GeoKernels: Modeling of Spatial Data on GeoManifolds

This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental data modeling on natural manifolds, such as complex topographies of the mountainous regions, where environmental processes are highly influenced by the relief. These relations, possibly regionalized and nonlinear, can be modeled from data with machine learning using the digital elevation models in semi-supervised kernel methods. The range of the tools and methodological issues discussed in the study includes feature selection and semisupervised Support Vector algorithms. The real case study devoted to data-driven modeling of meteorological fields illustrates the discussed approach.

Assessment of diesel exhaust particulate exposure and surface characteristics in association with levels of oxidative stress biomarkers

Exposure to PM10 and PM2.5 (particulate matter with aerodynamic diameter smaller than 10 μm and 2.5 μm, respectively) is associated with a range of adverse health effects, including cancer, pulmonary and cardiovascular diseases. Surface characteristics (chemical reactivity, surface area) are considered of prime importance to understand the mechanisms which lead to harmful effects. A hypothetical mechanism to explain these adverse effects is the ability of components (organics, metal ions) adsorbed on these particles to generate Reactive Oxygen Species (ROS), and thereby to cause oxidative stress in biological systems (Donaldson et al., 2003). ROS can attack almost any cellular structure, like DNA or cellular membrane, leading to the formation of a wide variety of degradation products which can be used as a biomarker of oxidative stress. The aim of the present research project is to test whether there is a correlation between the exposure to Diesel Exhaust Particulate (DEP) and the oxidative stress status. For that purpose, a survey has been conducted in real occupational situations where workers were exposed to DEP (bus depots). Different exposure variables have been considered: - particulate number, size distribution and surface area (SMPS); - particulate mass - PM2.5 and PM4 (gravimetry); - elemental and organic carbon (coulometry); - total adsorbed heavy metals - iron, copper, manganese (atomic adsorption); - surface functional groups present on aerosols (Knudsen flow reactor). (Demirdjian et al., 2005). Several biomarkers of oxidative stress (8-hydroxy-2'-deoxyguanosine and several aldehydes) have been determined either in urine or serum of volunteers. Results obtained during the sampling campaign in several bus depots indicated that the occupational exposure to particulates in these places was rather low (40-50 μg/m3 for PM4). Size distributions indicated that particles are within the nanometric range. Surface characteristics of sampled particles varied strongly, depending on the bus depot. They were usually characterized by high carbonyl and low acidic sites content. Among the different biomarkers which have been analyzed within the framework of this study, mean levels of 8- hydroxy-2'-deoxyguanosine and several aldehydes (hexanal, heptanal, octanal, nonanal) increased during two consecutive days of exposure for non-smokers. In order to bring some insight into the relation between the particulate characteristics and the formation of ROS by-products, biomarkers levels will be discussed in relation with exposure variables.

Respiratory effects of an exposure to grain dust among grain workers in the Vaud region (Switzerland)

Introduction: Bioaerosols such as grain dust (GD) elicit direct immunological reactions within the human respiratory system. Workplace-dependent exposure to GD may induce asthma, chronic bronchitis, and hypersensitivity pneumonitis. Aims: To assess the clinical impact of occupational exposure to GD and to determine quantitative biological markers of bioaerosol exposure in grain workers. Methods: This longitudinal study has been conducted from summer 2012 to summer 2013, comprising 6 groups of 30 active workers with different GD exposure patterns (4 groups of grain workers, 2 control groups). Two evaluations at high- and low-exposing seasons take place, during which an occupational and a medical history are questionnaire-assessed, lung function is evaluated by spirometry, airway inflammation is measured by exhaled nitric oxide (eNO) and specific blood IgG and IgE are titrated. Results: The preliminary results are those of 2 of the 4 exposed groups, (harvesters and mill workers), compared to the control groups, at first assessment (n=100). Mean age is 38.4 [years]; 98% are male. Exposed groups differ from controls (p<0.05) in daily contact with animals (57% vs. 40%) and active smoking (39% vs. 11%). Grain workers have more respiratory (50%), nasal (57%), ocular (45%) and dermatologic (36%) occupational symptoms than controls (6.4%, 19%, 16%, 6.4% respectively, p<0.05). Lower mean peak-expiratory-flow (PEF) values (96.1 ± 18.9 vs. 108.2 ± 17.4 [% of predicted], p<0.05) and eNO values (13.9 ± 9.6 vs. 20.5 ± 14.7 [ppm], p<0.05) are observed in the exposed groups. Conclusion: Preliminary results show a higher prevalence of clinical symptoms and a lower mean PEF value in the groups exposed to GD.

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.

Making sense of AMPA receptor trafficking by modeling molecular mechanisms of synaptic plasticity.

Synaptic plasticity involves a complex molecular machinery with various protein interactions but it is not yet clear how its components give rise to the different aspects of synaptic plasticity. Here we ask whether it is possible to mathematically model synaptic plasticity by making use of known substances only. We present a model of a multistable biochemical reaction system and use it to simulate the plasticity of synaptic transmission in long-term potentiation (LTP) or long-term depression (LTD) after repeated excitation of the synapse. According to our model, we can distinguish between two phases: first, a "viscosity" phase after the first excitation, the effects of which like the activation of NMDA receptors and CaMKII fade out in the absence of further excitations. Second, a "plasticity" phase actuated by an identical subsequent excitation that follows after a short time interval and causes the temporarily altered concentrations of AMPA subunits in the postsynaptic membrane to be stabilized. We show that positive feedback is the crucial element in the core chemical reaction, i.e. the activation of the short-tail AMPA subunit by NEM-sensitive factor, which allows generating multiple stable equilibria. Three stable equilibria are related to LTP, LTD and a third unfixed state called ACTIVE. Our mathematical approach shows that modeling synaptic multistability is possible by making use of known substances like NMDA and AMPA receptors, NEM-sensitive factor, glutamate, CaMKII and brain-derived neurotrophic factor. Furthermore, we could show that the heteromeric combination of short- and long-tail AMPA receptor subunits fulfills the function of a memory tag.

Domestic radon exposure and risk of childhood cancer: a prospective census-based cohort study

BACKGROUND: In contrast with established evidence linking high doses of ionizing radiation with childhood cancer, research on low-dose ionizing radiation and childhood cancer has produced inconsistent results. OBJECTIVE: We investigated the association between domestic radon exposure and childhood cancers, particularly leukemia and central nervous system (CNS) tumors. METHODS: We conducted a nationwide census-based cohort study including all children < 16 years of age living in Switzerland on 5 December 2000, the date of the 2000 census. Follow-up lasted until the date of diagnosis, death, emigration, a child's 16th birthday, or 31 December 2008. Domestic radon levels were estimated for each individual home address using a model developed and validated based on approximately 45,000 measurements taken throughout Switzerland. Data were analyzed with Cox proportional hazard models adjusted for child age, child sex, birth order, parents' socioeconomic status, environmental gamma radiation, and period effects. RESULTS: In total, 997 childhood cancer cases were included in the study. Compared with children exposed to a radon concentration below the median (< 77.7 Bq/m3), adjusted hazard ratios for children with exposure ≥ the 90th percentile (≥ 139.9 Bq/m3) were 0.93 (95% CI: 0.74, 1.16) for all cancers, 0.95 (95% CI: 0.63, 1.43) for all leukemias, 0.90 (95% CI: 0.56, 1.43) for acute lymphoblastic leukemia, and 1.05 (95% CI: 0.68, 1.61) for CNS tumors. CONCLUSIONS: We did not find evidence that domestic radon exposure is associated with childhood cancer, despite relatively high radon levels in Switzerland.

Total exposure and exposure rate effects for alcohol and smoking and risk of head and neck cancer: a pooled analysis of case-control studies.

Although cigarette smoking and alcohol consumption increase risk for head and neck cancers, there have been few attempts to model risks quantitatively and to formally evaluate cancer site-specific risks. The authors pooled data from 15 case-control studies and modeled the excess odds ratio (EOR) to assess risk by total exposure (pack-years and drink-years) and its modification by exposure rate (cigarettes/day and drinks/day). The smoking analysis included 1,761 laryngeal, 2,453 pharyngeal, and 1,990 oral cavity cancers, and the alcohol analysis included 2,551 laryngeal, 3,693 pharyngeal, and 3,116 oval cavity cancers, with over 8,000 controls. Above 15 cigarettes/day, the EOR/pack-year decreased with increasing cigarettes/day, suggesting that greater cigarettes/day for a shorter duration was less deleterious than fewer cigarettes/day for a longer duration. Estimates of EOR/pack-year were homogeneous across sites, while the effects of cigarettes/day varied, indicating that the greater laryngeal cancer risk derived from differential cigarettes/day effects and not pack-years. EOR/drink-year estimates increased through 10 drinks/day, suggesting that greater drinks/day for a shorter duration was more deleterious than fewer drinks/day for a longer duration. Above 10 drinks/day, data were limited. EOR/drink-year estimates varied by site, while drinks/day effects were homogeneous, indicating that the greater pharyngeal/oral cavity cancer risk with alcohol consumption derived from the differential effects of drink-years and not drinks/day.

Modeling the forensic two-trace problem with Bayesian networks

The forensic two-trace problem is a perplexing inference problem introduced by Evett (J Forensic Sci Soc 27:375-381, 1987). Different possible ways of wording the competing pair of propositions (i.e., one proposition advanced by the prosecution and one proposition advanced by the defence) led to different quantifications of the value of the evidence (Meester and Sjerps in Biometrics 59:727-732, 2003). Here, we re-examine this scenario with the aim of clarifying the interrelationships that exist between the different solutions, and in this way, produce a global vision of the problem. We propose to investigate the different expressions for evaluating the value of the evidence by using a graphical approach, i.e. Bayesian networks, to model the rationale behind each of the proposed solutions and the assumptions made on the unknown parameters in this problem.

Tolerance of whitefish embryos to Pseudomonas fluorescens linked to genetic and maternal effects, and reduced by previous exposure.

Juvenile or adult fish can alter their behaviour and rely on an innate and adaptive immune system to avoid/counteract pathogens, while fish embryos have to depend on egg characteristics and may be partly protected by their developing immune system that is building up from a certain age on. We developed an infection protocol that allows testing the reaction of individual whitefish embryos (Coregonus palaea) to repeated exposures to Pseudomonas fluorescens, an opportunistic bacterial fish pathogen. We used a full-factorial in vitro breeding design to separately test the effects of paternal and maternal contributions to the embryos' susceptibility to different kinds of pathogen exposure. We found that a first non-lethal exposure had immunosuppressive effects: pre-exposed embryos were more susceptible to future challenges with the same pathogen. At intermediate and high levels of pathogen intensity, maternal effects turned out to be crucial for the embryos' tolerance to infection. Paternal (i.e. genetic) effects played a significant role at the strongest level of infection, i.e. the embryos' own genetics already explained some of the variation in embryo susceptibility. Our findings suggest that whitefish embryos are largely protected by maternally transmitted substances, but build up some own innate immunocompetence several days before hatching.

Topical retinoids exposure during pregnancy.

Concerns have been raised with the topical use of retinoids since the publication of occasional cases associated with characteristic retinoid embryopathy, originally described after oral use. Epidemiological data are still scant. A collaborative study was carried out to evaluate the rate of congenital malformations following 1st trimester topical retinoid exposure. Using a standardized protocol exposed pregnancies and non exposed controls were prospectively recorded by the European Network of Teratology Information Services (ENTIS). A population of 222 pregnant women exposed to topical retinoids (median age [range]: 30 [21 - 42] years; gestational week at call: 7 [3 - 35]) were compared to 444 women not exposed (median age [range]: 32 [17 - 48] years; gestational week at call: 8 [2 - 39]). The following retinoids were identified: adapalene: 22; retinoic acid: 10; tretinoin: 135; isotretinoin:49, others: 6. The exposed and non-exposed groups did not differ in maternal alcohol and tobacco use, gestational duration, birth weight and length. There were no Abstracts: Clinical Pharmacology and Therapeutics IXth World Congress -2008 significant differences between groups in the rate of pregnancies ending in spontaneous abortion (8.7% in exposed vs. 5.9% in unexposed; P=0.18) or in infants with minor malformations (3.7% in exposed vs. 2.9% in unexposed; P=0.61) and major malformations (3.7% in exposed vs. 2.2% in unexposed; P=0.29). No child showed features of retinoid embryopathy. In conclusion, these results bring reassurance in cases of fortuitous topical retinoid exposure. However, according to the current knowledge, topical retinoids can not be recommended for use during pregnancy, as the risk/benefit ratio remains questionable.

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling

The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Pregnancy outcome following maternal exposure to statins: a multicentre prospective study.

OBJECTIVE: This contribution addresses the risk associated with exposure to statins during pregnancy. DESIGN: Multicentre observational prospective controlled study. SETTING: European Network of Teratology Information Services. POPULATION: Pregnant women who contacted one of 11 participating centres, seeking advice about exposure to statins during pregnancy, or to agents known to be nonteratogenic. METHODS: Pregnancies exposed during first trimester to statins were followed up prospectively, and their outcomes were compared with a matched control group. MAIN OUTCOME MEASURES: Rates of major birth defects, live births, miscarriages, elective terminations, preterm deliveries and gestational age and birthweight at delivery. RESULTS: We collected observations from 249 exposed pregnancies and 249 controls. The difference in the rate of major birth defects between the statin-exposed and the control groups was small and statistically nonsignificant (4.1% versus 2.7% odds ratio [OR] 1.5; 95% confidence interval [95% CI] 0.5-4.5, P = 0.43). In an adjusted Cox model, the difference between miscarriage rates was also small and not significant (hazard ratio 1.36, 95% CI 0.63-2.93, P = 0.43). Premature birth was more frequent in exposed pregnancies (16.1% versus 8.5%; OR 2.1, 95% CI 1.1-3.8, P = 0.019). Nonetheless, median gestational age at birth (39 weeks, interquartile range [IQR] 37-40 versus 39 weeks, IQR 38-40, P = 0.27) and birth weight (3280 g, IQR 2835-3590 versus 3250 g, IQR 2880-3630, P = 0.95) did not differ between exposed and non-exposed pregnancies. CONCLUSIONS: This study did not detect a teratogenic effect of statins. Its statistical power remains insufficient to challenge current recommendations of treatment discontinuation during pregnancy.