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Virtual Reality (VR) has been increasingly referred to as the “ultimate empathy machine” since it allows users to experience any situation from any point of view. However, empirical evidence supporting the claim that VR is a more effective method of eliciting empathy than traditional perspective-taking is limited. Two experiments were conducted in order to compare the short and long-term effects of a traditional perspective-taking task and a VR perspective-taking task (Study 1), and to explore the role of technological immersion when it comes to different types of mediated perspective-taking tasks (Study 2). Results of Study 1 show that over the course of eight weeks participants in both conditions reported feeling empathetic and connected to the homeless at similar rates, however, participants who became homeless in VR had more positive, longer-lasting attitudes toward the homeless and signed a petition supporting the homeless at a significantly higher rate than participants who performed a traditional perspective-taking task. Study 2 compared three different types of perspective-taking tasks with different levels of immersion (traditional vs. desktop computer vs. VR) and a control condition (where participants received fact-driven information about the homeless). Results show that participants who performed any type of perspective-taking task reported feeling more empathetic and connected to the homeless than the participants who only received information. Replicating the results from Study 1, there was no difference in self-report measures for any of the perspective-taking conditions, however, a significantly higher number of participants in the VR condition signed a petition supporting affordable housing for the homeless compared to the traditional and less immersive conditions. We discuss the theoretical and practical implications of these findings. [ABSTRACT FROM AUTHOR]

Objective: This meta-analysis evaluated the efficacy of behavioral classroom programs on symptoms of Attention-deficit Hyperactivity Disorder or Oppositional Defiant and/or Conduct Disorder in primary school children. Method: Online database searches (in PubMed, Embase, Psycinfo, and Eric) yielded nineteen randomized controlled trials (N = 18,094), comparing behavioral classroom programs (including multimodal programs involving a classroom program) to no treatment/treatment as usual. Random-effects meta-analyses were conducted for teacher-rated and classroom-observed disruptive classroom behavior and for classroom-observed on-task behavior. Post-hoc analyses investigated whether effects depended on type and severity of problem behavior. Meta-regressions studied the moderating effects of age, gender, and intervention duration. Results: Small positive effects were found on teacher-rated disruptive behavior (d = -0.20) and classroom-observed on-task behavior (d = 0.39). Program effects on teacher-rated disruptive behavior were unrelated to age, gender, type and severity, but negatively associated with intervention duration (R2 = 0.43). Conclusion: Behavioral classroom programs have small beneficial effects on disruptive behavior and on-task behavior. Results advocate universal programs for entire classrooms to prevent and reduce disruptive classroom behavior. [ABSTRACT FROM AUTHOR]

Child–nature interaction has undergone drastic changes in modern history, from a free outdoor childhood to a confined daily life connected to electronic devices, with negative consequences to development and well-being. Any resulting lack of connection to the natural environment can hamper involvement in solving environmental problems. This research attempted to assess children’s perceptions of nature, as well as their feelings and values. Six- to 14-year-old children from the Tupinambá group (n = 91), an indigenous society in Brazil, and from New York (n = 54) drew pictures of nature and answered five questions about their drawings, feelings, and values in regard to natural environments. Quantitative (descriptive) and qualitative (content) analyses of the drawings were carried out, and their liveness and animism were estimated. The answers given by children to the questions about nature were organized into emerging categories from the data. The Tupinambá children’s drawings were generally livelier than those of the New York children. However, the difference failed to reach statistical significance among the younger children, and the difference only approached significance among the older children. The drawings of the Tupinambá contained more animism, depicting non-humans and non-animals with facial expressions, than those of the New Yorkers. Compared with the New Yorkers, the Tupinambá children more often included human constructions such as roads and houses in their drawings. The indigenous children more often saw human and non-human elements as integrated compared with the nonindigenous children. The study reinforces theoretical tendencies about the environmental perception of children in relation to the natural environment and highlights peculiarities of the participating groups, indicating relevant questions for future investigations. [ABSTRACT FROM AUTHOR]

Background: Mathematical models are increasingly being used to evaluate strategies aiming to achieve the control or elimination of parasitic diseases. Recently, owing to growing realization that process-oriented models are useful for ecological forecasts only if the biological processes are well defined, attention has focused on data assimilation as a means to improve the predictive performance of these models. Methodology and principal findings: We report on the development of an analytical framework to quantify the relative values of various longitudinal infection surveillance data collected in field sites undergoing mass drug administrations (MDAs) for calibrating three lymphatic filariasis (LF) models (EPIFIL, LYMFASIM, and TRANSFIL), and for improving their predictions of the required durations of drug interventions to achieve parasite elimination in endemic populations. The relative information contribution of site-specific data collected at the time points proposed by the WHO monitoring framework was evaluated using model-data updating procedures, and via calculations of the Shannon information index and weighted variances from the probability distributions of the estimated timelines to parasite extinction made by each model. Results show that data-informed models provided more precise forecasts of elimination timelines in each site compared to model-only simulations. Data streams that included year 5 post-MDA microfilariae (mf) survey data, however, reduced each model’s uncertainty most compared to data streams containing only baseline and/or post-MDA 3 or longer-term mf survey data irrespective of MDA coverage, suggesting that data up to this monitoring point may be optimal for informing the present LF models. We show that the improvements observed in the predictive performance of the best data-informed models may be a function of temporal changes in inter-parameter interactions. Such best data-informed models may also produce more accurate predictions of the durations of drug interventions required to achieve parasite elimination. Significance: Knowledge of relative information contributions of model only versus data-informed models is valuable for improving the usefulness of LF model predictions in management decision making, learning system dynamics, and for supporting the design of parasite monitoring programmes. The present results further pinpoint the crucial need for longitudinal infection surveillance data for enhancing the precision and accuracy of model predictions of the intervention durations required to achieve parasite elimination in an endemic location. [ABSTRACT FROM AUTHOR]

Background: Deep learning (DL) based solutions have been proposed for interpretation of several imaging modalities including radiography, CT, and MR. For chest radiographs, DL algorithms have found success in the evaluation of abnormalities such as lung nodules, pulmonary tuberculosis, cystic fibrosis, pneumoconiosis, and location of peripherally inserted central catheters. Chest radiography represents the most commonly performed radiological test for a multitude of non-emergent and emergent clinical indications. This study aims to assess accuracy of deep learning (DL) algorithm for detection of abnormalities on routine frontal chest radiographs (CXR), and assessment of stability or change in findings over serial radiographs. Methods and findings: We processed 874 de-identified frontal CXR from 724 adult patients (> 18 years) with DL (Qure AI). Scores and prediction statistics from DL were generated and recorded for the presence of pulmonary opacities, pleural effusions, hilar prominence, and enlarged cardiac silhouette. To establish a standard of reference (SOR), two thoracic radiologists assessed all CXR for these abnormalities. Four other radiologists (test radiologists), unaware of SOR and DL findings, independently assessed the presence of radiographic abnormalities. A total 724 radiographs were assessed for detection of findings. A subset of 150 radiographs with follow up examinations was used to asses change over time. Data were analyzed with receiver operating characteristics analyses and post-hoc power analysis. Results: About 42% (305/ 724) CXR had no findings according to SOR; single and multiple abnormalities were seen in 23% (168/724) and 35% (251/724) of CXR. There was no statistical difference between DL and SOR for all abnormalities (p = 0.2–0.8). The area under the curve (AUC) for DL and test radiologists ranged between 0.837–0.929 and 0.693–0.923, respectively. DL had lowest AUC (0.758) for assessing changes in pulmonary opacities over follow up CXR. Presence of chest wall implanted devices negatively affected the accuracy of DL algorithm for evaluation of pulmonary and hilar abnormalities. Conclusions: DL algorithm can aid in interpretation of CXR findings and their stability over follow up CXR. However, in its present version, it is unlikely to replace radiologists due to its limited specificity for categorizing specific findings. [ABSTRACT FROM AUTHOR]

Neuroscience investigations are most often focused on the prediction of future perception or decisions based on prior brain states or stimulus presentations. However, the brain can also process information retroactively, such that later stimuli impact conscious percepts of the stimuli that have already occurred (called “postdiction”). Postdictive effects have thus far been mostly unimodal (such as apparent motion), and the models for postdiction have accordingly been limited to early sensory regions of one modality. We have discovered two related multimodal illusions in which audition instigates postdictive changes in visual perception. In the first illusion (called the “Illusory Audiovisual Rabbit”), the location of an illusory flash is influenced by an auditory beep-flash pair that follows the perceived illusory flash. In the second illusion (called the “Invisible Audiovisual Rabbit”), a beep-flash pair following a real flash suppresses the perception of the earlier flash. Thus, we showed experimentally that these two effects are influenced significantly by postdiction. The audiovisual rabbit illusions indicate that postdiction can bridge the senses, uncovering a relatively-neglected yet critical type of neural processing underlying perceptual awareness. Furthermore, these two new illusions broaden the Double Flash Illusion, in which a single real flash is doubled by two sounds. Whereas the double flash indicated that audition can create an illusory flash, these rabbit illusions expand audition’s influence on vision to the suppression of a real flash and the relocation of an illusory flash. These new additions to auditory-visual interactions indicate a spatio-temporally fine-tuned coupling of the senses to generate perception. [ABSTRACT FROM AUTHOR]

Background: Tuberculosis and HIV/AIDS are the major public health problems in many parts of the world particularly in resource limited countries like Ethiopia. Although studies have been conducted on the prevalence and associated factors of TB / HIV co-infection in Ethiopia, there is no comprehensive data on the magnitude and risk factors at a national and regional levels. Therefore, this review is aimed to summarize the prevalence of TB /HIV co-infection in Ethiopia using meta-analysis based on a systematic review of published articles & grey literatures. Methods: To conduct this systematic review and meta-analysis, major databases such as Pub Med, Google scholar, CINAHL, Africa Journals Online and Google were systematically searched using search terms. PRISMA guideline was followed in the study. Two authors extracted all necessary data using a standardized data extraction format, and analysis was done using STATA version 11. A Statistical heterogeneity across the studies was evaluated by using Cochran’s Q test and I2 statistic. The pooled effect size was conducted in the form of prevalence and associations were measured using odds ratio. Moreover, the univariate meta regression was performed by considering the sample size to determine potential sources of heterogeneity. The Egger’s weighted regression and Begg’s rank correlation tests were used to assess potential publication biases. Results: This meta-analysis included 21 studies with a total of 12,980 participants. The pooled prevalence of TB / HIV Co-infection was 25.59% (95% CI (20.89%–30.29%). A significant association was found between low CD4 counts (OR: 3.53; 95% CI: 1.55, 8.06), advanced WHO stage (OR: 6.81; 95% CI: 3.91, 11.88) and TB/ HIV/AIDS Co-infection. Conclusion: This finding revealed that the magnitude of TB /HIV co-infection in Ethiopia is increasing and deserves special attention. Low CD4 count and advanced WHO stage are contributing factors for dual infection. Establishing mechanisms such as Conducting surveillance to determine HIV burden among TB patients and TB burden among HIV patients, and intensifying the three I’s (Intensive case finding, INH Preventive Therapy and Infection control) should be routine work of clinicians. Moreover, early screening & treatment should be provided to those patients with low CD4 count and advanced WHO stage. [ABSTRACT FROM AUTHOR]

Private giving represents more than three fourths of all U.S. charitable donations, about 2% of total Gross Domestic Product (GDP). Private giving is a significant factor in funding the nonprofit sector of the U.S. economy, which accounts for more than 10% of total GDP. Despite the abundance of data available through tax forms and other sources, it is unclear which factors influence private donation, and a reliable predictive mechanism remains elusive. This study aims to develop predictive models to accurately estimate future charitable giving based on a set of potentially influential factors. We have selected several factors, including unemployment rate, household income, poverty level, population, sex, age, ethnicity, education level, and number of vehicles per household. This study sheds light on the relationship between donation and these variables. We use Stepwise Regression to identify the most influential variables among the available variables, based on which predictive models are developed. Multiple Linear Regression (MLR) and machine learning techniques, including Artificial Neural Networks (ANN) and Support Vector Regression (SVR) are used to develop the predictive models. The results suggest that population, education level, and the amount of charitable giving in the previous year are the most significant, independent variables. We propose three predictive models (MLR, ANN, and SVR) and validate them using 10-fold cross-validation method, then evaluate the performance using 9 different measuring criteria. All three models are capable of predicting the amount of future donations in a given region with good accuracy. Based on the evaluation criteria, using a test data set, ANN outperforms SVR and MLR in predicting the amount of charitable giving in the following year. [ABSTRACT FROM AUTHOR]

Background: Tuberculosis (TB) patients with human immunodeficiency virus (HIV) co-infection have worse TB treatment outcomes compared to patients with TB alone. The distribution of unfavourable treatment outcomes differs by socio-demographic and clinical characteristics, allowing for early identification of patients at risk. Objective: To develop a statistical model that can provide individual probabilities of unfavourable outcomes based on demographic and clinical characteristics of TB-HIV co-infected patients. Methodology: We used data from all TB patients with known HIV-positive test results (aged ≥15 years) registered for first-line anti-TB treatment (ATT) in 2015 under the Revised National TB Control Programme (RNTCP) in Delhi, India. We included variables on demographics and pre-treatment clinical characteristics routinely recorded and reported to RNTCP and the National AIDS Control Organization. Binomial logistic regression was used to develop a statistical model to estimate probabilities of unfavourable TB treatment outcomes (i.e., death, loss to follow-up, treatment failure, transfer out of program, and a switch to drug-resistant regimen). Results: Of 55,260 TB patients registered for ATT in 2015 in Delhi, 928 (2%) had known HIV-positive test results. Of these, 816 (88%) had drug-sensitive TB and were ≥15 years. Among 816 TB-HIV patients included, 157 (19%) had unfavourable TB treatment outcomes. We developed a model for predicting unfavourable outcomes using age, sex, disease classification (pulmonary versus extra-pulmonary), TB treatment category (new or previously treated case), sputum smear grade, known HIV status at TB diagnosis, antiretroviral treatment at TB diagnosis, and CD4 cell count at ATT initiation. The chi-square p-value for model calibration assessed using the Hosmer-Lemeshow test was 0.15. The model discrimination, measured as the area under the receiver operator characteristic (ROC) curve, was 0.78. Conclusion: The model had good internal validity, but should be validated with an independent cohort of TB-HIV co-infected patients to assess its performance before clinical or programmatic use. [ABSTRACT FROM AUTHOR]

Autophagy and phagocytosis are cellular immune mechanisms for internalization and elimination of intracellular and extracellular pathogens. Some pathogens have evolved the ability to inhibit or manipulate these processes, raising the prospect of adaptive reciprocal co-evolution by the host. We performed population genetic analyses on phagocytosis and autophagy genes in Drosophila melanogaster and D. simulans to test for molecular evolutionary signatures of immune adaptation. We found that phagocytosis and autophagy genes as a whole exhibited an elevated level of haplotype homozygosity in both species. In addition, we detected signatures of recent selection, notably in the Atg14 and Ykt6 genes in D. melanogaster and a pattern of elevated sequence divergence in the genderblind (gb) gene on the D. simulans lineage. These results suggest that the evolution of the host cellular immune system as a whole may be shaped by a dynamic conflict between Drosophila and its pathogens even without pervasive evidence of strong adaptive evolution at the individual gene level. [ABSTRACT FROM AUTHOR]

Primary and secondary metabolites exuded by plant roots have mainly been studied under laboratory conditions, while knowledge of root exudate patterns of plants growing in natural communities is very limited. Focusing on ten common European grassland plant species, we asked to which degree exuded metabolite compositions are specific to species or growth forms (forbs and grasses), depend on environments and local neighbourhoods, and reflect traditional plant functional traits. Root exudates were collected under field conditions and analysed using a non-targeted gas chromatography coupled mass spectrometry (GC-MS) approach. In total, we annotated 153 compounds of which 36 were identified by structure and name as metabolites mainly derived from the primary metabolism. Here we show by using variance partitioning, that the composition of exuded polar metabolites was mostly explained by plot identity, followed by plant species identity while plant species composition of the local neighbourhood played no role. Total and root dry biomass explained the largest proportion of variance in exudate composition, with additional variance explained by traditional plant traits. Although the exudate composition was quite similar between the two growth forms, we found some metabolites that occurred only in one of the two growth forms. Our study demonstrated the feasibility of measuring polar exudates under non-sterile field conditions by mass spectrometry, which opens new avenues of research for functional plant ecology. [ABSTRACT FROM AUTHOR]

Geographical variations and influential factors of disease prevalence are crucial information enabling optimal allocation of limited medical resources and prioritization of appropriate treatments for each regional unit. The purpose of this study was to explore the geographical variations and influential factors of cardiometabolic disease prevalence with respect to 230 administrative districts in South Korea. Global Moran’s I was calculated to determine whether the standardized prevalences of cardiometabolic diseases (hypertension, stroke, and diabetes mellitus) were spatially clustered. The CART algorithm was then applied to generate decision tree models that could extract the diseases’ regional influential factors from among 101 demographic, economic, and public health data variables. Finally, the accuracies of the resulting model–hypertension (67.4%), stroke (62.2%), and diabetes mellitus (56.5%)–were assessed by ten-fold cross-validation. Marriage rate was the main determinant of geographic variation in hypertension and stroke prevalence, which has the possibility that married life could have positive effects in lowering disease risks. Additionally, stress-related variables were extracted as factors positively associated with hypertension and stroke. In the opposite way, the wealth status of a region was found to have an influence on the prevalences of stroke and diabetes mellitus. This study suggested a framework for provision of novel insights into the regional characteristics of diseases and the corresponding influential factors. The results of the study are anticipated to provide valuable information for public health practitioners’ cost-effective disease management and to facilitate primary intervention and mitigation efforts in response to regional disease outbreaks. [ABSTRACT FROM AUTHOR]

Background: The employment rate among people with severe mental illness has recently increased, though it is still low. The motivation to work appears to be an important role as an intermediate outcome measure in vocational rehabilitation programs. In addition, measuring the work motivation for people with severe mental illness appears to be essential to identify candidates who are likely to benefit and monitor candidates’ motivation in a supported employment program. This study aimed to develop a new measure for assessing both intrinsic and extrinsic motivation to work among people with severe mental illness, as there are currently no well-established instruments of this kind. Methods: A focus group interview and review of previous qualitative research were used to identify possible items for inclusion in the new scale. A provisional scale was constructed and further refined for content and format based on feedback from a researcher and also three peer workers with severe mental illness. The resulting provisional 38-item version of the scale was completed by 136 respondents with severe mental illness, and we performed exploratory factor analysis to identify latent constructs within the new measure. The finalized scale was analyzed for test-retest reliability, internal consistency, and convergent validity. Result: An exploratory factor analysis yielded a four-factor scale with 23 items. The finalized 23 items had high internal consistency (Cronbach’s alpha = 0.91) and relatively high test-retest reliability (ICC = 0.83). The four subscales had fair internal consistency (Cronbach’s alpha ≥ 0.69) and good test-retest reliability (ICC ≥ 0.61). Convergent validity was weakly supported by the significant positive correlations with the overall question on motivation to work (r ≥ 0.19, p < 0.01). Besides these correlations, only the “Pressure from others” subscale was negatively and significantly correlated with the negative symptoms evaluated using the Positive and Negative Syndrome Scale (r = -0.18, p = 0.04). Conclusions: This study used factor analysis to develop a new multidimensional scale assessing motivation for competitive employment among persons with severe mental illness. The scale showed acceptable levels of reliability and factor-based and convergent validity. The new measure can be used for measuring the motivation for competitive employment among people with severe mental illness, and it would be useful to identify candidates who are likely to benefit from a certain supported employment program, and to monitor interim progress of the state of participants’ motivation in a program. [ABSTRACT FROM AUTHOR]

Background: The inflammatory potential of diet has been shown to have an association with the risk of several cancer types, but the evidence is inconsistent regarding the related risk of urologic cancer (UC). Therefore, we conducted the present meta-analysis to investigate the association between the inflammatory potential of diet and UC. Methods: PubMed, Embase and Web of Science were searched up to July 31, 2018. Two reviewers independently selected the studies and extracted the data. The pooled risk ratio (RR) and its 95% confidence interval (CI) were calculated using the Stata12.0 software package. Results: Nine case-control studies and three cohort studies including 83,197 subjects met the inclusion criteria. The overall meta-analysis results showed that individuals with the highest category of DII (dietary inflammatory index) were associated with an increased risk of prostate cancer (RR = 1.62, 95% CI: 1.30–2.02); subgroup analysis showed consistent results. For kidney and bladder cancer, significant positive associations were found in individuals with the highest category of DII score; however, no significant association was found between DII and the risk of urothelial cell carcinoma (UCC). Conclusion: Available data suggest that more pro-inflammatory diets are associated with an increased risk of prostate cancer, kidney cancer and bladder cancer. However, further well designed large-scaled cohort studies are warranted to provide more conclusive evidence. [ABSTRACT FROM AUTHOR]

The current study aimed to systematically review and meta-analyze concurrent and longitudinal associations between maternal depression symptoms and mother-child attachment during the preschool period (aged 2 to 7 years) as assessed using the coding systems by Cassidy and Marvin (1992) and Main and Cassidy (1988). The review was pre-registered with PROSPERO (International Prospective Register of Systematic Reviews; Registration number CRD42017073417) and was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A total of 7,969 records were screened and 18 articles were deemed as eligible for inclusion in the review. Studies were reviewed using qualitative synthesis techniques and, where appropriate, meta-analysis. Qualitative synthesis indicated that mothers of disorganized/controlling children most consistently reported the highest levels of depressive symptoms, both concurrently and longitudinally. The association between disorganized/controlling child attachment and concurrent maternal depressive symptoms was significant (n = 1,787; g = 0.27, 95% CI [0.13,0.40]), and was not moderated by sample type, child gender, or risk of bias. Findings of a relationship between child attachment insecurity and maternal depressive symptoms must be qualified due to significant within-study heterogeneity and publication bias. Results suggest that maternal depressive symptoms may confer risk for disorganized/controlling attachment during the preschool period. [ABSTRACT FROM AUTHOR]

Moral evaluations occur quickly following heuristic-like intuitive processes without effortful deliberation. There are several competing explanations for this. The ADC-model predicts that moral judgment consists in concurrent evaluations of three different intuitive components: the character of a person (Agent-component, A); their actions (Deed-component, D); and the consequences brought about in the situation (Consequences-component, C). Thereby, it explains the intuitive appeal of precepts from three dominant moral theories (virtue ethics, deontology, and consequentialism), and flexible yet stable nature of moral judgment. Insistence on single-component explanations has led to many centuries of debate as to which moral precepts and theories best describe (or should guide) moral evaluation. This study consists of two large-scale experiments and provides a first empirical investigation of predictions yielded by the ADC model. We use vignettes describing different moral situations in which all components of the model are varied simultaneously. Experiment 1 (within-subject design) shows that positive descriptions of the A-, D-, and C-components of moral intuition lead to more positive moral judgments in a situation with low-stakes. Also, interaction effects between the components were discovered. Experiment 2 further investigates these results in a between-subject design. We found that the effects of the A-, D-, and C-components vary in strength in a high-stakes situation. Moreover, sex, age, education, and social status had no effects. However, preferences for precepts in certain moral theories (PPIMT) partially moderated the effects of the A- and C-component. Future research on moral intuitions should consider the simultaneous three-component constitution of moral judgment. [ABSTRACT FROM AUTHOR]

Recent research suggests that personality, defined as consistent individual behavioral variation, in farm animals could be an important factor when considering their health, welfare, and productivity. However, behavioral tests are often performed individually and they might not reflect the behavioral differences manifested in every-day social environments. Furthermore, the contextual and longer-term temporal stability of personality traits have rarely been investigated in adult dairy cattle. In this study, we tested three groups of lactating Holstein cows (40 cows) using an individual arena test and a novel object test in groups to measure the contextual stability of behavior. Among the recorded individual test parameters, we used seven in the final analysis, which were determined by a systematic parameter reduction procedure. We found positive correlations between novel object contact duration in the group test and individual test parameters object contact duration (Rs = 0.361, P = 0.026) and movement duration (Rs = 0.336, P = 0.039). Both tests were repeated 6 months later to investigate their temporal stability whereby four individual test parameters were repeatable. There was no consistency in the group test results for 25 cows tested twice, possibly due to group composition changes. Furthermore, based on the seven individual test parameters, two personality traits (activity/exploration and boldness) were identified by principal component analysis. We found a positive association between the first and second tests for activity/exploration (Rs = 0.334, P = 0.058) and for boldness (Rs = 0.491, P = 0.004). Our results support the multidimensional nature of personality in adult dairy cattle and they indicate a link between behavior in individual and within-group situations. The lack of stability according to the group test results implies that group companions might have a stronger influence on individual behavior than expected. We suggest repeating the within-group behavioral measurements to study the relationship between the social environment and the manifestation of personality traits in every-day situations. [ABSTRACT FROM AUTHOR]

Emotional databases are important tools to study emotion recognition and their effects on various cognitive processes. Since, well-standardized large-scale emotional expression database is not available in India, we evaluated Radboud faces database (RaFD)—a freely available database of emotional facial expressions of adult Caucasian models, for Indian sample. Using the pictures from RaFD, we investigated the similarity and differences in self-reported ratings on emotion recognition accuracy as well as parameters of valence, clarity, genuineness, intensity and arousal of emotional expression, by following the same rating procedure as used for the validation of RaFD. We also systematically evaluated the universality hypothesis of emotion perception by analyzing differences in accuracy and ratings for different emotional parameters across Indian and Dutch participants. As the original Radboud database lacked arousal rating, we added this as a emotional parameter along with all other parameters. The results show that the overall accuracy of emotional expression recognition by Indian participants was high and very similar to the ratings from Dutch participants. However, there were significant cross-cultural differences in classification of emotion categories and their corresponding parameters. Indians rated certain expressions comparatively more genuine, higher in valence, and less intense in comparison to original Radboud ratings. The misclassifications/ confusion for specific emotional categories differed across the two cultures indicating subtle but significant differences between the cultures. In addition to understanding the nature of facial emotion recognition, this study also evaluates and enables the use of RaFD within Indian population. [ABSTRACT FROM AUTHOR]

This study examines the association between childhood socioeconomic position and objective physical capability including new functional measures of potential relevance to a population in late-middle age. The study population covers two Danish birth cohorts followed-up in the Copenhagen Aging and Midlife Biobank (age 48–58 years, 2009–2011, N = 4,204). Results from linear regression models revealed that being born in higher socioeconomic position was associated with higher jump height: Paternal occupational class four = 0.19 cm (95% confidence interval (CI): -0.44, 0.82), three = 0.59 cm (95% CI: -0.02, 1.19), two = 1.29 cm (95% CI: 0.64, 1.94), and one = 1.29 cm (95% CI: 0.45, 2.13) (reference = five); medium parental social class = 0.88 cm (95% CI: 0.03, 1.72) and high = 1.79 cm (95% CI: 0.94, 2.63) (reference = low). Higher childhood socioeconomic position was also associated with better chair rise performance and hand grip strength, while among women it was related to reduced flexibility: Medium parental social class = -1.31 cm (95% CI: -3.05, 0.42) and high = -2.20 cm (95% CI: -3.94, -0.47) (reference = low); unwed mother = 1.75 cm (95% CI: 0.36, 3.14) (reference = married). Overall, the findings suggest that higher childhood socioeconomic position is primarily related to moderately better scores in the most strenuous physical capability measures and hand grip strength among healthy adults in late-middle age. [ABSTRACT FROM AUTHOR]

Covariate selection is a fundamental step when building sparse prediction models in order to avoid overfitting and to gain a better interpretation of the classifier without losing its predictive accuracy. In practice the LASSO regression of Tibshirani, which penalizes the likelihood of the model by the L1 norm of the regression coefficients, has become the gold-standard to reach these objectives. Recently Lee and Oh developed a novel random-effect covariate selection method called the modified unbounded penalty (MUB) regression, whose penalization function can equal minus infinity at 0 in order to produce very sparse models. We sought to compare the predictive accuracy and the number of covariates selected by these two methods in several high-dimensional datasets, consisting in genes expressions measured to predict response to chemotherapy in breast cancer patients. These comparisons were performed by building the Receiver Operating Characteristics (ROC) curves of the classifiers obtained with the selected genes and by comparing their area under the ROC curve (AUC) corrected for optimism using several variants of bootstrap internal validation and cross-validation. We found consistently in all datasets that the MUB penalization selected a remarkably smaller number of covariates than the LASSO while offering a similar—and encouraging—predictive accuracy. The models selected by the MUB were actually nested in the ones obtained with the LASSO. Similar findings were observed when comparing these results to those obtained in their first publication by other authors or when using the area under the Precision-Recall curve (AUCPR) as another measure of predictive performance. In conclusion, the MUB penalization seems therefore to be one of the best options when sparsity is required in high-dimension. Further investigation in other datasets is however required to validate these findings. [ABSTRACT FROM AUTHOR]

Biological data sets are typically characterized by high dimensionality and low effect sizes. A powerful method for detecting systematic differences between experimental conditions in such multivariate data sets is multivariate pattern analysis (MVPA), particularly pattern classification. However, in virtually all applications, data from the classes that correspond to the conditions of interest are not homogeneous but contain subclasses. Such subclasses can for example arise from individual subjects that contribute multiple data points, or from correlations of items within classes. We show here that in multivariate data that have subclasses nested within its class structure, these subclasses introduce systematic information that improves classifiability beyond what is expected by the size of the class difference. We analytically prove that this subclass bias systematically inflates correct classification rates (CCRs) of linear classifiers depending on the number of subclasses as well as on the portion of variance induced by the subclasses. In simulations, we demonstrate that subclass bias is highest when between-class effect size is low and subclass variance high. This bias can be reduced by increasing the total number of subclasses. However, we can account for the subclass bias by using permutation tests that explicitly consider the subclass structure of the data. We illustrate our result in several experiments that recorded human EEG activity, demonstrating that parametric statistical tests as well as typical trial-wise permutation fail to determine significance of classification outcomes correctly. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to determine the predictive value of the neutrophil to lymphocyte ratio (NLR) in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Methods: A retrospective study was conducted from March 2012 to May 2016 in Fuxing Hospital, Capital University of Medical Science. We collected 906 cases (525 males, 381 females, mean age 81.86±9.75 years) diagnosed with AECOPD. The NLR was calculated from their white blood cell (WBC), neutrophil (NEU), and lymphocyte (LYM) counts, which were obtained at laboratory examination. Result: After treatment, 698 patients with AECOPD improved. The NLR was higher at admission (6.89±6.82) than after treatment (4.19±5.11) (P = 0.000). The area under the receiver operating characteristic curve (AUC) of the NLR for predicting the 28-day mortality rate was 0.737. Using 8.130 as the critical NLR value, the sensitivity was 60.5%, and the specificity was 74.8%. The AUC of the NLR for predicting the frequency of the need for invasive mechanical ventilation was 0.732. Using 10.345 as the critical NLR value, the sensitivity was 54.3%, and the specificity was 84.8%. The AUC of WBC, NEU and LYM for predicting 28-day mortality and the need for invasive mechanical ventilation in these patients were all less than 0.7. An increased NLR was an independent risk factor for 28-day mortality (OR = 1.067, 95% CI = 1.039 to 1.095, P = 0.000), intensive care unit occupancy (OR = 1.046, 95% CI = 1.023 to 1.068, P = 0.000), and the need for invasive mechanical ventilation (OR = 1.042, 95% CI = 1.019 to 1.066, P = 0.000). Compared with those patients without comorbidities, patients with renal dysfunction or upper gastrointestinal bleeding had an increased risk of death within 28 days (OR = 3.102, 95% CI = 1.525 to 6.312; OR = 4.598, 95% CI = 1.825 to 11.583, respectively), ICU admission (OR = 2.228, 95% CI = 1.286 to 3.860; OR = 3.103, 95% CI = 1.402 to 6.866, respectively), and the need for invasive mechanical ventilation (OR = 3.572, 95% CI = 1.822 to 7.000; OR = 4.279, 95% CI = 1.823 to 10.045, respectively). Conclusion: In patients with AECOPD, the accuracy of the NLR for predicting the 28-day mortality rate and frequency of the need for mechanical ventilation was significantly higher than the accuracy of WBC, NEU and LYM counts. AECOPD patients with an NLR≥8.130 had higher 28-day mortality rate, while those with an NLR ≥10.345 were more likely to need invasive mechanical ventilation. [ABSTRACT FROM AUTHOR]

In this work, we examined the longitudinal measurement invariance of a battery composed of distinct cognitive parameters. A sample of 86 individuals (53.5% females; mean age = 65.73), representative of the Portuguese older population, with respect to sex, age and level of education was assessed twice over an average of two years. By means of a confirmatory factor analysis approach, we tested whether a two-factor solution [corresponding to measures of memory performance (MEM) and executive functioning (EXEC)] was reliable over time. Nested models of longitudinal invariance demonstrated the existence of partial strong invariance over time. In other words, this indicates that there is an equivalence of the factorial structure and factor loadings for all items; this was also observed for the item intercepts for all the items, except for one of the items from the EXEC dimension. Stability coefficients revealed high associations between the dimensions over time and that, whereas there was a significant decline of the MEM across time, this was not observed for the EXEC dimension. These findings reveal that changes in MEM and EXEC scores can be attributed to true changes on these constructs, enabling the use of this battery as a reliable method to study cognitive aging. [ABSTRACT FROM AUTHOR]

Can structural information of proteins generate essential features for predicting the deleterious effect of a single nucleotide variant (SNV) independent of the known existence of the SNV in diseases? In this work, we answer the question by examining the performance of features generated from prior knowledge with the goal towards determining the pathogenic effect of rare variants in rare disease. We take the approach of prioritizing SNV loci focusing on protein structure-based features. The proposed structure-based features are generated from geometric, physical, chemical, and functional properties of the variant loci and structural neighbors of the loci utilizing multiple homologous structures. The performance of the structure-based features alone, trained on 80% of HumVar-HumDiv combination (HumVD-train) and tested on 20% of HumVar-HumDiv (HumVD-test), ClinVar and ClinVar rare variant rare disease (ClinVarRVRD) datasets, showed high levels of discernibility in determining the SNV’s pathogenic or benign effects on patients. Combined structure- and sequence-based features generated from prior knowledge on a random forest model further improved the F scores to 0.84 (HumVD-test), 0.75 (ClinVar), and 0.75 (ClinVarRVRD). Including features based on the difference between wild-type in addition to the features based on loci information increased the F score slightly more to 0.90 (HumVD-test), 0.78 (ClinVar), and 0.76 (ClinVarRVRD). The empirical examination and high F scores of the results based on loci information alone suggest that location of SNV plays a primary role in determining functional impact of mutation and that structure-based features can help enhance the prediction performance. [ABSTRACT FROM AUTHOR]

Background: We examined the equivalence of the individual and the country-level factor structure of the Belief in a Zero-Sum Game (BZSG) scale, a tool designed to measure antagonistic beliefs about social relations (i.e., perceived social antagonism) in the struggle for limited resources. Aims: In this article we focused on a test of construct isomorphism in a multilevel modeling approach. It was hypothesized that the BZSG measure satisfies all requirements for a strong level of configural isomorphism, and thus that it is useful to investigate BZSG at both the individual and the country levels. The relationships between the BZSG at a country level with other macro-socio-economic indicators were also investigated. Method: Multilevel confirmatory factor analysis (MCFA) was carried out on a cross-country sample composed of 11,368 participants from 43 different countries. We also used the country-level latent BZSG factor in each country as an indicator of a property that we attributed to a particular culture: cultural dimension (collectivism-individualism), macroeconomic indicators (GDP per capita and GNI per capita) and macrosocial indicators (Human Development Index and Democracy Index) describing societies. Results: The results revealed an isomorphic factor structure of perceived social antagonism (measured by BZSG scale), defined in terms of the equivalence factor structure at the both individual and country levels. Furthermore, the relationship between the perceived social antagonism, gross national income per capita, and collectivism were confirmed. Conclusions: Our study supports the usefulness of the BZSG scale for cross-cultural comparison, in the case of its isomorphic structure. At the country level, antagonistic beliefs emerge in hierarchical collectivist societies with lower income. The main contribution of this article is the presentation of the test of construct isomorphism. We made an effort to present a full perspective on construct isomorphism putting together two different but very recent approaches. [ABSTRACT FROM AUTHOR]

Perception of verticality is required for normal daily function, yet the typical human detection error range has not been well characterized. Vertical misperception has been correlated with poor postural control and functionality in patients after stroke and after vestibular disorders. Until now, all the published studies that assessed Subjective Postural Vertical (SPV) in the seated position used small groups to establish a reference value. However, this sample size does not represent the healthy population for comparison with conditions resulting in pathological vertical. Therefore, the primary objective was to conduct a systematic review with meta-analyses of Subjective Postural Vertical (SPV) data in seated position in healthy adults to establish the reference value with a representative sample. The secondary objective was to investigate the methodological characteristics of different assessment protocols of SPV described in the literature. A systematic literature search was conducted using Medline, EMBASE, and Cochrane libraries. Mean and standard deviation of SPV in frontal and sagittal planes were considered as effect size measures. Sixteen of 129 identified studies met eligibility criteria for our systematic review (n = 337 subjects in the frontal plane; n = 187 subjects in sagittal plane). The meta-analyses measure was estimated using the pooled mean as the estimator and its respective error. Mean reference values were 0.12°±1.49° for the frontal plane and 0.02°±1.82° for the sagittal plane. There was a small variability of the results and this systematic review resulted in representative values for SPV. The critical analysis of the studies and observed homogeneity in the sample suggests that the methodological differences used in the studies did not influence SPV assessment of directional bias in healthy subjects. These data can serve as a reference for clinical studies in disorders of verticality. [ABSTRACT FROM AUTHOR]

In view of the vast number of natural products with potential antiplasmodial bioactivity and cost of conducting antiplasmodial bioactivity assays, it may be judicious to learn from previous antiplasmodial bioassays and predict bioactivity of these natural products before experimental bioassays. This study set out to harness antimalarial bioactivity data of natural products to build accurate predictive models, utilizing classical machine learning approaches, which can find potential antimalarial hits from new sets of natural products. Classical machine learning approaches were used to build four classifier models (Naïve Bayesian, Voted Perceptron, Random Forest and Sequence Minimization Optimization of Support Vector Machines) from bioactivity data of natural products with in-vitro antiplasmodial activity (NAA) using a combination of the molecular descriptors and two-dimensional molecular fingerprints of the compounds. Models were evaluated with an independent test dataset. Possible chemical features associated with reported antimalarial activities of the compounds were also extracted. From the results, Random Forest (accuracy 82.81%, Kappa statistics 0.65 and Area under Receiver Operating Characteristics curve 0.91) and Sequential Minimization Optimization (accuracy 85.93%, Kappa statistics 0.72 and Area under Receiver Operating Characteristics curve 0.86) showed good predictive performance for the NAA dataset. The amine chemical group (specifically alkyl amines and basic nitrogen) was confirmed to be essential for antimalarial activity in active NAA dataset. This study built and evaluated classifier models that were used to predict the antiplasmodial bioactivity class (active or inactive) of a set of natural products from interBioScreen chemical library. [ABSTRACT FROM AUTHOR]

Understanding sensitive behaviors—those that are socially unacceptable or non-compliant with rules or regulations—is essential for creating effective interventions. Sensitive behaviors are challenging to study, because participants are unlikely to disclose sensitive behaviors for fear of retribution or due to social undesirability. Methods for studying sensitive behavior include randomized response techniques, which provide anonymity to interviewees who answer sensitive questions. A variation on this approach, the quantitative randomized response technique (QRRT), allows researchers to estimate the frequency or quantity of sensitive behaviors. However, to date no studies have used QRRT to identify potential drivers of non-compliant behavior because regression methodology has not been developed for the nonnegative count data produced by QRRT. We develop a Poisson regression methodology for QRRT data, based on maximum likelihood estimation computed via the expectation-maximization (EM) algorithm. The methodology can be implemented with relatively minor modification of existing software for generalized linear models. We derive the Fisher information matrix in this setting and use it to obtain the asymptotic variance-covariance matrix of the regression parameter estimates. Simulation results demonstrate the quality of the asymptotic approximations. The method is illustrated with a case study examining potential drivers of non-compliance with hunting regulations in Sierra Leone. The new methodology allows assessment of the importance of potential drivers of different quantities of non-compliant behavior, using a likelihood-based, information-theoretic approach. Free, open-source software is provided to support QRRT regression. [ABSTRACT FROM AUTHOR]

The independent mobility (IM), defined as the freedom of young people to travel without adult supervision, has been related to the physical activity time, the acquisition of personal autonomy, to less intense fear of crime, and to a stronger feeling of being part of their community and other health and social benefits. The aims of this study were to compare parents’ and adolescents’ traffic- and crime-related safety perceptions of their neighborhood and to analyze the associations of these perceptions with adolescents’ IM. A total of 291 adolescents and their parents completed the Neighborhood Environment Walkability Scale (NEWS) questionnaire. Multilevel (two-level models: individual level—neighborhood level) regression analyses were conducted to examine whether the environmental perceptions differed between parents and adolescents and the association between the parental and adolescents’ perception to the IM and the active independent mobility (AIM). Parents reported a more negative perception of traffic (except for amount and speed) and crime-related safety. Adolescents’ environmental perceptions were not associated with their IM but parental perceptions of traffic- and crime-related safety were associated with IM and with active IM, although not all associations were in the expected direction. Future urban policy efforts should address environments where parents perceive sufficient levels of safety to increase the levels of IM in adolescents. [ABSTRACT FROM AUTHOR]

Objective: The unique foot morphology and distinctive functions facilitate complex tasks and strategies such as standing, walking, and running. In those weight-bearing activities, postural stability (PS) plays an important role. Correlations among foot type, PS, and other musculoskeletal problems that increase sport injury risk are known. However, long-term associations among the foot type, the PS, and body weight (BW) distribution are lacking. Thus, the purpose of this study was to longitudinally identify changes in foot morphology, PS, and symmetry in BW distribution during adolescence among elite male soccer players. Methods: Thirty-five Czech elite male soccer players (age, 15.49 ± 0.61 years; BW, 64.11 ± 6.16 kg; body height, 174.62 ± 5.71 cm) underwent foot type, PS, and BW distribution measurements during 3 consecutive years (T1, T2, T3). The Chippaux-Smirak index (CSI), BW distribution, and centre of pressure (COP) displacement (total traveled way [TTW]) of each player for the preferred (PL) and non-preferred leg (NL) were acquired. Repeated-measures analysis of variance (RM ANOVA), Bonferroni´s post hoc tests, and partial eta-squared (ηp2) coefficient were used for investigating the effect of time on selected variables and effect size evaluation. Results: Statistically significant effect of time on CSI values (PL: F2,68 = 5.08, p < 0.01, ηp2 = 0.13 and NL: F2,68 = 10.87, p < 0.01, ηp2 = 0.24) and COP displacement values (PL: F2,68 = 5.07, p <0.01, ηp2 = 0.13; NL: F2,68 = 3.53, p <0.05, ηp2 = 0.09) for both legs over 3-years period was identified. Furthermore, the Bonferroni´s post hoc analysis revealed a significant improvement of PS values in the PL (TTWT1 = 1617.11 ± 520.22 mm vs. TTWT2 = 1405.29 ± 462.76, p < 0.05; and between TTWT1 = 1617.11 ± 520.22 mm vs. TTWT3 = 1370.46 ± 373.94, p < 0.05). Only BW distribution parameter showed no significant differences, although slightly improved over time. Conclusions: We observed changes in foot typology, PS, and BW distribution in young elite male soccer players during 3 consecutive years. Results demonstrated that changes in PS and body weight distribution under the high-load sport conditions during adolescence may improve with aging, except for foot morphology. Therefore, foot morphology should be carefully monitored to minimize sport injury risk in professional young soccer players during adolescence. Further research is necessary to determine more clear associations between these parameters, soccer-related injuries, and sport performances. [ABSTRACT FROM AUTHOR]

Background: The complexity and severity of traumatic wounds in military and civilian trauma demands improved wound assessment, before, during, and after treatment. Here, we explore the potential of 3 charge-coupled device (3CCD) imaging values to distinguish between traumatic wounds that heal following closure and those that fail. Previous studies demonstrate that normalized 3CCD imaging values exhibit a high correlation with oxygen saturation and allow for comparison of values between diverse clinical settings, including utilizing different equipment and lighting. Methods: We screened 119 patients at Walter Reed National Military Medical Center and at Grady Memorial Hospital with at least one traumatic extremity wound of ≥ 75 cm2. We collected images of each wound during each débridement surgery for a total of 66 patients. An in-house written computer application selected a region of interest in the images, separated the pixel color values, calculated relative values, and normalized them. We followed patients until the enrolled wounds were surgically closed, quantifying the number of wounds that dehisced (defined as wound failure or infection requiring return to the operating room after closure) or healed. Results: Wound failure occurred in 20% (19 of 96) of traumatic wounds. Normalized intensity values for patients with wounds that healed successfully were, on average, significantly different from values for patients with wounds that failed (p ≤ 0.05). Simple thresholding models and partial least squares discriminant analysis models performed poorly. However, a hierarchical cluster analysis model created with 17 variables including 3CCD data, wound surface area, and time from injury predicts wound failure with 76.9% sensitivity, 76.5% specificity, 76.6% accuracy, and a diagnostic odds ratio of 10.8 (95% confidence interval: 2.6–45.9). Conclusions: Imaging using 3CCD technology may provide a non-invasive and cost-effective method of aiding surgeons in deciding if wounds are ready for closure and could potentially decrease the number of required débridements and hospital days. The process may be automated to provide real-time feedback in the operating room and clinic. The low cost and small size of the cameras makes this technology attractive for austere and shipboard environments where space and weight are at a premium. [ABSTRACT FROM AUTHOR]

Motivation: The measurement of disease biomarkers in easily–obtained bodily fluids has opened the door to a new type of non–invasive medical diagnostics. New technologies are being developed and fine–tuned in order to make this possibility a reality. One such technology is Field Asymmetric Ion Mobility Spectrometry (FAIMS), which allows the measurement of volatile organic compounds (VOCs) in biological samples such as urine. These VOCs are known to contain a range of information on the relevant person’s metabolism and can in principle be used for disease diagnostic purposes. Key to the effective use of such data are well–developed data processing pipelines, which are necessary to extract the most useful data from the complex underlying biological structure. Results: In this study, we present a new data analysis pipeline for FAIMS data, and demonstrate a number of improvements over previously used methods. We evaluate the effect of a series of candidate operational steps during data processing, such as the use of wavelet transforms, principal component analysis (PCA), and classifier ensembles. We also demonstrate the use of FAIMS data in our pipeline to diagnose diabetes on the basis of a simple urine sample using machine learning classifiers. We present results for data generated from a case-control study of 115 urine samples, collected from 72 type II diabetic patients, with 43 healthy volunteers as negative controls. The resulting pipeline combines the steps that resulted in the best classification model performance. These include the use of a two–dimensional discrete wavelet transform, and the Wilcoxon rank–sum test for feature selection. We are able to achieve a best ROC curve AUC of 0.825 (0.747–0.9, 95% CI) for classification of diabetes vs control. We also note that this result is robust to changes in the data pipeline and different analysis runs, with AUC > 0.80 achieved in a range of cases. This is a substantial improvement in performance over previously used data processing methods in this area. Our ability to make strong statements about FAIMS ability to diagnose diabetes is sadly limited, as we found confounding effects from the demographics when including these data in the pipeline. The demographics alone produced a best AUC of 0.87 (0.795–0.94, 95% CI). While the combination of the demographics and FAIMS data resulted in an improvement on the AUC (0.907; 0.848–0.97, 95% CI), it did not prove to be a significant difference. Nevertheless, the pipeline itself shows a significant improvement in performance over more basic methods which have been used with FAIMS data in the past. [ABSTRACT FROM AUTHOR]

The attrition of women in academic careers is a major concern, particularly in Science, Technology, Engineering, and Mathematics subjects. One factor that can contribute to the attrition is the lack of visible role models for women in academia. At early career stages, the behaviour of the local community may play a formative role in identifying ingroup role models, shaping women’s impressions of whether or not they can be successful in academia. One common and formative setting to observe role models is the local departmental academic seminar, talk, or presentation. We thus quantified women’s visibility through the question-asking behaviour of academics at seminars using observations and an online survey. From the survey responses of over 600 academics in 20 countries, we found that women reported asking fewer questions after seminars compared to men. This impression was supported by observational data from almost 250 seminars in 10 countries: women audience members asked absolutely and proportionally fewer questions than male audience members. When asked why they did not ask questions when they wanted to, women, more than men, endorsed internal factors (e.g., not working up the nerve). However, our observations suggest that structural factors might also play a role; when a man was the first to ask a question, or there were fewer questions, women asked proportionally fewer questions. Attempts to counteract the latter effect by manipulating the time for questions (in an effort to provoke more questions) in two departments were unsuccessful. We propose alternative recommendations for creating an environment that makes everyone feel more comfortable to ask questions, thus promoting equal visibility for women and members of other less visible groups. [ABSTRACT FROM AUTHOR]

To evaluate the association between serum carotenoids and quantitative measures of retinal vasculature in elderly Singapore Chinese subjects. The following details were collected in 128 healthy subjects: sociodemographics, lifestyle information, medical and drug history, and anthropometric measurements. Serum concentrations of carotenoids were estimated in fasting venous blood using high performance liquid chromatography. Retinal vascular parameters were quantitatively measured from retinal photographs using a computer-assisted program (Singapore I Vessel Assessment). The mean age of the population was 54.1 years (range 40 to 81 years). In multiple linear regression analysis, per SD decrease in retinal arteriolar caliber [β = 0.045 (0.003 to 0.086), p = 0.036], per SD increase in retinal venular caliber [β = -0.045 (-0.086 to -0.003), p = 0.036] and per SD increase in arteriolar branching angle [β = -0.039 (-0.072 to -0.006), p = 0.021] were associated with decreased serum lutein. Per SD increase in retinal venular tortuosity [β = -0.0075 (-0.0145 to -0.0004), p = 0.039] and per SD increase in arteriolar branching angle (β = -0.0073 [-0.0142 to -0.0059], p = 0.041) were associated with decreased serum zeaxanthin. None of the other carotenoids demonstrated meaningful relationship with quantitative measures of retinal vasculature. Lower levels of lutein and zeaxanthin demonstrated significant relationship with adverse quantitative measures of retinal vasculature in elderly healthy subjects. [ABSTRACT FROM AUTHOR]

Countless neurodegenerative diseases are associated with perverse multiple targets of cyclic nucleotide signalling, hastening neuronal death. Cilostazol, a phosphodiesterase-III inhibitor, exerts neuroprotective effects against sundry models of neurotoxicity, however, its role against Huntington’s disease (HD) has not yet been tackled. Hence, its modulatory effect on several signalling pathways using the 3-nitropropionic acid (3-NP) model was conducted. Animals were injected with 3-NP (10 mg/kg/day, i.p) for two successive weeks with or without the administration of cilostazol (100 mg/kg/day, p.o.). Contrary to the 3-NP effects, cilostazol largely preserved striatal dopaminergic neurons, improved motor coordination, and enhanced the immunohistochemical reaction of tyrosine hydroxylase enzyme. The anti-inflammatory effect of cilostazol was documented by the pronounced reduction of the toll like receptor-4 (TLR-4) protein expression and the inflammatory cytokine IL-6, but with a marked elevation in IL-10 striatal contents. As a consequence, cilostazol reduced IL-6 downstream signal, where it promoted the level of suppressor of cytokine signalling 3 (SOCS3), while abated the phosphorylation of Janus Kinase 2 (JAK-2) and Signal transducers and activators of transcription 3 (STAT-3). Phosphorylation of the protein kinase B/glycogen synthase kinase-3β/cAMP response element binding protein (Akt/GSK-3β/CREB) cue is another signalling pathway that was modulated by cilostazol to further signify its anti-inflammatory and antiapoptotic capacities. The latter was associated with a reduction in the caspase-3 expression assessed by immunohistochemical assay. In conclusion the present study provided a new insight into the possible mechanisms by which cilostazol possesses neuroprotective properties. These intersecting mechanisms involve the interference between TLR-4, IL-6-IL-10/JAK-2/STAT-3/SOCS-3, and Akt/GSK-3β/CREB signalling pathways. [ABSTRACT FROM AUTHOR]

The IsoFishR application is a data reduction and analysis tool for laser-ablation strontium isotope data, following common best practices and providing reliable and reproducible results. Strontium isotope ratios (87Sr/86Sr) are a powerful geochemical tracer commonly applied in a wide range of scientific fields and laser-ablation inductively coupled mass spectrometry is considered the method of choice to obtain spatially resolved 87Sr/86Sr isotope ratios from a variety of sample materials. However, data reduction and analyses methods are variable between different research groups and research communities limiting reproducibility between studies. IsoFishR provides a platform to standardize these methods and can be used for both spot and time-resolved line transects. Furthermore, it provides advanced data analysis tools and filters for outlier removal, noise reduction, and visualization of time resolved data. The application can be downloaded from GitHub () and the source code is available, encouraging future development and evolution of this software. [ABSTRACT FROM AUTHOR]

Purpose: In Mexico, 39.5% of adolescents do not meet the World Health Organisation’s physical activity guidelines. Urbanicity is a potential correlate of physical activity. The aim of this study was to examine the associations between different aspects of urbanicity and adolescents’ physical activity. Methods: Participants were 4,079 Mexican adolescents aged 15–18 from Mexico City and Oaxaca, Mexico. Data was collected between February and June 2016. Multiple imputation of missing data was implemented after confirming values were missing at random. Multivariable regression models examined associations between five domains of self-reported physical activity: 1) moderate-to-vigorous physical activity, 2) sports activities, 3) leisure time activities, 4) Physical Education class at school, 5) active commuting to school; and a composite measure of urbanicity and its seven sub-scores: 1) demographic, 2) economic activity, 3) built environment, 4) communication, 5) education, 6) diversity and 7) health services. Multivariable regression models were adjusted for parents’ education and participants’ age. Results: Urbanicity was positively associated with activity spent in Physical Education class. The association between urbanicity and sport activities depended on state context. Communication-based urbanicity was negatively associated with leisure physical activity and active commuting. Population density was positively associated with active commuting. Conclusion: Urbanicity is associated with adolescents’ physical activity in Mexico. Findings were largely consistent between Mexico City and Oaxaca and highlight the value of examining urbanicity as a multidimensional construct. [ABSTRACT FROM AUTHOR]

Background: The impact of risk factors on poor outcome after ischemic stroke is well known, but estimating the amount of poor outcome attributable to single factors is challenging in presence of multimorbidity. We aim to compare population attributable risk estimates obtained from different statistical approaches regarding their consistency. We use a real-life data set from the PROSCIS study to identify predictors for mortality and functional impairment one year after first-ever ischemic stroke and quantify their contribution to poor outcome using population attributable risks. Methods: The PROSpective Cohort with Incident Stroke (PROSCIS) is a prospective observational hospital-based cohort study of patients after first-ever stroke conducted independently in Berlin (PROSCIS-B) and Munich (PROSCIS-M). The association of baseline factors with poor outcome one year after stroke in PROSCIS-B was analysed using multiple logistic regression analysis and population attributable risks were calculated, which were estimated using sequential population attributable risk based on a multiple generalized additive regression model, doubly robust estimation, as well as using average sequential population attributable risk. Findings were reproduced in an independent validation sample from PROSCIS-M. Results: Out of 507 patients with available outcome information after 12 months in PROSCIS-B, 20.5% suffered from poor outcome. Factors associated with poor outcome were age, pre-stroke physical disability, stroke severity (NIHSS), education, and diabetes mellitus. The order of risk factors ranked by magnitudes of population attributable risk was almost similar for all methods, but population attributable risk estimates varied markedly between the methods. In PROSCIS-M, incidence of poor outcome and distribution of baseline parameters were comparable. The multiple logistic regression model could be reproduced for all predictors, except pre-stroke physical disability. Similar to PROSCIS-B, the order of risk factors ranked by magnitudes of population attributable risk was almost similar for all methods, but magnitudes of population attributable risk differed markedly between the methods. Conclusions: Ranking of risk factors by population impact is not affected by the different statistical approaches. Thus, for a rational decision on which risk factor to target in disease interventions, population attributable risk is a supportive tool. However, population attributable risk estimates are difficult to interpret and are not comparable when they origin from studies applying different methodology. The predictors for poor outcome identified in PROSCIS-B have a relevant impact on mortality and functional impairment one year after first-ever ischemic stroke. [ABSTRACT FROM AUTHOR]

This study aimed to estimate prevalence of common mental disorders (CMD) and associated factors among dental students. In this cross-sectional study, 230 students answered a questionnaire and instruments to assess CMD (Self Reporting Questionnaire-20), hazardous alcohol consumption (Alcohol Use Disorder Identification Test), social support (Social Support Scale), perceptions of academic life (Dundee Ready Education Environment Measure), coping (Ways of Coping Inventory) and resilience (Resilience Scale). Bivariate analysis was conducted using the Chi-Square and Mann-Whitney tests. Logistic regression included all explanatory variableswith p<0.20 in the bivariate analysis, besides sex and academic year. The explanatory variables were analyzed in five successive blocks (backward-stepwise), until all variables presented statistical significance in the final model (p<0.05). The prevalence of CMD was 45.2% (95%CI: 38.7–51.6), with no significant differences between sexes. Students with no extracurricular activities, who had negatively self- assessed their health status and their academic performance, were about four times more likely to present CMD, followed by receiving psychological or psychiatric treatment during university (AOR: 2.65; 95%CI: 1.1–6.1) and those with high scores for confrontive coping (AOR: 1.20; 95%CI: 1.0–1.4). Resilience was a protective factor for CMD among dental students (AOR: 0.93; 95%CI: 0.9–1.0). Aspects related to academic performance, health status and confrontive coping strategies were risk factors to students’ mental health. Individuals with high levels of resilience showed lower prevalence of CMD. Further prospective studies could contribute to understanding the role of resilience among this population. [ABSTRACT FROM AUTHOR]

Various studies have determined that the Great East Japan Earthquake (GEJE) caused mental distress among residents in affected areas. However, previous studies had not considered the prevalence of mental distress before the GEJE, and ignored the impact of an aged society on mental distress. Therefore, we aimed to describe the prevalence of mental distress before the GEJE in Miyagi Prefecture, Japan and elucidate the effect of an aged society on mental distress. We conducted an ecological study, using municipality in Miyagi Prefecture as the study unit. We used the cross-sectional mail survey data conducted in February 2011. We performed a correlation analysis in each of the 39 municipalities in Miyagi Prefecture. The prevalence of serious mental distress was 9.1%. The proportion of the population aged 65 years or older was related to the prevalence of serious mental distress in municipalities with a low proportion of all workers engaged in primary industry and with a high estimated number of inpatients with mental illness. We found that residents in Miyagi Prefecture suffered from poor mental health before the GEJE. Aged society was related to serious mental distress in the areas with advanced industrial structure and more patients with mental illness. We should approach mental health problems in the context of social structure, particularly in an aged society, based on facts about mental distress before the GEJE. [ABSTRACT FROM AUTHOR]

Previous work suggests that to restore postural stability for individuals with lower-limb amputation, ankle-foot prostheses should be designed with a flat effective rocker shape for standing. However, most commercially available ankle-foot prostheses are designed with a curved effective rocker shape for walking. To address the demands of both standing and walking, we designed a novel bimodal ankle-foot prosthesis that can accommodate both functional modes using a rigid foot plate and an ankle that can lock and unlock. The primary objective of this study was to determine if the bimodal ankle-foot system could improve various aspects of standing balance (static, dynamic, and functional) and mobility in a group of Veterans with lower-limb amputation (n = 18). Standing balance was assessed while subjects completed a series of tests on a NeuroCom Clinical Research System (NeuroCom, a Division of Natus, Clackamas, OR), including a Sensory Organization Test, a Limits of Stability Test, and a modified Motor Control Test. Few statistically significant differences were observed between the locked and unlocked ankle conditions while subjects completed these tests. However, in the absence of visual feedback, the locked bimodal ankle appeared to improve static balance in a group of experienced lower-limb prosthesis users whose PLUS-M mobility rating was higher than approximately 73% of the sample population used to develop the PLUS-M survey. Given the statistically significant increase in mean equilibrium scores between the unlocked and locked conditions (p = 0.004), future testing of this system should focus on new amputees and lower mobility users (e.g., Medicare Functional Classification Level K1 and K2 prosthesis users). Furthermore, commercial implementation of the bimodal ankle-foot system should include a robust control system that can automatically switch between modes based on the user’s activity. [ABSTRACT FROM AUTHOR]

The purpose of this study was to estimate the prevalence of human papillomavirus (HPV) in vulvar cancer and determine whether positive HPV in vulvar cancer was associated with a better prognosis. Literature searches of Ovid EMBASE, PubMed, Web of Science and Cochrane Library were performed to identify related studies published from January 2000 to May 2017. A total of 33 studies including 7,721 subjects were selected in this meta-analysis. Overall, the HPV prevalence in vulvar cancer tissue was 34% (95% CI: 28%-39%) with 45% (95% CI: 28%-64%) in Asian populations and 34% (95% CI: 26%-42%) in Caucasian populations. The HPV-positive vulvar cancer was associated with better overall survival (hazard ratio = 0.64, 95% CI: 0.47–0.87; P = 0.004) and recurrence-free survival (hazard ratio = 0.66, 95% CI: 0.45–0.97; P = 0.03) compared with HPV-negative counterpart. HPV status may play an important role in predicting the prognosis of patients with vulvar cancer. The HPV-positive vulvar cancer women might relatively have a better survival than HPV-negative ones. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study is to perform the first meta-meta-analysis on the effectiveness of parent-based interventions for children with externalizing behavior problems. Even though parent-based interventions are considered as effective treatments the effects reported in meta-analyses are heterogeneous and the implementation in clinical practice is suboptimal. Recapitulative valid effect predictions are required to close the still existing gap between research findings and clinical practice. The meta-meta-analytic results on changes in child behavior shall result in a clear signal for clinical practice. Methods: This meta-meta-analysis encompasses 26 meta-analyses identified via search in electronic databases (PsycINFO, Medline, PubMed). Meta-analyses had to report effects of parent-based interventions on child behavior and focus on children under the age of 13 years with externalizing behavior problems in a clinical setting. Analyses were based on random-effects models. To combine results, the effect estimates of the meta-analyses were transformed to SMD and weighted to correct for primary study overlap. The meta-meta-analysis is registered on PROSPERO, registration number CRD42016036486 and was conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses statement (PRISMA). Results: The results indicate a significant moderate overall effect for child behavior (SMD = 0.46) as well as for parent reports (SMD = 0.51) and observational data (SMD = 0.62). Further analyses focusing on child externalizing behavior yielded significant and moderate effects (SMD = 0.45). All effects remained stable to follow-up. Considerable heterogeneity was observed within results. Conclusion: Parent-based interventions are shown to be effective in improving behavior in children with externalizing behavior problems, as assessed using parent reports and observational measures. The present results should encourage health care providers to apply evidence-based parent-based interventions. [ABSTRACT FROM AUTHOR]

We examined the effect of hearing two types of self-relevant words, one’s own name and the name of others, on vigilant attention, arousal, and subjective sleepiness during performing the Psychomotor Vigilance Test (PVT). Participants performed the PVT under three experimental conditions, (a) hearing own full name (high self-relevant condition), (b) hearing other’s name (low self- relevant condition) and (c) the control condition with no stimuli. Participants heard the names every 20 sec. Self-relevance was assessed before the experiment using the self-relevance scale. The results of the behavioral effects are relatively small and not consistently supported by all of the performance indicators. A tentative conclusion, based on the overall pattern of results, is that (1) arousal increased by hearing a name, regardless of its self-relevance, and (2) hearing less self-relevant stimuli such as other’s name had a distractive effect on ongoing task performance, although it increased arousal, being aware that further experiments are urgently necessary. [ABSTRACT FROM AUTHOR]

Arterial stiffness, typically assessed as the aortic pulse wave velocity (PWV), and central blood pressure levels may be indicators of cardiovascular disease (CVD) risk. This ancillary study to the Systolic Blood Pressure Intervention Trial (SPRINT) obtained baseline assessments (at randomization) of PWV and central systolic blood pressure (C-SBP) to: 1) characterize these vascular measurements in the SPRINT cohort, and 2) test the hypotheses that PWV and C-SBP are associated with glucose homeostasis and markers of chronic kidney disease (CKD). The SphygmoCor® CPV device was used to assess carotid-femoral PWV and its pulse wave analysis study protocol was used to obtain C-SBP. Valid results were obtained from 652 participants. Mean (±SD) PWV and C-SBP for the SPRINT cohort were 10.7 ± 2.7 m/s and 132.0 ± 17.9 mm Hg respectively. Linear regression analyses for PWV and C-SBP results adjusted for age, sex, and race/ethnicity in relation to several markers of glucose homeostasis and CKD did not identify any significant associations with the exception of a marginally statistically significant and modest association between PWV and urine albumin-to-creatinine ratio (linear regression estimate ± SE, 0.001 ± 0.0006; P-value 0.046). In a subset of SPRINT participants, PWV was significantly higher than in prior studies of normotensive persons, as expected. For older age groups in the SPRINT cohort (age > 60 years), PWV was compared with a reference population of hypertensive individuals. There were no compelling associations noted between PWV or C-SBP and markers of glucose homeostasis or CKD. Clinical Trial Registration: . [ABSTRACT FROM AUTHOR]

In human societies, agents are assumed to experience being the author of their own actions. These basic motoric experiences of action are influenced by social hierarchies, leading to surprising and morally significant results. Here we ask whether, under coercion, the sense of agency and responsibility pass from the person who receives orders to the person who gives them. Volunteers took turns to play the roles of ‘commander’, ‘agent’ or ‘victim’ in a task where the commander coerced the agent to deliver painful shocks to the ‘victim’. We used ‘intentional binding’ as an implicit measure of sense of agency in both commanders and agents, in conditions of coercion and free-choice. We observed a reduced sense of agency when agents received coercive instructions, relative to when they freely chose which action to execute. We also found that sense of agency in the commanders was reduced when they coerced agents to administer the shock on their behalf, relative to when they acted by themselves. This last effect was associated with the commander’s self-reported level on a psychopathy scale. Thus, coercion resulted in neither commander nor agent feeling agency for the effect of the action, as measured through implicit methods. Our results could have profound implications for social decision-making and social regulation of moral behaviour. [ABSTRACT FROM AUTHOR]

Objective: To examine whether childbearing before age 18 in Sub-Saharan Africa is associated with increased risk of maternal and child complications through a systematic literature review and meta-analysis. Methods: The literature on adolescent pregnancy and associated complications in Sub-Saharan Africa was reviewed. A systematic electronic database search in Medline and Embase identified relevant papers. Studies were eligible for inclusion if they had numeric data on maternal mortality, pre-eclampsia, eclampsia, preterm birth, low birth weight, small for gestational age, stillbirth, neonatal death or perinatal death. We included studies on adolescents aged 17 years or younger, and with a comparison group of adult women aged between 20 and 35 years. The quality of the articles was assessed. Meta-analyses were conducted when there were at least three included studies with minor clinical heterogeneity in population and outcome measures. Results: Eighteen studies met our inclusion criteria. There were many studies from Sub-Saharan Africa with data on the age group 15–19 years old, but few studies had separate data on adolescents <18 years old. All included studies were of either moderate or low quality. Adolescents had an increased risk of low birth weight, pre-eclampsia/eclampsia, preterm birth and maternal and perinatal mortality. We found a lower, nonsignificant risk of stillbirth and for small for gestational age babies among the young mothers. Conclusion: In this systematic review, the findings indicate that young maternal age is associated with some unfavorable outcomes in Sub-Saharan Africa. High quality observational studies that adjust for sociodemographic factors are lacking. [ABSTRACT FROM AUTHOR]

Back pain is the #1 cause of years lived with disability worldwide, yet surprisingly little is known regarding the biology underlying this symptom. We conducted a genome-wide association study (GWAS) meta-analysis of chronic back pain (CBP). Adults of European ancestry were included from 15 cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and from the UK Biobank interim data release. CBP cases were defined as those reporting back pain present for ≥3–6 months; non-cases were included as comparisons (“controls”). Each cohort conducted genotyping using commercially available arrays followed by imputation. GWAS used logistic regression models with additive genetic effects, adjusting for age, sex, study-specific covariates, and population substructure. The threshold for genome-wide significance in the fixed-effect inverse-variance weighted meta-analysis was p<5×10−8. Suggestive (p<5×10−7) and genome-wide significant (p<5×10−8) variants were carried forward for replication or further investigation in the remaining UK Biobank participants not included in the discovery sample. The discovery sample comprised 158,025 individuals, including 29,531 CBP cases. A genome-wide significant association was found for the intronic variant rs12310519 in SOX5 (OR 1.08, p = 7.2×10−10). This was subsequently replicated in 283,752 UK Biobank participants not included in the discovery sample, including 50,915 cases (OR 1.06, p = 5.3×10−11), and exceeded genome-wide significance in joint meta-analysis (OR 1.07, p = 4.5×10−19). We found suggestive associations at three other loci in the discovery sample, two of which exceeded genome-wide significance in joint meta-analysis: an intergenic variant, rs7833174, located between CCDC26 and GSDMC (OR 1.05, p = 4.4×10−13), and an intronic variant, rs4384683, in DCC (OR 0.97, p = 2.4×10−10). In this first reported meta-analysis of GWAS for CBP, we identified and replicated a genetic locus associated with CBP (SOX5). We also identified 2 other loci that reached genome-wide significance in a 2-stage joint meta-analysis (CCDC26/GSDMC and DCC). [ABSTRACT FROM AUTHOR]

Mutation cluster analysis is critical for understanding certain mutational mechanisms relevant to genetic disease, diversity, and evolution. Yet, whole genome sequencing for detection of mutation clusters is prohibitive with high cost for most organisms and population surveys. Single nucleotide polymorphism (SNP) genotyping arrays, like the Mouse Diversity Genotyping Array, offer an alternative low-cost, screening for mutations at hundreds of thousands of loci across the genome using experimental designs that permit capture of de novo mutations in any tissue. Formal statistical tools for genome-wide detection of mutation clusters under a microarray probe sampling system are yet to be established. A challenge in the development of statistical methods is that microarray detection of mutation clusters is constrained to select SNP loci captured by probes on the array. This paper develops a Monte Carlo framework for cluster testing and assesses test statistics for capturing potential deviations from spatial randomness which are motivated by, and incorporate, the array design. While null distributions of the test statistics are established under spatial randomness via the homogeneous Poisson process, power performance of the test statistics is evaluated under postulated types of Neyman-Scott clustering processes through Monte Carlo simulation. A new statistic is developed and recommended as a screening tool for mutation cluster detection. The statistic is demonstrated to be excellent in terms of its robustness and power performance, and useful for cluster analysis in settings of missing data. The test statistic can also be generalized to any one dimensional system where every site is observed, such as DNA sequencing data. The paper illustrates how the informal graphical tools for detecting clusters may be misleading. The statistic is used for finding clusters of putative SNP differences in a mixture of different mouse genetic backgrounds and clusters of de novo SNP differences arising between tissues with development and carcinogenesis. [ABSTRACT FROM AUTHOR]