ABSTRACT
Uncertainty has been a central concept in psychological theories of anxiety. However, this concept has been plagued by divergent connotations and operationalizations. The lack of consensus hinders the current search for cognitive and biological mechanisms of anxiety, jeopardizes theory creation and comparison, and restrains translation of basic research into improved diagnoses and interventions. Drawing upon uncertainty decomposition in Bayesian Decision Theory, we propose a well-defined conceptual structure of uncertainty in cognitive and clinical sciences, with a focus on anxiety. We discuss how this conceptual structure provides clarity and can be naturally applied to existing frameworks of psychopathology research. Furthermore, it allows formal quantification of various types of uncertainty that can benefit both research and clinical practice in the era of computational psychiatry.
ABSTRACT
Gene-environment and nutrition-environment studies often involve testing of high-dimensional interactions between two sets of variables, each having potentially complex nonlinear main effects on an outcome. Construction of a valid and powerful hypothesis test for such an interaction is challenging, due to the difficulty in constructing an efficient and unbiased estimator for the complex, nonlinear main effects. In this work we address this problem by proposing a Cross-validated Ensemble of Kernels (CVEK) that learns the space of appropriate functions for the main effects using a cross-validated ensemble approach. With a carefully chosen library of base kernels, CVEK flexibly estimates the form of the main-effect functions from the data, and encourages test power by guarding against over-fitting under the alternative. The method is motivated by a study on the interaction between metal exposures in utero and maternal nutrition on children's neurodevelopment in rural Bangladesh. The proposed tests identified evidence of an interaction between minerals and vitamins intake and arsenic and manganese exposures. Results suggest that the detrimental effects of these metals are most pronounced at low intake levels of the nutrients, suggesting nutritional interventions in pregnant women could mitigate the adverse impacts of in utero metal exposures on children's neurodevelopment.
ABSTRACT
To describe distributions of immune markers in children and young adults by sex and HIV status, and within groups, investigate associations of immune markers with bone density across Tanner stage. Using data and samples from 353 participants in a cross-sectional study in youth with perinatally acquired HIV (PHIV) and matched HIV-negative controls, distributions of inflammation and activation immune markers were described by sex and HIV status. Correlations and structural equation models (SEM) were used to explore marginal and multivariable associations of the immune markers with bone density and to assess whether patterns of association varied by sex and HIV status. Immune marker distributions did not differ by sex, but there were some differences by HIV status. Correlation patterns among bone, body composition, and immune markers were similar across the sex and HIV status groups. Conclusions from SEMs were limited by small sample sizes, but there was some indication that patterns of association between bone density and certain immune markers differed in male PHIV with more advanced Tanner stage compared to the other three groups. In conclusion, distributions of bone density, body composition, and immune markers may vary by sex and HIV status, although associations among these outcomes within sex and HIV status groups appear similar. Bone density of male PHIV appears to be more negatively affected than females, regardless of female HIV status. Larger longitudinal studies across Tanner stages are needed to further explore potential biological relationships between immune markers and bone density in youth living with HIV.
