Toxicity screenings of nanomaterials: challenges due to interference with assay processes and components of classic in vitro tests.

Given the multiplicity of nanoparticles (NPs), there is a requirement to develop screening strategies to evaluate their toxicity. Within the EU-funded FP7 NanoTEST project, a panel of medically relevant NPs has been used to develop alternative testing strategies of NPs used in medical diagnostics. As conventional toxicity tests cannot necessarily be directly applied to NPs in the same manner as for soluble chemicals and drugs, we determined the extent of interference of NPs with each assay process and components. In this study, we fully characterized the panel of NP suspensions used in this project (poly(lactic-co-glycolic acid)-polyethylene oxide [PLGA-PEO], TiO2, SiO2, and uncoated and oleic-acid coated Fe3O4) and showed that many NP characteristics (composition, size, coatings, and agglomeration) interfere with a range of in vitro cytotoxicity assays (WST-1, MTT, lactate dehydrogenase, neutral red, propidium iodide, (3)H-thymidine incorporation, and cell counting), pro-inflammatory response evaluation (ELISA for GM-CSF, IL-6, and IL-8), and oxidative stress detection (monoBromoBimane, dichlorofluorescein, and NO assays). Interferences were assay specific as well as NP specific. We propose how to integrate and avoid interference with testing systems as a first step of a screening strategy for biomedical NPs.

Data-division-specific robustness and power of randomization tests for ABAB designs

This study deals with the statistical properties of a randomization test applied to an ABAB design in cases where the desirable random assignment of the points of change in phase is not possible. In order to obtain information about each possible data division we carried out a conditional Monte Carlo simulation with 100,000 samples for each systematically chosen triplet. Robustness and power are studied under several experimental conditions: different autocorrelation levels and different effect sizes, as well as different phase lengths determined by the points of change. Type I error rates were distorted by the presence of autocorrelation for the majority of data divisions. Satisfactory Type II error rates were obtained only for large treatment effects. The relationship between the lengths of the four phases appeared to be an important factor for the robustness and the power of the randomization test.

Randomization tests for ABAB designs: Comparing-data-division-specific and common distributions

Monte Carlo simulations were used to generate data for ABAB designs of different lengths. The points of change in phase are randomly determined before gathering behaviour measurements, which allows the use of a randomization test as an analytic technique. Data simulation and analysis can be based either on data-division-specific or on common distributions. Following one method or another affects the results obtained after the randomization test has been applied. Therefore, the goal of the study was to examine these effects in more detail. The discrepancies in these approaches are obvious when data with zero treatment effect are considered and such approaches have implications for statistical power studies. Data-division-specific distributions provide more detailed information about the performance of the statistical technique.

Measuring individuals' response quality in self-administered psychological tests : an introduction to Gendre's functional method

The functional method is a new test theory using a new scoring method that assumes complexity in test structure, and thus takes into account every correlation between factors and items. The main specificity of the functional method is to model test scores by multiple regression instead of estimating them by using simplistic sums of points. In order to proceed, the functional method requires the creation of hyperspherical measurement space, in which item responses are expressed by their correlation with orthogonal factors. This method has three main qualities. First, measures are expressed in the absolute metric of correlations; therefore, items, scales and persons are expressed in the same measurement space using the same single metric. Second, factors are systematically orthogonal and without errors, which is optimal in order to predict other outcomes. Such predictions can be performed to estimate how one would answer to other tests, or even to model one's response strategy if it was perfectly coherent. Third, the functional method provides measures of individuals' response validity (i.e., control indices). Herein, we propose a standard procedure in order to identify whether test results are interpretable and to exclude invalid results caused by various response biases based on control indices.

Prevalence of alcohol-impaired drivers based on random breath tests in a roadside survey

Sobriety checkpoints are not usually randomly located by traffic authorities. As such, information provided by non-random alcohol tests cannot be used to infer the characteristics of the general driving population. In this paper a case study is presented in which the prevalence of alcohol-impaired driving is estimated for the general population of drivers. A stratified probabilistic sample was designed to represent vehicles circulating in non-urban areas of Catalonia (Spain), a region characterized by its complex transportation network and dense traffic around the metropolis of Barcelona. Random breath alcohol concentration tests were performed during spring 2012 on 7,596 drivers. The estimated prevalence of alcohol-impaired drivers was 1.29 PER CENT, which is roughly a third of the rate obtained in non-random tests. Higher rates were found on weekends (1.90 PER CENT on Saturdays, 4.29 PER CENT on Sundays) and especially at night. The rate is higher for men (1.45 PER CENT) than for women (0.64 PER CENT) and the percentage of positive outcomes shows an increasing pattern with age. In vehicles with two occupants, the proportion of alcohol-impaired drivers is estimated at 2.62 PER CENT, but when the driver was alone the rate drops to 0.84 PER CENT, which might reflect the socialization of drinking habits. The results are compared with outcomes in previous surveys, showing a decreasing trend in the prevalence of alcohol-impaired drivers over time.

Comparison of Griffiths-II and Bayley-II tests for the developmental assessment of high-risk infants.

INTRODUCTION: Two important risk factors for abnormal neurodevelopment are preterm birth and neonatal hypoxic ischemic encephalopathy. The new revisions of Griffiths Mental Development Scale (Griffiths-II, [1996]) and the Bayley Scales of Infant Development (BSID-II, [1993]) are two of the most frequently used developmental diagnostics tests. The Griffiths-II is divided into five subscales and a global development quotient (QD), and the BSID-II is divided into two scales, the Mental scale (MDI) and the Psychomotor scale (PDI). The main objective of this research was to establish the extent to which developmental diagnoses obtained using the new revisions of these two tests are comparable for a given child. MATERIAL AND METHODS: Retrospective study of 18-months-old high-risk children examined with both tests in the follow-up Unit of the Clinic of Neonatology of our tertiary care university Hospital between 2011 and 2012. To determine the concurrent validity of the two tests paired t-tests and Pearson product-moment correlation coefficients were computed. Using the BSID-II as a gold standard, the performance of the Griffiths-II was analyzed with receiver operating curves. RESULTS: 61 patients (80.3% preterm, 14.7% neonatal asphyxia) were examined. For the BSID-II the MDI mean was 96.21 (range 67-133) and the PDI mean was 87.72 (range 49-114). For the Griffiths-II, the QD mean was 96.95 (range 60-124), the locomotors subscale mean was 92.57 (range 49-119). The score of the Griffiths locomotors subscale was significantly higher than the PDI (p<0.001). Between the Griffiths-II QD and the BSID-II MDI no significant difference was found, and the area under the curve was 0.93, showing good validity. All correlations were high and significant with a Pearson product-moment correlation coefficient >0.8. CONCLUSIONS: The meaning of the results for a given child was the same for the two tests. Two scores were interchangeable, the Griffiths-II QD and the BSID-II MDI.