Squirrelpox virus: assessing prevalence, transmission and environmental degradation

Red squirrels (Sciurus vulgaris) declined in Great Britain and Ireland during the last century, due to habitat loss and the introduction of grey squirrels (Sciurus carolinensis), which competitively exclude the red squirrel and act as a reservoir for squirrelpox virus (SQPV). The disease is generally fatal to red squirrels and their ecological replacement by grey squirrels is up to 25 times faster where the virus is present. We aimed to determine: (1) the seropositivity and prevalence of SQPV DNA in the invasive and native species at a regional scale; (2) possible SQPV transmission routes; and, (3) virus degradation rates under differing environmental conditions. Grey (n = 208) and red (n = 40) squirrel blood and tissues were sampled. Enzyme-linked immunosorbent assay (ELISA) and quantitative real-time polymerase chain reaction (qPCR) techniques established seropositivity and viral DNA presence, respectively. Overall 8% of squirrels sampled (both species combined) had evidence of SQPV DNA in their tissues and 22% were in possession of antibodies. SQPV prevalence in sampled red squirrels was 2.5%. Viral loads were typically low in grey squirrels by comparison to red squirrels. There was a trend for a greater number of positive samples in spring and summer than in winter. Possible transmission routes were identified through the presence of viral DNA in faeces (red squirrels only), urine and ectoparasites (both species). Virus degradation analyses suggested that, after 30 days of exposure to six combinations of environments, there were more intact virus particles in scabs kept in warm (25°C) and dry conditions than in cooler (5 and 15°C) or wet conditions. We conclude that SQPV is present at low prevalence in invasive grey squirrel populations with a lower prevalence in native red squirrels. Virus transmission could occur through urine especially during warm dry summer conditions but, more notably, via ectoparasites, which are shared by both species

Trichotillometry: the reliability and practicality of hair pluckability as a method of nutritional assessment

<p>Abstract</p> <p>Background</p> <p>A nutritional assessment method that is quick and easy to conduct would be extremely useful in a complex emergency, where currently there is no agreed practical and acceptable method. Hair pluckability has been suggested to be a useful method of assessing protein nutritional status. The aim was to investigate the reliability of the trichotillometer and to explore the effects of patient characteristics on hair epilation force.</p> <p>Methods</p> <p>Three observers plucked hair from twelve participants to investigate the within- and between-observer reliability. To investigate the effect of patient characteristics on hair pluckability, 12 black African and 12 white volunteers were recruited. Participants completed a short questionnaire to provide basic information on their characteristics and hair.</p> <p>Results</p> <p>Mean hair pluckability measurements for the 12 participants obtained by the three observers (39.5 g, 41.2 g and 32.7 g) were significantly different (p < 0.001). Significant variation between patients was also found (p < 0.001). None of the patient characteristics significantly affected hair pluckability, with the exception of age, although this relationship was not consistent.</p> <p>Conclusion</p> <p>Due to significant variation in measurements, hair pluckability does not appear to be a reliable method for assessing adult nutritional status. Hair pluckability could be a useful method of nutritional assessment in complex humanitarian emergencies but only if the reliability was improved.</p

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression

We applied several regression and deep learning methods to predict fluid intelligence scores from T1-weighted MRI scans as part of the ABCD Neurocognitive Prediction Challenge (ABCD-NP-Challenge) 2019. We used voxel intensities and probabilistic tissue-type labels derived from these as features to train the models. The best predictive performance (lowest mean-squared error) came from Kernel Ridge Regression (KRR; $\lambda=10$), which produced a mean-squared error of 69.7204 on the validation set and 92.1298 on the test set. This placed our group in the fifth position on the validation leader board and first place on the final (test) leader board.Comment: Winning entry in the ABCD Neurocognitive Prediction Challenge at MICCAI 2019. 7 pages plus references, 3 figures, 1 tabl

Heritability estimates of the Big Five personality traits based on common genetic variants

According to twin studies, the Big Five personality traits have substantial heritable components explaining 40–60% of the variance, but identification of associated genetic variants has remained elusive. Consequently, knowledge regarding the molecular genetic architecture of personality and to what extent it is shared across the different personality traits is limited. Using genomic-relatedness-matrix residual maximum likelihood analysis (GREML), we here estimated the heritability of the Big Five personality factors (extraversion, agreeableness, conscientiousness, neuroticism and openness for experience) in a sample of 5011 European adults from 527 469 single-nucleotide polymorphisms across the genome. We tested for the heritability of each personality trait, as well as for the genetic overlap between the personality factors. We found significant and substantial heritability estimates for neuroticism (15%, s.e.=0.08, P=0.04) and openness (21%, s.e.=0.08, P<0.01), but not for extraversion, agreeableness and conscientiousness. The bivariate analyses showed that the variance explained by common variants entirely overlapped between neuroticism and openness (rG=1.00, P <0.001), despite low phenotypic correlation (r=−0.09, P <0.001), suggesting that the remaining unique heritability may be determined by rare or structural variants. As far as we are aware of, this is the first study estimating the shared and unique heritability of all Big Five personality traits using the GREML approach. Findings should be considered exploratory and suggest that detectable heritability estimates based on common variants is shared between neuroticism and openness to experiences

Social Cognitive Role of Schizophrenia Candidate Gene GABRB2

10.1371/journal.pone.0062322PLoS ONE84

Comparison of the sensitivity of the UKCAT and A levels to sociodemographic characteristics: a national study

Background: The UK Clinical Aptitude Test (UKCAT) was introduced to facilitate widening participation in medical and dental education in the UK by providing universities with a continuous variable to aid selection; one that might be less sensitive to the sociodemographic background of candidates compared to traditional measures of educational attainment. Initial research suggested that males, candidates from more advantaged socioeconomic backgrounds and those who attended independent or grammar schools performed better on the test. The introduction of the A* grade at A level permits more detailed analysis of the relationship between UKCAT scores, secondary educational attainment and sociodemographic variables. Thus, our aim was to further assess whether the UKCAT is likely to add incremental value over A level (predicted or actual) attainment in the selection process. Methods: Data relating to UKCAT and A level performance from 8,180 candidates applying to medicine in 2009 who had complete information relating to six key sociodemographic variables were analysed. A series of regression analyses were conducted in order to evaluate the ability of sociodemographic status to predict performance on two outcome measures: A level ‘best of three’ tariff score; and the UKCAT scores. Results: In this sample A level attainment was independently and positively predicted by four sociodemographic variables (independent/grammar schooling, White ethnicity, age and professional social class background). These variables also independently and positively predicted UKCAT scores. There was a suggestion that UKCAT scores were less sensitive to educational background compared to A level attainment. In contrast to A level attainment, UKCAT score was independently and positively predicted by having English as a first language and male sex. Conclusions: Our findings are consistent with a previous report; most of the sociodemographic factors that predict A level attainment also predict UKCAT performance. However, compared to A levels, males and those speaking English as a first language perform better on UKCAT. Our findings suggest that UKCAT scores may be more influenced by sex and less sensitive to school type compared to A levels. These factors must be considered by institutions utilising the UKCAT as a component of the medical and dental school selection process

Cerebral Blood Flow during Rest Associates with General Intelligence and Creativity

Recently, much scientific attention has been focused on resting brain activity and its investigation through such methods as the analysis of functional connectivity during rest (the temporal correlation of brain activities in different regions). However, investigation of the magnitude of brain activity during rest has focused on the relative decrease of brain activity during a task, rather than on the absolute resting brain activity. It is thus necessary to investigate the association between cognitive factors and measures of absolute resting brain activity, such as cerebral blood flow (CBF), during rest (rest-CBF). In this study, we examined this association using multiple regression analyses. Rest-CBF was the dependent variable and the independent variables included two essential components of cognitive functions, psychometric general intelligence and creativity. CBF was measured using arterial spin labeling and there were three analyses for rest-CBF; namely mean gray matter rest-CBF, mean white matter rest-CBF, and regional rest-CBF. The results showed that mean gray and white matter rest-CBF were significantly and positively correlated with individual psychometric intelligence. Furthermore, mean white matter rest-CBF was significantly and positively correlated with creativity. After correcting the effect of mean gray matter rest-CBF the significant and positive correlation between regional rest-CBF in the perisylvian anatomical cluster that includes the left superior temporal gyrus and insula and individual psychometric intelligence was found. Also, regional rest-CBF in the precuneus was significantly and negatively correlated with individual creativity. Significance of these results of regional rest-CBF did not change when the effect of regional gray matter density was corrected. The findings showed mean and regional rest-CBF in healthy young subjects to be correlated with cognitive functions. The findings also suggest that, even in young cognitively intact subjects, resting brain activity (possibly underlain by default cognitive activity or metabolic demand from developed brain structures) is associated with cognitive functions

Defects and lithium migration in Li₂CuO₂

Li2CuO2 is an important candidate material as a cathode in lithium ion batteries. Atomistic simulation methods are used to investigate the defect processes, electronic structure and lithium migration mechanisms in Li2CuO2. Here we show that the lithium energy of migration via the vacancy mechanism is very low, at 0.11 eV. The high lithium Frenkel energy (1.88 eV/defect) prompted the consideration of defect engineering strategies in order to increase the concentration of lithium vacancies that act as vehicles for the vacancy mediated lithium self-diffusion in Li2CuO2. It is shown that aluminium doping will significantly reduce the energy required to form a lithium vacancy from 1.88 eV to 0.97 eV for every aluminium introduced, however, it will also increase the migration energy barrier of lithium in the vicinity of the aluminium dopant to 0.22 eV. Still, the introduction of aluminium is favourable compared to the lithium Frenkel process. Other trivalent dopants considered herein require significantly higher solution energies, whereas their impact on the migration energy barrier was more pronounced. When considering the electronic structure of defective Li2CuO2, the presence of aluminium dopants results in the introduction of electronic states into the energy band gap. Therefore, doping with aluminium is an effective doping strategy to increase the concentration of lithium vacancies, with a minimal impact on the kinetics

Stomach cancer and occupational exposure to asbestos: a meta-analysis of occupational cohort studies

BACKGROUND: A recent Monographs Working Group of the International Agency for Research on Cancer concluded that there is limited evidence for a causal association between exposure to asbestos and stomach cancer. METHODS: We performed a meta-analysis to quantitatively evaluate this association. Random effects models were used to summarise the relative risks across studies. Sources of heterogeneity were explored through subgroup analyses and meta-regression. RESULTS: We identified 40 mortality cohort studies from 37 separate papers, and cancer incidence data were extracted for 15 separate cohorts from 14 papers. The overall meta-SMR for stomach cancer for total cohort was 1.15 (95% confidence interval 1.03–1.27), with heterogeneous results across studies. Statistically significant excesses were observed in North America and Australia but not in Europe, and for generic asbestos workers and insulators. Meta-SMRs were larger for cohorts reporting a SMR for lung cancer above 2 and cohort sizes below 1000. CONCLUSIONS: Our results support the conclusion by IARC that exposure to asbestos is associated with a moderate increased risk of stomach cancer

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models