Validation of Logistic Regression Models for Landslide Susceptibility Maps

A wide range of numerical models and tools have been developed over the last decades to support the decision making process in environmental applications, ranging from physical models to a variety of statistically-based methods. In this study, a landslide susceptibility map of a part of Three Gorges Reservoir region of China was produced, employing binary logistic regression analyses. The available information includes the digital elevation model of the region, geological map and different GIS layers including land cover data obtained from satellite imagery. The landslides were observed and documented during the field studies. The validation analysis is exploited to investigate the quality of mapping.

Time-series regression models to study the short-term effects of environmental factors on health

Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants

Robust regression in biological assay: application to the evaluation of alternative experimental techniques.

Robust Huber type regression and testing of linear hypotheses are adapted to statistical analysis of parallel line and slope ratio assays. They are applied in the evaluation of results of several experiments carried out in order to compare and validate alternatives to animal experimentation based on embryo and cell cultures. Computational procedures necessary for the application of robust methods of analysis used the conversational statistical package ROBSYS. Special commands for the analysis of parallel line and slope ratio assays have been added to ROBSYS.

Tests for sex-biased dispersal using bi-parentally inherited genetic markers.

Understanding why dispersal is sex-biased in many taxa is still a major concern in evolutionary ecology. Dispersal tends to be male-biased in mammals and female-biased in birds, but counter-examples exist and little is known about sex bias in other taxa. Obtaining accurate measures of dispersal in the field remains a problem. Here we describe and compare several methods for detecting sex-biased dispersal using bi-parentally inherited, codominant genetic markers. If gene flow is restricted among populations, then the genotype of an individual tells something about its origin. Provided that dispersal occurs at the juvenile stage and that sampling is carried out on adults, genotypes sampled from the dispersing sex should on average be less likely (compared to genotypes from the philopatric sex) in the population in which they were sampled. The dispersing sex should be less genetically structured and should present a larger heterozygote deficit. In this study we use computer simulations and a permutation test on four statistics to investigate the conditions under which sex-biased dispersal can be detected. Two tests emerge as fairly powerful. We present results concerning the optimal sampling strategy (varying number of samples, individuals, loci per individual and level of polymorphism) under different amounts of dispersal for each sex. These tests for biases in dispersal are also appropriate for any attribute (e.g. size, colour, status) suspected to influence the probability of dispersal. A windows program carrying out these tests can be freely downloaded from http://www.unil.ch/izea/softwares/fstat.html

Bi-ventricular axial micropump: impact on blood cell integrity.

BACKGROUND AND OBJECTIVE: Off-pump coronary artery bypass grafting has stimulated the development of micro-pumps designed to prevent the hemodynamic instability induced by heart luxation for the exposure of target vessels of the posterior wall. Impella (Aachen, Germany) developed micro-pumps with a miniaturized propeller system for both sides of the heart. The aim of this study was to analyze the impact of both pumps working together on blood cell integrity. MATERIALS AND METHODS: Both right and left-sided micro-pumps were implanted in 5 calves (body weight, 72_4 Kg) during 3 h. Blood samples for hematology and hemolysis parameters were drawn hourly. RESULTS: Both pumps performed well with a flow of 3.6 L +/- 0.3 L during the 3 h of the experiment with stable hemodynamic conditions. Mixed venous oxygen saturation was 63.4 +/- 15.2% at baseline and 63.8 +/- 16.3% at the end of the experiment (P = ns). Red cell count, LDH and free plasma hemoglobin were 6.7 +/- 2.1 x 10(12)/L, 1807 +/- 437 IU/L, and 32 +/- 9 mg/L at baseline vs. 6.1 +/- 2.1 x 10(12)/L, 1871 +/- 410 IU/L, and 52 +/- 9 mg/L at the end of the experiment (P = ns for all comparisons). Platelet count exhibited a non-significant drop (872 +/- 126 vs. 715 +/- 22 x 10(9)/L). CONCLUSIONS: This double pump system based on the Archimed screw principle is hematologically well tolerated under conditions of prolonged cardiac assist.

Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

Dubost, 250 cmc sur bi-temps [course motocycliste Paris-Reims-Paris, 6 juillet 1919] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 54735

Parenteral is more efficient than mucosal immunization to induce regression of human papillomavirus-associated genital tumors.

Cervical cancer is a public health concern as it represents the second cause of cancer death in women worldwide. High-risk human papillomaviruses (HPV) are the etiologic agents, and HPV E6 and/or E7 oncogene-specific therapeutic vaccines are under development to treat HPV-related lesions in women. Whether the use of mucosal routes of immunization may be preferable for inducing cell-mediated immune responses able to eradicate genital tumors is still debated because of the uniqueness of the female genital mucosa (GM) and the limited experimentation. Here, we compared the protective activity resulting from immunization of mice via intranasal (i.n.), intravaginal (IVAG) or subcutaneous (s.c.) routes with an adjuvanted HPV type 16 E7 polypeptide vaccine. Our data show that s.c. and i.n. immunizations elicited similar frequencies and avidity of TetE71CD81 and E7-specific Interferon-gamma-secreting cells in the GM, whereas slightly lower immune responses were induced by IVAG immunization. In a novel orthotopic murine model, both s.c. and i.n. immunizations allowed for complete long-term protection against genital E7-expressing tumor challenge. However, only s.c. immunization induced complete regression of already established genital tumors. This suggests that the higher E7-specific systemic response observed after s.c. immunization may contribute to the regression of growing genital tumors, whereas local immune responses may be sufficient to impede genital challenges. Thus, our data show that for an efficiently adjuvanted protein-based vaccine, parenteral vaccination route is superior to mucosal vaccination route for inducing regression of established genital tumors in a murine model of HPV-associated genital cancer.

Characteristics and effectiveness of diabetes self-management educational programs targeted to racial/ethnic minority groups: a systematic review, meta-analysis and meta-regression.

BACKGROUND It is not clear to what extent educational programs aimed at promoting diabetes self-management in ethnic minority groups are effective. The aim of this work was to systematically review the effectiveness of educational programs to promote the self-management of racial/ethnic minority groups with type 2 diabetes, and to identify programs' characteristics associated with greater success. METHODS We undertook a systematic literature review. Specific searches were designed and implemented for Medline, EMBASE, CINAHL, ISI Web of Knowledge, Scirus, Current Contents and nine additional sources (from inception to October 2012). We included experimental and quasi-experimental studies assessing the impact of educational programs targeted to racial/ethnic minority groups with type 2 diabetes. We only included interventions conducted in countries members of the OECD. Two reviewers independently screened citations. Structured forms were used to extract information on intervention characteristics, effectiveness, and cost-effectiveness. When possible, we conducted random-effects meta-analyses using standardized mean differences to obtain aggregate estimates of effect size with 95% confidence intervals. Two reviewers independently extracted all the information and critically appraised the studies. RESULTS We identified thirty-seven studies reporting on thirty-nine educational programs. Most of them were conducted in the US, with African American or Latino participants. Most programs obtained some benefits over standard care in improving diabetes knowledge, self-management behaviors and clinical outcomes. A meta-analysis of 20 randomized controlled trials (3,094 patients) indicated that the programs produced a reduction in glycated hemoglobin of -0.31% (95% CI -0.48% to -0.14%). Diabetes knowledge and self-management measures were too heterogeneous to pool. Meta-regressions showed larger reduction in glycated hemoglobin in individual and face to face delivered interventions, as well as in those involving peer educators, including cognitive reframing techniques, and a lower number of teaching methods. The long-term effects remain unknown and cost-effectiveness was rarely estimated. CONCLUSIONS Diabetes self-management educational programs targeted to racial/ethnic minority groups can produce a positive effect on diabetes knowledge and on self-management behavior, ultimately improving glycemic control. Future programs should take into account the key characteristics identified in this review.

Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

LDLs stimulate p38 MAPKs and wound healing through SR-BI independently of Ras and PI3 kinase.

Intracellular signals elicited by LDLs are likely to play a role in the pathogenesis associated with increased LDL blood levels. We have previously determined that LDL stimulation of human skin fibroblasts, used as a model system for adventitial fibroblasts, activates p38 mitogen-activated protein kinases (MAPKs), followed by IL-8 production and increased wound-healing capacity of the cells. The proximal events triggering these responses had not been characterized, however. Here we show that MAPK kinases MKK3 and MKK6, but not MKK4, are the upstream kinases responsible for the activation of the p38 MAPKs and stimulation of wound closure in response to LDLs. Phosphoinositide 3 kinases (PI3Ks) and Ras have been suggested to participate in lipoprotein-induced MAPK activation. However, specific PI3K inhibitors or expression of a dominant-negative form of Ras failed to blunt LDL-induced p38 MAPK activation. The classical LDL receptor does not participate in LDL signaling, but the contribution of other candidate lipoprotein receptors has not been investigated. Using cells derived from scavenger receptor class B type I (SR-BI) knockout mice or the BLT-1 SR-BI inhibitor, we now show that this receptor is required for LDLs to stimulate p38 MAPKs and to promote wound healing. Identification of MKK3/6 and SR-BI as cellular relays in LDL-mediated p38 activation further defines the signaling events that could participate in LDL-mediated pathophysiological responses.

Regression of cardiac growth in kidney transplant recipients using anti-m-TOR drugs plus RAS blockers: a controlled longitudinal study.

BACKGROUND Left ventricular hypertrophy (LVH) is common in kidney transplant (KT) recipients. LVH is associated with a worse outcome, though m-TOR therapy may help to revert this complication. We therefore conducted a longitudinal study to assess morphological and functional echocardiographic changes after conversion from CNI to m-TOR inhibitor drugs in nondiabetic KT patients who had previously received RAS blockers during the follow-up. METHODS We undertook a 1-year nonrandomized controlled study in 30 non-diabetic KT patients who were converted from calcineurin inhibitor (CNI) to m-TOR therapy. A control group received immunosuppressive therapy based on CNIs. Two echocardiograms were done during the follow-up. RESULTS Nineteen patients were switched to SRL and 11 to EVL. The m-TOR group showed a significant reduction in LVMi after 1 year (from 62 ± 22 to 55 ± 20 g/m2.7; P=0.003, paired t-test). A higher proportion of patients showing LVMi reduction was observed in the m-TOR group (53.3 versus 29.3%, P=0.048) at the study end. In addition, only 56% of the m-TOR patients had LVH at the study end compared to 77% of the control group (P=0.047). A significant change from baseline in deceleration time in early diastole was observed in the m-TOR group compared with the control group (P=0.019). CONCLUSIONS Switching from CNI to m-TOR therapy in non-diabetic KT patients may regress LVH, independently of blood pressure changes and follow-up time. This suggests a direct non-hemodynamic effect of m-TOR drugs on cardiac mass.