In vivo targeting of an anti-tumor antibody coupled to antigenic MHC class I complexes induces specific growth inhibition and regression of established syngeneic tumor grafts.

The concept of antibody-mediated targeting of antigenic MHC/peptide complexes on tumor cells in order to sensitize them to T-lymphocyte cytotoxicity represents an attractive new immunotherapy strategy. In vitro experiments have shown that an antibody chemically conjugated or fused to monomeric MHC/peptide can be oligomerized on the surface of tumor cells, rendering them susceptible to efficient lysis by MHC-peptide restricted specific T-cell clones. However, this strategy has not yet been tested entirely in vivo in immunocompetent animals. To this aim, we took advantage of OT-1 mice which have a transgenic T-cell receptor specific for the ovalbumin (ova) immunodominant peptide (257-264) expressed in the context of the MHC class I H-2K(b). We prepared and characterized conjugates between the Fab' fragment from a high-affinity monoclonal antibody to carcinoembryonic antigen (CEA) and the H-2K(b) /ova peptide complex. First, we showed in OT-1 mice that the grafting and growth of a syngeneic colon carcinoma line transfected with CEA could be specifically inhibited by systemic injections of the conjugate. Next, using CEA transgenic C57BL/6 mice adoptively transferred with OT-1 spleen cells and immunized with ovalbumin, we demonstrated that systemic injections of the anti-CEA-H-2K(b) /ova conjugate could induce specific growth inhibition and regression of well-established, palpable subcutaneous grafts from the syngeneic CEA-transfected colon carcinoma line. These results, obtained in a well-characterized syngeneic carcinoma model, demonstrate that the antibody-MHC/peptide strategy can function in vivo. Further preclinical experimental studies, using an anti-viral T-cell response, will be performed before this new form of immunotherapy can be considered for clinical use.

Responsiveness of astrocytes in serum-free aggregate cultures to epidermal growth factor: dependence on the cell cycle and the epidermal growth factor concentration.

Serum-free aggregating cell cultures of fetal rat telencephalon treated with low doses (0.5 nM) of epidermal growth factor (EGF) showed a small, transient increase in DNA synthesis but no significant changes in total DNA and protein content. By contrast, treatment with high doses (13 nM) of EGF caused a marked stimulation of DNA synthesis as well as a net increase in DNA and protein content. The expression of the astrocyte-specific enzyme, glutamine synthetase, was greatly enhanced both at low and at high EGF concentrations. These results suggest that at low concentration EGF stimulates exclusively the differentiation of astrocytes, whereas at high concentration, EGF has also a mitogenic effect. Nonproliferating astrocytes in cultures treated with 0.4 microM 1-beta-D-arabinofuranosyl-cytosine were refractory to EGF treatment, indicating that their responsiveness to EGF is cell cycle-dependent. Binding studies using a crude membrane fraction of 5-day cultures showed a homogeneous population of EGF binding sites (Kd approximately equal to 2.6 nM). Specific EGF binding sites were found also in non-proliferating (and nonresponsive) cultures, although they showed slightly reduced affinity and binding capacity. This finding suggests that the cell cycle-dependent control of astroglial responsiveness to EGF does not occur at the receptor level. However, it was found that the specific EGF binding sites disappear with progressive cellular differentiation.

Recent misconceptions about the "database search problem": a probabilistic analysis using Bayesian networks

This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern.

Improving generalized regression analysis for the spatial prediction of forest communities

Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.

Solving higher-dimensional continuous time stochastic control problems by value function regression

The paper develops a method to solve higher-dimensional stochasticcontrol problems in continuous time. A finite difference typeapproximation scheme is used on a coarse grid of low discrepancypoints, while the value function at intermediate points is obtainedby regression. The stability properties of the method are discussed,and applications are given to test problems of up to 10 dimensions.Accurate solutions to these problems can be obtained on a personalcomputer.

Should we await IFN-free regimens to treat HCV genotype 1 treatment-naive patients? A cost-effectiveness analysis (ANRS 95141).

BACKGROUND & AIMS: In treatment-naive patients mono-infected with genotype 1 chronic HCV, treatments with telaprevir/boceprevir (TVR/BOC)-based triple therapy are standard-of-care. However, more efficacious direct-acting antivirals (IFN-based new DAAs) are available and interferon-free (IFN-free) regimens are imminent (2015). METHODS: A mathematical model estimated quality-adjusted life years, cost and incremental cost-effectiveness ratios of (i) IFN-based new DAAs vs. TVR/BOC-based triple therapy; and (ii) IFN-based new DAAs initiation strategies, given that IFN-free regimens are imminent. The sustained virological response in F3-4/F0-2 was 71/89% with IFN-based new DAAs, 85/95% with IFN-free regimens, vs. 64/80% with TVR/BOC-based triple therapy. Serious adverse events leading to discontinuation were taken as: 0-0.6% with IFN-based new DAAs, 0% with IFN-free regimens, vs. 1-10% with TVR/BOC-based triple therapy. Costs were euro60,000 for 12weeks of IFN-based new DAAs and two times higher for IFN-free regimens. RESULTS: Treatment with IFN-based new DAAs when fibrosis stage ⩾F2 is cost-effective compared to TVR/BOC-based triple therapy (euro37,900/QALY gained), but not at F0-1 (euro103,500/QALY gained). Awaiting the IFN-free regimens is more effective, except in F4 patients, but not cost-effective compared to IFN-based new DAAs. If we decrease the cost of IFN-free regimens close to that of IFN-based new DAAs, then awaiting the IFN-free regimen becomes cost-effective. CONCLUSIONS: Treatment with IFN-based new DAAs at stage ⩾F2 is both effective and cost-effective compared to TVR/BOC triple therapy. Awaiting IFN-free regimens and then treating regardless of fibrosis is more efficacious, except in F4 patients; however, the cost-effectiveness of this strategy is highly dependent on its cost.

Impact of navigator timing on free-breathing submillimeter 3D coronary magnetic resonance angiography.

The purpose of this study was to investigate the impact of navigator timing on image quality in navigator-gated and real-time motion-corrected, free-breathing, three-dimensional (3D) coronary MR angiography (MRA) with submillimeter spatial image resolution. Both phantom and in vivo investigations were performed. 3D coronary MRA with real-time navigator technology was applied using variable navigator time delays (time delay between the navigator and imaging sequences) and varying spatial resolutions. Quantitative objective and subjective image quality parameters were assessed. For high-resolution imaging, reduced image quality was found as a function of increasing navigator time delay. Lower spatial resolution coronary MRA showed only minor sensitivity to navigator timing. These findings were consistent among volunteers and phantom experiments. In conclusion, for submillimeter navigator-gated and real-time motion-corrected 3D coronary MRA, shortening the time delay between the navigator and the imaging portion of the sequence becomes increasingly important for improved spatial resolution.

Weighted Kernel regression

In the fixed design regression model, additional weights areconsidered for the Nadaraya--Watson and Gasser--M\"uller kernel estimators.We study their asymptotic behavior and the relationships between new andclassical estimators. For a simple family of weights, and considering theIMSE as global loss criterion, we show some possible theoretical advantages.An empirical study illustrates the performance of the weighted estimatorsin finite samples.

How wide is the gap? An investigation of gender wage differences using quantile regression

In this paper we examine the determinants of wages and decompose theobserved differences across genders into the "explained by differentcharacteristics" and "explained by different returns components"using a sample of Spanish workers. Apart from the conditionalexpectation of wages, we estimate the conditional quantile functionsfor men and women and find that both the absolute wage gap and thepart attributed to different returns at each of the quantiles, farfrom being well represented by their counterparts at the mean, aregreater as we move up in the wage range.

Exact tests for correlation and for the slope in simple linear regressions without making assumptions

We present an exact test for whether two random variables that have known bounds on their support are negatively correlated. The alternative hypothesis is that they are not negatively correlated. No assumptions are made on the underlying distributions. We show by example that the Spearman rank correlation test as the competing exact test of correlation in nonparametric settings rests on an additional assumption on the data generating process without which it is not valid as a test for correlation.We then show how to test for the significance of the slope in a linear regression analysis that invovles a single independent variable and where outcomes of the dependent variable belong to a known bounded set.

Forecasting and turning point predictions in a Bayesian panel VAR model

We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model which accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for a particular type of diffuse, for Minnesota-type and for hierarchical priors. Formulas for multistep, multiunit point and average forecasts are provided. An application to the problem of forecasting the growth rate of output and of predicting turning points in the G-7 illustrates the approach. A comparison with alternative forecasting methods is also provided.

Physical activity assessment using a pedometer and its comparison with a questionnaire in a large population survey.

The aim of this study was to evaluate the use of the pedometer in epidemiologic research on physical activity. Within the framework of a health examination survey in 1988-1989, physical activity was assessed in a representative population sample of 493 men and women aged 25-74 years who were residents of Switzerland. They wore a pedometer for 1 week at work and during leisure time, and the results, converted into steps per day, were compared with answers to a questionnaire. The average number of steps per day decreased from 11,900 to 6,700 and from 9,300 to 7,300 for men and women, respectively, in the youngest to the oldest age groups. For men, categorized according to type of physical activity at work, there was a highly significant difference in the number of steps (p < 0.001), whereas in women the results were associated with leisure-time physical activity (p = 0.003). For both sexes, practicing sports more than once a week was associated with an important increase in steps per day. Analyzing the number of steps according to the day of the week and occupational category produced an unexpected result: Men with a physically active job engaged in more leisure-time physical activity on the weekend. The pedometer proved to be useful in assessing physical activity in a large, free-living population.

Label-free cytotoxicity screening assay by digital holographic microscopy

Abstract We introduce a label-free technology based on digital holographic microscopy (DHM) with applicability for screening by imaging, and we demonstrate its capability for cytotoxicity assessment using mammalian living cells. For this first high content screening compatible application, we automatized a digital holographic microscope for image acquisition of cells using commercially available 96-well plates. Data generated through both label-free DHM imaging and fluorescence-based methods were in good agreement for cell viability identification and a Z'-factor close to 0.9 was determined, validating the robustness of DHM assay for phenotypic screening. Further, an excellent correlation was obtained between experimental cytotoxicity dose-response curves and known IC values for different toxic compounds. For comparable results, DHM has the major advantages of being label free and close to an order of magnitude faster than automated standard fluorescence microscopy.

Resting metabolic rate in six- to ten-year-old obese and nonobese children.

The resting metabolic rate (RMR) and body composition of 130 obese and nonobese prepubertal children, aged 6 to 10 years, were assessed by indirect calorimetry and skin-fold thickness, respectively. The mean (+/- SD) RMR was 4619 +/- 449 kJ.day-1 (164 +/- 31 kJ.kg body weight-1 x day-1) in the 62 boys and 4449 +/- 520 kJ.day-1 (147 +/- 32 kJ.kg body weight-1 x day-1) in the 68 girls. Fat-free mass was the best single predictor of RMR (R2 = 0.64; p < 0.001). Step-down multiple regression analysis, with independent variables such as age, gender, weight, and height, allowed several RMR predictive equations to be developed. An equation for boys is as follows: RMR (kJ.day-1) = 1287 + 28.6 x Weight(kg) + 23.6 x Height(cm) - 69.1 x Age(yr) (R2 = 0.58; p < 0.001). An equation for girls is as follows: RMR (kJ.day-1 = 1552 + 35.8 x Weight (kg) + 15.6 x Height (cm) - 36.3 x Age (yr) (R2 = 0.69; p < 0.001). Comparison between the measured RMR and that predicted by currently used formulas showed that most of these equations tended to overestimate the RMR of both genders, especially in overweight children.