Progression of retinal pigment epithelial atrophy in stargardt disease

• PURPOSE: To evaluate retinal pigment epithelial (RPE) atrophy in patients with Stargardt disease using autofluorescence imaging (AF). • DESIGN: Retrospective observational case series. • METHODS: Demographics, best-corrected visual acuity (BCVA), AF images, and electrophysiology responses (group 1, macular dysfunction; group 2, macula + cone dysfunction; group 3, macula + cone-rod dysfunction) were evaluated at presentation and follow-up in a group of 12 patients (24 eyes) with Stargardt disease. The existence, development, and rate of enlargement of areas of RPE atrophy over time were evaluated using AF imaging. A linear regression model was used to investigate the effects of AF and electrophysiology on rate of atrophy enlargement and BCVA, adjusting for age of onset and duration of disease. • RESULTS: Eight male and 4 female patients (median age 42 years; range 24-69 years) were followed for a median of 41.5 months (range 13-66 months). All 12 patients had reduced AF compatible with RPE atrophy at presentation and in all patients the atrophy enlarged during follow-up. The mean rate of atrophy enlargement for all patients was 1.58 mm /y (SD 1.25 mm /y; range 0.13-5.27 mm /y). Only the pattern of functional loss present as detected by electrophysiology was statistically significantly associated with the rate of atrophy enlargement when correcting for other variables (P <.001), with patients in group 3 (macula + cone-rod dysfunction) having the fastest rate of atrophy enlargement (1.97 mm /y, SD 0.70 mm /y) (group 1 [macula] 1.09 mm /y, SD 0.53 mm /y; group 2 [macula + cone] 1.89 mm /y, SD 2.27 mm /y). • CONCLUSION: Variable rates of atrophy enlargement were observed in patients with Stargardt disease. The pattern of functional loss detected on electrophysiology was strongly associated with the rate of atrophy enlargement over time, thus serving as the best prognostic indicator for patients with this inherited retinal disease. © 2012 Elsevier Inc. All rights reserved.

A Randomized Controlled Trial of Interventions to Promote Adjustment in Children With Congenital Heart Disease Entering School and Their Families

Objective: To report on a randomized controlled trial of psychological interventions to promote adjustment in children with congenital heart disease and their families.
Method: Following baseline assessment, 90 children (aged 4–5 years) and their families were randomly assigned to an Intervention or Control group before entering school. 68 (76%) were retained at 10-month follow-up.
Results: Gains were observed on measures of maternal mental health and family functioning. Although no differences were found on measures of child behavior at home or school, children in the intervention group were perceived as “sick” less often by their mother and missed fewer days from school. A regression model, using baseline measures as predictors, highlighted the importance of maternal mental health, worry and child neurodevelopmental functioning for child behavioral outcomes almost a year later.
Conclusions: The intervention promoted clinically significant gains for the child and family. The program is of generalizable significance.

Interventions to improve the appropriate use of polypharmacy for older people

Background
Inappropriate polypharmacy is a particular concern in older people and is associated with negative health outcomes. Choosing the best interventions to improve appropriate polypharmacy is a priority, hence interest in appropriate polypharmacy, where many medicines may be used to achieve better clinical outcomes for patients, is growing.

Objectives
This review sought to determine which interventions, alone or in combination, are effective in improving the appropriate use of polypharmacy and reducing medication-related problems in older people.

Search methods
In November 2013, for this first update, a range of literature databases including MEDLINE and EMBASE were searched, and handsearching of reference lists was performed. Search terms included 'polypharmacy', 'medication appropriateness' and 'inappropriate prescribing'.

Selection criteria
A range of study designs were eligible. Eligible studies described interventions affecting prescribing aimed at improving appropriate polypharmacy in people 65 years of age and older in which a validated measure of appropriateness was used (e.g. Beers criteria, Medication Appropriateness Index (MAI)).

Data collection and analysis
Two review authors independently reviewed abstracts of eligible studies, extracted data and assessed risk of bias of included studies. Study-specific estimates were pooled, and a random-effects model was used to yield summary estimates of effect and 95% confidence intervals (CIs). The GRADE (Grades of Recommendation, Assessment, Development and Evaluation) approach was used to assess the overall quality of evidence for each pooled outcome.

Main results
Two studies were added to this review to bring the total number of included studies to 12. One intervention consisted of computerised decision support; 11 complex, multi-faceted pharmaceutical approaches to interventions were provided in a variety of settings. Interventions were delivered by healthcare professionals, such as prescribers and pharmacists. Appropriateness of prescribing was measured using validated tools, including the MAI score post intervention (eight studies), Beers criteria (four studies), STOPP criteria (two studies) and START criteria (one study). Interventions included in this review resulted in a reduction in inappropriate medication usage. Based on the GRADE approach, the overall quality of evidence for all pooled outcomes ranged from very low to low. A greater reduction in MAI scores between baseline and follow-up was seen in the intervention group when compared with the control group (four studies; mean difference -6.78, 95% CI -12.34 to -1.22). Postintervention pooled data showed a lower summated MAI score (five studies; mean difference -3.88, 95% CI -5.40 to -2.35) and fewer Beers drugs per participant (two studies; mean difference -0.1, 95% CI -0.28 to 0.09) in the intervention group compared with the control group. Evidence of the effects of interventions on hospital admissions (five studies) and of medication-related problems (six studies) was conflicting.

Authors' conclusions
It is unclear whether interventions to improve appropriate polypharmacy, such as pharmaceutical care, resulted in clinically significant improvement; however, they appear beneficial in terms of reducing inappropriate prescribing.

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.

Centennial-scale climate change in Ireland during the Holocene

We examine mid- to late Holocene centennial-scale climate variability in Ireland using proxy data from peatlands, lakes and a speleothem. A high degree of between-record variability is apparent in the proxy data and significant chronological uncertainties are present. However, tephra layers provide a robust tool for correlation and improve the chronological precision of the records. Although we can find no statistically significant coherence in the dataset as a whole, a selection of high-quality peatland water table reconstructions co-vary more than would be expected by chance alone. A locally weighted regression model with bootstrapping can be used to construct a ‘best-estimate’ palaeoclimatic reconstruction from these datasets. Visual comparison and cross-wavelet analysis of peatland water table compilations from Ireland and Northern Britain show that there are some periods of coherence between these records. Some terrestrial palaeoclimatic changes in Ireland appear to coincide with changes in the North Atlantic thermohaline circulation and solar activity. However, these relationships are inconsistent and may be obscured by chronological uncertainties. We conclude by suggesting an agenda for future Holocene climate research in Ireland. ©2013 Elsevier B.V. All rights reserved.

Country-of-origin effects on Russian wine consumers

In recent years, Russia has experienced significant economic growth. The wine industry is among those most affected by increases in disposable income. As a consequence, Russian wine importers have widened the range at the upper end of the quality spectrum. In the current scenario, some key questions arise concerning consumer attitudes toward wine and the way it is perceived in this evolving market. This article attempts to investigate such concerns through a choice experiment approach conducted by means of a questionnaire-based survey submitted to 388 Russian households located in the country's three largest cities (Moscow, Saint Petersburg, and Novosibirsk). In the experiment, respondents were asked to choose their favorite wine among seven dry red wines. The stated choices are analyzed using a random utility model to obtain an estimation of the price effect through a triangular distribution. Our results indicate the presence of three distinct market segments in the Russian wine market: a segment with only high-quality, highly priced Italian and French wines, a medium-quality segment currently limited to Spanish wines, and a much lower quality segment of wines in which demand for alcohol is essentially satisfied.

IntCal13 and Marine13 Radiocarbon Age Calibration Curves 0-50,000 Years Cal BP

The IntCal09 and Marine09 radiocarbon calibration curves have been revised utilizing newly available and updated data sets from C measurements on tree rings, plant macrofossils, speleothems, corals, and foraminifera. The calibration curves were derived from the data using the random walk model (RWM) used to generate IntCal09 and Marine09, which has been revised to account for additional uncertainties and error structures. The new curves were ratified at the 21st International Radiocarbon conference in July 2012 and are available as Supplemental Material at www.radiocarbon.org. The database can be accessed at http://intcal.qub.ac.uk/intcal13/.

Optimization through quantum annealing: theory and some applications

Quantum annealing is a promising tool for solving optimization problems, similar in some ways to the traditional ( classical) simulated annealing of Kirkpatrick et al. Simulated annealing takes advantage of thermal fluctuations in order to explore the optimization landscape of the problem at hand, whereas quantum annealing employs quantum fluctuations. Intriguingly, quantum annealing has been proved to be more effective than its classical counterpart in many applications. We illustrate the theory and the practical implementation of both classical and quantum annealing - highlighting the crucial differences between these two methods - by means of results recently obtained in experiments, in simple toy-models, and more challenging combinatorial optimization problems ( namely, Random Ising model and Travelling Salesman Problem). The techniques used to implement quantum and classical annealing are either deterministic evolutions, for the simplest models, or Monte Carlo approaches, for harder optimization tasks. We discuss the pro and cons of these approaches and their possible connections to the landscape of the problem addressed.

Walking Exercise for Chronic Musculoskeletal Pain: Systematic Review and Meta-Analysis

Objective: To systematically review the evidence examining effects of walking interventions on pain and self-reported function in individuals with chronic musculoskeletal pain.
Data Sources: Six electronic databases (Medline, CINAHL, PsychINFO, PEDro, Sport Discus and the Cochrane Central Register of Controlled Trials) were searched from January 1980 up to March 2014.
Study Selection: Randomized and quasi-randomized controlled trials in adults with chronic low back pain, osteoarthritis or fibromyalgia comparing walking interventions to a non-exercise or non-walking exercise control group.
Data Extraction: Data were independently extracted using a standardized form. Methodological quality was assessed using the United States Preventative Services Task Force (USPSTF) system.
Data Synthesis: Twenty-six studies (2384 participants) were included and suitable data from 17 were pooled for meta-analysis with a random effects model used to calculate between group mean differences and 95% confidence intervals. Data were analyzed according to length of follow-up (short-term: ≤8 weeks post randomization; medium-term: >2 months - 12 months; long-term: > 12 months). Interventions were associated with small to moderate improvements in pain at short (mean difference (MD) -5.31, 95% confidence interval (95% CI) -8.06 to -2.56) and medium-term follow-up (MD -7.92, 95% CI -12.37 to -3.48). Improvements in function were observed at short (MD -6.47, 95% CI -12.00 to -0.95), medium (MD -9.31, 95% CI -14.00 to -4.61) and long-term follow-up (MD -5.22, 95% CI 7.21 to -3.23).
Conclusions: Evidence of fair methodological quality suggests that walking is associated with significant improvements in outcome compared to control interventions but longer-term effectiveness is uncertain. Using the USPSTF system, walking can be recommended as an effective form of exercise or activity for individuals with chronic musculoskeletal pain but should be supplemented with strategies aimed at maintaining participation. Further work is also required examining effects on important health related outcomes in this population in robustly designed studies.

Root Cause Analysis by a Combined Sparse Classification and Monte Carlo Approach

Classification methods with embedded feature selection capability are very appealing for the analysis of complex processes since they allow the analysis of root causes even when the number of input variables is high. In this work, we investigate the performance of three techniques for classification within a Monte Carlo strategy with the aim of root cause analysis. We consider the naive bayes classifier and the logistic regression model with two different implementations for controlling model complexity, namely, a LASSO-like implementation with a L1 norm regularization and a fully Bayesian implementation of the logistic model, the so called relevance vector machine. Several challenges can arise when estimating such models mainly linked to the characteristics of the data: a large number of input variables, high correlation among subsets of variables, the situation where the number of variables is higher than the number of available data points and the case of unbalanced datasets. Using an ecological and a semiconductor manufacturing dataset, we show advantages and drawbacks of each method, highlighting the superior performance in term of classification accuracy for the relevance vector machine with respect to the other classifiers. Moreover, we show how the combination of the proposed techniques and the Monte Carlo approach can be used to get more robust insights into the problem under analysis when faced with challenging modelling conditions.

Characterisation of the frequent exacerbator phenotype in COPD patients in a large UK primary care population

BACKGROUND: The 'frequent exacerbator' is recognised as an important phenotype in COPD. Current understanding about this phenotype comes from prospective longitudinal clinical trials in secondary/tertiary care with little information reported in primary care populations.

AIMS: To characterize the frequent-exacerbator phenotype and identify associated risk factors in a large UK primary care COPD population.

METHODS: Using a large database of primary care patients from 80 UK general practices, patients were categorised using GOLD 2014 criteria into high and low risk groups based on exacerbation history. A multivariate logistic regression model was used to investigate covariates associated with the frequent-exacerbator phenotype and risk of experiencing a severe exacerbation (leading to hospitalisation).

RESULTS: Of the total study population (n = 9219), 2612 (28%) fulfilled the criteria for high risk frequent-exacerbators. Independent risk factors (adjusted odds ratio [95% CI]) for ≥2 exacerbations were: most severely impaired modified Medical Research Council (mMRC) dyspnoea score (mMRC grade 4: 4.37 [2.64-7.23]), lower FEV1 percent predicted (FEV1 <30%: 2.42 [1.61-3.65]), co-morbid cardiovascular disease (1.42 [1.19-1.68]), depression (1.56 [1.22-1.99]) or osteoporosis (1.54 [1.19-2.01]), and female gender (1.20 [1.01-1.43]). Older patients (≥75 years), those with most severe lung impairment (FEV1 <30%), those with highest mMRC score and those with co-morbid osteoporosis were identified as most at risk of experiencing exacerbations requiring hospitalisation.

CONCLUSIONS: Although COPD exacerbations occur across all grades of disease severity, female patients with high dyspnoea scores, more severely impaired lung function and co-morbidities are at greatest risk. Elderly patients, with severely impaired lung function, high mMRC scores and osteoporosis are associated with experience of severe exacerbations requiring hospitalisation.

Perception and Automatic Recognition of Laughter from Whole-Body Motion: Continuous and Categorical Perspectives

Despite its importance in social interactions, laughter remains little studied in affective computing. Intelligent virtual agents are often blind to users’ laughter and unable to produce convincing laughter themselves. Respiratory, auditory, and facial laughter signals have been investigated but laughter-related body movements have received less attention. The aim of this study is threefold. First, to probe human laughter perception by analyzing patterns of categorisations of natural laughter animated on a minimal avatar. Results reveal that a low dimensional space can describe perception of laughter “types”. Second, to investigate observers’ perception of laughter (hilarious, social, awkward, fake, and non-laughter) based on animated avatars generated from natural and acted motion-capture data. Significant differences in torso and limb movements are found between animations perceived as laughter and those perceived as non-laughter. Hilarious laughter also differs from social laughter. Different body movement features were indicative of laughter in sitting and standing avatar postures. Third, to investigate automatic recognition of laughter to the same level of certainty as observers’ perceptions. Results show recognition rates of the Random Forest model approach human rating levels. Classification comparisons and feature importance analyses indicate an improvement in recognition of social laughter when localized features and nonlinear models are used.

Metastatic non-small cell lung cancer: a benchmark for quality end-of-life cancer care?

Objectives: To investigate the quality of end-of-life care for patients with metastatic non-small cell lung cancer (NSCLC). Design and participants: Retrospective cohort study of patients from first hospitalisation for metastatic disease until death, using hospital, emergency department and death registration data from Victoria, Australia, between 1 July 2003 and 30 June 2010. Main outcome measures: Emergency department and hospital use; aggressiveness of care including intensive care and chemotherapy in last 30 days; palliative and supportive care provision; and place of death. Results: Metastatic NSCLC patients underwent limited aggressive treatment such as intensive care (5%) and chemotherapy (< 1%) at the end of life; however, high numbers died in acute hospitals (42%) and 61% had a length of stay of greater than 14 days in the last month of life. Although 62% were referred to palliative care services, this occurred late in the illness. In a logistic regression model adjusted for year of metastasis, age, sex, metastatic site and survival, the odds ratio (OR) of dying in an acute hospital bed compared with death at home or in a hospice unit decreased with receipt of palliative care (OR, 0.25; 95% CI, 0.21–0.30) and multimodality supportive care (OR, 0.65; 95% CI, 0.56–0.75). Conclusion: Because early palliative care for patients with metastatic NSCLC is recommended, we propose that this group be considered a benchmark of quality end-of-life care. Future work is required to determine appropriate quality-of-care targets in this and other cancer patient cohorts, with particular focus on the timeliness of palliative care engagement.

Are there latitudinal gradients in species turnover?

Aim To examine the effect on the observed relationship betw een spatial turnover and latitude of both the measure of beta diversity used and the method of analysis.

Location The empirical analyses presented herein are for the New World.

Methods We take the spatial distributions of the owls of the New World as an exemplar data set to investigate the patterns of beta diversity across latitudes revealed by different analytical methods. To illustrate the strengths and weaknesses of alternative measures of beta diversity and different analytical approaches, we also use a simple random distribution model, focusing in particular on the influence of richness gradients and landmass geometry.

Results Our simple spatial model of turnover demonstrates that different combinations of analytical approach and measure of beta diversity can give rise to strikingly different relationships between turnover and latitude. The analyses of the bird data for the owls of the New World demonstrate that this observation extends to real data.

Conclusions For the particular assemblage considered, we present strong evidence that species richness declines at higher latitudes, and there is also some evidence that species turnover is greater nearer the equator, despite conceptual and practical difficulties involved in analysing spatial patterns of species turnover. We suggest some ways of overcoming these difficulties.

Bird diversity and environmental gradients in Britain:a test of the species-energy hypothesis

1. We tested the species diversity-energy hypothesis using the British bird fauna. This predicts that temperature patterns should match diversity patterns. We also tested the hypothesis that the mechanism operates directly through effects of temperature on thermoregulatory loads; this further predicts that seasonal changes in temperature cause matching changes in patterns of diversity, and that species' body mass is influential.

2. We defined four assemblages using migration status (residents or visitors) and season (summer or winter distribution). Records of species' presence/absence in a total of 2362, 10 x 10-km, quadrats covering most of Britain were used, together with a wide selection of habitat, topographic and seasonal climatic data.

3. We fitted a logistic regression model to each species' distribution using the environmental data. We then combined these individual species models mathematically to form a diversity model. Analysis of this composite model revealed that summer temperature was the factor most strongly associated with diversity.

4. Although the species-energy hypothesis was supported, the direct mechanism, predicting an important role for body mass and matching seasonal patterns of change between diversity and temperature, was not supported.

5. However, summer temperature is the best overall explanation for bird diversity patterns in Britain. It is a better predictor of winter diversity than winter temperature. Winter diversity is predicted more precisely from environmental factors than summer diversity.

6. Climate change is likely to influence the diversity of different areas to different extents; for resident species, low diversity areas may respond more strongly as climate change progresses. For winter visitors, higher diversity areas may respond more strongly, while summer visitors are approximately neutral.