Development of a barcoding database for the UK Collembola: early results

We report early results from a project to accumulate COI barcodes from UK Collembola to conrm taxonomy and explore their status at an international level. We validated COI sequences for 48 species of Collembola, ranging from 335–670 bp. Of these, seventeen species matched public sequences of the same name, six species were identiable but the molecular identity disagreed with the morphological identication, and twenty ve species gave no reliable match. The successful matches included accurate matches to BINs from countries far from the UK, including Canada, South Africa and Russia. We suggest that, in many cases, these may have been accidentally transported with horticultural materials

Lesion detection and Grading of Diabetic Retinopathy via Two-stages Deep Convolutional Neural Networks

We propose an automatic diabetic retinopathy (DR) analysis algorithm based on two-stages deep convolutional neural networks (DCNN). Compared to existing DCNN-based DR detection methods, the proposed algorithm have the following advantages: (1) Our method can point out the location and type of lesions in the fundus images, as well as giving the severity grades of DR. Moreover, since retina lesions and DR severity appear with different scales in fundus images, the integration of both local and global networks learn more complete and specific features for DR analysis. (2) By introducing imbalanced weighting map, more attentions will be given to lesion patches for DR grading, which significantly improve the performance of the proposed algorithm. In this study, we label 12,206 lesion patches and re-annotate the DR grades of 23,595 fundus images from Kaggle competition dataset. Under the guidance of clinical ophthalmologists, the experimental results show that our local lesion detection net achieve comparable performance with trained human observers, and the proposed imbalanced weighted scheme also be proved to significantly improve the capability of our DCNN-based DR grading algorithm

Associations between data-driven lifestyle profiles and cognitive function in the AusDiab study

Background: Mounting evidence highlights the importance of combined modifiable lifestyle factors in reducing risk of cognitive decline and dementia. Several a priori additive scoring approaches have been established; however, limited research has employed advanced data-driven approaches to explore this association. This study aimed to examine the association between data-driven lifestyle profiles and cognitive function in community-dwelling Australian adults. Methods: A cross-sectional study of 4561 Australian adults (55.3% female, mean age 60.9 ± 11.3 years) was conducted. Questionnaires were used to collect self-reported data on diet, physical activity, sedentary time, smoking status, and alcohol consumption. Cognitive testing was undertaken to assess memory, processing speed, and vocabulary and verbal knowledge. Latent Profile Analysis (LPA) was conducted to identify subgroups characterised by similar patterns of lifestyle behaviours. The resultant subgroups, or profiles, were then used to further explore associations with cognitive function using linear regression models and an automatic Bolck, Croon & Hagenaars (BCH) approach. Results: Three profiles were identified: (1) “Inactive, poor diet” (76.3%); (2) “Moderate activity, non-smokers” (18.7%); and (3) “Highly active, unhealthy drinkers” (5.0%). Profile 2 “Moderate activity, non-smokers” exhibited better processing speed than Profile 1 “Inactive, poor diet”. There was also some evidence to suggest Profile 3 “Highly active, unhealthy drinkers” exhibited poorer vocabulary and verbal knowledge compared to Profile 1 and poorer processing speed and memory scores compared to Profile 2. Conclusion: In this population of community-dwelling Australian adults, a sub-group characterised by moderate activity levels and higher rates of non-smoking had better cognitive function compared to two other identified sub-groups. This study demonstrates how LPA can be used to highlight sub-groups of a population that may be at increased risk of dementia and benefit most from lifestyle-based multidomain intervention strategies

Inter-reader agreement of the PI-QUAL score for prostate MRI quality in the NeuroSAFE PROOF trial

Objectives: The Prostate Imaging Quality (PI-QUAL) score assesses the quality of multiparametric MRI (mpMRI). A score of 1 means all sequences are below the minimum standard of diagnostic quality, 3 implies that the scan is of sufficient diagnostic quality, and 5 means that all three sequences are of optimal diagnostic quality. We investigated the inter-reader reproducibility of the PI-QUAL score in patients enrolled in the NeuroSAFE PROOF trial. Methods: We analysed the scans of 103 patients on different MR systems and vendors from 12 different hospitals. Two dedicated radiologists highly experienced in prostate mpMRI independently assessed the PI-QUAL score for each scan. Interobserver agreement was assessed using Cohen’s kappa with standard quadratic weighting (κw) and percent agreement. Results: The agreement for each single PI-QUAL score was strong (κw = 0.85 and percent agreement = 84%). A similar agreement (κw = 0.82 and percent agreement = 84%) was observed when the scans were clustered into three groups (PI-QUAL 1–2 vs PI-QUAL 3 vs PI-QUAL 4–5). The agreement in terms of diagnostic quality for each single sequence was highest for T2-weighted imaging (92/103 scans; 89%), followed by dynamic contrast-enhanced sequences (91/103; 88%) and diffusion-weighted imaging (80/103; 78%). Conclusion: We observed strong reproducibility in the assessment of PI-QUAL between two radiologists with high expertise in prostate mpMRI. At present, PI-QUAL offers clinicians the only available tool for evaluating and reporting the quality of prostate mpMRI in a systematic manner but further refinements of this scoring system are warranted

Assessing the performance of multiobjective genetic algorithms for optimization of a batch process scheduling problem

Scheduling optimization problems provide much potential for innovative solutions by genetic algorithms. The complexities, constraints and practicalities of the scheduling process motivate the development of genetic algorithm (GA) techniques to allow innovative and flexible scheduling solutions. Multiobjective genetic algorithms (MOGAs) extend the standard evolutionary-based genetic algorithm optimization technique to allow individual treatment of several objectives simultaneously. This allows the user to attempt to optimize several conflicting objectives, and to explore the trade-offs, conflicts and constraints inherent in this process. The area of MOGA performance assessment and comparison is a relatively new field, as much research concentrates on applications rather than the theory. However, the theoretical exploration of MOGA performance can have tangible effects on the development of highly practical applications, such as the process plant scheduling system under development in this work. By assessing and comparing the strengths, variations and limitations of the developing MOGA using a quantitative method, a highly efficient MOGA can develop to suit the application. The user can also gain insight into behaviour the application itself. In this work, four MOGAs are implemented to solve a process scheduling optimization problem; using two and five objectives, and two schedule building rules

Interleukin-1 regulates multiple atherogenic mechanisms in response to fat feeding

Background: Atherosclerosis is an inflammatory process that develops in individuals with known risk factors that include hypertension and hyperlipidaemia, influenced by diet. However, the interplay between diet, inflammatory mechanisms and vascular risk factors requires further research. We hypothesised that interleukin-1 (IL-1) signaling in the vessel wall would raise arterial blood pressure and promote atheroma. Methodology/Principal Findings: Apoe(-/-) and Apoe(-/-)/IL-1R1(-/-) mice were fed high fat diets for 8 weeks, and their blood pressure and atherosclerosis development measured. Apoe(-/-)/IL-R1(-/-) mice had a reduced blood pressure and significantly less atheroma than Apoe(-/-) mice. Selective loss of IL-1 signaling in the vessel wall by bone marrow transplantation also reduced plaque burden (p<0.05). This was associated with an IL-1 mediated loss of endothelium-dependent relaxation and an increase in vessel wall Nox 4. Inhibition of IL-1 restored endothelium-dependent vasodilatation and reduced levels of arterial oxidative stress. Conclusions/Significance: The IL-1 cytokine system links atherogenic environmental stimuli with arterial inflammation, oxidative stress, increased blood pressure and atherosclerosis. This is the first demonstration that inhibition of a single cytokine can block the rise in blood pressure in response to an environmental stimulus. IL-1 inhibition may have profound beneficial effects on atherogenesis in man

Ethnic differences in Glycaemic control in people with type 2 diabetes mellitus living in Scotland

Background and Aims: Previous studies have investigated the association between ethnicity and processes of care and intermediate outcomes of diabetes, but there are limited population-based studies available. The aim of this study was to use population-based data to investigate the relationships between ethnicity and glycaemic control in men and women with diabetes mellitus living in Scotland.&lt;p&gt;&lt;/p&gt; Methods: We used a 2008 extract from the population-based national electronic diabetes database of Scotland. The association between ethnicity with mean glycaemic control in type 2 diabetes mellitus was examined in a retrospective cohort study, including adjustment for a number of variables including age, sex, socioeconomic status, body mass index (BMI), prescribed treatment and duration of diabetes.&lt;p&gt;&lt;/p&gt; Results: Complete data for analyses were available for 56,333 White Scottish adults, 2,535 Pakistanis, 857 Indians, 427 Chinese and 223 African-Caribbeans. All other ethnic groups had significantly (p&#60;0.05) greater proportions of people with suboptimal glycaemic control (HbA1c &#62;58 mmol/mol, 7.5%) compared to the White Scottish group, despite generally younger mean age and lower BMI. Fully adjusted odds ratios for suboptimal glycaemic control were significantly higher among Pakistanis and Indians (1.85, 95% CI: 1.68–2.04, and 1.62,95% CI: 1.38–1.89) respectively.&lt;p&gt;&lt;/p&gt; Conclusions: Pakistanis and Indians with type 2 diabetes mellitus were more likely to have suboptimal glycaemic control than the white Scottish population. Further research on health services and self-management are needed to understand the association between ethnicity and glycaemic control to address ethnic disparities in glycaemic control.&lt;p&gt;&lt;/p&gt