Two monoclonal rat antibodies with specificity for the beta-chain variable region V beta 6 of the murine T-cell receptor.

Two rat monoclonal antibodies (mAbs), 44-22-1 and 46-6B5, which recognize an alloreactive cytotoxic clone, 3F9, have been further tested on a panel of T hybridomas and cytotoxic T-cell clones for binding and functional activities. The mAbs recognized only those cells sharing the expression of the T-cell receptor beta-chain variable region gene V beta 6 with 3F9. All V beta 6+ cells were activated by these mAbs under cross-linking conditions and their antigen-specific activation was blocked by soluble mAb. Furthermore, depletion of 46-6B5+ normal lymph node T cells eliminated all cells expressing the epitope recognized by 44-22-1 and V beta 6 mRNA.

Comparability of clinical wear measurements by optical 3D laser scanning in two different centers.

OBJECTIVE: The purpose of this study was to compare the use of different variables to measure the clinical wear of two denture tooth materials in two analysis centers. METHODS: Twelve edentulous patients were provided with full dentures. Two different denture tooth materials (experimental material and control) were placed randomly in accordance with the split-mouth design. For wear measurements, impressions were made after an adjustment phase of 1-2 weeks and after 6, 12, 18, and 24 months. The occlusal wear of the posterior denture teeth of 11 subjects was assessed in two study centers by use of plaster replicas and 3D laser-scanning methods. In both centers sequential scans of the occlusal surfaces were digitized and superimposed. Wear was described by use of four different variables. Statistical analysis was performed after log-transformation of the wear data by use of the Pearson and Lin correlation and by use of a mixed linear model. RESULTS: Mean occlusal vertical wear of the denture teeth after 24 months was between 120μm and 212μm, depending on wear variable and material. For three of the four variables, wear of the experimental material was statistically significantly less than that of the control. Comparison of the two study centers, however, revealed correlation of the wear variables was only moderate whereas strong correlation was observed among the different wear variables evaluated by each center. SIGNIFICANCE: Moderate correlation was observed for clinical wear measurements by optical 3D laser scanning in two different study centers. For the two denture tooth materials, wear measurements limited to the attrition zones led to the same qualitative assessment.

Assessing the Relationship between the Baseline Value of a Continuous Variable and Subsequent Change over Time

Analyzing the relationship between the baseline value and subsequent change of a continuous variable is a frequent matter of inquiry in cohort studies. These analyses are surprisingly complex, particularly if only two waves of data are available. It is unclear for non-biostatisticians where the complexity of this analysis lies and which statistical method is adequate.With the help of simulated longitudinal data of body mass index in children,we review statistical methods for the analysis of the association between the baseline value and subsequent change, assuming linear growth with time. Key issues in such analyses are mathematical coupling, measurement error, variability of change between individuals, and regression to the mean. Ideally, it is better to rely on multiple repeated measurements at different times and a linear random effects model is a standard approach if more than two waves of data are available. If only two waves of data are available, our simulations show that Blomqvist's method - which consists in adjusting for measurement error variance the estimated regression coefficient of observed change on baseline value - provides accurate estimates. The adequacy of the methods to assess the relationship between the baseline value and subsequent change depends on the number of data waves, the availability of information on measurement error, and the variability of change between individuals.

Imputation in data fusion of heterogeneous data sets a model-based numerical experiment

Given the very large amount of data obtained everyday through population surveys, much of the new research again could use this information instead of collecting new samples. Unfortunately, relevant data are often disseminated into different files obtained through different sampling designs. Data fusion is a set of methods used to combine information from different sources into a single dataset. In this article, we are interested in a specific problem: the fusion of two data files, one of which being quite small. We propose a model-based procedure combining a logistic regression with an Expectation-Maximization algorithm. Results show that despite the lack of data, this procedure can perform better than standard matching procedures.

Determinants of Corporate Disclosure : A Multicountry, Multilevel Model

Abstract The complexity of the current business world is making corporate disclosure more and more important for information users. These users, including investors, financial analysts, and government authorities rely on the disclosed information to make their investment decisions, analyze and recommend shares, and to draft regulation policies. Moreover, the globalization of capital markets has raised difficulties for information users in understanding the differences incorporate disclosure across countries and across firms. Using a sample of 797 firms from 34 countries, this thesis advances the literature on disclosure by illustrating comprehensively the disclosure determinants originating at firm systems and national systems based on the multilevel latent variable approach. Under this approach, the overall variation associated with the firm-specific variables is decomposed into two parts, the within-country and the between-country part. Accordingly, the model estimates the latent association between corporate disclosure and information demand at two levels, the within-country and the between-country level. The results indicate that the variables originating from corporate systems are hierarchically correlated with those from the country environment. The information demand factor indicated by the number of exchanges listed and the number of analyst recommendations can significantly explain the variation of corporate disclosure for both "within" and "between" countries. The exogenous influences of firm fundamentals-firm size and performance-are exerted indirectly through the information demand factor. Specifically, if the between-country variation in firm variables is taken into account, only the variables of legal systems and economic growth keep significance in explaining the disclosure differences across countries. These findings strongly support the hypothesis that disclosure is a response to both corporate systems and national systems, but the influence of the latter on disclosure reflected significantly through that of the former. In addition, the results based on ADR (American Depositary Receipt) firms suggest that the globalization of capital markets is harmonizing the disclosure behavior of cross-boundary listed firms, but it cannot entirely eliminate the national features in disclosure and other firm-specific characteristics.

MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status.

The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p < 0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients (n = 50; kappa = 0.88; outcome, log-rank p < 0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50 % regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM-450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types.

Wear of two denture teeth materials in vivo-2-year results.

OBJECTIVE: (1) To quantify wear of two different denture tooth materials in vivo with two study designs, (2) to relate tooth variables to vertical loss. METHODS: Two different denture tooth materials had been used (experimental material=test; DCL=control). In study 1 (split-mouth, 6 test centers) 60 subjects received complete dentures, in study 2 (two-arm, 1 test center) 29 subjects. In study 1 the mandibular dentures were supported by implants in 33% of the subjects, in study 2 only in 3% of the subjects. Impressions of the dentures were taken and poured with improved stone at baseline and after 6, 12, 18 and 24 months. Each operator evaluated the wear subjectively. Wear analysis was carried out with a laser scanning device. Maximal vertical loss of the attrition zones was calculated for each tooth cusp and tooth. A mixed linear model was used to statistically analyse the logarithmically transformed wear data. RESULTS: Due to drop-outs and unmatchable casts, only 47 subjects of study 1 and 14 of study 2 completed the 2-year recall. Overall, 75% of all teeth present could be analysed. There was no statistically difference in the overall wear between the test and control material for either study 1 or study 2. The relative increase in wear over time was similar in both study designs. However, a strong subject effect and center effect were observed. The fixed factors included in the model (time, tooth, center, etc.) accounted for 43% of the variability, whereas the random subject effect accounted for another 30% of the variability, leaving about 28% of unexplained variability. More wear was consistently recorded in the maxillary teeth compared to the mandibular teeth and in the first molar teeth compared to the premolar teeth and the second molars. Likewise, the supporting cusps showed more wear than the non-supporting cusps. The amount of wear did not depend on whether or not the lower dentures were supported by implants. The subjective wear was correct in about 67% of the cases if it is postulated that a wear difference of 100μm should be subjectively detectable. SIGNIFICANCE: The clinical wear of denture teeth is highly variable with a strong patient effect. More wear can be expected in maxillary denture teeth compared to mandibular teeth, first molars compared to premolars and supported cusps compared to non-supported cusps. Laboratory data on the wear of denture tooth materials may not be confirmed in well-structured clinical trials probably due to the large inter-individual variability.

Hydrogen and oxygen isotope behaviors during variable degrees of upper mantle melting: Example from the basaltic glasses from Macquarie Island

We present measurements of hydrogen and oxygen isotopes in MORB glasses from Macquarie Island (SW. Pacific Ocean) coupled with determination of bulk H2O content by two independent techniques: total dehydration and FTIR. The incompatible trace elements in these glasses vary by a factor of 12 to 17, with K2O varying from 0.1 to 1.7 wt.%; these ranges reflect a variable degree of closed-system mantle melting, estimated from 1 to 15%. Water concentrations determined by the two techniques match well, yielding a range from 0.25 to 1.49 wt.% which correlates positively with all of the measured incompatible trace elements, suggesting that water is un-degassed, and behaves conservatively during mantle melting. Also, the agreement between the FTIR-determined and extracted water contents gives us confidence that the measured isotopic values of hydrogen reflect that of the mantle. Comparison of the range of water content with that of other incompatible trace elements allows estimation of the water partition coefficient in lherzolite, 0.0208 (ranging from 0.017 to 0.023), and the water content in the source, 386 ppm (ranging from 370 to 440 ppm). We observe a fairly narrow range in delta D and delta O-18 values of -75.5 +/- 4.5 parts per thousand and 5.50 +/- 0 .05 parts per thousand respectively, that can be explained by partial melting of normal lherzolitic mantle. The measured delta D and delta O-18 values of Macquarie Island glasses that range from nepheline- to hypersthene-normative, and from MORB to EMORB in composition, are identical to those in average global MORB. The observed lack of variation of delta D and delta O-18 with 1 to 15% degree of mantle melting is consistent with a bulk melting model of delta D and delta O-18 fractionation, in which water is rapidly scavenged into the first partial melt. The narrow ranges of delta D and delta O-18 in normal mantle are mostly due to the buffering effect of clino- and orthopyroxenes in the residual assemblage; additionally, fast ``wet'' diffusion of oxygen and hydrogen isotopes through the melting regions may further smooth isotopic differences. (C) 2012 Elsevier B.V. All rights reserved.

Two-dimensional probabilistic inversion of plane-wave electromagnetic data: Methodology, model constraints and joint inversion with electrical resistivity data

Probabilistic inversion methods based on Markov chain Monte Carlo (MCMC) simulation are well suited to quantify parameter and model uncertainty of nonlinear inverse problems. Yet, application of such methods to CPU-intensive forward models can be a daunting task, particularly if the parameter space is high dimensional. Here, we present a 2-D pixel-based MCMC inversion of plane-wave electromagnetic (EM) data. Using synthetic data, we investigate how model parameter uncertainty depends on model structure constraints using different norms of the likelihood function and the model constraints, and study the added benefits of joint inversion of EM and electrical resistivity tomography (ERT) data. Our results demonstrate that model structure constraints are necessary to stabilize the MCMC inversion results of a highly discretized model. These constraints decrease model parameter uncertainty and facilitate model interpretation. A drawback is that these constraints may lead to posterior distributions that do not fully include the true underlying model, because some of its features exhibit a low sensitivity to the EM data, and hence are difficult to resolve. This problem can be partly mitigated if the plane-wave EM data is augmented with ERT observations. The hierarchical Bayesian inverse formulation introduced and used herein is able to successfully recover the probabilistic properties of the measurement data errors and a model regularization weight. Application of the proposed inversion methodology to field data from an aquifer demonstrates that the posterior mean model realization is very similar to that derived from a deterministic inversion with similar model constraints.

Combining conservative and variable markers to inferthe evolutionary history of Prunus subgen. Amygdalus s.l.under domestication

The genus Prunus L. is large and economically important. However, phylogenetic relationships within Prunus at low taxonomic level, particularly in the subgenus Amygdalus L. s.l., remain poorly investigated. This paper attempts to document the evolutionary history of Amygdalus s.l. and establishes a temporal framework, by assembling molecular data from conservative and variable molecular markers. The nuclear s6pdh gene in combination with the plastid trnSG spacer are analyzed with bayesian and maximum likelihood methods. Since previous phylogenetic analysis with these markers lacked resolution, we additionally analyzed 13 nuclear SSR loci with the δµ2 distance, followed by an unweighted pair group method using arithmetic averages algorithm. Our phylogenetic analysis with both sequence and SSR loci confirms the split between sections Amygdalus and Persica, comprising almonds and peaches, respectively. This result is in agreement with biogeographic data showing that each of the two sections is naturally distributed on each side of the Central Asian Massif chain. Using coalescent based estimations, divergence times between the two sections strongly varied when considering sequence data only or combined with SSR. The sequence-only based estimate (5 million years ago) was congruent with the Central Asian Massif orogeny and subsequent climate change. Given the low level of differentiation within the two sections using both marker types, the utility of combining microsatellites and data sequences to address phylogenetic relationships at low taxonomic level within Amygdalus is discussed. The recent evolutionary histories of almond and peach are discussed in view of the domestication processes that arose in these two phenotypically-diverging gene pools: almonds and peaches were domesticated from the Amygdalus s.s. and Persica sections, respectively. Such economically important crops may serve as good model to study divergent domestication process in close genetic pool.