reviews of people’s perspectives and experiences, searching that is sensitive and aimed at reducing geographical bias in database sources is recommended

Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

Background Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure. Methods We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008–11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003–13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken. Findings Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10−10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10−8 DHFR p=8·37 × 10−7 MTRNR2L2 p=2·15 × 10−9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10−4 DHFR p=8·45 × 10−4 MTRNR2L2 p=1·20 × 10−3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10−8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16–0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06–0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset. Interpretation The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation

A modified-optimal energy management strategy of fuel cell- battery hybrid energy storage system for marine application

Considering the present limitations of battery technology, a hybrid combination of fuel cells (FCs) and batteries can be considered as one of the environment friendly, reliable, and efficient energy solutions for marine ship applications. However, proper energy and power management are some of the critical issues for fuel cell-based energy storage system (ESS) because the degradation of a fuel cell lifetime is strongly affected by its operating condition. In this paper, a modified-optimal energy management strategy (MOEMS) is proposed which determines the power-split ratio between the FC and battery efficiently. By integrating the popular gradient-descent algorithm into a state machine control the proposed controller is realized. The performance of the MOEMS is compared with conventional EMS with simulation. Results suggest that the proposed EMS improve the fuel cell lifetime by 44% while reducing the fuel consumption by 7% compared to the basic EMSs