A consensus approach for estimating health risk: Application to inhalation cancer risks.

Conducting a risk assessment is challenging because various and contrasting risk indicators are available, which can lead to discrepancies and, sometimes, conflicting conclusions. Constructing and using a consensus risk indicator (CRI) could provide a reliable alternative that is consistent and supports direct comparisons. The goal of this study is to propose a structured and pragmatic approach for constructing a CRI distribution and demonstrate its feasibility and easy implementation when conducting risk assessments. A CRI distribution is constructed as a weighted combination of existing indicators where the weights are obtained by using the overlapping areas of an individual indicator's distribution and an aggregated reference distribution. The approach is illustrated through an assessment of human cancer risk following inhalation exposure. The CRI is constructed using eight risk indicators. The CRI distribution parameters for 199 human carcinogenic chemicals associated with inhalation exposure were determined and are presented in an interactive table. To aid the wider implementation of the CRI approach, a user-friendly and interactive web application, named InCaRisk, was created to facilitate the cancer risk estimation following inhalation exposure. Our approach could be useful for enhancing the quality of regulatory decisions and protecting human health from environmental pollutants; our approach can be applied for a given health outcome, route of exposure and exposure setting.

Determining the binding parameters from co-sedimentation assays.

The stoichiometry n and the dissociation constant [Formula: see text] are key binding parameters characterizing the ligand-macromolecule interactions and equilibria. Equilibrium co-sedimentation experiments are performed in varying the concentration of one of the reactant while keeping constant that of the other reactant. The measured observable is the fraction [Formula: see text] of bound ligands when the ligand concentration is kept constant while that of macromolecules is varying whereas it is the macromolecule coverage [Formula: see text] with bound ligands when the ligand concentration is varying while that of macromolecules is kept constant. We have derived general expressions for [Formula: see text] and [Formula: see text] and subsequently showed that those expressions are in perfect agreement with simulations for a system of large ligands binding on macromolecules. Approximations have been developed to derive mathematical simple analytical expressions for [Formula: see text] and [Formula: see text] that can be used to fit the experimental data and thus extract, n and [Formula: see text] within the framework of equilibrium co-sedimentation assays. The method usefulness is illustrated and demonstrated by fitting the data from the literature using the derived formulas to determine the binding parameters.

Evaluation of In-House and Commercial Serological Tests for Diagnosis of Human Tularemia.

Tularemia is a zoonosis caused by the bacterium Francisella tularensis Its specific diagnosis remains based on serological methods, while F. tularensis is rarely detected in clinical samples by culture or PCR. The aim of the present study was to evaluate the performance of the Serion enzyme-linked immunosorbent assay (ELISA) classic Francisella tularensis IgG and IgM tests (Virion/Serion GmbH Institute, Würzburg, Germany) and the VIRapid tularemia immunochromatographic test (ICT) (Vircell, Granada, Spain) compared to that of the in-house microagglutination test (MAT) and indirect immunofluorescence assay (IFA) currently used at the French National Reference Center for Francisella We evaluated 256 consecutive sera from 208 patients, including 51 confirmed and 23 probable tularemia cases, and 134 control patients not infected with F. tularensis The IFA tests displayed 72.5% sensitivity for IgM (cutoff titer ≥80) and 74.5% for IgG (cutoff titer ≥160), and 99.3% specificity for both IgM and IgG. Using cutoffs advocated by the manufacturer, the Serion ELISAs displayed 88.2% sensitivity for IgM and 86.3% for IgG antibodies; specificity was 94.8% for IgM and 95.5% for IgG. Compared to MAT and IFA tests, the Serion ELISAs allowed earlier detection of specific antibodies (1 to 2 weeks versus 2 to 3 weeks after the onset of symptoms). The ICT sensitivity and specificity were 90% and 83.6%, respectively, when considering the cutoff advocated by the manufacturer. In conclusion, the Serion ELISAs are useful as screening tests for tularemia diagnosis, but additional confirmatory tests (such as MAT and IFA) are needed, especially in areas of low endemicity.

Urinary elimination kinetics of 3-hydroxybenzo(a)pyrene and 1-hydroxypyrene of workers in a prebake aluminum electrode production plant: Evaluation of diuresis correction methods for routine biological monitoring.

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous carcinogenic pollutants emitted in complex mixtures in the ambient air and contribute to the incidence of human cancers. Taking into account all absorption routes, biomonitoring is more relevant than atmospheric measurements to health risk assessment, but knowledge about how to use biomarkers is essential. In this work, urinary elimination kinetic of 1-hydroxypyrene (1-OHP) and 3-hydroxybenzo(a)pyrene (3-OHBaP) were studied in six electrometallurgy workers after PAHs exposure. Spot samples were collected on pre- and post-shift of the last workday then the whole urinations were separately sampled during the weekend. Non-linear mixed effects models were built to study inter- and intra-individual variability of both urinary metabolites toxicokinetic and investigate diuresis correction ways. Comparison of models confirmed the diuresis correction requirement to perform urinary biomonitoring of pyrene and BaP exposure. Urinary creatinine was found as a better way than specific gravity to normalize urinary concentrations of 1-OHP and as a good compromise for 3-OHBaP. Maximum observed levels were 1.0 µmol/mol creatinine and 0.8nmol/mol creatinine for 1-OHP and 3-OHBaP, respectively. Urinary 1-OHP concentrations on post-shift were higher than pre-shift for each subject, while 3-OHBaP levels were steady or decreased, and maximum urinary excretion rates of 3-OHBaP was delayed compared to 1-OHP. These results were consistent with the sampling time previously proposed for 3-OHBaP analysis, the next morning after exposure. Apparent urinary half-life of 1-OHP and 3-OHBaP ranged from 12.0h to 18.2h and from 4.8h to 49.5h, respectively. Finally, inter-individual variability of 1-OHP half-life seemed linked with the cutaneous absorption extent during exposure, while calculation of 3-OHBaP half-life required the awareness of individual urinary background level. The toxicokinetic modeling described here is an efficient tool which could be used to describe elimination kinetic and determine diuresis correction way for any other urinary biomarkers of chemicals or metals exposure.

Analytical correlation functions for motion through diffusivity landscapes.

Diffusion of a particle through an energy and diffusivity landscape is a very general phenomenon in numerous systems of soft and condensed matter. On the one hand, theoretical frameworks such as Langevin and Fokker-Planck equations present valuable accounts to understand these motions in great detail, and numerous studies have exploited these approaches. On the other hand, analytical solutions for correlation functions, as, e.g., desired by experimentalists for data fitting, are only available for special cases. We explore the possibility to use different theoretical methods in the specific picture of time-dependent switching between diffusive states to derive analytical functions that allow to link experimental and simulation results to theoretical calculations. In particular, we present a closed formula for diffusion switching between two states, as well as a general recipe of how to generalize the formula to multiple states.

Ranking occupational contexts associated with risk of non-Hodgkin lymphoma.

BACKGROUND: Risk factors associated with non-Hodgkin lymphoma (NHL) remain unknown, but certain occupational contexts (OCs) have been implicated. The objective of this study was to inventory, from the accumulated knowledge, associations between OCs and NHL risk. METHODS: Literature was used to identify the NHL-associated OCs. For each context, items were ranked both by scientific interest and the association strength. RESULTS: Three ranked lists of OCs related to NHL were constructed. We found that NHL was associated with 31 occupational activities, 91 occupational exposures, and 35 occupational activity-exposure combinations. Among them, 5 activities, 2 exposures, and 3 combinations, involving agricultural or industrial sector and solvents or pesticides, were highlighted with the highest publications number and the strongest association with NHL risk. CONCLUSION: These results could be useful in both providing a ranked inventory of OCs associated with NHL risk and highlighting "hot" occupational activities and exposures. Am. J. Ind. Med. 59:561-574, 2016. © 2016 Wiley Periodicals, Inc.

Size independence of statistics for boundary collisions of random walks and its implications for spin-polarized gases.

A bounded random walk exhibits strong correlations between collisions with a boundary. For a one-dimensional walk, we obtain the full statistical distribution of the number of such collisions in a time t. In the large t limit, the fluctuations in the number of collisions are found to be size independent (independent of the distance between boundaries). This occurs for any interboundary distance, from less to greater than the mean free path, and means that this boundary effect does not decay with increasing system size. As an application, we consider spin-polarized gases, such as 3-helium, in the three-dimensional diffusive regime. The above results mean that the depolarizing effect of rare magnetic impurities in the container walls is orders of magnitude larger than a Smoluchowski assumption (to neglect correlations) would imply. This could explain why depolarization is so sensitive to the container's treatment with magnetic fields prior to its use.

Calibration methodology of low-cost sensors for high-quality monitoring of fine particulate matter.

Low concentrations of pollutants may already be associated with significant health effects. An accurate assessment of individual exposure to pollutants therefore requires measuring pollutant concentrations at the finest possible spatial and temporal scales. Low-cost sensors (LCS) of particulate matter (PM) meet this need so well that their use is constantly growing worldwide. However, everyone agrees that LCS must be calibrated before use. Several calibration studies have already been published, but there is not yet a standardized and well-established methodology for PM sensors. In this work, we develop a method combining an adaptation of an approach developed for gas-phase pollutants with a dust event preprocessing to calibrate PM LCS (PMS7003) commonly used in urban environments. From the selection of outliers to model tuning and error estimation, the developed protocol allows to analyze, process and calibrate LCS data using multilinear (MLR) and random forest (RFR) regressions for comparison with a reference instrument. We demonstrate that the calibration performance was very good for PM1 and PM2.5 but turns out less good for PM10 (R2 = 0.94, RMSE = 0.55 µg/m3, NRMSE = 12 % for PM1 with MLR, R2 = 0.92, RMSE = 0.70 µg/m3, NRMSE = 12 % for PM2.5 with RFR and R2 = 0.54, RMSE = 2.98 µg/m3, NRMSE = 27 % for PM10 with RFR). Dust events removal significantly improved LCS accuracy for PM2.5 (11 % increase of R2 and 49 % decrease of RMSE) but no significant changes for PM1. Best calibration models included internal relative humidity and temperature for PM2.5 and only internal relative humidity for PM1. It turns out that PM10 cannot be properly measured and calibrated because of technical limitations of the PMS7003 sensor. This work therefore provides guidelines for PM LCS calibration. This represents a first step toward standardizing calibration protocols and facilitating collaborative research.

Modelling occupational inhalation exposure to concentration peaks of chemicals and associated health risk assessment.

OBJECTIVES: The aims of this study were to estimate inhalation exposure to chemicals and the resulting acute health risks for working scenarios characterized by successive peaks of pollutant concentrations. METHODS: A stochastic two-zone model combining a time-varying emission function and field-derived probabilistic distributed input parameter was used to predict both instantaneous and 15-min averaged pollutant concentrations during the decanting operations performed in a pathology laboratory. The location of the workers was taken into account in the model for computing probability distributions of inhalation exposures and for subsequently characterizing hazard quotients (HQ) for health risk purposes. The model was assessed by comparison with repeated individual monitoring performed on the workers during the same tasks. RESULTS: Modelled inhalation exposure profiles revealed 15-min average concentrations of 1.7 and 208 mg m(-) (3) for formaldehyde (FA) and toluene (TOL), respectively. The individual monitoring performed showed similar average concentrations, with 1.2 and 175 mg m(-) (3) for FA and TOL. No more than three to five successive FA concentration peaks were generally sufficient in the modelling exercise to provide 15-min estimated exposures exceeding short-term exposure limits (STEL). Modelled HQ higher than unity and STEL exceedance probabilities higher than 0.5 were found for FA, whereas estimated TOL health risks were notably lower according to high exposure limits. Estimated inhalation exposure distributions frequently ranged over one order of magnitude for the two pollutants, reflecting both the natural exposure variability and the uncertainty of some of the two-zone model input parameters. CONCLUSIONS: These findings indicate that the developed approach may be useful for modelling occupational exposures and acute health risks related to chemicals in situations involving time-varying emission sources. Modelled exposure distributions may also be used within Bayesian decision analysis frameworks for making exposure judgements and refining risk management measures.

Health risk assessment with multiple reference indices.

BACKGROUND: Conducting a risk assessment can be challenging, especially when dealing with several reference indices, which could lead to conflicting conclusions between studies. The common approach is to use a reference index from a single source based on the risk assessor's preference. OBJECTIVES: To propose an approach for constructing a multi-reference index-based aggregated risk estimate using mathematical objectivity to reflect all of the available information. METHODS: The aggregated risk estimate based on multiple reference indices (AREMRI) results from the weighted linear combination of risk distributions that were obtained with each reference index available. The weights were calculated using the degree of agreement among the reference index-based risk distributions. The approach is illustrated through three practical cases of benzene inhalation cancer risk assessment using inhalation unit risks (IURs) from six different regulatory agencies. RESULTS: The degrees of agreement between the reference index-based risk distribution, obtained with the six IURs, ranged from 0.7 to 92%. The highest weights were attributed to reference index-based risk distributions that had the highest degree of agreement with the maximum number of other reference index-based risk distributions. Regardless of the practical case considered, the AREMRI risk distribution resulted in the third highest risk compared to the six single risk distributions. CONCLUSION: Our approach can be useful in the presence of several reference indices by providing useful insights, consistency and direct comparisons between studies to support better-informed risk assessment and management decisions. This approach can shed some light on some of the uncertainties associated with the toxicological reference values in a risk assessment associated with the toxicological reference values. If the uncertainty is large, more detailed evaluation of the toxicological reference values would be needed.

Modelling of the transmission dynamics of carbapenem-resistant Klebsiella pneumoniae in hospitals and design of control strategies.

Carbapenem-resistant Klebsiella pneumoniae (CRKP) has emerged as a major threat to global public health. Epidemiological and infection controls associated with CRKP are challenging because of several potential elements involved in a complicated cycle of transmission. Here, we proposed a comprehensive mathematical model to investigate the transmission dynamics of CRKP, determine factors affecting the prevalence, and evaluate the impact of interventions on transmission. The model includes the essential compartments, which are uncolonized, asymptomatic colonized, symptomatic colonized, and relapsed patients. Additionally, symptomatic colonized and relapsed patients were further classified into subpopulations according to their number of treatment failures or relapses. We found that the admission of colonized patients and use of antibiotics significantly impacted the endemic transmission in health care units. Thus, we introduced the treatment efficacy, defined by combining the treatment duration and probability of successful treatment, to characterize and describe the effects of antibiotic treatment on transmission. We showed that a high antibiotic treatment efficacy results in a significantly reduced likelihood of patient readmission in the health care unit. Additionally, our findings demonstrate that CRKP transmission with different epidemiological characteristics must be controlled using distinct interventions.

Air pollution and health impacts during the COVID-19 lockdowns in Grenoble, France.

It is undeniable that exposure to outdoor air pollution impacts the health of populations and therefore constitutes a public health problem. Any actions or events causing variations in air quality have repercussions on populations' health. Faced with the worldwide COVID-19 health crisis that began at the end of 2019, the governments of several countries were forced, in the beginning of 2020, to put in place very strict containment measures that could have led to changes in air quality. While many works in the literature have studied the issue of changes in the levels of air pollutants during the confinements in different countries, very few have focused on the impact of these changes on health risks. In this work, we compare the 2020 period, which includes two lockdowns (March 16 - May 10 and a partial shutdown Oct. 30 - Dec. 15) to a reference period 2015-2019 to determine how these government-mandated lockdowns affected concentrations of NO2, O3, PM2.5, and PM10, and how that affected human health factors, including low birth weight, lung cancer, mortality, asthma, non-accidental mortality, respiratory, and cardiovascular illnesses. To this end, we structured 2020 into four periods, alternating phases of freedom and lockdowns characterized by a stringency index. For each period, we calculated (1) the differences in pollutant levels between 2020 and a reference period (2015-2019) at both background and traffic stations; and (2) the resulting variations in the epidemiological based relative risks of health outcomes. As a result, we found that relative changes in pollutant levels during the 2020 restriction period were as follows: NO2 (-32%), PM2.5 (-22%), PM10 (-15%), and O3 (+10.6%). The pollutants associated with the highest health risk reductions in 2020 were PM2.5 and NO2, while PM10 and O3 changes had almost no effect on health outcomes. Reductions in short-term risks were related to reductions in PM2.5 (-3.2% in child emergency room visits for asthma during the second lockdown) and NO2 (-1.5% in hospitalizations for respiratory causes). Long-term risk reductions related to PM2.5 were low birth weight (-8%), mortality (-3.3%), and lung cancer (-2%), and to NO2 for mortality (-0.96%). Overall, our findings indicate that the confinement period in 2020 resulted in a substantial improvement in air quality in the Grenoble area.

The dynamical Matryoshka model: 1. Incoherent neutron scattering functions for lipid dynamics in bilayers.

Fluid lipid bilayers are the building blocks of biological membranes. Although there is a large amount of experimental data using incoherent quasi-elastic neutron scattering (QENS) techniques to study membranes, very little theoretical works have been developed to study the local dynamics of membranes. The main objective of this work is to build a theoretical framework to study and describe the local dynamics of lipids and derive analytical expressions of intermediate scattering functions (ISF) for QENS. As results, we developed the dynamical Matryoshka model which describes the local dynamics of lipid molecules in membrane layers as a nested hierarchical convolution of three motional processes: (i) individual motions described by the vibrational motions of H-atoms; (ii) internal motions including movements of the lipid backbone, head groups and tails, and (iii) molecule movements of the lipid molecule as a whole. The analytical expressions of the ISF associated with these movements are all derived. For use in analyzing the QENS experimental data, we also derived an analytical expression for the aggregate ISF of the Matryoshka model which involves an elastic term plus three inelastic terms of well-separated time scales and whose amplitudes and rates are functions of the lipid motions. And as an illustrative application, we used the aggregated ISF to analyze the experimental QENS data on a lipid sample of multilamellar bilayers of DMPC (1,2-dimyristoyl-sn-glycero-3-phosphocholine). It is clear from this analysis that the dynamical Matryoshka model describes very well the experimental data and allow extracting the dynamical parameters of the studied system.

In vitro reconstitution of kallikrein-kinin system and progress curve analysis.

Human kallikrein-kinin system (KKS) is a proteolytic cascade with two serine-protease zymogen couples (Factor XII and prekallikrein (PK) and their activated forms, FXIIa, PKa, respectively), releasing bradykinin by cleavage of native high-molecular-weight kininogen (nHK) into cleaved HK. For KKS investigation in human plasma, this cascade is usually triggered on ice eventually by mixing with purified proteins. It has been established that purified FXIIa, PK, and nHK required a fixed order and timing for mixing protein on ice to ensure reproducibility of testing, we investigated the activation kinetics of both enzymes. The activation process of this in vitro minimal reconstitution of KKS was studied by progress curve analysis, in condition of high enzyme/substrate ratio and by using on natural rather than peptide substrates. FXIIa and PKa were found five-times less active on ice than at 37°C: kcat = 0.133 ± 0.034 and 0.0119 ± 0.0027 s-1, KM = 672 ± 150 and 115 ± 24 nM, respectively. The progress curve analysis of our in vitro KKS reconstitutions differed from a Michaelis-Menten mathematical simulation by a faster initial rate and a slower late rate. These two features were also observed ex vivo by using dextran sulfate-activated plasma and could reinforce the hypothesis of a maximal local effect (bradykinin release) and a minimal systemic consequence (PK preservation) in KKS activation process. Analyzing the complete curve of cold KKS activation would provide valuable information for ex vivo investigation of KKS in samples from patients presenting with hereditary angioedema and other inflammatory conditions.

Modeling of the combined dynamics of leptospirosis transmission and seroconversion in herds.

Leptospirosis is a zoonotic disease-causing illness in both humans and animals resulting in related economic impacts due to production loss as well as prevention and control efforts. Several mathematical models have been proposed to study the dynamics of infection but none of them has so far taken into account the dynamics of seroconversion. In this study, we have developed a general framework, based on the kinetic model for animal leptospirosis, that combines both the antibody (exposure marker) and infection dynamics to simultaneously follows both seroconversion and infection status of leptospirosis in a herd population. It is a stochastic compartmental model (for transition rates) with time delay (for seroconversion) which describes the progression of infection by a SEIRS (susceptible, exposed, infected, removed and susceptible) approach and seroconversion by four-state antibody kinetics (antibody negative and three antibody positive states of different antibody levels). The model shows that it is possible to assess and follow both seroconversion and infection status through the prism of diagnostic testing. Such an approach of combined kinetics could prove very useful to assist the competent authorities in their analyzes of epidemic situations and in the implementation of strategies for controlling and managing the associated risks.

The dynamical Matryoshka model: 3. Diffusive nature of the atomic motions contained in a new dynamical model for deciphering local lipid dynamics.

In accompanying papers [Bicout et al., BioRxiv https://doi.org/10.1101/2021.09.21.461198 (2021); Cissé et al., BioRxiv https://doi.org/10.1101/2022.03.30.486370 (2022)], a new model called Matryoshka model has been proposed to describe the geometry of atomic motions in phospholipid molecules in bilayers and multilamellar vesicles based on their quasielastic neutron scattering (QENS) spectra. Here, in order to characterize the relaxational aspects of this model, the energy widths of the QENS spectra of the samples were analyzed first in a model-free way. The spectra were decomposed into three Lorentzian functions, which are classified as slow, intermediate, and fast motions depending on their widths. The analysis provides the diffusion coefficients, residence times, and geometrical parameters for the three classes of motions. The results corroborate the parameter values such as the amplitudes and the mobile fractions of atomic motions obtained by the application of the Matryoshka model to the same samples. Since the current analysis was carried out independently of the development of the Matryoshka model, the present results enhance the validity of the model. The model will serve as a powerful tool to decipher the dynamics of lipid molecules not only in model systems, but also in more complex systems such as mixtures of different kinds of lipids or natural cell membranes.

The dynamical Matryoshka model: 2. Modeling of local lipid dynamics at the sub-nanosecond timescale in phospholipid membranes.

Biological membranes are generally formed by lipids and proteins. Often, the membrane properties are studied through model membranes formed by phospholipids only. They are molecules composed by a hydrophilic head group and hydrophobic tails, which can present a panoply of various motions, including small localized movements of a few atoms up to the diffusion of the whole lipid or collective motions of many of them. In the past, efforts were made to measure these motions experimentally by incoherent neutron scattering and to quantify them, but with upcoming modern neutron sources and instruments, such models can now be improved. In the present work, we expose a quantitative and exhaustive study of lipid dynamics on DMPC and DMPG membranes, using the Matryoshka model recently developed by our group. The model is confronted here to experimental data collected on two different membrane samples, at three temperatures and two instruments. Despite such complexity, the model describes reliably the data and permits to extract a series of parameters. The results compare also very well to other values found in the literature.

Population dynamics of a poultry hematophagous mite: characterization of the population growth and identification of factors of its slowdown using closed mesocosms.

BACKGROUND: A thorough knowledge of the population dynamics of pests and of the main factors affecting population growth is an important prerequisite for the development of effective control strategies. Failures of various treatments aimed at regulating populations of Dermanyssus gallinae are regularly reported in poultry farms and pullulations occur very quickly after first detection. To finely characterize population dynamics of D. gallinae, and to identify the factors modulating population growth, we conducted two successive multi-generation experiments using closed mesocosms equipped with or without automatic counters and housing a host full- or part-time (three nights per week). RESULTS: Population growth was very rapid and the adult to juvenile ratio very different from the prediction by a mathematical model. A male-biased sex ratio was observed in some mesocosms from 21 days and in most mesocosms from 35 days of population growth originating from an inoculum of adult females. A dramatic slowdown in growth was measured in mesocosms equipped with trackers, where the mites' path to the host was constrained. The slowdown in population growth induced by the intermittent presence of the host compared to its full-time presence was much less marked. CONCLUSION: These findings suggest avenues of research for new management methods. They question the relevance of a critical threshold based on traditional trap monitoring to manage D. gallinae. Our results highlight a unique characteristic of D. gallinae that makes it a recalcitrant case to threshold-based practices recommended for integrated pest management (IPM) against other arthropod pests. The dramatic effect of a physical constraint for the mite to access the host (unnatural constrained path) confirms an observation made in 1917 and is a reason to design perches that are less conducive to parasite traffic. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Occupational exposome: a network-based approach for characterizing Occupational Health Problems.

Surveillance of work-related diseases and associated exposures is a major issue of public health, in particular for identifying and preventing new threats for health. In the occupational health context, the French national occupational disease surveillance and prevention network (RNV3P) have constructed a growing database that records every year all Occupational Health Problems (OHPs) diagnosed by a network of physician specialists. The network aims to provide and develop an expertise on the disease-exposure relationships, and uses the RNV3P database for developing the surveillance of OHPs and for the detection of emerging associations between diseases and occupational exposures. In this paper, we have developed the theoretical framework of the occupational exposome, defined as a network of OHPs linked by similar occupational exposures, as a novel approach which allows to characterize and to analyze the disease-exposure associations reported in the RNV3P database in the form of a relational network. Next, the occupational exposome is structured in terms of occupational exposure groups which constitute informative sub-sets of hazards considered as the backbone tree spectrum of the occupational exposures potentially related to a disease. To illustrate the wide possibilities of this method, the exposome approach is applied to the RNV3P database's sample of Non-Hodgkin Lymphomas (NHLs). As a result, we found that the NHL occupational exposome could be described in terms of 86 embedded exposure groups, defined as a set of OHPs sharing at least one component of the occupational multi-exposure. For example, "organic solvents and thinners" is the most represented hazards related to NHLs, but is also co-associated to "benzene", "ionizing radiations" or "agricultural products". From the knowledge stored in the database by physician experts, the occupational exposome constitutes a decisive step towards the evolving monitoring of multi-exposure associated to a given disease.

Theoretical formulation for mosquito host-feeding patterns: application to a West Nile virus focus of southern France.

Host-feeding patterns play a key role in the transmission of vector-borne diseases such as West Nile fever, which involves two kinds of vertebrates, birds and mammals. In this study, we propose a theoretical formulation for mosquito host-feeding patterns using three quantities, as follows: the apparent attractiveness/contact probabilities, the conditional host(-feeding) preferences, and the enzootic versus bridge probabilities. Using results from host-baited trap collections, the quantities defined above were assessed for the most abundant mosquito species in the main West Nile virus focus of southern France. We found that host availability is important in determining the efficiency of bridge vectors, and that even ornithophilic mosquitoes like Culex species, classically classified as enzootic vectors, may turn out to be efficient bridge vectors in certain contexts of host abundance. Our developed theoretical framework can easily be adapted and applied to other experimental data and other vector-borne diseases.