All-ceramic or metal-ceramic tooth-supported fixed dental prostheses (FDPs)? A systematic review of the survival and complication rates. Part I: Single crowns (SCs).

OBJECTIVE To assess the 5-year survival of metal-ceramic and all-ceramic tooth-supported single crowns (SCs) and to describe the incidence of biological, technical and esthetic complications. METHODS Medline (PubMed), Embase, Cochrane Central Register of Controlled Trials (CENTRAL) searches (2006-2013) were performed for clinical studies focusing on tooth-supported fixed dental prostheses (FDPs) with a mean follow-up of at least 3 years. This was complimented by an additional hand search and the inclusion of 34 studies from a previous systematic review [1,2]. Survival and complication rates were analyzed using robust Poisson's regression models to obtain summary estimates of 5-year proportions. RESULTS Sixty-seven studies reporting on 4663 metal-ceramic and 9434 all-ceramic SCs fulfilled the inclusion criteria. Seventeen studies reported on metal-ceramic crowns, and 54 studies reported on all-ceramic crowns. Meta-analysis of the included studies indicated an estimated survival rate of metal-ceramic SCs of 94.7% (95% CI: 94.1-96.9%) after 5 years. This was similar to the estimated 5-year survival rate of leucit or lithium-disilicate reinforced glass ceramic SCs (96.6%; 95% CI: 94.9-96.7%), of glass infiltrated alumina SCs (94.6%; 95% CI: 92.7-96%) and densely sintered alumina and zirconia SCs (96%; 95% CI: 93.8-97.5%; 92.1%; 95% CI: 82.8-95.6%). In contrast, the 5-year survival rates of feldspathic/silica-based ceramic crowns were lower (p<0.001). When the outcomes in anterior and posterior regions were compared feldspathic/silica-based ceramic and zirconia crowns exhibited significantly lower survival rates in the posterior region (p<0.0001), the other crown types performed similarly. Densely sintered zirconia SCs were more frequently lost due to veneering ceramic fractures than metal-ceramic SCs (p<0.001), and had significantly more loss of retention (p<0.001). In total higher 5 year rates of framework fracture were reported for the all-ceramic SCs than for metal-ceramic SCs. CONCLUSIONS Survival rates of most types of all-ceramic SCs were similar to those reported for metal-ceramic SCs, both in anterior and posterior regions. Weaker feldspathic/silica-based ceramics should be limited to applications in the anterior region. Zirconia-based SCs should not be considered as primary option due to their high incidence of technical problems.

Pre-clinical in vivo models for the screening of bone biomaterials for oral/craniofacial indications: focus on small-animal models.

Preclinical in vivo experimental studies are performed for evaluating proof-of-principle concepts, safety and possible unwanted reactions of candidate bone biomaterials before proceeding to clinical testing. Specifically, models involving small animals have been developed for screening bone biomaterials for their potential to enhance bone formation. No single model can completely recreate the anatomic, physiologic, biomechanic and functional environment of the human mouth and jaws. Relevant aspects regarding physiology, anatomy, dimensions and handling are discussed in this paper to elucidate the advantages and disadvantages of small-animal models. Model selection should be based not on the 'expertise' or capacities of the team, but rather on a scientifically solid rationale, and the animal model selected should reflect the question for which an answer is sought. The rationale for using heterotopic or orthotopic testing sites, and intraosseous, periosseous or extraskeletal defect models, is discussed. The paper also discusses the relevance of critical size defect modeling, with focus on calvarial defects in rodents. In addition, the rabbit sinus model and the capsule model in the rat mandible are presented and discussed in detail. All animal experiments should be designed with care and include sample-size and study-power calculations, thus allowing generation of meaningful data. Moreover, animal experiments are subject to ethical approval by the relevant authority. All procedures and the postoperative handling and care, including postoperative analgesics, should follow best practice.

All-loop anomalous dimensions in integrable λ-deformed σ-models

We calculate the all-loop anomalous dimensions of current operators in λ-deformed σ-models. For the isotropic integrable deformation and for a semi-simple group G we compute the anomalous dimensions using two different methods. In the first we use the all-loop effective action and in the second we employ perturbation theory along with the Callan–Symanzik equation and in conjunction with a duality-type symmetry shared by these models. Furthermore, using CFT techniques we compute the all-loop anomalous dimension of bilinear currents for the isotropic deformation case and a general G . Finally we work out the anomalous dimension matrix for the cases of anisotropic SU(2) and the two couplings, corresponding to the symmetric coset G/H and a subgroup H, splitting of a group G.

Plasma environment of a weak comet – Predictions for Comet 67P/Churyumov–Gerasimenko from multifluid-MHD and Hybrid models

The interaction of a comet with the solar wind undergoes various stages as the comet’s activity varies along its orbit. For a comet like 67P/Churyumov–Gerasimenko, the target comet of ESA’s Rosetta mission, the various features include the formation of a Mach cone, the bow shock, and close to perihelion even a diamagnetic cavity. There are different approaches to simulate this complex interplay between the solar wind and the comet’s extended neutral gas coma which include magnetohydrodynamics (MHD) and hybrid-type models. The first treats the plasma as fluids (one fluid in basic single fluid MHD) and the latter treats the ions as individual particles under the influence of the local electric and magnetic fields. The electrons are treated as a charge-neutralizing fluid in both cases. Given the different approaches both models yield different results, in particular for a low production rate comet. In this paper we will show that these differences can be reduced when using a multifluid instead of a single-fluid MHD model and increase the resolution of the Hybrid model. We will show that some major features obtained with a hybrid type approach like the gyration of the cometary heavy ions and the formation of the Mach cone can be partially reproduced with the multifluid-type model.

An improved single-plaquette gauge action

We describe and test a nonperturbatively improved single-plaquette lattice action for 4-d SU(2) and SU(3) pure gauge theory, which suppresses large fluctuations of the plaquette, without requiring the naive continuum limit for smooth fields. We tune the action parameters based on torelon masses in moderate cubic physical volumes, and investigate the size of cut-off effects in other physical quantities, including torelon masses in asymmetric spatial volumes, the static quark potential, and gradient flow observables. In 2-d O(N) models similarly constructed nearest-neighbor actions have led to a drastic reduction of cut-off effects, down to the permille level, in a wide variety of physical quantities. In the gauge theories, we find significant reduction of lattice artifacts, and for some observables, the coarsest lattice result is very close to the continuum value. We estimate an improvement factor of 40 compared to using the Wilson gauge action to achieve the same statistical accuracy and suppression of cut-off effects.

A Single-blinded, Randomized Clinical Trial of How to Implement an Evidence-based Treatment for Generalized Anxiety Disorder [IMPLEMENT] — Effects of Three Different Strategies of Implementation

BACKGROUND: Despite long-standing calls to disseminate evidence-based treatments for generalized anxiety (GAD), modest progress has been made in the study of how such treatments should be implemented. The primary objective of this study was to test three competing strategies on how to implement a cognitive behavioral treatment (CBT) for out-patients with GAD (i.e., comparison of one compensation vs. two capitalization models). METHODS: For our three-arm, single-blinded, randomized controlled trial (implementation of CBT for GAD [IMPLEMENT]), we recruited adults with GAD using advertisements in high-circulation newspapers to participate in a 14-session cognitive behavioral treatment (Mastery of your Anxiety and Worry, MAW-packet). We randomly assigned eligible patients using a full randomization procedure (1:1:1) to three different conditions of implementation: adherence priming (compensation model), which had a systematized focus on patients' individual GAD symptoms and how to compensate for these symptoms within the MAW-packet, and resource priming and supportive resource priming (capitalization model), which had systematized focuses on patients' strengths and abilities and how these strengths can be capitalized within the same packet. In the intention-to-treat population an outcome composite of primary and secondary symptoms-related self-report questionnaires was analyzed based on a hierarchical linear growth model from intake to 6-month follow-up assessment. This trial is registered at ClinicalTrials.gov (identifier: NCT02039193) and is closed to new participants. FINDINGS: From June 2012 to Nov. 2014, from 411 participants that were screened, 57 eligible participants were recruited and randomly assigned to three conditions. Forty-nine patients (86%) provided outcome data at post-assessment (14% dropout rate). All three conditions showed a highly significant reduction of symptoms over time. However, compared with the adherence priming condition, both resource priming conditions indicated faster symptom reduction. The observer ratings of a sub-sample of recorded videos (n = 100) showed that the therapists in the resource priming conditions conducted more strength-oriented interventions in comparison with the adherence priming condition. No patients died or attempted suicide. INTERPRETATION: To our knowledge, this is the first trial that focuses on capitalization and compensation models during the implementation of one prescriptive treatment packet for GAD. We have shown that GAD related symptoms were significantly faster reduced by the resource priming conditions, although the limitations of our study included a well-educated population. If replicated, our results suggest that therapists who implement a mental health treatment for GAD might profit from a systematized focus on capitalization models. FUNDING: Swiss Science National Foundation (SNSF-Nr. PZ00P1_136937/1) awarded to CF. KEYWORDS: Cognitive behavioral therapy; Evidence-based treatment; Implementation strategies; Randomized controlled trial

Exact moment calculations for genetic models with migration, mutation, and drift

Using properties of moment stationarity we develop exact expressions for the mean and covariance of allele frequencies at a single locus for a set of populations subject to drift, mutation, and migration. Some general results can be obtained even for arbitrary mutation and migration matrices, for example: (1) Under quite general conditions, the mean vector depends only on mutation rates, not on migration rates or the number of populations. (2) Allele frequencies covary among all pairs of populations connected by migration. As a result, the drift, mutation, migration process is not ergodic when any finite number of populations is exchanging genes. in addition, we provide closed form expressions for the mean and covariance of allele frequencies in Wright's finite-island model of migration under several simple models of mutation, and we show that the correlation in allele frequencies among populations can be very large for realistic rates of mutation unless an enormous number of populations are exchanging genes. As a result, the traditional diffusion approximation provides a poor approximation of the stationary distribution of allele frequencies among populations. Finally, we discuss some implications of our results for measures of population structure based on Wright's F-statistics.

Single nucleotide polymorphism (SNP) selection for genotype-phenotype association studies

With hundreds of single nucleotide polymorphisms (SNPs) in a candidate gene and millions of SNPs across the genome, selecting an informative subset of SNPs to maximize the ability to detect genotype-phenotype association is of great interest and importance. In addition, with a large number of SNPs, analytic methods are needed that allow investigators to control the false positive rate resulting from large numbers of SNP genotype-phenotype analyses. This dissertation uses simulated data to explore methods for selecting SNPs for genotype-phenotype association studies. I examined the pattern of linkage disequilibrium (LD) across a candidate gene region and used this pattern to aid in localizing a disease-influencing mutation. The results indicate that the r2 measure of linkage disequilibrium is preferred over the common D′ measure for use in genotype-phenotype association studies. Using step-wise linear regression, the best predictor of the quantitative trait was not usually the single functional mutation. Rather it was a SNP that was in high linkage disequilibrium with the functional mutation. Next, I compared three strategies for selecting SNPs for application to phenotype association studies: based on measures of linkage disequilibrium, based on a measure of haplotype diversity, and random selection. The results demonstrate that SNPs selected based on maximum haplotype diversity are more informative and yield higher power than randomly selected SNPs or SNPs selected based on low pair-wise LD. The data also indicate that for genes with small contribution to the phenotype, it is more prudent for investigators to increase their sample size than to continuously increase the number of SNPs in order to improve statistical power. When typing large numbers of SNPs, researchers are faced with the challenge of utilizing an appropriate statistical method that controls the type I error rate while maintaining adequate power. We show that an empirical genotype based multi-locus global test that uses permutation testing to investigate the null distribution of the maximum test statistic maintains a desired overall type I error rate while not overly sacrificing statistical power. The results also show that when the penetrance model is simple the multi-locus global test does as well or better than the haplotype analysis. However, for more complex models, haplotype analyses offer advantages. The results of this dissertation will be of utility to human geneticists designing large-scale multi-locus genotype-phenotype association studies. ^

Cross-Country Evidence on Output Growth Volatility: Nonstationary Variance and GARCH Models

This paper revisits the issue of conditional volatility in real GDP growth rates for Canada, Japan, the United Kingdom, and the United States. Previous studies find high persistence in the volatility. This paper shows that this finding largely reflects a nonstationary variance. Output growth in the four countries became noticeably less volatile over the past few decades. In this paper, we employ the modified ICSS algorithm to detect structural change in the unconditional variance of output growth. One structural break exists in each of the four countries. We then use generalized autoregressive conditional heteroskedasticity (GARCH) specifications modeling output growth and its volatility with and without the break in volatility. The evidence shows that the time-varying variance falls sharply in Canada, Japan, and the U.K. and disappears in the U.S., excess kurtosis vanishes in Canada, Japan, and the U.S. and drops substantially in the U.K., once we incorporate the break in the variance equation of output for the four countries. That is, the integrated GARCH (IGARCH) effect proves spurious and the GARCH model demonstrates misspecification, if researchers neglect a nonstationary unconditional variance.

On the Existence and Characterization of Markovian Equilibrium in Models with Simple Non-Paternalistic Altruism

This paper provides sufficient conditions for existence of Markovian equilibrium in models with non-paternalistic altruism extending to one generation ahead. When utility is non-separable, we show that each equilibrium savings policy correspondence is increasing everywhere and single-valued, except perhaps on a countable number of points. It is also upper hemi-continuous where it is single valued. When utility is separable, we show that the equilibrium is unique, increasing, and continuous, and we provide an algorithm converging uniformly to the equilibrium.

Adiposity and the perilipin gene: The role of single locus and multilocus variation, obesity-related quantitative traits, and disease-related phenotypes in the Atherosclerosis Risk in Communities (ARIC) study

Obesity is a complex multifactorial disease and is a public health priority. Perilipin coats the surface of lipid droplets in adipocytes and is believed to stabilize these lipid bodies by protecting triglyceride from early lipolysis. This research project evaluated the association between genetic variation within the human perilipin (PLIN) gene and obesity-related quantitative traits and disease-related phenotypes in Non-Hispanic White (NHW) and African American (AA) participants from the Atherosclerosis Risk in Communities (ARIC) Study. ^ Multivariate linear regression, multivariate logistic regression, and Cox proportional hazards models evaluated the association between single gene variants (rs2304794, rs894160, rs8179071, and rs2304795) and multilocus variation (rs894160 and rs2304795) within the PLIN gene and both obesity-related quantitative traits (body weight, body mass index [BMI], waist girth, waist-to-hip ratio [WHR], estimated percent body fat, and plasma total triglycerides) and disease-related phenotypes (prevalent obesity, metabolic syndrome [MetS], prevalent coronary heart disease [CHD], and incident CHD). Single variant analyses were stratified by race and gender within race while multilocus analyses were stratified by race. ^ Single variant analyses revealed that rs2304794 and rs894160 were significantly related to plasma triglyceride levels in all NHWs and NHW women. Among AA women, variant rs8179071 was associated with triglyceride levels and rs2304794 was associated with risk-raising waist circumference (>0.8 in women). The multilocus effects of variants rs894160 and rs2304795 were significantly associated with body weight, waist girth, WHR, estimated percent body fat, class II obesity (BMI ≥ 35 kg/m2), class III obesity (BMI ≥ 35 kg/m2), and risk-raising WHR (>0.9 in men and >0.8 in women) in AAs. Variant rs2304795 was significantly related to prevalent MetS among AA males and prevalent CHD in NHW women; multilocus effects of the PLIN gene were associated with prevalent CHD among NHWs. Rs2304794 was associated with incident CHD in the absence of the MetS among AAs. These findings support the hypothesis that variation within the PLIN gene influences obesity-related traits and disease-related phenotypes. ^ Understanding these effects of the PLIN genotype on the development of obesity can potentially lead to tailored health promotion interventions that are more effective. ^

Study of length of stay in the cardiovascular intensive care unit

Coronary artery bypass graft (CABG) surgery is among the most common operations performed in the United States and accounts for more resources expended in cardiovascular medicine than any other single procedure. CABG surgery patients initially recover in the Cardiovascular Intensive Care Unit (CVICU). The post-procedure CVICU length of stay (LOS) goal is two days or less. A longer ICU LOS is associated with a prolonged hospital LOS, poor health outcomes, greater use of limited resources, and increased medical costs. ^ Research has shown that experienced clinicians can predict LOS no better than chance. Current CABG surgery LOS risk models differ greatly in generalizability and ease of use in the clinical setting. A predictive model that identified modifiable pre- and intra-operative risk factors for CVICU LOS greater than two days could have major public health implications as modification of these identified factors could decrease CVICU LOS and potentially minimize morbidity and mortality, optimize use of limited health care resources, and decrease medical costs. ^ The primary aim of this study was to identify modifiable pre-and intra-operative predictors of CVICU LOS greater than two days for CABG surgery patients with cardiopulmonary bypass (CPB). A secondary aim was to build a probability equation for CVICU LOS greater than two days. Data were extracted from 416 medical records of CABG surgery patients with CPB, 50 to 80 years of age, recovered in the CVICU of a large teaching, referral hospital in southeastern Texas, during the calendar year 2004 and the first quarter of 2005. Exclusion criteria included Diagnosis Related Group (DRG) 106, CABG surgery without CPB, CABG surgery with other procedures, and operative deaths. The data were analyzed using multivariate logistic regression for an alpha=0.05, power=0.80, and correlation=0.26. ^ This study found age, history of peripheral arterial disease, and total operative time equal to and greater than four hours to be independent predictors of CVICU LOS greater than two days. The probability of CVICU LOS greater than two days can be calculated by the following equation: -2.872941 +.0323081 (age in years) + .8177223 (history of peripheral arterial disease) + .70379 (operative time). ^

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Mean dynamic topography and oceanographic parameters estimated from an inverse model and satellite geodesy, with link to model result in one single NetCDF file (392 MB), including the inverse data error covariance

Geostrophic surface velocities can be derived from the gradients of the mean dynamic topography-the difference between the mean sea surface and the geoid. Therefore, independently observed mean dynamic topography data are valuable input parameters and constraints for ocean circulation models. For a successful fit to observational dynamic topography data, not only the mean dynamic topography on the particular ocean model grid is required, but also information about its inverse covariance matrix. The calculation of the mean dynamic topography from satellite-based gravity field models and altimetric sea surface height measurements, however, is not straightforward. For this purpose, we previously developed an integrated approach to combining these two different observation groups in a consistent way without using the common filter approaches (Becker et al. in J Geodyn 59(60):99-110, 2012, doi:10.1016/j.jog.2011.07.0069; Becker in Konsistente Kombination von Schwerefeld, Altimetrie und hydrographischen Daten zur Modellierung der dynamischen Ozeantopographie, 2012, http://nbn-resolving.de/nbn:de:hbz:5n-29199). Within this combination method, the full spectral range of the observations is considered. Further, it allows the direct determination of the normal equations (i.e., the inverse of the error covariance matrix) of the mean dynamic topography on arbitrary grids, which is one of the requirements for ocean data assimilation. In this paper, we report progress through selection and improved processing of altimetric data sets. We focus on the preprocessing steps of along-track altimetry data from Jason-1 and Envisat to obtain a mean sea surface profile. During this procedure, a rigorous variance propagation is accomplished, so that, for the first time, the full covariance matrix of the mean sea surface is available. The combination of the mean profile and a combined GRACE/GOCE gravity field model yields a mean dynamic topography model for the North Atlantic Ocean that is characterized by a defined set of assumptions. We show that including the geodetically derived mean dynamic topography with the full error structure in a 3D stationary inverse ocean model improves modeled oceanographic features over previous estimates.

Planktonic foraminiferal oxygen isotopes of ODP Site 143-865 samples

Cool tropical sea surface temperatures (SSTs) are reported for warm Paleogene greenhouse climates based on the d18O of planktonic foraminiferal tests. These results are difficult to reconcile with models of greenhouse gas-forced climate. It has been suggested that this "cool tropics paradox" arises from postdepositional alteration of foraminiferal calcite, yielding erroneously high d18O values. Recrystallization of foraminiferal tests is cryptic and difficult to quantify, and the compilation of robust d18O records from moderately altered material remains challenging. Scanning electron microscopy of planktonic foraminiferal chamber-wall cross sections reveals that the basal area of muricae, pustular outgrowths on the chamber walls of species belonging to the genus Morozovella, contain no mural pores and may be less susceptible to postdepositional alteration. We analyzed the d18O in muricae bases of morozovellids from the central Pacific (Ocean Drilling Program Site 865) by ion microprobe using 10 ?m pits with an analytical reproducibility of ±0.34 per mil (2 standard deviations). In situ measurements of d18O in these domains yield consistently lower values than those published for conventional multispecimen analyses. Assuming that the original d18O is largely preserved in the basal areas of muricae, this new d18O record indicates Early Paleogene (~49-56 Ma) tropical SSTs in the central Pacific were 4°-8°C higher than inferred from the previously published d18O record and that SSTs reached at least ~33°C during the Paleocene-Eocene thermal maximum. This study demonstrates the utility of ion microprobe analysis for generating more reliable paleoclimate records from moderately altered foraminiferal tests preserved in deep-sea sediments.