Chlorhexidine and preservation of sound tooth structure in older adults. A placebo-controlled trial

The Trial to Enhance Elderly Teeth Health (TEETH) was designed to test the impact of regular rinsing with a 0.12% chlorhexidine (CHX) solution on tooth loss, and the causes of tooth loss (caries, periodontal disease and trauma) were also investigated. This paper reports on the effectiveness of a 0.12% CHX solution for controlling caries using a tooth surface (coronal and root) survival analysis. A total of 1,101 low income elders in Seattle (United States) and Vancouver (Canada), aged 60-75 years, were recruited for a double-blind clinical trial and assigned to either a CHX (n = 550) or a placebo (n = 551) mouth rinse. Subjects alternated between daily rinsing for 1 month, followed by weekly rinsing for 5 months. All sound coronal and root surfaces at baseline were followed annually for up to 5 years. At each follow-up examination, those tooth surfaces with caries, restored, or extracted were scored as 'carious'. The hazard ratio associated with CHX for a sound surface to become filled, decayed, or extracted was 0.87 for coronal surfaces (95% confidence interval: 0.71-1.14, p = 0.20) and 0.91 for root surfaces (95% confidence interval: 0.73-1.14, p = 0.41). These findings suggest that regular rinsing with CHX does not have a substantial effect on the preservation of sound tooth structure in older adults.

Modeling contaminant behavior in Lake Superior : a comparison of PCBs, PBDEs, and mercury

A mass‐balance model for Lake Superior was applied to polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and mercury to determine the major routes of entry and the major mechanisms of loss from this ecosystem as well as the time required for each contaminant class to approach steady state. A two‐box model (water column, surface sediments) incorporating seasonally adjusted environmental parameters was used. Both numerical (forward Euler) and analytical solutions were employed and compared. For validation, the model was compared with current and historical concentrations and fluxes in the lake and sediments. Results for PCBs were similar to prior work showing that air‐water exchange is the most rapid input and loss process. The model indicates that mercury behaves similarly to a moderately‐chlorinated PCB, with air‐water exchange being a relatively rapid input and loss process. Modeled accumulation fluxes of PBDEs in sediments agreed with measured values reported in the literature. Wet deposition rates were about three times greater than dry particulate deposition rates for PBDEs. Gas deposition was an important process for tri‐ and tetra‐BDEs (BDEs 28 and 47), but not for higher‐brominated BDEs. Sediment burial was the dominant loss mechanism for most of the PBDE congeners while volatilization was still significant for tri‐ and tetra‐BDEs. Because volatilization is a relatively rapid loss process for both mercury and the most abundant PCBs (tri‐ through penta‐), the model predicts that similar times (from 2 ‐ 10 yr) are required for the compounds to approach steady state in the lake. The model predicts that if inputs of Hg(II) to the lake decrease in the future then concentrations of mercury in the lake will decrease at a rate similar to the historical decline in PCB concentrations following the ban on production and most uses in the U.S. In contrast, PBDEs are likely to respond more slowly if atmospheric concentrations are reduced in the future because loss by volatilization is a much slower process for PBDEs, leading to lesser overall loss rates for PBDEs in comparison to PCBs and mercury. Uncertainties in the chemical degradation rates and partitioning constants of PBDEs are the largest source of uncertainty in the modeled times to steady‐state for this class of chemicals. The modeled organic PBT loading rates are sensitive to uncertainties in scavenging efficiencies by rain and snow, dry deposition velocity, watershed runoff concentrations, and uncertainties in air‐water exchange such as the effect of atmospheric stability.

Highly Efficient Non-palladium Catalyzed Controlled Synthesis and X-ray Analysis of Functionalized 1,2-Diaryl-, 1,2,3-Triaryl- and 1,2,3,4-Tetraarylbenzene

A general, two-step highly efficient synthesis of 1,2-diaryl-, 1,2,3-triaryl- and 1,2,3,4-tetraarylbenzenes from simple stitching of alpha-oxo-ketene-S,S-acetals and active methylene compounds via a ‘lactone intermediate’ is described. This procedure offers easy access to highly functionalized arylated-benzenes containing sterically demanding groups in good to excellent yields. The novelty of the procedure lies in the fabrication of aromatic compounds with desired conformational flexibility along the molecular axis in a transition metal-free environment through easily accessible precursors. The crystal analysis of these arylated-benzene scaffolds showed that the peripheral aryl rings are arranged in propeller-like fashion with respect to the central benzene rings. Examination of the crystal packing in the structure of a 1,2,3,4-tetraarylbenzene 12c revealed a “N…pi interaction” between molecules related by a two-fold screw axis running in a direction. It is interesting that the repeat of the array of N…pi interaction around the axis of the 1,2,3,4-tetraarylbenzene 12c enforces the molecules in a helical pattern.

Learning Analytics: Challenges and Future Research Directions

In recent years, learning analytics (LA) has attracted a great deal of attention in technology-enhanced learning (TEL) research as practitioners, institutions, and researchers are increasingly seeing the potential that LA has to shape the future TEL landscape. Generally, LA deals with the development of methods that harness educational data sets to support the learning process. This paper provides a foundation for future research in LA. It provides a systematic overview on this emerging field and its key concepts through a reference model for LA based on four dimensions, namely data, environments, context (what?), stakeholders (who?), objectives (why?), and methods (how?). It further identifies various challenges and research opportunities in the area of LA in relation to each dimension.

Affective attitudes to face images associated with intracerebral EEG source location before face viewing

We investigated whether different, personality-related affective attitudes are associated with different brain electric field (EEG) sources before any emotional challenge (stimulus exposure). A 27-channel EEG was recorded in 15 subjects during eyes-closed resting. After recording, subjects rated 32 images of human faces for affective appeal. The subjects in the first (i.e., most negative) and fourth (i.e., most positive) quartile of general affective attitude were further analyzed. The EEG data (mean=25±4.8 s/subject) were subjected to frequency-domain model dipole source analysis (FFT-Dipole-Approximation), resulting in 3-dimensional intracerebral source locations and strengths for the delta–theta, alpha, and beta EEG frequency band, and for the full range (1.5–30 Hz) band. Subjects with negative attitude (compared to those with positive attitude) showed the following source locations: more inferior for all frequency bands, more anterior for the delta–theta band, more posterior and more right for the alpha, beta and 1.5–30 Hz bands. One year later, the subjects were asked to rate the face images again. The rating scores for the same face images were highly correlated for all subjects, and original and retest affective mean attitude was highly correlated across subjects. The present results show that subjects with different affective attitudes to face images had different active, cerebral, neural populations in a task-free condition prior to viewing the images. We conclude that the brain functional state which implements affective attitude towards face images as a personality feature exists without elicitors, as a continuously present, dynamic feature of brain functioning.

An assessment of obesity and hyperphagia in individuals with Smith-Magenis syndrome

Smith-Magenis syndrome (SMS;OMIM# 182290) is a multiple congenital anomalies and mental retardation syndrome caused by a 3.7- Mb deletion on chromosome 17p11.2 or a mutation in the RAI1 gene. Although the majority of the SMS phenotype has been well described, limited studies are available describing growth patterns in SMS. There is some evidence that individuals with SMS develop obesity. Thus, this study aims to characterize the growth and potential influence of hyperphagia in a cohort of individuals with SMS. A retrospective chart review was conducted of 78 individuals with SMS through Baylor College of Medicine (BCM) at Texas Children¡¯s Hospital (TCH.) All documented height and weight measurements were abstracted and Z-scores (SD units) for height-for-age, length-for-age and BMI-for-age were calculated. Mail-out questionnaires were provided to the corresponding parents of the cohort to assess for the presence of hyperphagia through a validated hyperphagia questionnaire (HQ). Analysis of this data demonstrates that by the age ¡Ý 20 years males with SMS have mean BMI¡¯s in the 85th-90th percentile corresponding to an overweight BMI, and females with SMS had mean BMI¡¯s in the 95th -97th percentile corresponding to an obese BMI. Parents indicated that hyperphagia is present in individuals with SMS as 76% of parent¡¯s report having to lock food away from their child. Females¡¯ age ¡Ý 20 years of age had the highest mean behavior, drive and severity scores as well as the highest BMI. Thus, this study concludes that it appears overweight and obesity, as well as hyperphagia, are present in this cohort of SMS individuals. The results of this study will hopefully enable parents and caregivers of children with SMS to take preventative measures in order to control food related behaviors present in their children as well as to prevent overweight and obesity and the associated negative health consequences.

Smooth Muscle Hyperplasia due to ACTA2/MYH11 Mutations: Identification of Novel Pathology and Pathways Leading to Aneurysms and Diverse Vascular Occlusive Diseases

Missense mutations in smooth muscle cell (SMC) specific ACTA2 (á-actin) and MYH11 (â-myosin heavy chain) cause diffuse and diverse vascular diseases, including thoracic aortic aneurysms and dissections (TAAD) and early onset coronary artery disease and stroke. The mechanism by which these mutations lead to dilatation of some arteries but occlusion of others is unknown. We hypothesized that the mutations act through two distinct mechanisms to cause varied vascular diseases: a loss of function, leading to decreased SMC contraction and aneurysms, and a gain of function, leading to increased SMC proliferation and occlusive disease. To test this hypothesis, ACTA2 mutant SMCs and myofibroblasts were assessed and found to not form á-actin filaments whereas control cells did, suggesting a dominant negative effect of ACTA2 mutations on filament formation. A loss of á-actin filaments would be predicted to cause decreased SMC contractility. Histological examination of vascular tissues from patients revealed SMC hyperplasia leading to arterial stenosis and occlusion, supporting a gain of function associated with the mutant gene. Furthermore, ACTA2 mutant SMCs and myofibroblasts proliferated more rapidly in static culture than control cells (p<0.05). We also determined that Acta2-/- mice have ascending aortic aneurysms. Histological examination revealed aortic medial SMC hyperplasia, but minimal features of medial degeneration. Acta2-/- SMCs proliferated more rapidly in culture than wildtype (p<0.05), and microarray analysis of Acta2-/- SMCs revealed increased expression of Actg2, 15 collagen genes, and multiple focal adhesion genes. Acta2-/- SMCs showed altered localization of vinculin and zyxin and increased phosphorylated focal adhesion kinase (FAK) in focal adhesions. A specific FAK inhibitor decreased Acta2-/- SMC proliferation to levels equal to wildtype SMCs (p<0.05), suggesting that FAK activation leads to the increased proliferation. We have described a unique pathology associated with ACTA2 and MYH11 mutations, as well as an aneurysm phenotype in Acta2-/- mice. Additionally, we identified a novel pathogenic pathway for vascular occlusive disease due to loss of SMC contractile filaments, alterations in focal adhesions, and activation of FAK signaling in SMCs with ACTA2 mutations.

Observational Research on NCDs in HIV-Positive Populations: Conceptual and Methodological Considerations

: Noncommunicable diseases (NCDs) account for a growing burden of morbidity and mortality among people living with HIV in low- and middle-income countries (LMICs). HIV infection and antiretroviral therapy interact with NCD risk factors in complex ways, and research into this "web of causation" has so far been largely based on data from high-income countries. However, improving the understanding, treatment, and prevention of NCDs in LMICs requires region-specific evidence. Priority research areas include: (1) defining the burden of NCDs among people living with HIV, (2) understanding the impact of modifiable risk factors, (3) evaluating effective and efficient care strategies at individual and health systems levels, and (4) evaluating cost-effective prevention strategies. Meeting these needs will require observational data, both to inform the design of randomized trials and to replace trials that would be unethical or infeasible. Focusing on Sub-Saharan Africa, we discuss data resources currently available to inform this effort and consider key limitations and methodological challenges. Existing data resources often lack population-based samples; HIV-negative, HIV-positive, and antiretroviral therapy-naive comparison groups; and measurements of key NCD risk factors and outcomes. Other challenges include loss to follow-up, competing risk of death, incomplete outcome ascertainment and measurement of factors affecting clinical decision making, and the need to control for (time-dependent) confounding. We review these challenges and discuss strategies for overcoming them through augmented data collection and appropriate analysis. We conclude with recommendations to improve the quality of data and analyses available to inform the response to HIV and NCD comorbidity in LMICs.

Granular layer in the periplasmic space of gram-positive bacteria and fine structures of Enterococcus gallinarum and Streptococcus gordonii septa revealed by cryo-electron microscopy of vitreous sections.

High-resolution structural information on optimally preserved bacterial cells can be obtained with cryo-electron microscopy of vitreous sections. With the help of this technique, the existence of a periplasmic space between the plasma membrane and the thick peptidoglycan layer of the gram-positive bacteria Bacillus subtilis and Staphylococcus aureus was recently shown. This raises questions about the mode of polymerization of peptidoglycan. In the present study, we report the structure of the cell envelope of three gram-positive bacteria (B. subtilis, Streptococcus gordonii, and Enterococcus gallinarum). In the three cases, a previously undescribed granular layer adjacent to the plasma membrane is found in the periplasmic space. In order to better understand how nascent peptidoglycan is incorporated into the mature peptidoglycan, we investigated cellular regions known to represent the sites of cell wall production. Each of these sites possesses a specific structure. We propose a hypothetic model of peptidoglycan polymerization that accommodates these differences: peptidoglycan precursors could be exported from the cytoplasm to the periplasmic space, where they could diffuse until they would interact with the interface between the granular layer and the thick peptidoglycan layer. They could then polymerize with mature peptidoglycan. We report cytoplasmic structures at the E. gallinarum septum that could be interpreted as cytoskeletal elements driving cell division (FtsZ ring). Although immunoelectron microscopy and fluorescence microscopy studies have demonstrated the septal and cytoplasmic localization of FtsZ, direct visualization of in situ FtsZ filaments has not been obtained in any electron microscopy study of fixed and dehydrated bacteria.

Variability of daily winter wind speed distribution over Northern Europe during the past millennium in regional and global climate simulations

We analyse the variability of the probability distribution of daily wind speed in wintertime over Northern and Central Europe in a series of global and regional climate simulations covering the last centuries, and in reanalysis products covering approximately the last 60 years. The focus of the study lies on identifying the link of the variations in the wind speed distribution to the regional near-surface temperature, to the meridional temperature gradient and to the North Atlantic Oscillation. Our main result is that the link between the daily wind distribution and the regional climate drivers is strongly model dependent. The global models tend to behave similarly, although they show some discrepancies. The two regional models also tend to behave similarly to each other, but surprisingly the results derived from each regional model strongly deviates from the results derived from its driving global model. In addition, considering multi-centennial timescales, we find in two global simulations a long-term tendency for the probability distribution of daily wind speed to widen through the last centuries. The cause for this widening is likely the effect of the deforestation prescribed in these simulations. We conclude that no clear systematic relationship between the mean temperature, the temperature gradient and/or the North Atlantic Oscillation, with the daily wind speed statistics can be inferred from these simulations. The understand- ing of past and future changes in the distribution of wind speeds, and thus of wind speed extremes, will require a detailed analysis of the representation of the interaction between large-scale and small-scale dynamics.

High affinity targeting of CD23 inhibits IgE synthesis in human B cells.

The low-affinity IgE receptor FcϵRII (CD23) is part of the regulatory system controlling IgE synthesis in human B cells and exists in membrane and soluble forms. Binding of IgE to CD23 has been described to have stabilizing effects and to prevent cleavage of CD23. Previous experiments using anti-CD23 antibodies reduced IgE synthesis but were difficult to interpret as the antibody Fc part might also mediate feedback mechanisms. The purpose of this study was to investigate the regulatory role of CD23, by using designed ankyrin repeat proteins (DARPins) that specifically recognize CD23. Anti-CD23 DARPins were isolated by ribosome display and were produced as monovalent and bivalent constructs. Affinities to CD23 were measured by surface plasmon resonance. IgE synthesis and up-regulation of CD23 in human peripheral B cells were induced by IL-4 and anti-CD40 antibody. We assessed CD23 expression and its stabilization by FACS and used an ELISA for detecting soluble CD23. IgE synthesis was measured by ELISA and real-time PCR. Surface plasmon resonance revealed affinities of the DARPins to CD23 in the pico-molar range. Anti-CD23 DARPins strongly inhibited binding of IgE to CD23 and share thus a similar binding epitope as IgE. The DARPins stabilized membrane CD23 and reduced IgE synthesis in an isotype specific manner. Furthermore, the anti-CD23 DARPins decreased IgE transcript through inhibition of mature Cϵ RNA synthesis suggesting a posttranscriptional control mechanism. This study demonstrates that targeting CD23 alone is sufficient to inhibit IgE synthesis and suggests that a negative signaling occurs directly through the CD23 molecule.

LONGITUDINAL GROWTH PARAMETERS AND THEIR ECOLOGICAL DETERMINANTS (SEASONALITY)

The growth patterns of weight from birth through the first twelve months of life among rural Taiwanese infants were investigated with the following objectives: (i) compare each of the parameters of the Count model estimated for infants who were nutritionally at risk with those for a reference population from the United States; and (ii) within the Taiwanese infants, account for the variance in the growth patterns in the first and second six months of life on the basis of selected ecological factors.^ The significance between group differences were observed in the patterns of the weight growth in both linear growth and in the timing and the direction of velocity changes. A significant decline in growth velocity was observed among Taiwanese infants at about the fourth month of life. The decline is in keeping with a recent proposal made by J. C. Waterlow regarding the timing of change in growth velocity among nutritionally at risk populations in developing countries. The growth course of a nutritionally at risk infant during the first three months is apparently protected by the nurturance of the mother and innate biological properties of the infant.^ A highly significant portion of the growth variance in the second six months of life was accounted for by exogenous factors and biological factors related to the infant. Conversely, none of the growth variance in the first six months of life was accounted for by predictor variables. The most potent determinant of growth in the second six months of life was seasonality which represents a multiple environmental event.^ The model parameters estimated from the Count model represent different aspect of physical growth; yet the correlation coefficients between parameters b and c are high (r > .80). Clearly, the biological interpretation of the model parameters requires analysis of the whole function in the specific context of a given age period. ^

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

La divulgación científica de análisis sensorial de vinos en soporte web

En esta tesis se trabaja sobre la hipótesis de que el componente didáctico del discurso divulgativo queda delimitado por estrategias discursivas originadas en el tratamiento modal y actualizadas en los niveles funcional, situacional, semántico y formal-gramatical. El objetivo es caracterizar tales estrategias para identificar tendencias en la realización lingüísticodiscursiva del componente didáctico. El corpus se ha formado teniendo en cuenta soporte (web), formato (hipertexto) y dominio disciplinar (Análisis Sensorial de Vinos). La metodología es, fundamentalmente, cualitativo-ejemplar, basada en el modelo multinivel propuesto por Ciapuscio (2003) para el análisis de textos especializados. Los resultados sugieren que en el nivel funcional, el componente didáctico se distingue por el predominio de los términos positivos de las categorías modales epistémica (función informar) y ética (función dirigir); en el nivel situacional, por tres tipos de construcciones discursivas: la del enunciador experto, la del enunciatario lego y la de la pertenencia del lego a la comunidad especializada; en el nivel semántico, por la estandarización de partes textuales y por el predominio tanto de axiologización eufórica ética y cognoscitiva, como de secuencias expositivas y de procedimientos explicativos causales, descriptivos e ilustrativos; en el nivel formal, por recursos paratextuales e hipertextuales que refuerzan la actualización del componente didáctico.

Comparación socioeconómica de las empresas agrarias de producción ecológica y convencional en Aragón, España : Problemas y oportunidades

El trabajo presenta los problemas y oportunidades de la agricultura ecológica en Aragón, España. Con esta finalidad, se compara la agricultura ecológica con la convencional tanto en los aspectos socioeconómicos como medioambientales. Como base de esta comparativa, se presentan algunos de los principios básicos de la agricultura ecológica y su estructura contable de costes, obtenida a través de un trabajo de campo en Aragón y bases de datos oficiales, así como datos sobre su consumo y distribución; finalmente se sugieren algunas vías de actuación pública que pueden apoyar las oportunidades de la agricultura ecológica.