Prospective assessment of CYP2D6 by genotyping, phenotyping and measurement of tamoxifen, PD 05-09 4-hydroxy-tamoxifen and endoxifen in breast cancer patients treated with tamoxifen.

Tamoxifen (tam) is a widely used endocrine therapy in the treatment of early and advanced stage breast cancer in women and men. It is a pro-drug having weak affinity with the estrogen receptor and needs to be converted to its main metabolite, endoxifen (endox), to have full anticancer activity. Cytochrome 2D6 (CYP2D6) plays a major role in the metabolism of tamoxifen to endoxifen. It is genetically highly polymorphic and its activity influences profoundly the synthesis of endoxifen and potentially the efficacy of tamoxifen treatment. Genotyping is currently the most widely used approach in studies and also in clinical practice to categorize patients as poor- (PM), intermediate- (IM), extensive- (EM) and ultra rapid-metabolizers (UM). Some clinicians already use genotyping in order to tailor the endocrine therapy of their patients. Owing to the large inter-individual variations in concentrations of the active moitey due to genetic and non-genetic influences renders the predictive value of the test uncertain for an individual patient. A significant number of patients classified as EM or IM by genotyping have indeed relatively low endoxifen levels similar to PMs1. This suggests that genotyping is probably not the opti ma l meth o d f or predi cti ng end oxif en l evels.

Looking for Validity or Testing It? The Perils of Stepwise Regression, Extreme-Scores Analysis, Heteroscedasticity, and Measurement Error

When researchers introduce a new test they have to demonstrate that it is valid, using unbiased designs and suitable statistical procedures. In this article we use Monte Carlo analyses to highlight how incorrect statistical procedures (i.e., stepwise regression, extreme scores analyses) or ignoring regression assumptions (e.g., heteroscedasticity) contribute to wrong validity estimates. Beyond these demonstrations, and as an example, we re-examined the results reported by Warwick, Nettelbeck, and Ward (2010) concerning the validity of the Ability Emotional Intelligence Measure (AEIM). Warwick et al. used the wrong statistical procedures to conclude that the AEIM was incrementally valid beyond intelligence and personality traits in predicting various outcomes. In our re-analysis, we found that the reliability-corrected multiple correlation of their measures with personality and intelligence was up to .69. Using robust statistical procedures and appropriate controls, we also found that the AEIM did not predict incremental variance in GPA, stress, loneliness, or well-being, demonstrating the importance for testing validity instead of looking for it.

Octopus Standard Automated Perimetry, Pulsar Perimetry, Moorfields Motion Displacement Test and Heidelberg Retinal Tomography in Glaucoma Detection - A Comparison of Diagnostic Accuracy

Purpose: To investigate the accuracy of 4 clinical instruments in the detection of glaucomatous damage. Methods: 102 eyes of 55 test subjects (Age mean = 66.5yrs, range = [39; 89]) underwent Heidelberg Retinal Tomography (HRTIII), (disc area<2.43); and standard automated perimetry (SAP) using Octopus (Dynamic); Pulsar (TOP); and Moorfields Motion Displacement Test (MDT) (ESTA strategy). Eyes were separated into three groups 1) Healthy (H): IOP<21mmHg and healthy discs (clinical examination), 39 subjects, 78 eyes; 2) Glaucoma suspect (GS): Suspicious discs (clinical examination), 12 subjects, 15 eyes; 3) Glaucoma (G): progressive structural or functional loss, 14 subjects, 20 eyes. Clinical diagnostic precision was examined using the cut-off associated with the p<5% normative limit of MD (Octopus/Pulsar), PTD (MDT) and MRA (HRT) analysis. The sensitivity, specificity and accuracy were calculated for each instrument. Results: See table Conclusions: Despite the advantage of defining glaucoma suspects using clinical optic disc examination, the HRT did not yield significantly higher accuracy than functional measures. HRT, MDT and Octopus SAP yielded higher accuracy than Pulsar perimetry, although results did not reach statistical significance. Further studies are required to investigate the structure-function correlations between these instruments.

Contact tracing investigation after professional exposure to tuberculosis in a Swiss hospital using both tuberculin skin test and IGRA.

SETTING: A 950 bed teaching hospital in Switzerland. AIM: To describe the result of a contact investigation among health care workers (HCW) and patients after exposure to a physician with smear-positive pulmonary tuberculosis in a hospital setting using standard tuberculin skin tests (TST) and Interferon-gamma release assay (IGRA). METHOD: HCW with a negative or unknown TST at hiring had a TST two weeks after the last contact with the index case (T0), repeated six weeks later if negative (T6). All exposed HCW had a T-SPOT.TB at T0 and T6. Exposed patients had a TST six weeks after the last contact, and a T-SPOT.TB if the TST was positive. RESULTS: Among 101 HCW, 17/73 (22%) had a positive TST at T0. TST was repeated in 50 at T6 and converted from negative to positive in eight (16%). Twelve HCW had a positive T-SPOT.TB at T0 and ten converted from negative to positive at T6. Seven HCW with a positive T-SPOT.TB reverted to negative at T6 or at later controls, most of them with test values close to the cut-off. Among 27 exposed patients tested at six weeks, ten had a positive TST, five of them confirmed by a positive T-SPOT.TB. CONCLUSIONS: HCW tested twice after exposure to a case of smear-positive pulmonary TB demonstrated a possible conversion in 10% with T-SPOT and 16% with TST. Some T-SPOT.TB reverted from positive to negative during the follow-up, mostly tests with a value close to the cut-off. Due to the variability of the test results, it seems advisable to repeat the test with values close to the cut-off before diagnosing the presence of a tuberculous infection.

The association between drinking motives and alcohol-related consequences - room for biases and measurement issues?

Aims  To investigate whether the predominant finding of generalized positive associations between self-rated motives for drinking alcohol and negative consequences of drinking alcohol are influenced by (i) using raw scores of motives that may weight inter-individual response behaviours too strongly, and (ii) predictor-criterion contamination by using consequence items where respondents attribute alcohol use as the cause. Design  Cross-sectional study within the European School Survey Project on Alcohol and other Drugs (ESPAD). Setting  School classes. Participants  Students, aged 13-16 (n = 5633). Measurements  Raw, rank and mean-variance standardized scores of the Drinking Motives Questionnaire-Revised (DMQ-R); four consequences: serious problems with friends, sexual intercourse regretted the next day, physical fights and troubles with the police, each itemized with attribution ('because of your alcohol use') and without. Findings  As found previously in the literature, raw scores for all drinking motives had positive associations with negative consequences of drinking, while transformed (rank or Z) scores showed a more specific pattern: external reinforcing motives (social, conformity) had negative and internal reinforcing motives (enhancement, coping) had non-significant or positive associations with negative consequences. Attributed consequences showed stronger associations with motives than non-attributed ones. Conclusion  Standard scoring of the Drinking Motives Questionnaire (Revised) fails to capture motives in a way that permits specific associations with different negative consequences to be identified, whereas use of rank or Z-scores does permit this. Use of attributed consequences overestimates the association with drinking motives.

Detection and measurement of paracaspase MALT1 activity.

The paracaspase MALT1 is a Cys-dependent, Arg-specific protease that plays an essential role in the activation and proliferation of lymphocytes during the immune response. Oncogenic activation of MALT1 is associated with the development of specific forms of B-cell lymphomas. Through specific cleavage of its substrates, MALT1 controls various aspects of lymphocyte activation, including the activation of transcriptional pathways, the stabilization of mRNAs, and an increase in cellular adhesion. In lymphocytes, the activity of MALT1 is tightly controlled by its inducible monoubiquitination, which promotes the dimerization of MALT1. Here, we describe both in vitro and in vivo assays that have been developed to assess MALT1 activity.

Biofilm formation on bone grafts and bone graft substitutes: comparison of different materials by a standard in vitro test and microcalorimetry.

We analyzed the initial adhesion and biofilm formation of Staphylococcus aureus (ATCC 29213) and S. epidermidis RP62A (ATCC 35984) on various bone grafts and bone graft substitutes under standardized in vitro conditions. In parallel, microcalorimetry was evaluated as a real-time microbiological assay in the investigation of biofilm formation and material science research. The materials beta-tricalcium phosphate (beta-TCP), processed human spongiosa (Tutoplast) and poly(methyl methacrylate) (PMMA) were investigated and compared with polyethylene (PE). Bacterial counts (log(10) cfu per sample) were highest on beta-TCP (S. aureus 7.67 +/- 0.17; S. epidermidis 8.14 +/- 0.05) while bacterial density (log(10) cfu per surface) was highest on PMMA (S. aureus 6.12 +/- 0.2, S. epidermidis 7.65 +/- 0.13). Detection time for S. aureus biofilms was shorter for the porous materials (beta-TCP and processed human spongiosa, p < 0.001) compared to the smooth materials (PMMA and PE), with no differences between beta-TCP and processed human spongiosa (p > 0.05) or PMMA and PE (p > 0.05). In contrast, for S. epidermidis biofilms the detection time was different (p < 0.001) between all materials except between processed human spongiosa and PE (p > 0.05). The quantitative analysis by quantitative culture after washing and sonication of the material demonstrated the importance of monitoring factors like specific surface or porosity of the test materials. Isothermal microcalorimetry proved to be a suitable tool for an accurate, non-invasive and real-time microbiological assay, allowing the detection of bacterial biomass without removing the biofilm from the surface.

Automatic Mapping and Classification of Spatial Environmental Data

The paper deals with the development and application of the generic methodology for automatic processing (mapping and classification) of environmental data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve the problem of spatial data mapping (regression). The Probabilistic Neural Network (PNN) is considered as an automatic tool for spatial classifications. The automatic tuning of isotropic and anisotropic GRNN/PNN models using cross-validation procedure is presented. Results are compared with the k-Nearest-Neighbours (k-NN) interpolation algorithm using independent validation data set. Real case studies are based on decision-oriented mapping and classification of radioactively contaminated territories.

What drives invasibility? A multi-model inference test and spatial modelling of alien plant species richness patterns in northern Portugal

Understanding and anticipating biological invasions can focus either on traits that favour species invasiveness or on features of the receiving communities, habitats or landscapes that promote their invasibility. Here, we address invasibility at the regional scale, testing whether some habitats and landscapes are more invasible than others by fitting models that relate alien plant species richness to various environmental predictors. We use a multi-model information-theoretic approach to assess invasibility by modelling spatial and ecological patterns of alien invasion in landscape mosaics and testing competing hypotheses of environmental factors that may control invasibility. Because invasibility may be mediated by particular characteristics of invasiveness, we classified alien species according to their C-S-R plant strategies. We illustrate this approach with a set of 86 alien species in Northern Portugal. We first focus on predictors influencing species richness and expressing invasibility and then evaluate whether distinct plant strategies respond to the same or different groups of environmental predictors. We confirmed climate as a primary determinant of alien invasions and as a primary environmental gradient determining landscape invasibility. The effects of secondary gradients were detected only when the area was sub-sampled according to predictions based on the primary gradient. Then, multiple predictor types influenced patterns of alien species richness, with some types (landscape composition, topography and fire regime) prevailing over others. Alien species richness responded most strongly to extreme land management regimes, suggesting that intermediate disturbance induces biotic resistance by favouring native species richness. Land-use intensification facilitated alien invasion, whereas conservation areas hosted few invaders, highlighting the importance of ecosystem stability in preventing invasions. Plants with different strategies exhibited different responses to environmental gradients, particularly when the variations of the primary gradient were narrowed by sub-sampling. Such differential responses of plant strategies suggest using distinct control and eradication approaches for different areas and alien plant groups.

Stochastic inversion of tracer test and electrical geophysical data to estimate hydraulic conductivities.

Quantifying the spatial configuration of hydraulic conductivity (K) in heterogeneous geological environments is essential for accurate predictions of contaminant transport, but is difficult because of the inherent limitations in resolution and coverage associated with traditional hydrological measurements. To address this issue, we consider crosshole and surface-based electrical resistivity geophysical measurements, collected in time during a saline tracer experiment. We use a Bayesian Markov-chain-Monte-Carlo (McMC) methodology to jointly invert the dynamic resistivity data, together with borehole tracer concentration data, to generate multiple posterior realizations of K that are consistent with all available information. We do this within a coupled inversion framework, whereby the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration. To minimize computational expense, a facies-based subsurface parameterization is developed. The Bayesian-McMC methodology allows us to explore the potential benefits of including the geophysical data into the inverse problem by examining their effect on our ability to identify fast flowpaths in the subsurface, and their impact on hydrological prediction uncertainty. Using a complex, geostatistically generated, two-dimensional numerical example representative of a fluvial environment, we demonstrate that flow model calibration is improved and prediction error is decreased when the electrical resistivity data are included. The worth of the geophysical data is found to be greatest for long spatial correlation lengths of subsurface heterogeneity with respect to wellbore separation, where flow and transport are largely controlled by highly connected flowpaths.

Computer Aided Detection and measurement of peripheral artery disease.

Computer-Aided Tomography Angiography (CTA) images are the standard for assessing Peripheral artery disease (PAD). This paper presents a Computer Aided Detection (CAD) and Computer Aided Measurement (CAM) system for PAD. The CAD stage detects the arterial network using a 3D region growing method and a fast 3D morphology operation. The CAM stage aims to accurately measure the artery diameters from the detected vessel centerline, compensating for the partial volume effect using Expectation Maximization (EM) and a Markov Random field (MRF). The system has been evaluated on phantom data and also applied to fifteen (15) CTA datasets, where the detection accuracy of stenosis was 88% and the measurement accuracy was with an 8% error.

Skeletal muscle mitochondrial energetics are associated with maximal aerobic capacity and walking speed in older adults.

BACKGROUND: Lower ambulatory performance with aging may be related to a reduced oxidative capacity within skeletal muscle. This study examined the associations between skeletal muscle mitochondrial capacity and efficiency with walking performance in a group of older adults. METHODS: Thirty-seven older adults (mean age 78 years; 21 men and 16 women) completed an aerobic capacity (VO peak) test and measurement of preferred walking speed over 400 m. Maximal coupled (State 3; St3) mitochondrial respiration was determined by high-resolution respirometry in saponin-permeabilized myofibers obtained from percutanous biopsies of vastus lateralis (n = 22). Maximal phosphorylation capacity (ATP) of vastus lateralis was determined in vivo by P magnetic resonance spectroscopy (n = 30). Quadriceps contractile volume was determined by magnetic resonance imaging. Mitochondrial efficiency (max ATP production/max O consumption) was characterized using ATP per St3 respiration (ATP/St3). RESULTS: In vitro St3 respiration was significantly correlated with in vivo ATP (r = .47, p = .004). Total oxidative capacity of the quadriceps (St3*quadriceps contractile volume) was a determinant of VO peak (r = .33, p = .006). ATP (r = .158, p = .03) and VO peak (r = .475, p < .0001) were correlated with preferred walking speed. Inclusion of both ATP/St3 and VO peak in a multiple linear regression model improved the prediction of preferred walking speed (r = .647, p < .0001), suggesting that mitochondrial efficiency is an important determinant for preferred walking speed. CONCLUSIONS: Lower mitochondrial capacity and efficiency were both associated with slower walking speed within a group of older participants with a wide range of function. In addition to aerobic capacity, lower mitochondrial capacity and efficiency likely play roles in slowing gait speed with age.