BPA qualtitative and quantitative assessment associated with orthodontic bonding in vivo

OBJECTIVE To assess the in vivo amount of BPA released from a visible light-cured orthodontic adhesive, immediately after bracket bonding. METHODS 20 orthodontic patients were recruited after obtaining informed consent. All patients received 24 orthodontic brackets in both dental arches. In Group A (11 patients), 25 ml of tap water were used for mouth rinsing, whereas in Group B (9 patients) a simulated mouth rinse formulation was used: a mixture of 20 ml de-ionized water plus 5 ml absolute ethanol. Rinsing solutions were collected before, immediately after placing the orthodontic appliances and after washing out the oral cavity and were then stored in glass tubes. Rinsing was performed in a single phase for 60s with the entire volume of each liquid. The BPA analysis was performed by gas chromatography-mass spectrometry. RESULTS An increase in BPA concentration immediately after the 1st post-bonding rinse was observed, for both rinsing media, which was reduced after the 2nd post-bonding rinse. Water exhibited higher levels of BPA concentration than water/ethanol after 1st and 2nd post-bonding rinses. Two-way mixed Repeated Measures ANOVA showed that the primary null hypothesis declaring mean BPA concentration to be equal across rinsing medium and rinsing status was rejected (p-value <0.001). The main effects of the rinsing medium and status, as well as their interaction were found to be statistically significant (p-values 0.048, <0.001 and 0.011 respectively). SIGNIFICANCE A significant pattern of increase of BPA concentration, followed by a decrease that reached the initial values was observed. The amount of BPA was relatively low and far below the reference limits of tolerable daily intake.

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

Assessment of CTF boiling transition and critical heat flux modeling capabilities using the OECD/NRC BFBT and PSBT benchmark databases

The need to refine models for best-estimate calculations, based on good-quality experimental data, has been expressed in many recent meetings in the field of nuclear applications. The modeling needs arising in this respect should not be limited to the currently available macroscopic methods but should be extended to next-generation analysis techniques that focus on more microscopic processes. One of the most valuable databases identified for the thermalhydraulics modeling was developed by the Nuclear Power Engineering Corporation (NUPEC), Japan. From 1987 to 1995, NUPEC performed steady-state and transient critical power and departure from nucleate boiling (DNB) test series based on the equivalent full-size mock-ups. Considering the reliability not only of the measured data, but also other relevant parameters such as the system pressure, inlet sub-cooling and rod surface temperature, these test series supplied the first substantial database for the development of truly mechanistic and consistent models for boiling transition and critical heat flux. Over the last few years the Pennsylvania State University (PSU) under the sponsorship of the U.S. Nuclear Regulatory Commission (NRC) has prepared, organized, conducted and summarized the OECD/NRC Full-size Fine-mesh Bundle Tests (BFBT) Benchmark. The international benchmark activities have been conducted in cooperation with the Nuclear Energy Agency/Organization for Economic Co-operation and Development (NEA/OECD) and Japan Nuclear Energy Safety (JNES) organization, Japan. Consequently, the JNES has made available the Boiling Water Reactor (BWR) NUPEC database for the purposes of the benchmark. Based on the success of the OECD/NRC BFBT benchmark the JNES has decided to release also the data based on the NUPEC Pressurized Water Reactor (PWR) subchannel and bundle tests for another follow-up international benchmark entitled OECD/NRC PWR Subchannel and Bundle Tests (PSBT) benchmark. This paper presents an application of the joint Penn State University/Technical University of Madrid (UPM) version of the well-known subchannel code COBRA-TF, namely CTF, to the critical power and departure from nucleate boiling (DNB) exercises of the OECD/NRC BFBT and PSBT benchmarks

Multispectral microscopy and quantitative texture

CAMEVA SYSTEM Automated optical identification of ore minerals in polished samples using multispectral digital images Support for basic ore microscopy / ore identification Geometallurgy: Automated system for quantitative mineralogy applications, more efficient than manual methods and less expensive than SEM systems

Post-­‐occupancy monitoring of two flats in Madrid: development and assessment of a mixed methods methodology

Recent research has shown large differences between the expected and the actual energy consumption in buildings. The differences have been attributed partially, to the assumptions made during the design phase of buildings when simulation methods are employed. More accurate occupancy profiles on building operation could help to carry out more precise building performance calculations. This study focuses on the post-occupancy evaluation of two apartments, one renovated and one non renovated, in Madrid within the same building complex. The aim of this paper is to present an application of the mixed-methods methodology (Creswell, 2007) to assess thermal comfort and occupancy practices used in the case studies, and to discuss the shortcomings and opportunities associated with it. The mixed-methods methodology offers strategies for integrating qualitative and quantitative methods to investigate complex phenomena. This approach is expected to contribute to the growing knowledge of occupants’ behaviour and building performance by explaining the differences observed between energy consumption and thermal comfort in relation to people’s saving and comfort practices and the related experiences, preferences and values.

Quantitative methods of estimating groundwater supplies /

Mode of access: Internet.

Methods in modeling income in the near term (MINT I) /

"June 2001."

Applying quantitative methods in the assessment of outcomes of pharmacotherapy of psoriasis

Healthcare providers and policy makers are faced with an ever-increasing number of medical publications. Searching for relevant information and keeping up to date with new research findings remains a constant challenge. It has been widely acknowledged that narrative reviews of the literature are susceptible to several types of bias and a systematic approach may protect against these biases. The aim of this thesis was to apply quantitative methods in the assessment of outcomes of topical therapies for psoriasis. In particular, to systematically examine the comparative efficacy, tolerability and cost-effectiveness of topical calcipotriol in the treatment of mild-to-moderate psoriasis. Over the years, a wide range of techniques have been used to evaluate the severity of psoriasis and the outcomes from treatment. This lack of standardisation complicates the direct comparison of results and ultimately the pooling of outcomes from different clinical trials. There is a clear requirement for more comprehensive tools for measuring drug efficacy and disease severity in psoriasis. Ideally, the outcome measures need to be simple, relevant, practical, and widely applicable, and the instruments should be reliable, valid and responsive. The results of the meta-analysis reported herein show that calcipotriol is an effective antipsoriatic agent. In the short-tenn, the pooled data found calcipotriol to be more effective than calcitriol, tacalcitol, coal tar and short-contact dithranol. Only potent corticosteroids appeared to have comparable efficacy, with less short-term side-effects. Potent corticosteroids also added to the antipsoriatic effect of calcipotriol, and appeared to suppress the occurrence of calcipotriol-induced irritation. There was insufficient evidence to support any large effects in favour of improvements in efficacy when calcipotriol is used in combination with systemic therapies in patients with severe psoriasis. However, there was a total absence of long-term morbidity data on the effectiveness of any of the interventions studied. Decision analysis showed that, from the perspective of the NHS as payer, the relatively small differences in efficacy between calcipotriol and short-contact dithranol lead to large differences in the direct cost of treating patients with mildto-moderate plaque psoriasis. Further research is needed to examine the clinical and economic issues affecting patients under treatment for psoriasis in the UK. In particular, the maintenance value and cost/benefit ratio for the various treatment strategies, and the assessment of patient's preferences has not yet been adequately addressed for this chronic recurring disease.

Quantitative methods in neuropathology

The last decade has seen a considerable increase in the application of quantitative methods in the study of histological sections of brain tissue and especially in the study of neurodegenerative disease. These disorders are characterised by the deposition and aggregation of abnormal or misfolded proteins in the form of extracellular protein deposits such as senile plaques (SP) and intracellular inclusions such as neurofibrillary tangles (NFT). Quantification of brain lesions and studying the relationships between lesions and normal anatomical features of the brain, including neurons, glial cells, and blood vessels, has become an important method of elucidating disease pathogenesis. This review describes methods for quantifying the abundance of a histological feature such as density, frequency, and 'load' and the sampling methods by which quantitative measures can be obtained including plot/quadrat sampling, transect sampling, and the point-quarter method. In addition, methods for determining the spatial pattern of a histological feature, i.e., whether the feature is distributed at random, regularly, or is aggregated into clusters, are described. These methods include the use of the Poisson and binomial distributions, pattern analysis by regression, Fourier analysis, and methods based on mapped point patterns. Finally, the statistical methods available for studying the degree of spatial correlation between pathological lesions and neurons, glial cells, and blood vessels are described.

Revealing 4-hydroxynonenal-histidine adducts as qualitative and quantitative biomarker of oxidative stress, lipid peroxidation and oxidative homeostasis

Findings on growth regulating activities of the end-product of lipid peroxidation 4-hydroxy-2-nonenal (HNE), which acts as a “second messenger of free radicals”, overlapped with the development of antibodies specific for the aldehyde-protein adducts. These led to qualitative immunochemical determinations of the HNE presence in various pathophysiological processes and to the change of consideration of the aldehyde’s bioactivities from toxicity into cell signalling. Moreover, findings of the HNE-protein adduct in various organs under physiological circumstances support the concept of “oxidative homeostasis”, which implies that oxidative stress and lipid peroxidation are not only pathological but also physiological processes. Reactive aldehydes, at least HNE, could play important role in oxidative homeostasis, while complementary research approaches might reveal the relevance of the aldehydic-protein adducts as major biomarkers of oxidative stress, lipid peroxidation and oxidative homeostasis. Aiming to join efforts in such research activities researchers interacting through the International 4-Hydroxynonenal Club acting within the SFRR-International and through networking projects of the system of the European Cooperation in Science and Technology (COST) carried validation of the methods for lipid peroxidation and further developed the genuine 4-HNE-His ELISA founding quantitative and qualitative methods for detection of 4-HNE-His adducts as valuable tool to study oxidative stress and lipid peroxidation in cell cultures, various organs and tissues and eventually for human plasma and serum analyses [1]. Reference: 1. Weber, Daniela. Lidija, Milkovic. Measurement of HNE-protein adducts in human plasma and serum by ELISA—Comparison of two primary antibodies. Redox Biol. 2013. 226-233.

Methods of modeling the future shift of the so called Moesz-line

It is important to the landscape architects to become acquainted with the results of the regional climate models so they can adapt to the warmer and more arid future climate. Modelling the potential distribution area of certain plants, which was the theme of our former research, can be a convenient method to visualize the effects of the climate change. A similar but slightly better method is modelling the Moesz-line, which gives information on distribution and usability of numerous plants simultaneously. Our aim is to display the results on maps and compare the different modelling methods (Line modelling, Distribution modelling, Isotherm modelling). The results are spectacular and meet our expectations: according to two of the three tested methods the Moesz-line will shift from South Slovakia to Central Poland in the next 60 years.

Development of a mathematical and computer model to assess water quality impacts of hazardous compounds from minor gasoline spills in the inter-tidal zone of the Miami River, Florida

The objective of this study was to develop a model to predict transport and fate of gasoline components of environmental concern in the Miami River by mathematically simulating the movement of dissolved benzene, toluene, xylene (BTX), and methyl-tertiary-butyl ether (MTBE) occurring from minor gasoline spills in the inter-tidal zone of the river. Computer codes were based on mathematical algorithms that acknowledge the role of advective and dispersive physical phenomena along the river and prevailing phase transformations of BTX and MTBE. Phase transformations included volatilization and settling. ^ The model used a finite-difference scheme of steady-state conditions, with a set of numerical equations that was solved by two numerical methods: Gauss-Seidel and Jacobi iterations. A numerical validation process was conducted by comparing the results from both methods with analytical and numerical reference solutions. Since similar trends were achieved after the numerical validation process, it was concluded that the computer codes algorithmically were correct. The Gauss-Seidel iteration yielded at a faster convergence rate than the Jacobi iteration. Hence, the mathematical code was selected to further develop the computer program and software. The model was then analyzed for its sensitivity. It was found that the model was very sensitive to wind speed but not to sediment settling velocity. ^ A computer software was developed with the model code embedded. The software was provided with two major user-friendly visualized forms, one to interface with the database files and the other to execute and present the graphical and tabulated results. For all predicted concentrations of BTX and MTBE, the maximum concentrations were over an order of magnitude lower than current drinking water standards. It should be pointed out, however, that smaller concentrations than the latter reported standards and values, although not harmful to humans, may be very harmful to organisms of the trophic levels of the Miami River ecosystem and associated waters. This computer model can be used for the rapid assessment and management of the effects of minor gasoline spills on inter-tidal riverine water quality. ^

“Mind the gap”: Qualitative Researchers and Mixed Methods Research

This paper presents a heuristic investigation of mixed methods organized around three pairs of opposing standpoints: methods (qualitative vs. quantitative), paradigms (constructivist vs. post positive), and inquiry approaches (dialectical vs. pragmatic).

Methods matter: computational modelling in public health policy and planning

This work is aimed at understanding and unifying information on epidemiological modelling methods and how those methods relate to public policy addressing human health, specifically in the context of infectious disease prevention, pandemic planning, and health behaviour change. This thesis employs multiple qualitative and quantitative methods, and presents as a manuscript of several individual, data-driven projects that are combined in a narrative arc. The first chapter introduces the scope and complexity of this interdisciplinary undertaking, describing several topical intersections of importance. The second chapter begins the presentation of original data, and describes in detail two exercises in computational epidemiological modelling pertinent to pandemic influenza planning and policy, and progresses in the next chapter to present additional original data on how the confidence of the public in modelling methodology may have an effect on their planned health behaviour change as recommended in public health policy. The thesis narrative continues in the final data-driven chapter to describe how health policymakers use modelling methods and scientific evidence to inform and construct health policies for the prevention of infectious diseases, and concludes with a narrative chapter that evaluates the breadth of this data and recommends strategies for the optimal use of modelling methodologies when informing public health policy in applied public health scenarios.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials. © 2015, The Author(s).