Does present use of cardiovascular medication reflect elevated cardiovascular risk scores estimated ten years ago? A population based longitudinal observational study

Background It is desirable that those at highest risk of cardiovascular disease should have priority for preventive measures, eg. treatment with prescription drugs to modify their risk. We wanted to investigate to what extent present use of cardiovascular medication (CVM) correlates with cardiovascular risk estimated by three different risk scores (Framingham, SCORE and NORRISK) ten years ago. Methods Prospective logitudinal observational study of 20 252 participants in The Hordaland Health Study born 1950-57, not using CVM in 1997-99. Prescription data obtained from The Norwegian Prescription Database in 2008. Results 26% of men and 22% of women aged 51-58 years had started to use some CVM during the previous decade. As a group, persons using CVM scored significantly higher on the risk algorithms Framingham, SCORE and NORRISK compared to those not treated. 16-20% of men and 20-22% of women with risk scores below the high-risk thresholds for the three risk scores were treated with CVM, while 60-65% of men and 25-45% of women with scores above the high-risk thresholds received no treatment. Among women using CVM, only 2.2% (NORRISK), 4.4% (SCORE) and 14.5% (Framingham) had risk scores above the high-risk values. Low education, poor self-reported general health, muscular pains, mental distress (in females only) and a family history of premature cardiovascular disease correlated with use of CVM. Elevated blood pressure was the single factor most strongly predictive of CVM treatment. Conclusion Prescription of CVM to middle-aged individuals by large seems to occur independently of estimated total cardiovascular risk, and this applies especially to females

Mapping Migratory Bird Prevalence Using Remote Sensing Data Fusion

This is the publisher’s final pdf. The published article is copyrighted by the Public Library of Science and can be found at: http://www.plosone.org/home.action.Background: Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. \ud \ud Methodology and Principal Findings: A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. \ud \ud Conclusion and Significance: Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level

SLC6A3 and body mass index in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial

<p>Abstract</p> <p>Background</p> <p>To investigate the contribution of the dopamine transporter to dopaminergic reward-related behaviors and anthropometry, we evaluated associations between polymorphisms at the dopamine transporter gene(<it>SLC6A3</it>) and body mass index (BMI), among participants in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial.</p> <p>Methods</p> <p>Four polymorphisms (rs6350, rs6413429, rs6347 and the 3' variable number of tandem repeat (3' VNTR) polymorphism) at the <it>SLC6A3 </it>gene were genotyped in 2,364 participants selected from the screening arm of PLCO randomly within strata of sex, age and smoking history. Height and weight at ages 20 and 50 years and baseline were assessed by questionnaire. BMI was calculated and categorized as underweight, normal, overweight and obese (<18.5, 18.5–24.9, 25.0–29.9, or ≥ 30 kg/m², respectively). Odds ratios (ORs) and 95% confidence intervals (CIs) of <it>SLC6A3 </it>genotypes and haplotypes were computed using conditional logistic regression.</p> <p>Results</p> <p>Compared with individuals having a normal BMI, obese individuals at the time of the baseline study questionnaire were less likely to possess the <it>3' </it>VNTR variant allele with 9 copies of the repeated sequence in a dose-dependent model (** is referent; OR_*9= 0.80, OR₉₉= 0.47, p_trend= 0.005). Compared with individuals having a normal BMI at age 50, overweight individuals (A-C-G-* is referent; OR_A-C-G-9= 0.80, 95% CI 0.65–0.99, p = 0.04) and obese individuals (A-C-G-* is referent; OR_A-C-G-9= 0.70, 95% CI 0.49–0.99, p = 0.04) were less likely to possess the haplotype with the 3'variant allele (A-C-G-9).</p> <p>Conclusion</p> <p>Our results support a role of genetic variation at the dopamine transporter gene, <it>SLC6A3</it>, as a modifier of BMI.</p

The effect of high-polyphenol Mediterranean diet on visceral adiposity: the DIRECT PLUS randomized controlled trial

Background Mediterranean (MED) diet is a rich source of polyphenols, which benefit adiposity by several mechanisms. We explored the effect of the green-MED diet, twice fortified in dietary polyphenols and lower in red/processed meat, on visceral adipose tissue (VAT). Methods In the 18-month Dietary Intervention Randomized Controlled Trial PoLyphenols UnproceSsed (DIRECT-PLUS) weight-loss trial, 294 participants were randomized to (A) healthy dietary guidelines (HDG), (B) MED, or (C) green-MED diets, all combined with physical activity. Both isocaloric MED groups consumed 28 g/day of walnuts (+ 440 mg/day polyphenols). The green-MED group further consumed green tea (3–4 cups/day) and Wolffia globosa (duckweed strain) plant green shake (100 g frozen cubes/day) (+ 800mg/day polyphenols) and reduced red meat intake. We used magnetic resonance imaging (MRI) to quantify the abdominal adipose tissues. Results Participants (age = 51 years; 88% men; body mass index = 31.2 kg/m2; 29% VAT) had an 89.8% retention rate and 79.3% completed eligible MRIs. While both MED diets reached similar moderate weight (MED: − 2.7%, green-MED: − 3.9%) and waist circumference (MED: − 4.7%, green-MED: − 5.7%) loss, the green-MED dieters doubled the VAT loss (HDG: − 4.2%, MED: − 6.0%, green-MED: − 14.1%; p < 0.05, independent of age, sex, waist circumference, or weight loss). Higher dietary consumption of green tea, walnuts, and Wolffia globosa; lower red meat intake; higher total plasma polyphenols (mainly hippuric acid), and elevated urine urolithin A polyphenol were significantly related to greater VAT loss (p < 0.05, multivariate models). Conclusions A green-MED diet, enriched with plant-based polyphenols and lower in red/processed meat, may be a potent intervention to promote visceral adiposity regression

Anomalous visual experience is linked to perceptual uncertainty and visual imagery vividness

An imbalance between top-down and bottom-up processing on perception (specifically, over-reliance on top-down processing) can lead to anomalous perception, such as illusions. One factor that may be involved in anomalous perception is visual mental imagery, which is the experience of “seeing” with the mind’s eye. There are vast individual differences in self-reported imagery vividness, and more vivid imagery is linked to a more sensory-like experience. We, therefore, hypothesized that susceptibility to anomalous perception is linked to individual imagery vividness. To investigate this, we adopted a paradigm that is known to elicit the perception of faces in pure visual noise (pareidolia). In four experiments, we explored how imagery vividness contributes to this experience under different response instructions and environments. We found strong evidence that people with more vivid imagery were more likely to see faces in the noise, although removing suggestive instructions weakened this relationship. Analyses from the first two experiments led us to explore confidence as another factor in pareidolia proneness. We, therefore, modulated environment noise and added a confidence rating in a novel design. We found strong evidence that pareidolia proneness is correlated with uncertainty about real percepts. Decreasing perceptual ambiguity abolished the relationship between pareidolia proneness and both imagery vividness and confidence. The results cannot be explained by incidental face-like patterns in the noise, individual variations in response bias, perceptual sensitivity, subjective perceptual thresholds, viewing distance, testing environments, motivation, gender, or prosopagnosia. This indicates a critical role of mental imagery vividness and perceptual uncertainty in anomalous perceptual experience. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00426-020-01364-7) contains supplementary material, which is available to authorized users

The consumer scam: an agency-theoretic approach

Despite the extensive body of literature that aims to explain the phenomenon of consumer scams, the structure of information in scam relationships remains relatively understudied. The purpose of this article is to develop an agency-theoretical approach to the study of information in perpetrator-victim interactions. Drawing a distinction between failures of observation and failures of judgement in the pre-contract phase, we introduce a typology and a set of propositions that explain the severity of adverse selection problems in three classes of scam relationships. Our analysis provides a novel, systematic explanation of the structure of information that facilitates scam victimisation, while also enabling critical scrutiny of a core assumption in agency theory regarding contract design. We highlight the role of scam perpetrators as agents who have access to private information and exercise considerable control over the terms and design of scam relationships. Focusing on the consumer scam context, we question a theoretical assumption, largely taken for granted in the agency literature, that contact design is necessarily in the purview of the uninformed principal

A Macroecological Analysis of SERA Derived Forest Heights and Implications for Forest Volume Remote Sensing

Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H100, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H100 and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 102–106 plants/hectare and heights 6–49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H100

The protocadherin 17 gene affects cognition, personality, amygdala structure and function, synapse development and risk of major mood disorders

Major mood disorders, which primarily include bipolar disorder and major depressive disorder, are the leading cause of disability worldwide and pose a major challenge in identifying robust risk genes. Here, we present data from independent large-scale clinical data sets (including 29 557 cases and 32 056 controls) revealing brain expressed protocadherin 17 (PCDH17) as a susceptibility gene for major mood disorders. Single-nucleotide polymorphisms (SNPs) spanning the PCDH17 region are significantly associated with major mood disorders; subjects carrying the risk allele showed impaired cognitive abilities, increased vulnerable personality features, decreased amygdala volume and altered amygdala function as compared with non-carriers. The risk allele predicted higher transcriptional levels of PCDH17 mRNA in postmortem brain samples, which is consistent with increased gene expression in patients with bipolar disorder compared with healthy subjects. Further, overexpression of PCDH17 in primary cortical neurons revealed significantly decreased spine density and abnormal dendritic morphology compared with control groups, which again is consistent with the clinical observations of reduced numbers of dendritic spines in the brains of patients with major mood disorders. Given that synaptic spines are dynamic structures which regulate neuronal plasticity and have crucial roles in myriad brain functions, this study reveals a potential underlying biological mechanism of a novel risk gene for major mood disorders involved in synaptic function and related intermediate phenotypes