Three years in vivo wear: core-ceramic, veneers, and enamel antagonists.

OBJECTIVES: Test the hypotheses that there are equivalent wear rates for enamel-versus-enamel and ceramic-versus-enamel, analyzing the in vivo wear of crown ceramics, their natural enamel antagonists, and the corresponding two contralateral teeth; and, that bite force does not correlate with the wear. METHODS: A controlled, clinical trial was conducted involving patients needing full coverage crowns opposing enamel antagonists. Bite forces were measured using a bilateral gnathodynamometer. Single-unit restorations of metal/ceramic (Argedent 62, Argen Corp/IPS d.SIGN veneer); or, core-ceramic/veneer from either, Empress2/Eris, or e.max Press core/e.max Ceram glaze (ceramics: Ivoclar Vivadent, USA) were randomly assigned, fabricated and cemented. Impressions were made of the ceramic crowns, as well as each maxillary and mandibular quadrant at one week (baseline) and one, two and three years. Resulting models were scanned (3D laser scanner). Maximum wear was calculated by superimposing baseline with annual images. RESULTS: There were a total of thirty-six crowns required for thirty-one patients. Each restoration had three associated enamel teeth: crown, (1) antagonist, (2) contralateral and (3) contralateral-antagonist. SAS PROC MIXED (α=0.05) indicated no statistical significance for mean maximum wear among crown ceramics, enamel antagonists and contralaterals. However, enamel wear was statistically significant in relation to intraoral location (p=0.04) and among years (p<0.02). Analyzed alone, the enamel contralateral-antagonist exhibited significantly greater wear (p<0.001). Considering all wear sites, there was no correlation with bite force (p=0.15). SIGNIFICANCE: The ceramics and their antagonists exhibited in vivo wear rates within the range of normal enamel. Future studies should examine the wear implications of the contralateral-antagonist enamel.

Interval estimation in two-stage, drop-the-losers clinical trials with flexible treatment selection.

In a two-stage, drop-the-losers clinical trial, researchers choose the 'best' among a number of treatments at an interim analysis after the first stage. The selected treatment continues to the second stage for confirmation of efficacy, and the remaining treatments (the 'losers') are dropped from the study. Wu et al. (Biometrika 2010; 97:405-418) showed how to construct confidence limits for the mean difference between the selected treatment and the control when the treatment is chosen after the first stage based on the highest efficacy in the primary clinical endpoint. In this article, we show how to construct a lower confidence limit for the mean difference when the treatment is chosen based on first-stage safety data, early endpoint efficacy data, a combination of safety and efficacy data or any other prespecified selection rule. The result extends the applicability of drop-the-losers designs, for in practice, the 'best' treatment often is not chosen for efficacy alone.

Development and temporal organization of repetitive behavior in an animal model.

Despite repetitive behaviors being a common feature of a number of clinical disorders and ubiquitous in normative development, little attention has been given to their ontogeny or temporal dynamics. We characterized these features in a mouse model of repetitive behavior to identify discrete trajectories of development and developmental changes in temporal dynamics. Three qualitatively distinct trajectory groups were identified which allowed for an examination of the interaction between temporal organization and developmental trajectory. Significant differences in temporal dynamics were found across development and among trajectory groups. Significant interactions of trajectory group and developmental period on temporal organization were also found. The combination of group-based trajectory modeling and a novel method for analysis and graphic depiction of temporal organization allowed for the exploration of the interplay between these two fundamental behavioral processes. Such methods may be useful tools in the assessment and treatment of repetitive behavior in clinical populations.

Identifying temporally differentially expressed genes through functional principal components analysis.

Time course gene microarray is an important tool to identify genes with differential expressions over time. Traditional analysis of variance (ANOVA) type of longitudinal investigation may not be applicable because of irregular time intervals and possible missingness due to contamination in microarray experiments. Functional principal components analysis is proposed to test hypotheses in the change of the mean curves. A permutation test under a mild assumption is used to make the method more robust. The proposed method outperforms the recently developed extraction of differential gene expression and a 2-way mixed effects ANOVA under reasonable gene expression models in simulation. Real data on transcriptional profiles of blood cells microarray from treated and untreated individuals were used to illustrate this method.

An optimal DNA pooling strategy for progressive fine mapping.

We present a cost-effective DNA pooling strategy for fine mapping of a single Mendelian gene in controlled crosses. The theoretical argument suggests that it is potentially possible for a single-stage pooling approach to reduce the overall experimental expense considerably by balancing costs for genotyping and sample collection. Further, the genotyping burden can be reduced through multi-stage pooling. Numerical results are provided for practical guidelines. For example, the genotyping effort can be reduced to only a small fraction of that needed for individual genotyping at a small loss of estimation accuracy or at a cost of increasing sample sizes slightly when recombination rates are 0.5% or less. An optimal two-stage pooling scheme can reduce the amount of genotyping to 19.5%, 14.5% and 6.4% of individual genotyping efforts for identifying a gene within 1, 0.5, and 0.1 cM, respectively. Finally, we use a genetic data set for mapping the rice xl(t) gene to demonstrate the feasibility and efficiency of the DNA pooling strategy. Taken together, the results demonstrate that this DNA pooling strategy can greatly reduce the genotyping burden and the overall cost in fine mapping experiments.

Procedural learning and cognitive flexibility in a mouse model of restricted, repetitive behaviour.

Restricted, repetitive behaviours (e.g., stereotypies, compulsions, rituals) in neurodevelopmental disorders have been linked to alterations in cortico-basal ganglia circuitry. Cognitive processes mediated by this circuitry (e.g., procedural learning, executive function) are likely to be impaired in individuals exhibiting high rates of repetitive behaviour. To test this hypothesis, we assessed both procedural learning and cognitive flexibility (reversal learning) using a T-maze task in deer mice (Peromyscus maniculatus) exhibiting various rates of repetitive behaviour (vertical jumping and backward somersaulting). These mice exhibited high rates of stereotypy when reared in standard rodent cages, and such behaviour was significantly attenuated by housing them in larger more complex environments. Mice reared in complex environments exhibited significantly better procedural and reversal learning than standard caged mice. Thus, early experience associated with the prevention and attenuation of stereotypy was associated with better striatally mediated learning and cognitive flexibility. Stereotypy score was significantly correlated with the number of errors made in reversal learning, and interacted with housing condition to affect overall cognitive performance. Our findings support the applicability of the deer mouse model of spontaneous stereotypy to a wider range of restricted, repetitive behaviour (e.g., insistence on sameness) typical of neurodevelopmental disorders.

D-cycloserine does not enhance exposure-response prevention therapy in obsessive-compulsive disorder.

Obsessive-compulsive disorder is a common, chronic, and oftentimes disabling disorder. The only established first-line treatments for obsessive-compulsive disorder are exposure and response prevention therapy and the serotonin reuptake inhibitors. Many patients do not experience complete symptom resolution with either modality and require augmentation approaches. Recent animal and clinical data suggest that D-cycloserine, a partial agonist that acts at the strychnine-insensitive glycine-recognition site of the N-methyl-D-aspartate receptor complex, may enhance extinction learning that occurs in exposure-based psychotherapies. Given this, this study examined if D-cycloserine (250 mg) enhances the overall efficacy and rate of change of exposure and response prevention therapy for adult obsessive-compulsive disorder. Participants were 24 adults meeting Diagnostic and Statistical Manual of Mental Disorders-IV criteria for obsessive-compulsive disorder. The study design was a randomized, double-blinded, placebo-controlled augmentation trial examining exposure and response prevention therapy+D-cycloserine versus exposure and response prevention therapy+placebo. All patients received 12 weekly sessions of exposure and response prevention treatment. The first session involved building a ritual hierarchy and providing psychoeducation about obsessive-compulsive disorder. The second session involved a practice exposure. Sessions 3-12 involved exposure and response prevention exercises. D-cycloserine or placebo (250 mg) was taken 4 h before every session. No significant group differences were found across outcome variables. The rate of improvement did not differ between groups. The present results fail to support the use of D-cycloserine with exposure and response prevention therapy for adult obsessive-compulsive disorder. As this study is the first to explore this question and a number of methodological issues must be considered when interpreting the findings, the conclusions that may be drawn from our results are limited.

Relationship of movements and behaviors to Group A Streptococcus infections in elementary school children.

BACKGROUND: Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcus (PANDAS) research is based on the hypothesis that infections trigger changes in behavior and movement in children. METHODS: We enrolled 693 children (ages 3 to 12 years) into a systematic, longitudinal study. Data were collected monthly for 8 months (October-May) to determine point prevalence of Group A Streptococcal (GAS) infections, tics, behavior, and choreiform movements. Simultaneous throat cultures were obtained, and relational analyses were made between GAS and movement/observation ratings. RESULTS: Combined behavior/GAS associations (concurrent with or 3 subsequent months to GAS) revealed a strong relationship, relative risk (RR) of 1.71 (p < .0001). Detailed analysis revealed that balance/swaying and non-tic grimacing were responsible for a significant proportion of this association (RR = 2.92, p < .0001). A strong seasonal pattern was found, with fall being more significant for GAS infections and observation ratings (p < .0001) compared with winter/spring. Children with repeated streptococcus (n = 64) showed higher rates of behavior and distal choreiform observations (p = .005). CONCLUSIONS: Motor/behavior changes were noted to occur in relationship to positive GAS culture with support that repeated GAS increases risk.

Predictability analysis for an automated seizure prediction algorithm.

Epileptic seizures of mesial temporal origin are preceded by changes in signal properties detectable in the intracranial EEG. A series of computer algorithms designed to detect the changes in spatiotemporal dynamics of the EEG signals and to warn of impending seizures have been developed. In this study, we evaluated the performance of a novel adaptive threshold seizure warning algorithm (ATSWA), which detects the convergence in Short-Term Maximum Lyapunov Exponent (STLmax) values among critical intracranial EEG electrode sites, as a function of different seizure warning horizons (SWHs). The ATSWA algorithm was compared to two statistical based naïve prediction algorithms (periodic and random) that do not employ EEG information. For comparison purposes, three performance indices "area above ROC curve" (AAC), "predictability power" (PP) and "fraction of time under false warnings" (FTF) were defined and the effect of SWHs on these indices was evaluated. The results demonstrate that this EEG based seizure warning method performed significantly better (P < 0.05) than both naïve prediction schemes. Our results also show that the performance indexes are dependent on the length of the SWH. These results suggest that the EEG based analysis has the potential to be a useful tool for seizure warning.

Estimating effects of a single gene and polygenes on quantitative traits from a diallel design.

A genetic model is developed with additive and dominance effects of a single gene and polygenes as well as general and specific reciprocal effects for the progeny from a diallel mating design. The methods of ANOVA, minimum norm quadratic unbiased estimation (MINQUE), restricted maximum likelihood estimation (REML), and maximum likelihood estimation (ML) are suggested for estimating variance components, and the methods of generalized least squares (GLS) and ordinary least squares (OLS) for fixed effects, while best linear unbiased prediction, linear unbiased prediction (LUP), and adjusted unbiased prediction are suggested for analyzing random effects. Monte Carlo simulations were conducted to evaluate the unbiasedness and efficiency of statistical methods involving two diallel designs with commonly used sample sizes, 6 and 8 parents, with no and missing crosses, respectively. Simulation results show that GLS and OLS are almost equally efficient for estimation of fixed effects, while MINQUE (1) and REML are better estimators of the variance components and LUP is most practical method for prediction of random effects. Data from a Drosophila melanogaster experiment (Gilbert 1985a, Theor appl Genet 69:625-629) were used as a working example to demonstrate the statistical analysis. The new methodology is also applicable to screening candidate gene(s) and to other mating designs with multiple parents, such as nested (NC Design I) and factorial (NC Design II) designs. Moreover, this methodology can serve as a guide to develop new methods for detecting indiscernible major genes and mapping quantitative trait loci based on mixture distribution theory. The computer program for the methods suggested in this article is freely available from the authors.

Is speeding a form of gambling in adolescents?

Speeding is a major contributor to motor vehicle accidents, which are the leading cause of death in adolescents. This study compares the extent to which adolescents with gambling behavior and substance use reported driving over the posted speed limits ("speeding"). Florida adolescents ages 13-17 (n = 1051) were surveyed, and asked about gambling activities, problems related to gambling, substance use, demographic questions, and speeding. Of the 562 respondents who were drivers, the gender distribution was 52.1% male and 47.9% female. Of those respondents, 76.9% were Caucasian, 6.8% were African American, 10.1% were Hispanic, and 6.1% were Native American/Asian/Other. Simple correlation analysis revealed that self-reported speeding is significantly related to gambling behavior and substance use. When a linear regression model was used, four factors showed the most significant influence on self-reported speeding: past year gambling tendency, age, trouble with the police due to drinking, and tranquilizer usage. Gambling behavior and high-risk speeding (driving ≥ 10 mph over speed limit) also were noted to be positively correlated. Our data indicate a relationship between risky driving, gambling, and other risk-taking behaviors in adolescents, and support the hypothesis that speeding may be a form of gambling behavior in this age group.

An improved procedure for gene selection from microarray experiments using false discovery rate criterion.

BACKGROUND: A large number of genes usually show differential expressions in a microarray experiment with two types of tissues, and the p-values of a proper statistical test are often used to quantify the significance of these differences. The genes with small p-values are then picked as the genes responsible for the differences in the tissue RNA expressions. One key question is what should be the threshold to consider the p-values small. There is always a trade off between this threshold and the rate of false claims. Recent statistical literature shows that the false discovery rate (FDR) criterion is a powerful and reasonable criterion to pick those genes with differential expression. Moreover, the power of detection can be increased by knowing the number of non-differential expression genes. While this number is unknown in practice, there are methods to estimate it from data. The purpose of this paper is to present a new method of estimating this number and use it for the FDR procedure construction. RESULTS: A combination of test functions is used to estimate the number of differentially expressed genes. Simulation study shows that the proposed method has a higher power to detect these genes than other existing methods, while still keeping the FDR under control. The improvement can be substantial if the proportion of true differentially expressed genes is large. This procedure has also been tested with good results using a real dataset. CONCLUSION: For a given expected FDR, the method proposed in this paper has better power to pick genes that show differentiation in their expression than two other well known methods.

Improvement of mapping accuracy by unifying linkage and association analysis.

It is well known that pedigree/family data record information on the coexistence in founder haplotypes of alleles at nearby loci and the cotransmission from parent to offspring that reveal different, but complementary, profiles of the genetic architecture. Either conventional linkage analysis that assumes linkage equilibrium or family-based association tests (FBATs) capture only partial information, leading to inefficiency. For example, FBATs will fail to detect even very tight linkage in the case where no allelic association exists, while a violation of the assumption of linkage equilibrium will result in biased estimation and reduced efficiency in linkage mapping. In this article, by using a data augmentation technique and the EM algorithm, we propose a likelihood-based approach that embeds both linkage and association analyses into a unified framework for general pedigree data. Relative to either linkage or association analysis, the proposed approach is expected to have greater estimation accuracy and power. Monte Carlo simulations support our theoretical expectations and demonstrate that our new methodology: (1) is more powerful than either FBATs or classic linkage analysis; (2) can unbiasedly estimate genetic parameters regardless of whether association exists, thus remedying the bias and less precision of traditional linkage analysis in the presence of association; and (3) is capable of identifying tight linkage alone. The new approach also holds the theoretical advantage that it can extract statistical information to the maximum extent and thereby improve mapping accuracy and power because it integrates multilocus population-based association study and pedigree-based linkage analysis into a coherent framework. Furthermore, our method is numerically stable and computationally efficient, as compared to existing parametric methods that use the simplex algorithm or Newton-type methods to maximize high-order multidimensional likelihood functions, and also offers the computation of Fisher's information matrix. Finally, we apply our methodology to a genetic study on bone mineral density (BMD) for the vitamin D receptor (VDR) gene and find that VDR is significantly linked to BMD at the one-third region of the wrist.

A model for estimating joint maternal-offspring effects on seed development in autogamous plants.

We present a statistical model for testing and estimating the effects of maternal-offspring genome interaction on the embryo and endosperm traits during seed development in autogamous plants. Our model is constructed within the context of maximum likelihood implemented with the EM algorithm. Extensive simulations were performed to investigate the statistical properties of our approach. We have successfully identified a quantitative trait locus that exerts a significant maternal-offspring interaction effect on amino acid contents of the endosperm in maize, demonstrating the power of our approach. This approach will be broadly useful in mapping endosperm traits for many agriculturally important crop plants and also make it possible to study the genetic significance of double fertilization in the evolution of higher plants.

Cerebral edema in childhood diabetic ketoacidosis: natural history, radiographic findings, and early identification.

OBJECTIVE: Children who develop cerebral edema (CE) during diabetic ketoacidosis (DKA) exhibit definable signs and symptoms of neurological collapse early enough to allow intervention to prevent brain damage. Our objective was to develop a model for early detection of CE in children with DKA. RESEARCH DESIGN AND METHODS: A training sample of 26 occurrences of DKA complicated by severe CE and 69 episodes of uncomplicated DKA was reviewed. Signs of neurological disease were incorporated into a bedside evaluation protocol that was applied to an independent test sample of 17 patients previously reported to have developed symptomatic CE during treatment for DKA. Head computed tomograms and their reports were reviewed. RESULTS: The protocol allowed 92% sensitivity and 96% specificity for the recognition of CE sufficiently early for intervention. The diagnostic criteria were fulfilled in two temporal patterns, defining early- and late-onset CE. Although initial computed tomograms were often normal, the findings also included diffuse CE and focal brain injury, the latter only in patients with an early onset of abnormal neurological signs. CONCLUSIONS: CE may occur in the absence of acute changes on head computed tomograms. Early detection of CE at the bedside using an evidence-based protocol permits intervention in time to prevent permanent brain damage.

Controlled evaluation of the STARBRIGHT CD-ROM program for children and adolescents with Cystic Fibrosis.

OBJECTIVE: To evaluate the effectiveness of the STARBRIGHT Fitting Cystic Fibrosis Into Your Life Everyday CD-ROM. Data were analyzed to evaluate the effectiveness of the program as an educational tool for children and adolescents with cystic fibrosis (CF). METHODS: Forty-seven children and adolescents with CF between the ages of 7 and 17 years were enrolled in the study. Participants completed an initial evaluation of CF-related knowledge and coping skills and were then randomly assigned to one of two groups: the treatment group or the wait-list control group. Participants then viewed the CD-ROM, and researchers completed posttest measures. RESULTS: Analyses indicated that both disease-related knowledge and coping strategies generated by children and adolescents with CF improved as a result of the intervention and that this effect was replicated in the wait-list group. CONCLUSIONS: In sum, the results of the current study indicate that the STARBRIGHT CD-ROM program is a promising intervention for increasing CF-related knowledge and the competence of children's and adolescents' coping strategies. These positive results are enhanced by the brief, inexpensive, and portable nature of this educational program.

A double-blind, placebo-controlled trial of olanzapine addition in fluoxetine-refractory obsessive-compulsive disorder.

BACKGROUND: One of the few combination approaches to the treatment of obsessive-compulsive disorder (OCD) with encouraging support is the addition of an antipsychotic to a serotonin reuptake inhibitor. METHODS: The study consisted of a 6-week, placebo-controlled addition of olanzapine 5-10 mg (6.1 +/- 2.1 mg, mean +/- SD) to fluoxetine in OCD subjects who were partial or nonresponders to an 8-week, open-label fluoxetine trial (40 mg in 43 subjects, 20 mg in 1 subject). RESULTS: Both the fluoxetine-plus-olanzapine (n = 22) and fluoxetine-plus-placebo (n = 22) groups improved significantly over 6 weeks [F(3,113) = 11.64, p <.0001] according to Yale-Brown Obsessive Compulsive Scale scores with repeated-measures analysis of variance; however, the treatment x time interaction was not significant for olanzapine versus placebo addition to fluoxetine. CONCLUSIONS: These findings indicate no additional advantage of adding olanzapine for 6 weeks in OCD patients who have not had a satisfactory response to fluoxetine for 8 weeks, compared with extending the monotherapy trial.

Quantitative trait loci for growth trajectories in Populus.

Growth trajectories are a biological process important to plant and animal breeding, and to evolutionary genetic studies. In this article, we report the detection of quantitative trait loci (QTLs) responsible for growth trajectories in poplars that are used as a model system for the study of forest biology. These QTLs were localized on a genetic linkage map of polymorphic markers using a statistical mapping method incorporating growth-curve models. The effects of the QTLs on growth are described as a function of age, so that age-specific changes in QTL effects can be readily projected throughout the entire growth process. The QTLs identified display increased effects on growth when trees age, yet the timing of QTL activation is earlier for stem height than diameter, which is consistent with the ecological viewpoint of canopy competition. The implications of the results for breeding and silviculture are discussed.

A haplotype-based algorithm for multilocus linkage disequilibrium mapping of quantitative trait loci with epistasis.

For tightly linked loci, cosegregation may lead to nonrandom associations between alleles in a population. Because of its evolutionary relationship with linkage, this phenomenon is called linkage disequilibrium. Today, linkage disequilibrium-based mapping has become a major focus of recent genome research into mapping complex traits. In this article, we present a new statistical method for mapping quantitative trait loci (QTL) of additive, dominant, and epistatic effects in equilibrium natural populations. Our method is based on haplotype analysis of multilocus linkage disequilibrium and exhibits two significant advantages over current disequilibrium mapping methods. First, we have derived closed-form solutions for estimating the marker-QTL haplotype frequencies within the maximum-likelihood framework implemented by the EM algorithm. The allele frequencies of putative QTL and their linkage disequilibria with the markers are estimated by solving a system of regular equations. This procedure has significantly improved the computational efficiency and the precision of parameter estimation. Second, our method can detect marker-QTL disequilibria of different orders and QTL epistatic interactions of various kinds on the basis of a multilocus analysis. This can not only enhance the precision of parameter estimation, but also make it possible to perform whole-genome association studies. We carried out extensive simulation studies to examine the robustness and statistical performance of our method. The application of the new method was validated using a case study from humans, in which we successfully detected significant QTL affecting human body heights. Finally, we discuss the implications of our method for genome projects and its extension to a broader circumstance. The computer program for the method proposed in this article is available at the webpage http://www.ifasstat.ufl.edu/genome/~LD.

Comparison of blood pressure measurement consistency using tonometric and automated oscillometric instruments.

To effectively evaluate treatments for hypertension, researchers and clinicians must be able to measure blood pressure (BP) in a valid and reliable way. The purpose of this study is to compare measurements made in the clinic using beat-to-beat radial BP tonometry, measurements made during 24 hours using an ambulatory BP monitor, and measurements made in the clinic using an automated oscillometric BP monitor. Fifty-seven adults with primary hypertension participated in this study, which used a repeated measures descriptive design. Clinic and ABPM daytime averages were compatible for both SBP and DBP. In contrast, clinic SBP was 7.56 mmHg higher than the beat-to-beat SBP; clinic DBP was 9.83 mmHg higher than the beat-to-beat DBP. These data suggest that automated clinic measurements may be used in place of daytime ambulatory BP measurements. We also estimate sample sizes for future studies based on characteristics of clinic BP.