Predicting the naturalistic course in anxiety disorders using clinical and biological markers:a machine learning approach

BackgroundDisease trajectories of patients with anxiety disorders are highly diverse and approximately 60% remain chronically ill. The ability to predict disease course in individual patients would enable personalized management of these patients. This study aimed to predict recovery from anxiety disorders within 2 years applying a machine learning approach.MethodsIn total, 887 patients with anxiety disorders (panic disorder, generalized anxiety disorder, agoraphobia, or social phobia) were selected from a naturalistic cohort study. A wide array of baseline predictors (N = 569) from five domains (clinical, psychological, sociodemographic, biological, lifestyle) were used to predict recovery from anxiety disorders and recovery from all common mental disorders (CMDs: anxiety disorders, major depressive disorder, dysthymia, or alcohol dependency) at 2-year follow-up using random forest classifiers (RFCs).ResultsAt follow-up, 484 patients (54.6%) had recovered from anxiety disorders. RFCs achieved a cross-validated area-under-the-receiving-operator-characteristic-curve (AUC) of 0.67 when using the combination of all predictor domains (sensitivity: 62.0%, specificity 62.8%) for predicting recovery from anxiety disorders. Classification of recovery from CMDs yielded an AUC of 0.70 (sensitivity: 64.6%, specificity: 62.3%) when using all domains. In both cases, the clinical domain alone provided comparable performances. Feature analysis showed that prediction of recovery from anxiety disorders was primarily driven by anxiety features, whereas recovery from CMDs was primarily driven by depression features.ConclusionsThe current study showed moderate performance in predicting recovery from anxiety disorders over a 2-year follow-up for individual patients and indicates that anxiety features are most indicative for anxiety improvement and depression features for improvement in general

Self-report and parent-report of physical and psychosocial well-being in Dutch adolescents with type 1 diabetes in relation to glycemic control

BACKGROUND: To determine physical and psychosocial well-being of adolescents with type 1 diabetes by self-report and parent report and to explore associations with glycemic control and other clinical and socio-demographic characteristics. METHODS: Demographic, medical and psychosocial data were gathered from 4 participating outpatient pediatric diabetes clinics in the Netherlands. Ninety-one patients completed the Child Health Questionnaire-CF87 (CHQ-CF87), Centre for Epidemiological Studies scale for Depression (CES-D), and the DFCS (Diabetes-specific Family Conflict Scale). Parents completed the CHQ-PF50, CES-D and the DFCS. RESULTS: Mean age was 14.9 years (± 1.1), mean HbA(1c )8.8% (± 1.7; 6.2–15.0%). Compared to healthy controls, patients scored lower on CHQ subscales role functioning-physical and general health. Parents reported less favorable scores on the behavior subscale than adolescents. Fewer diabetes-specific family conflicts were associated with better psychosocial well-being and less depressive symptoms. Living in a one-parent family, being member of an ethnic minority and reporting lower well-being were all associated with higher HbA(1c )values. CONCLUSION: Overall, adolescents with type 1 diabetes report optimal well-being and parent report is in accordance with these findings. Poor glycemic control is common, with single-parent families and ethnic minorities particularly at risk. High HbA(1c )values are related to lower social and family functioning

The aortic root in repaired tetralogy of Fallot:Serial measurements and impact of losartan treatment

Background: Aortic root dilatation is common in adults with repaired tetralogy of Fallot (rTOF) and might lead to aortic dissection. However, little is known on progression of aortic dilatation and the effect of pharmaceutical treatment. This study aims to determine factors associated with aortic growth and investigate effects of losartan. Methods and results: We performed a prespecified analysis from the 1:1 randomized, double-blind REDEFINE trial. Aortic root diameters were measured at baseline and after 2.0 ± 0.3 years of follow-up using cardiovascular magnetic resonance (CMR) imaging. A total of 66 patients were included (68% men, age 40 ± 12 years, baseline aortic root 37 ± 6 mm, 32% aortic dilatation (>40 mm)). There was a trend towards slow aortic root growth (+0.6 ± 2.3 mm after two years, p = 0.06) (n = 60). LV stroke volume was the only factor associated with both a larger baseline aortic root (β: 0.09 mm/ml (95% C.I.:0.02, 0.15), p = 0.010) and with aortic growth during follow-up (β: 0.04 mm/ml (95% C.I.:0.005, 0.066), p = 0.024), after correction for age, sex, and body surface area using linear regression analysis. No treatment effect of losartan was found (p = 0.17). Conclusions: Aortic root dilatation was present in about one-third of rTOF patients. A larger LV stroke volume was associated with both a larger baseline aortic root and ongoing growth. Our findings provide no arguments for lower aortic diameter thresholds for prophylactic surgery compared to the general population

Monitoring and Discussing Health-Related Quality of Life in Adolescents With Type 1 Diabetes Improve Psychosocial Well-Being: A randomized controlled trial

OBJECTIVE—To test the effects of monitoring and discussing of health-related quality of life (HRQoL) in adolescents with type 1 diabetes in a multicenter randomized controlled trial

Maatschappelijke acceptatie van (grootschalige) veehouderij in LOG's : over de houding van burgers en boeren en rollen van overheden = Societal acceptance of (large-scale) farming in LOG's : on the attitude of citizens and farmers and roles of governments

The report provides insight into reasons for (non-) acceptance of large-scale farms in LOG areas, the decision making by provinces and municipalities and (desired) roles of governments

Universal Artifacts Affect the Branching of Phylogenetic Trees, Not Universal Scaling Laws

The superficial resemblance of phylogenetic trees to other branching structures allows searching for macroevolutionary patterns. However, such trees are just statistical inferences of particular historical events. Recent meta-analyses report finding regularities in the branching pattern of phylogenetic trees. But is this supported by evidence, or are such regularities just methodological artifacts? If so, is there any signal in a phylogeny?In order to evaluate the impact of polytomies and imbalance on tree shape, the distribution of all binary and polytomic trees of up to 7 taxa was assessed in tree-shape space. The relationship between the proportion of outgroups and the amount of imbalance introduced with them was assessed applying four different tree-building methods to 100 combinations from a set of 10 ingroup and 9 outgroup species, and performing covariance analyses. The relevance of this analysis was explored taking 61 published phylogenies, based on nucleic acid sequences and involving various taxa, taxonomic levels, and tree-building methods.All methods of phylogenetic inference are quite sensitive to the artifacts introduced by outgroups. However, published phylogenies appear to be subject to a rather effective, albeit rather intuitive control against such artifacts. The data and methods used to build phylogenetic trees are varied, so any meta-analysis is subject to pitfalls due to their uneven intrinsic merits, which translate into artifacts in tree shape. The binary branching pattern is an imposition of methods, and seldom reflects true relationships in intraspecific analyses, yielding artifactual polytomies in short trees. Above the species level, the departure of real trees from simplistic random models is caused at least by two natural factors--uneven speciation and extinction rates; and artifacts such as choice of taxa included in the analysis, and imbalance introduced by outgroups and basal paraphyletic taxa. This artifactual imbalance accounts for tree shape convergence of large trees.There is no evidence for any universal scaling in the tree of life. Instead, there is a need for improved methods of tree analysis that can be used to discriminate the noise due to outgroups from the phylogenetic signal within the taxon of interest, and to evaluate realistic models of evolution, correcting the retrospective perspective and explicitly recognizing extinction as a driving force. Artifacts are pervasive, and can only be overcome through understanding the structure and biological meaning of phylogenetic trees. Catalan Abstract in Translation S1

A living lab approach to understanding dairy farmers' needs of technologies and data to improve herd health: Focus groups from 6 European countries

For successful development and adoption of technology on dairy farms, farmers need to be included in the innovation process. However, the design of agricultural technologies usually takes a top-down approach with little involvement of end-users at the early stages. Living Labs offer a methodology that involve end-users throughout the development process and emphasize the importance of understanding users' needs. Currently, exploration of dairy farmers' needs of technologies has been limited to specific types of technology (e.g., smartphone apps) and adult cattle. The aim of this study was to use a Living Lab approach to identify dairy farmers' needs of data and technologies to improve herd health and inform innovation development. Eighteen focus groups were conducted with, in total, 80 dairy farmers from Belgium, Ireland, the Netherlands, Norway, Sweden, and the UK. Data were analyzed using Template Analysis and 6 themes were generated which represented the fundamental needs of autonomy, comfort, competence, community and relatedness, purpose, and security. Farmers favored technologies that provided them with convenience, facilitated their knowledge and understanding of problems on farm, and allowed them to be self-reliant. Issues with data sharing and accessibility, and usability of software were barriers to technology use. Furthermore, farmers were facing problems around recruitment and management of labor and needed ways to reduce stress. Controlling aspects of the barn environment, such as air quality, hygiene, and stocking density, was a particular concern in relation to youngstock management. In conclusion, the findings suggest that developers of farm technologies may want to include farmers in the design process to ensure a positive user experience and improve accessibility. The needs identified in this study can be used as a framework when designing farm technologies to strengthen need satisfaction and reduce any potential harm toward needs

Systematic Evaluation of the Descriptive and Predictive Performance of Paediatric Morphine Population Models

Purpose: A framework for the evaluation of paediatric population models is proposed and applied to two different paediatric population pharmacokinetic models for morphine. One covariate model was based on a systematic covariate analysis, the other on fixed allometric scaling principles. Methods: The six evaluation criteria in the framework were 1) number of parameters and condition number, 2) numerical diagnostics, 3) prediction-based diagnostics, 4) η-shrinkage, 5) simulation-based diagnostics, 6) diagnostics of individual and population parameter estimates versus covariates, including measurements of bias and precision of the population values compared to the observed individual values. The framework entails both an internal and external model evaluation procedure. Results: The application of the framework to the two models resulted in the detection of overparameterization and misleading diagnostics based on individual predictions caused by high shrinkage. The diagnostic of individual and population parameter estimates versus covariates proved to be highly informative in assessing obtained covariate relationships. Based on the framework, the systematic covariate model proved to be superior over the fixed allometric model in terms of predictive performance. Conclusions: The proposed framework is suitable for the evaluation of paediatric (covariate) models and should be applied to corroborate the descriptive and predictive properties of these models

Tracking Membrane Protein Association in Model Membranes

Membrane proteins are essential in the exchange processes of cells. In spite of great breakthrough in soluble proteins studies, membrane proteins structures, functions and interactions are still a challenge because of the difficulties related to their hydrophobic properties. Most of the experiments are performed with detergent-solubilized membrane proteins. However widely used micellar systems are far from the biological two-dimensions membrane. The development of new biomimetic membrane systems is fundamental to tackle this issue