Examination of the overlap between DSM-111-R overanxious disorder and DSM-IV generalized anxiety disorder in childhood

Since DSM-III-R criteria for Overanxious Disorder (OAD) was subsumed under Generalized Anxiety Disorder (GAD) in DSM-IV, three studies have investigated the overlap between the diagnoses. Although two studies have identified children meeting both OAD and GAD criteria (OAD/GAD group), a third study has identified children who met criteria for OAD, but not GAD (OAD group). Based on finding these two groups of children, we examined whether children in the OAD group (n= 30) could be differentiated from children in the OAD/GAD group (n=81) based on self and parent report of anxious symptoms and level of functional impairment. Conditional probability rates were also calculated for each of the DSM anxious symptoms to determine their overall clinicalutility. Findings revealed that the OAD group of children experienced fewer anxious symptoms than children in the OAD/GAD group, though both groups showed some amount of impairment. The implications for research and practice are discussed.

Generalized atoms in molecules approach (GAIM approach)

This thesis involves two parts. The first is a new-proposed theoretical approach called generalized atoms in molecules (GAIM). The second is a computational study on the deamination reaction of adenine with OH⁻/nH₂O (n=0, 1, 2, 3) and 3H₂O. The GAIM approach aims to solve the energy of each atom variationally in the first step and then to build the energy of a molecule from each atom. Thus the energy of a diatomic molecule (A-B) is formulated as a sum of its atomic energies, EA and EB. Each of these atomic energies is expressed as, EA = Hᴬ + Vₑₑᴬᴬ + 1/2Vₑₑᴬ<>ᴮ EB = Hᴮ + Vₑₑᴮᴮ + 1/2Vₑₑᴬ<>ᴮ where; Hᴬ and Hᴮ are the kinetic and nuclear attraction energy of electrons of atoms A and B, respectively; Vₑₑᴬᴬ and Vₑₑᴮᴮ are the interaction energy between the electrons on atoms A and B, respectively; and Vₑₑᴬ<>ᴮ is the interaction energy between the electrons of atom A with the electrons of atom B. The energy of the molecule is then minimized subject to the following constraint, |ρA(r)dr + |ρB(r)dr = N where ρA(r) and ρB(r) are the electron densities of atoms A and B, respectively, and N is the number of electrons. The initial testing of the performance of GAIM was done through calculating dissociation curves for H₂, LiH, Li₂, BH, HF, HCl, N₂, F₂, and Cl₂. The numerical results show that GAIM performs very well with H₂, LiH, Li₂, BH, HF, and HCl. GAIM shows convergence problems with N₂, F₂, and Cl₂ due to difficulties in reordering the degenerate atomic orbitals Pₓ, Py, and Pz in N, F, and Cl atoms. Further work for the development of GAIM is required. Deamination of adenine results in one of several forms of premutagenic lesions occurring in DNA. In this thesis, mechanisms for the deamination reaction of adenine with OH⁻/nH₂O, (n = 0, 1, 2, 3) and 3H₂O were investigated. HF/6-31G(d), B3LYP/6-31G(d), MP2/6-31G(d), and B3LYP/6-31+G(d) levels of theory were employed to optimize all the geometries. Energies were calculated at the G3MP2B3 and CBS-QB3 levels of theory. The effect of solvent (water) was computed using the polarizable continuum model (PCM). Intrinsic reaction coordinate (IRC) calculations were performed for all transition states. Five pathways were investigated for the deamination reaction of adenine with OH⁻/nH₂O and 3H₂O. The first four pathways (A-D) begin with by deprotonation at the amino group of adenine by OH⁻, while pathway E is initiated by tautomerization of adenine. For all pathways, the next two steps involve the formation of a tetrahedral intermediate followed by dissociation to yield products via a 1,3-hydrogen shift. Deamination with a single OH⁻ has a high activation barrier (190 kJ mol⁻¹ using G3MP2B3 level) for the rate-determining step. Addition of one water molecule reduces this barrier by 68 kJ mol⁻¹ calculated at G3MP2B3 level. Adding more water molecules decreases the overall activation energy of the reaction, but the effect becomes smaller with each additional water molecule. The most plausible mechanism is pathway E, the deamination reaction of adenine with 3H₂O, which has an overall G3MP2B3 activation energy of 139 and 137 kJ mol⁻¹ in the gas phase and PCM, respectively. This barrier is lower than that for the deamination with OH⁻/3H₂O by 6 and 2 kJ mol⁻¹ in the gas phase and PCM, respectively.

Spatial modeling of data with excessive zeros applied to reindeer pellet-group counts

We analyze a real data set pertaining to reindeer fecal pellet-group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation. We use conditionally autoregressive random effects for modeling of spatial correlation in a Poisson generalized linear mixed model (GLMM), quasi-Poisson hierarchical generalized linear model (HGLM), zero-inflated Poisson (ZIP), and hurdle models. The quasi-Poisson HGLM allows for both under- and overdispersion with excessive zeros, while the ZIP and hurdle models allow only for overdispersion. In analyzing the real data set, we see that the quasi-Poisson HGLMs can perform better than the other commonly used models, for example, ordinary Poisson HGLMs, spatial ZIP, and spatial hurdle models, and that the underdispersed Poisson HGLMs with spatial correlation fit the reindeer data best. We develop R codes for fitting these models using a unified algorithm for the HGLMs. Spatial count response with an extremely high proportion of zeros, and underdispersion can be successfully modeled using the quasi-Poisson HGLM with spatial random effects.

Generalized cluster states based on finite groups

We define generalized cluster states based on finite group algebras in analogy to the generalization of the toric code to the Kitaev quantum double models. We do this by showing a general correspondence between systems with CSS structure and finite group algebras, and applying this to the cluster states to derive their generalization. We then investigate properties of these states including their projected entangled pair state representations, global symmetries, and relationship to the Kitaev quantum double models. We also discuss possible applications of these states.

Use of ordinal outcomes in vascular prevention trials: comparison with binary outcomes in published trials

Background and Purpose—Vascular prevention trials mostly count “yes/no” (binary) outcome events, eg, stroke/no stroke. Analysis of ordered categorical vascular events (eg, fatal stroke/nonfatal stroke/no stroke) is clinically relevant and could be more powerful statistically. Although this is not a novel idea in the statistical community, ordinal outcomes have not been applied to stroke prevention trials in the past. Methods—Summary data on stroke, myocardial infarction, combined vascular events, and bleeding were obtained by treatment group from published vascular prevention trials. Data were analyzed using 10 statistical approaches which allow comparison of 2 ordinal or binary treatment groups. The results for each statistical test for each trial were then compared using Friedman 2-way analysis of variance with multiple comparison procedures. Results—Across 85 trials (335 305 subjects) the test results differed substantially so that approaches which used the ordinal nature of stroke events (fatal/nonfatal/no stroke) were more efficient than those which combined the data to form 2 groups (P0.0001). The most efficient tests were bootstrapping the difference in mean rank, Mann–Whitney U test, and ordinal logistic regression; 4- and 5-level data were more efficient still. Similar findings were obtained for myocardial infarction, combined vascular outcomes, and bleeding. The findings were consistent across different types, designs and sizes of trial, and for the different types of intervention. Conclusions—When analyzing vascular events from prevention trials, statistical tests which use ordered categorical data are more efficient and are more likely to yield reliable results than binary tests. This approach gives additional information on treatment effects by severity of event and will allow trials to be smaller. (Stroke. 2008;39:000-000.)