Appropriateness of colonoscopy in Europe (EPAGE II): presentation of methodology, general results, and analysis of complications.

BACKGROUND AND STUDY AIMS: Appropriate use of colonoscopy is a key component of quality management in gastrointestinal endoscopy. In an update of a 1998 publication, the 2008 European Panel on the Appropriateness of Gastrointestinal Endoscopy (EPAGE II) defined appropriateness criteria for various colonoscopy indications. This introductory paper therefore deals with methodology, general appropriateness, and a review of colonoscopy complications. METHODS:The RAND/UCLA Appropriateness Method was used to evaluate the appropriateness of various diagnostic colonoscopy indications, with 14 multidisciplinary experts using a scale from 1 (extremely inappropriate) to 9 (extremely appropriate). Evidence reported in a comprehensive updated literature review was used for these decisions. Consolidation of the ratings into three appropriateness categories (appropriate, uncertain, inappropriate) was based on the median and the heterogeneity of the votes. The experts then met to discuss areas of disagreement in the light of existing evidence, followed by a second rating round, with a subsequent third voting round on necessity criteria, using much more stringent criteria (i. e. colonoscopy is deemed mandatory). RESULTS: Overall, 463 indications were rated, with 55 %, 16 % and 29 % of them being judged appropriate, uncertain and inappropriate, respectively. Perforation and hemorrhage rates, as reported in 39 studies, were in general < 0.1 % and < 0.3 %, respectively CONCLUSIONS: The updated EPAGE II criteria constitute an aid to clinical decision-making but should in no way replace individual judgment. Detailed panel results are freely available on the internet (www.epage.ch) and will thus constitute a reference source of information for clinicians.

Modeling of the TCR-MHC-peptide complex.

The methodology for generating a homology model of the T1 TCR-PbCS-K(d) class I major histocompatibility complex (MHC) class I complex is presented. The resulting model provides a qualitative explanation of the effect of over 50 different mutations in the region of the complementarity determining region (CDR) loops of the T cell receptor (TCR), the peptide and the MHC's alpha(1)/alpha(2) helices. The peptide is modified by an azido benzoic acid photoreactive group, which is part of the epitope recognized by the TCR. The construction of the model makes use of closely related homologs (the A6 TCR-Tax-HLA A2 complex, the 2C TCR, the 14.3.d TCR Vbeta chain, the 1934.4 TCR Valpha chain, and the H-2 K(b)-ovalbumine peptide), ab initio sampling of CDR loops conformations and experimental data to select from the set of possibilities. The model shows a complex arrangement of the CDR3alpha, CDR1beta, CDR2beta and CDR3beta loops that leads to the highly specific recognition of the photoreactive group. The protocol can be applied systematically to a series of related sequences, permitting the analysis at the structural level of the large TCR repertoire specific for a given peptide-MHC complex.

Phase-based manganese enhanced MRI, a new methodology to enhance brain cytoarchitectural contrast and study manganese uptake.

PURPOSE: As the magnetic susceptibility induced frequency shift increases linearly with magnetic field strength, the present work evaluates manganese as a phase imaging contrast agent and investigates the dose dependence of brain enhancement in comparison to T1 -weighted imaging after intravenous administration of MnCl2 . METHODS: Experiments were carried out on 12 Sprague-Dawley rats. MnCl2 was infused intravenously with the following doses: 25, 75, 125 mg/kg (n=4). Phase, T1 -weighted images and T1 maps were acquired before and 24h post MnCl2 administration at 14.1 Tesla. RESULTS: Manganese enhancement was manifested in phase imaging by an increase in frequency shift differences between regions rich in calcium gated channels and other tissues, together with local increase in signal to noise ratio (from the T1 reduction). Such contrast improvement allowed a better visualization of brain cytoarchitecture. The measured T1 decrease observed across different manganese doses and in different brain regions were consistent with the increase in the contrast to noise ratio (CNR) measured by both T1 -weighted and phase imaging, with the strongest variations being observed in the dentate gyrus and olfactory bulb. CONCLUSION: Overall from its high sensitivity to manganese combined with excellent CNR, phase imaging is a promising alternative imaging protocol to assess manganese enhanced MRI at ultra high field. Magn Reson Med 72:1246-1256, 2014. © 2013 Wiley Periodicals, Inc.

Which is the optimal sampling strategy for habitat suitability modelling

Designing an efficient sampling strategy is of crucial importance for habitat suitability modelling. This paper compares four such strategies, namely, 'random', 'regular', 'proportional-stratified' and 'equal -stratified'- to investigate (1) how they affect prediction accuracy and (2) how sensitive they are to sample size. In order to compare them, a virtual species approach (Ecol. Model. 145 (2001) 111) in a real landscape, based on reliable data, was chosen. The distribution of the virtual species was sampled 300 times using each of the four strategies in four sample sizes. The sampled data were then fed into a GLM to make two types of prediction: (1) habitat suitability and (2) presence/ absence. Comparing the predictions to the known distribution of the virtual species allows model accuracy to be assessed. Habitat suitability predictions were assessed by Pearson's correlation coefficient and presence/absence predictions by Cohen's K agreement coefficient. The results show the 'regular' and 'equal-stratified' sampling strategies to be the most accurate and most robust. We propose the following characteristics to improve sample design: (1) increase sample size, (2) prefer systematic to random sampling and (3) include environmental information in the design'

Statistical learning theory for geospatial data. Case study: Aral sea

In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).

A statistical methodology for the comparison of blue gel pen inks analyzed by laser desorption/ionization mass spectrometry

A statistical methodology for the objective comparison of LDI-MS mass spectra of blue gel pen inks was evaluated. Thirty-three blue gel pen inks previously studied by RAMAN were analyzed directly on the paper using both positive and negative mode. The obtained mass spectra were first compared using relative areas of selected peaks using the Pearson correlation coefficient and the Euclidean distance. Intra-variability among results from one ink and inter-variability between results from different inks were compared in order to choose a differentiation threshold minimizing the rate of false negative (i.e. avoiding false differentiation of the inks). This yielded a discriminating power of up to 77% for analysis made in the negative mode. The whole mass spectra were then compared using the same methodology, allowing for a better DP in the negative mode of 92% using the Pearson correlation on standardized data. The positive mode results generally yielded a lower differential power (DP) than the negative mode due to a higher intra-variability compared to the inter-variability in the mass spectra of the ink samples.

The effects of dominance, regular inbreeding and sampling design on Q(ST), an estimator of population differentiation for quantitative traits.

To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) < F(ST) is predicted under homogenizing selection. However, nonadditive effects can alter these predictions. Here, we investigate the influence of dominance on the relation between Q(ST) and F(ST) for neutral traits. Using analytical results and computer simulations, we show that dominance generally deflates Q(ST) relative to F(ST). Under inbreeding, the effect of dominance vanishes, and we show that for selfing species, a better estimate of Q(ST) is obtained from selfed families than from half-sib families. We also compare several sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.

The sampling of ignitable liquids on suspects' hands

In arson cases, the collection and detection of traces of ignitable liquids on a suspect's hands can provide information to a forensic investigation. Police forces currently lack a simple, robust, efficient and reliable solution to perform this type of swabbing. In this article, we describe a study undertaken to develop a procedure for the collection of ignitable liquid residues on the hands of arson suspects. Sixteen different collection supports were considered and their applicability for the collection of gasoline traces present on hands and their subsequent analysis in a laboratory was evaluated. Background contamination, consisting of volatiles emanating from the collection supports, and collection efficiencies of the different sampling materials were assessed by passive headspace extraction with an activated charcoal strip (DFLEX device) followed by gas chromatography-mass spectrometry (GC-MS) analysis. After statistical treatment of the results, non-powdered latex gloves were retained as the most suitable method of sampling. On the basis of the obtained results, a prototype sampling kit was designed and tested. This kit is made of a three compartment multilayer bag enclosed in a sealed metal can and containing three pairs of non-powdered latex gloves: one to be worn by the sampler, one consisting of a blank sample and the last one to be worn by the person suspected to have been in contact with ignitable liquids. The design of the kit was developed to be efficient in preventing external and cross-contaminations.

Mass conservative three-dimensional water tracer distribution from Markov chain Monte Carlo inversion of time-lapse ground-penetrating radar data

Time-lapse geophysical measurements are widely used to monitor the movement of water and solutes through the subsurface. Yet commonly used deterministic least squares inversions typically suffer from relatively poor mass recovery, spread overestimation, and limited ability to appropriately estimate nonlinear model uncertainty. We describe herein a novel inversion methodology designed to reconstruct the three-dimensional distribution of a tracer anomaly from geophysical data and provide consistent uncertainty estimates using Markov chain Monte Carlo simulation. Posterior sampling is made tractable by using a lower-dimensional model space related both to the Legendre moments of the plume and to predefined morphological constraints. Benchmark results using cross-hole ground-penetrating radar travel times measurements during two synthetic water tracer application experiments involving increasingly complex plume geometries show that the proposed method not only conserves mass but also provides better estimates of plume morphology and posterior model uncertainty than deterministic inversion results.

Pattern recognition ecological niche models fit to presence-only and presence-absence data

1. Identifying the boundary of a species' niche from observational and environmental data is a common problem in ecology and conservation biology and a variety of techniques have been developed or applied to model niches and predict distributions. Here, we examine the performance of some pattern-recognition methods as ecological niche models (ENMs). Particularly, one-class pattern recognition is a flexible and seldom used methodology for modelling ecological niches and distributions from presence-only data. The development of one-class methods that perform comparably to two-class methods (for presence/absence data) would remove modelling decisions about sampling pseudo-absences or background data points when absence points are unavailable. 2. We studied nine methods for one-class classification and seven methods for two-class classification (five common to both), all primarily used in pattern recognition and therefore not common in species distribution and ecological niche modelling, across a set of 106 mountain plant species for which presence-absence data was available. We assessed accuracy using standard metrics and compared trade-offs in omission and commission errors between classification groups as well as effects of prevalence and spatial autocorrelation on accuracy. 3. One-class models fit to presence-only data were comparable to two-class models fit to presence-absence data when performance was evaluated with a measure weighting omission and commission errors equally. One-class models were superior for reducing omission errors (i.e. yielding higher sensitivity), and two-classes models were superior for reducing commission errors (i.e. yielding higher specificity). For these methods, spatial autocorrelation was only influential when prevalence was low. 4. These results differ from previous efforts to evaluate alternative modelling approaches to build ENM and are particularly noteworthy because data are from exhaustively sampled populations minimizing false absence records. Accurate, transferable models of species' ecological niches and distributions are needed to advance ecological research and are crucial for effective environmental planning and conservation; the pattern-recognition approaches studied here show good potential for future modelling studies. This study also provides an introduction to promising methods for ecological modelling inherited from the pattern-recognition discipline.

Parents' willingness to pay for diminishing children's pain during blood sampling.

BACKGROUND: Blood sampling is a frequent medical procedure, very often considered as a stressful experience by children. Local anesthetics have been developed, but are expensive and not reimbursed by insurance companies in our country. We wanted to assess parents' willingness to pay (WTP) for this kind of drug. PATIENTS AND METHODS: Over 6 months, all parents of children presenting for general (GV) or specialized visit (SV) with blood sampling. WTP was assessed through three scenarios [avoiding blood sampling (ABS), using the drug on prescription (PD), or over the counter (OTC)], with a payment card system randomized to ascending or descending order of prices (AO or DO). RESULTS: Fifty-six responses were collected (34 GV, 22 SV, 27 AO and 29 DO), response rate 40%. Response distribution was wide, with median WTP of 40 for ABS, 25 for PD, 10 for OTC, which is close to the drug's real price. Responses were similar for GV and SV. Median WTP amounted to 0.71, 0.67, 0.20% of respondents' monthly income for the three scenarios, respectively, with a maximum at 10%. CONCLUSIONS: Assessing parents' WTP in an outpatient setting is difficult, with wide result distribution, but median WTP is close to the real drug price. This finding could be used to promote insurance coverage for this drug.