Search

Abstract Background As discontinuation in in vitro fertilization (IVF) programs has been associated with a poor prognosis, one hypothesis is that some couple-specific predictive factors in IVF may be shared with opposite effect by both success (i.e. live birth) and treatment discontinuation processes. Our objective was to perform a joint analysis of these two processes to examine the hypothesis of a link between the two processes. Methods Analyses were conducted on a retrospective cohort of 3,002 women who began IVF between 1998 and 2002 in two French IVF centers: a Parisian center and a center in a medium-sized city in central France. A shared random effects model based on a joint modelization of IVF treatment success and discontinuation was used to study the link between the two processes. Results Success and discontinuation processes were significantly linked in the medium-sized city center, whereas they were not linked in the Parisian center. The center influenced risk of treatment discontinuation but not chance of success. The well-known inverse-J relation between the woman’s age and chance of success was observed, as expected. Risk of discontinuation globally increased as the woman’s age increased. Conclusions The link between success and discontinuation processes could depend on the fertility center. In particular, the woman’s decision to pursue or to discontinue IVF in a particular center could depend on the presence of other IVF centers in the surrounding area.

Objective: A recent update of the French cohort of uranium miners added seven years of follow-up data. We use these new data to look for new possible radon-related increased risks and refine the estimation of the potential association between cumulative radon exposure and four cancer sites: lung cancer, kidney cancer, brain and central nervous system (CNS) cancer and leukemia (excluding chronic lymphocytic leukemia, which is not radiation-induced)., Methods: Several parametric survival models are proposed, fitted and compared under the Bayesian paradigm, to perform new and original exposure-risk analyses. In line with recent UNSCEAR recommendations, we consider time-related effect modifiers and exposure rate as potential effect modifying factors. We use Bayesian model selection criteria to identify radon-related increased hazard rates., Results: Under the assumption of a linear exposure-risk relationship, we found a substantial evidence for a strictly positive effect of cumulative radon exposure on the hazard rate of death by lung cancer among French uranium miners. Given the current available data under the assumptions of a linear or log-linear exposure-risk relationship, it is not possible to conclude in favour of the absence or the existence of a strictly positive effect of chronic exposure to radon on the hazard rate of death by kidney cancer. Regarding death by brain and CNS cancer, there is a substantial evidence for the absence of radon-related effect. Finally, under the assumption of a log-linear exposure-risk relationship, a small positive radon-related effect appears when looking at the risk of death by leukemia (excluding CLL)., Conclusion: This study investigates the existence of radon-related increased risk of death by lung cancer, kidney cancer, brain and CNS cancer and leukemia under a Bayesian framework and assumptions of linear and log-linear exposure-risk relationships. If there is no doubt in the interpretation of the results for lung cancer and brain and CNS cancer, the conclusion is less clear-cut in the case of kidney cancer and leukemia (excluding CLL). A future update of the French cohort, increasing the follow-up time for miners, may help to reach a clearer conclusion for these two cancer sites., Competing Interests: Declarations Conflict of interest All the authors declare no Conflict of interest. Ethics approval and consent to participate This study is approved by the Advisory Committee on Information Processing in Health Research (CCTIRS) of the Ministry of Higher Education and Research (protocol code 11.374, approved 16 June 2011) and by the French Data Protection Authority (Commission Nationale de l’Informatique et des Libertés, CNIL) (authorization DR-2012-611, 16 December 2012). Consent for publication Not applicable., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Context: Public interest for citizen science (CS) in environmental health is growing. The goals of environmental health research projects are diverse, as are the methods used to reach these goals. Opportunities for greater implication of the civil society and related challenges differ at each step of such projects. These methodological aspects need to be widely shared and understood by all stakeholders. The LILAS initiative (acronym for "application of citizen science approaches such as LIving LAbS to research on environmental exposures and chronic risks") aimed to 1) favor a mutual understanding of the main issues and research methods in environmental health, of their stakes for different actors, but also of the requirements, strengths and limitations of these methods and to 2) identify expected benefits and points of attention related to stronger degrees of participation as part of environmental health research projects., Methods: The LILAS initiative gathered institutional researchers, academics and civil society representatives interested in environmental exposures. Five meetings allowed to collectively identify different types of environmental health research studies and reflect about the benefits, limitations, and methodological issues related to the introduction of growing citizen participation as part of such studies. An analytic table matrix summarizing these aspects was co-created and filled by participants, as a tool devoted to help stakeholders with the definition of future CS research projects in environmental health., Results: For different fields of research (e.g.: studies for assessment of environmental exposures, interventions on these exposures, quantitative risk assessment, epidemiological studies), the matrix lists expected benefits for various stakeholders, the fundamental principles of research methods and related practical constraints, but also advantages and limitations related to the use of CS or conventional research approaches., Conclusion: The LILAS initiative allowed to develop a tool which provides consolidated grounds for the co-creation of research projects on environmental exposures involving CS., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: Increased risks of central nervous system (CNS) tumors and leukemia associated with computed tomography (CT) exposure during childhood have been reported in recent epidemiological studies. However, no evidence of increased risks was suggested in a previous analysis of the French CT cohort. This study benefits from an updated cohort with a longer follow-up and a larger sample size of patients., Methods: The patients were followed from the date of their first CT (between 2000 and 2011) until their date of cohort exit defined as the earliest among the following: 31 December 2016, date of death, date of first cancer diagnosis or date of their 18 th birthday. Cancer incidence, vital status, cancer predisposing factors (PFs), and additional CT scans were collected via external national databases. Hazard ratios (HRs) associated to cumulative organ doses and sex were estimated from Cox models., Results: At the end of follow-up, mean cumulative doses were 27.7 and 10.3 mGy for the brain and the red bone marrow (RBM), respectively. In patients without PFs, an HR per 10 mGy of 1.05 (95% CI: 1.01-1.09) for CNS tumors, 1.17 (95% CI: 1.09-1.26) for leukemia, and 0.96 (95% CI: 0.63-1.45) for lymphoma was estimated. These estimates were not modified by the inclusion of CT scans performed outside the participating hospitals or after the inclusion period., Conclusions: This study shows statistically significant dose-response relationships for CNS tumors and leukemia for patients without PFs., Key Points: • Computed tomography is the most important contributor to the collective dose for diagnostic imaging to the French population. • Concerns have been raised about possible cancer risks, particularly after exposure to CT in childhood, due to the greater radiation sensitivity of children and to their longer life expectancy. • Analysis of the updated French CT cohort shows statistically significant dose-response relationships for CNS tumors and leukemia., (© 2022. The Author(s), under exclusive licence to European Society of Radiology.)

Complement C1q is a multifunctional protein able to sense pathogens and immune molecules such as immunoglobulins and pentraxins, and to trigger the classical complement pathway through activation of its two associated proteases, C1r and C1s. C1q is a multimeric protein composed of three homologous yet distinct polypeptide chains A, B, and C, each composed of an N-terminal collagen-like sequence and a C-terminal globular gC1q module, that assemble into six heterotrimeric (A-B-C) subunits. This hexameric structure exhibits the characteristic shape of a bouquet of flowers, comprising six collagen-like triple helices, each terminating in a trimeric C-terminal globular head. We have produced previously functional recombinant full-length C1q in stably transfected HEK 293-F cells, with a FLAG tag inserted at the C-terminal end of C1qC chain. We report here the generation of additional recombinant C1q proteins, with a FLAG tag fused to the C-terminus of C1qA or C1qB chains, or to the N-terminus of the C1qC chain. Two other variants harboring a Myc or a 6-His tag at the C-terminal end of C1qC were also produced. We show that all C1q variants, except for the His-tagged protein, can be produced at comparable yields and are able to bind with similar affinities to either IgM, a ligand of the globular regions, or to the C1r 2 -C1s 2 tetramer, and to trigger IgM-mediated serum complement activation. These new recombinant C1q variants provide additional tools to investigate the multiple functions of C1q., (Copyright © 2021 Elsevier B.V. All rights reserved.)

As multifactorial and chronic diseases, cancers are among these pathologies for which the exposome concept is essential to gain more insight into the associated etiology and, ultimately, lead to better primary prevention strategies for public health. Indeed, cancers result from the combined influence of many genetic, environmental and behavioral stressors that may occur simultaneously and interact. It is thus important to properly account for multifactorial exposure patterns when estimating specific cancer risks at individual or population level. Nevertheless, the risk factors, especially environmental, are still too often considered in isolation in epidemiological studies. Moreover, major statistical difficulties occur when exposures to several factors are highly correlated due, for instance, to common sources shared by several pollutants. Suitable statistical methods must then be used to deal with these multicollinearity issues. In this work, we focused on the specific problem of estimating a disease risk from highly correlated environmental exposure covariates and a censored survival outcome. We extended Bayesian profile regression mixture (PRM) models to this context by assuming an instantaneous excess hazard ratio disease sub-model. The proposed hierarchical model incorporates an underlying truncated Dirichlet process mixture as an attribution sub-model. A specific adaptive Metropolis-Within-Gibbs algorithm-including label switching moves-was implemented to infer the model. This allows simultaneously clustering individuals with similar risks and similar exposure characteristics and estimating the associated risk for each group. Our Bayesian PRM model was applied to the estimation of the risk of death by lung cancer in a cohort of French uranium miners who were chronically and occupationally exposed to multiple and correlated sources of ionizing radiation. Several groups of uranium miners with high risk and low risk of death by lung cancer were identified and characterized by specific exposure profiles. Interestingly, our case study illustrates a limit of MCMC algorithms to fit full Bayesian PRM models even if the updating schemes for the cluster labels incorporate label-switching moves. Then, although this paper shows that Bayesian PRM models are promising tools for exposome research, it also opens new avenues for methodological research in this class of probabilistic models., (Copyright © 2020 Belloni, Laurent, Guihenneuc and Ancelet.)

Nanodiamonds are promising nanomedicines for diagnostic and therapeutic applications. As nanodiamonds are mainly administered intravenously, it is critical to understand the humoral immune response upon exposure to nanodiamonds. Here, we report the interactions of pristine, oxidized, and PEG-functionalized nanodiamonds with human complement, an important part of our humoral innate immunity. In particular, we report the nanodiamond binding properties of the recognition protein of the classical complement pathway: C1q, which also takes part in many other physiological and pathological processes. Our results show similar trends in the effects of C1q on the three types of nanodiamonds. Complement activation assays using human serum show that the nanodiamonds trigger slight activities via the alternative pathway and no response via the classical pathway. Nevertheless, surface plasmon resonance shows that C1q binds the nanodiamonds and transmission electron microscopy reveals their agglutination. Studies with macrophages further show that C1q attachment affects their phagocytosis and cytokine response., (Copyright © 2018. Published by Elsevier Inc.)

Exposure measurement error can be seen as one of the most important sources of uncertainty in studies in epidemiology. When the aim is to assess the effects of measurement error on statistical inference or to compare the performance of several methods for measurement error correction, it is indispensable to be able to generate different types of measurement error. This paper compares two approaches for the generation of Berkson error, which have recently been applied in radiation epidemiology, in their ability to generate exposure data that satisfy the properties of the Berkson model. In particular, it is shown that the use of one of the methods produces results that are not in accordance with two important properties of Berkson error.

Exposure measurement error represents one of the most important sources of uncertainty in epidemiology. When exposure uncertainty is not or only poorly accounted for, it can lead to biased risk estimates and a distortion of the shape of the exposure-response relationship. In occupational cohort studies, the time-dependent nature of exposure and changes in the method of exposure assessment may create complex error structures. When a method of group-level exposure assessment is used, individual worker practices and the imprecision of the instrument used to measure the average exposure for a group of workers may give rise to errors that are shared between workers, within workers or both. In contrast to unshared measurement error, the effects of shared errors remain largely unknown. Moreover, exposure uncertainty and magnitude of exposure are typically highest for the earliest years of exposure. We conduct a simulation study based on exposure data of the French cohort of uranium miners to compare the effects of shared and unshared exposure uncertainty on risk estimation and on the shape of the exposure-response curve in proportional hazards models. Our results indicate that uncertainty components shared within workers cause more bias in risk estimation and a more severe attenuation of the exposure-response relationship than unshared exposure uncertainty or exposure uncertainty shared between individuals. These findings underline the importance of careful characterisation and modeling of exposure uncertainty in observational studies.

Polydiacetylene (pDA) micelles have been demonstrated to be effective drug carriers for cancer therapy in mouse model. However, little is known about their interaction with the human complement system, which constitutes an important part of the innate immune system and can cause severe hypersensitivity reactions. Herein, we investigate the influence of micelle surface charge on the binding of complement protein C1q, the target recognition unit that activates the classical complement pathway and performs a range of other important physiological functions. Besides the classical pathway, we also investigate the surface charge effect on complement activities through the other activation pathways, namely, the MBL-dependent lectin pathway and the alternative pathway. We synthesized three samples of pDA micelles bearing neutral, anionic, and cationic surface charge motifs, respectively. Surface plasmon resonance showed that none of these micelles interacted with C1q. Results from serum complement activation assays indicated that all micelles were inert to complement, except for the anionic pDA micelles, which activated the alternative pathway., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Surface modification of nanoparticles with poly(ethylene glycol) (PEG) is used in biomedicine to increase the circulation time of the particles after intravenous injection. Here, we study the interaction of PEG-covered carbon nanotubes (CNTs) with the serum complement protein C1q. Besides being the target-recognizing unit of the initiating complex for the classical pathway of complement in our innate immune system, C1q is involved in a range of important physiological processes. We modified the surface of multiwalled CNTs with covalently grafted PEG and physically adsorbed PEG. Transmission electron microscopy revealed the interaction of these PEG-coated CNTs with C1q. We found abundant C1q coverage on the PEG-grafted CNTs but not on the CNTs with adsorbed PEG. We tested the ability of these CNTs to activate the complement system using in vitro complement activation assays. None of the CNTs studied activated the C1q-dependent classical complement pathway. These findings are pertinent to the safe design and novel biomedical applications of PEGylated CNTs.

Anemia is a frequent cytopenia in myelodysplastic syndromes (MDS) and most patients require red blood cell transfusion resulting in iron overload (IO). Deferasirox (DFX) has become the standard treatment of IO in MDS and it displays positive effects on erythropoiesis. In low risk MDS samples, mechanisms improving erythropoiesis after DFX treatment remain unclear. Herein, we addressed this question by using liquid cultures with iron overload of erythroid precursors treated with low dose of DFX (3μM), which corresponds to DFX 5 mg/kg/day, an unusual dose used for iron chelation. We highlight a decreased apoptosis rate and an increased proportion of cycling cells, both leading to higher proliferation rates. The iron chelation properties of low dose DFX failed to activate the Iron Regulatory Proteins and to support iron depletion, but low dose DFX dampers intracellular reactive oxygen species. Furthermore low concentrations of DFX activate the NF-κB pathway in erythroid precursors triggering anti-apoptotic and anti-inflammatory signals. Establishing stable gene silencing of the Thioredoxin (TRX) 1 genes, a NF-κB modulator, showed that fine-tuning of reactive oxygen species (ROS) levels regulates NF-κB. These results justify a clinical trial proposing low dose DFX in MDS patients refractory to erythropoiesis stimulating agents., Competing Interests: CONFLICTS OF INTEREST Sophie Park: research funding by Novartis. The remaining authors declare no conflicts of interest.

Many occupational cohort studies on underground miners have demonstrated that radon exposure is associated with an increased risk of lung cancer mortality. However, despite the deleterious consequences of exposure measurement error on statistical inference, these analyses traditionally do not account for exposure uncertainty. This might be due to the challenging nature of measurement error resulting from imperfect surrogate measures of radon exposure. Indeed, we are typically faced with exposure uncertainty in a time-varying exposure variable where both the type and the magnitude of error may depend on period of exposure. To address the challenge of accounting for multiplicative and heteroscedastic measurement error that may be of Berkson or classical nature, depending on the year of exposure, we opted for a Bayesian structural approach, which is arguably the most flexible method to account for uncertainty in exposure assessment. We assessed the association between occupational radon exposure and lung cancer mortality in the French cohort of uranium miners and found the impact of uncorrelated multiplicative measurement error to be of marginal importance. However, our findings indicate that the retrospective nature of exposure assessment that occurred in the earliest years of mining of this cohort as well as many other cohorts of underground miners might lead to an attenuation of the exposure-risk relationship. More research is needed to address further uncertainties in the calculation of lung dose, since this step will likely introduce important sources of shared uncertainty.

The potential health impacts of chronic exposures to uranium, as they occur in occupational settings, are not well characterized. Most epidemiological studies have been limited by small sample sizes, and a lack of harmonization of methods used to quantify radiation doses resulting from uranium exposure. Experimental studies have shown that uranium has biological effects, but their implications for human health are not clear. New studies that would combine the strengths of large, well-designed epidemiological datasets with those of state-of-the-art biological methods would help improve the characterization of the biological and health effects of occupational uranium exposure. The aim of the European Commission concerted action CURE (Concerted Uranium Research in Europe) was to develop protocols for such a future collaborative research project, in which dosimetry, epidemiology and biology would be integrated to better characterize the effects of occupational uranium exposure. These protocols were developed from existing European cohorts of workers exposed to uranium together with expertise in epidemiology, biology and dosimetry of CURE partner institutions. The preparatory work of CURE should allow a large scale collaborative project to be launched, in order to better characterize the effects of uranium exposure and more generally of alpha particles and low doses of ionizing radiation.

Uncertainty on the parameters that describe the transfer of radioactive materials into the (terrestrial) environment may be characterized thanks to datasets such as those compiled within International Atomic Energy Agency (IAEA) documents. Nevertheless, the information included in these documents is too poor to derive a relevant and informative uncertainty distribution regarding dry interception of radionuclides by the pasture grass and the leaves of vegetables. In this paper, 145 sets of dry interception measurements by the aboveground biomass of specific plants were collected from published scientific papers. A Bayesian meta-analysis was performed to derive the posterior probability distributions of the parameters that reflect their uncertainty given the collected data. Four competing models were compared in terms of both fitting performances and predictive abilities to reproduce plausible dry interception data. The asymptotic interception factor, applicable whatever the species and radionuclide to the highest aboveground biomass values (e.g. mature leafy vegetables), was estimated with the best model, to be 0.87 with a 95% credible interval (0.85, 0.89)., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

The investigation of potential adverse health effects of occupational exposures to ionizing radiation, on uranium miners, is an important area of research. Radon is a well-known carcinogen for lung, but the link between radiation exposure and other diseases remains controversial, particularly for kidney cancer. The aims of this study were therefore to perform external kidney cancer mortality analyses and to assess the relationship between occupational radiation exposure and kidney cancer mortality, using competing risks methodology, from two uranium miners cohorts. The French (n = 3,377) and German (n = 58,986) cohorts of uranium miners included 11 and 174 deaths from kidney cancer. For each cohort, the excess of kidney cancer mortality has been assessed by standardized mortality ratio (SMR) corrected for the probability of known causes of death. The associations between cumulative occupational radiation exposures (radon, external gamma radiation and long-lived radionuclides) or kidney equivalent doses and both the cause-specific hazard and the probability of occurrence of kidney cancer death have been estimated with Cox and Fine and Gray models adjusted to date of birth and considering the attained age as the timescale. No significant excess of kidney cancer mortality has been observed neither in the French cohort (SMR = 1.49, 95 % confidence interval [0.73; 2.67]) nor in the German cohort (SMR = 0.91 [0.77; 1.06]). Moreover, no significant association between kidney cancer mortality and any type of occupational radiation exposure or kidney equivalent dose has been observed. Future analyses based on further follow-up updates and/or large pooled cohorts should allow us to confirm or not the absence of association.

The potential adverse effects associated with exposure to ionizing radiation from computed tomography (CT) in pediatrics must be characterized in relation to their expected clinical benefits. Additional epidemiological data are, however, still awaited for providing a lifelong overview of potential cancer risks. This paper gives predictions of potential lifetime risks of cancer incidence that would be induced by CT examinations during childhood in French routine practices in pediatrics. Organ doses were estimated from standard radiological protocols in 15 hospitals. Excess risks of leukemia, brain/central nervous system, breast and thyroid cancers were predicted from dose-response models estimated in the Japanese atomic bomb survivors' dataset and studies of medical exposures. Uncertainty in predictions was quantified using Monte Carlo simulations. This approach predicts that 100,000 skull/brain scans in 5-year-old children would result in eight (90 % uncertainty interval (UI) 1-55) brain/CNS cancers and four (90 % UI 1-14) cases of leukemia and that 100,000 chest scans would lead to 31 (90 % UI 9-101) thyroid cancers, 55 (90 % UI 20-158) breast cancers, and one (90 % UI <0.1-4) leukemia case (all in excess of risks without exposure). Compared to background risks, radiation-induced risks would be low for individuals throughout life, but relative risks would be highest in the first decades of life. Heterogeneity in the radiological protocols across the hospitals implies that 5-10 % of CT examinations would be related to risks 1.4-3.6 times higher than those for the median doses. Overall excess relative risks in exposed populations would be 1-10 % depending on the site of cancer and the duration of follow-up. The results emphasize the potential risks of cancer specifically from standard CT examinations in pediatrics and underline the necessity of optimization of radiological protocols.

Complement C1q is a hexameric molecule assembled from 18 polypeptide chains of three different types encoded by three genes. This versatile recognition protein senses a wide variety of immune and nonimmune ligands, including pathogens and altered self components, and triggers the classical complement pathway through activation of its associated proteases C1r and C1s. We report a method for expression of recombinant full-length human C1q involving stable transfection of HEK 293-F mammalian cells and fusion of an affinity tag to the C-terminal end of the C chain. The resulting recombinant (r) C1q molecule is similar to serum C1q as judged from biochemical and structural analyses and exhibits the characteristic shape of a bunch of flowers. Analysis of its interaction properties by surface plasmon resonance shows that rC1q retains the ability of serum C1q to associate with the C1s-C1r-C1r-C1s tetramer, to recognize physiological C1q ligands such as IgG and pentraxin 3, and to trigger C1r and C1s activation. Functional analysis of rC1q variants carrying mutations of LysA59, LysB61, and/or LysC58, in the collagen-like stems, demonstrates that LysB61 and LysC58 each play a key role in the interaction with C1s-C1r-C1r-C1s, with LysA59 being involved to a lesser degree. We propose that LysB61 and LysC58 both form salt bridges with outer acidic Ca(2+) ligands of the C1r and C1s CUB (complement C1r/C1s, Uegf, bone morphogenetic protein) domains. The expression method reported here opens the way for deciphering the molecular basis of the unusual binding versatility of C1q by mapping the residues involved in the sensing of its targets and the binding of its receptors.

Previous epidemiological studies and quantitative risk assessments (QRA) have suggested that natural background radiation may be a cause of childhood leukemia. The present work uses a QRA approach to predict the excess risk of childhood leukemia in France related to three components of natural radiation: radon, cosmic rays and terrestrial gamma rays, using excess relative and absolute risk models proposed by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). Both models were developed from the Life Span Study (LSS) of Japanese A-bomb survivors. Previous risk assessments were extended by considering uncertainties in radiation-related leukemia risk model parameters as part of this process, within a Bayesian framework. Estimated red bone marrow doses cumulated during childhood by the average French child due to radon, terrestrial gamma and cosmic rays are 4.4, 7.5 and 4.3 mSv, respectively. The excess fractions of cases (expressed as percentages) associated with these sources of natural radiation are 20 % [95 % credible interval (CI) 0-68 %] and 4 % (95 % CI 0-11 %) under the excess relative and excess absolute risk models, respectively. The large CIs, as well as the different point estimates obtained under these two models, highlight the uncertainties in predictions of radiation-related childhood leukemia risks. These results are only valid provided that models developed from the LSS can be transferred to the population of French children and to chronic natural radiation exposures, and must be considered in view of the currently limited knowledge concerning other potential risk factors for childhood leukemia. Last, they emphasize the need for further epidemiological investigations of the effects of natural radiation on childhood leukemia to reduce uncertainties and help refine radiation protection standards.

The Monte Carlo (MC) simulation approach is traditionally used in food safety risk assessment to study quantitative microbial risk assessment (QMRA) models. When experimental data are available, performing Bayesian inference is a good alternative approach that allows backward calculation in a stochastic QMRA model to update the experts' knowledge about the microbial dynamics of a given food-borne pathogen. In this article, we propose a complex example where Bayesian inference is applied to a high-dimensional second-order QMRA model. The case study is a farm-to-fork QMRA model considering genetic diversity of Bacillus cereus in a cooked, pasteurized, and chilled courgette purée. Experimental data are Bacillus cereus concentrations measured in packages of courgette purées stored at different time-temperature profiles after pasteurization. To perform a Bayesian inference, we first built an augmented Bayesian network by linking a second-order QMRA model to the available contamination data. We then ran a Markov chain Monte Carlo (MCMC) algorithm to update all the unknown concentrations and unknown quantities of the augmented model. About 25% of the prior beliefs are strongly updated, leading to a reduction in uncertainty. Some updates interestingly question the QMRA model., (© 2012 Society for Risk Analysis.)

Complement receptor type 1 (CR1) is a membrane receptor expressed on a wide range of cells. It is involved in immune complex clearance, phagocytosis, and complement regulation. Its ectodomain is composed of 30 complement control protein (CCP) modules, organized into four long homologous repeats (A-D). In addition to its main ligands C3b and C4b, CR1 was reported to interact with C1q and mannan-binding lectin (MBL) likely through its C-terminal region (CCP22-30). To decipher the interaction of human CR1 with the recognition proteins of the lectin complement pathway, a recombinant fragment encompassing CCP22-30 was expressed in eukaryotic cells, and its interaction with human MBL and ficolins was investigated using surface plasmon resonance spectroscopy. MBL and L-ficolin were shown to interact with immobilized soluble CR1 and CR1 CCP22-30 with apparent dissociation constants in the nanomolar range, indicative of high affinity. The binding site for CR1 was located at or near the MBL-associated serine protease (MASP) binding site in the collagen stalks of MBL and L-ficolin, as shown by competition experiments with MASP-3. Accordingly, the mutation of an MBL conserved lysine residue essential for MASP binding (K55) abolished binding to soluble CR1 and CCP22-30. The CR1 binding site for MBL/ficolins was mapped to CCP24-25 of long homologous repeat D using deletion mutants. In conclusion, we show that ficolins are new CR1 ligands and propose that MBL/L-ficolin binding involves major ionic interactions between conserved lysine residues of their collagen stalks and surface exposed acidic residues located in CR1 CCP24 and/or CCP25.

When analyzing the geographical variations of disease risk, one common problem is data sparseness. In such a setting, we investigate the possibility of using Bayesian shared spatial component models to strengthen inference and correct for any spatially structured sources of bias, when distinct data sources on one or more related diseases are available. Specifically, we apply our models to analyze the spatial variation of risk of two forms of scrapie infection affecting sheep in Wales (UK) using three surveillance sources on each disease. We first model each disease separately from the combined data sources and then extend our approach to jointly analyze diseases and data sources. We assess the predictive performances of several nested joint models through pseudo cross-validatory predictive model checks., (© Crown copyright 2011.)

Variants of the human C1 inhibitor serpin domain containing three N-linked carbohydrates at positions 216, 231, and 330 (C1inhDelta97), a single carbohydrate at position 330 (C1inhDelta97DM), or no carbohydrate were produced in a baculovirus/insect cells system. An N-terminally His-tagged C1inhDelta97 variant was also produced. Removal of the oligosaccharide at position 330 dramatically decreased expression, precluding further analysis. All other variants were characterized chemically and shown to inhibit C1s activity and C1 activation in the same way as native C1 inhibitor. Likewise, they formed covalent complexes with C1s as shown by SDS-PAGE analysis. C1 inhibitor and its variants inhibited the ability of C1r-like protease to activate C1s, but did not form covalent complexes with this protease. The interaction of C1 inhibitor and its variants with heparin was investigated by surface plasmon resonance, yielding K(D) values of 16.7 x 10(-8) M (C1 inhibitor), 2.3 x 10(-8) M (C1inhDelta97), and 3.6 x 10(-8) M (C1inhDelta97DM). C1s also bound to heparin, with lower affinity (K(D) = 108 x 10(-8) M). Using the same technique, 50% inhibition of the binding of C1 inhibitor and C1s to heparin was achieved using heparin oligomers containing eight and six saccharide units, respectively. These values roughly correlate with the size of 10 saccharide units yielding half-maximal potentiation of the inhibition of C1s activity by C1 inhibitor, consistent with a "sandwich" mechanism. Using a thermal shift assay, heparin was shown to interact with the C1s serine protease domain and the C1 inhibitor serpin domain, increasing and decreasing their thermal stability, respectively.

We introduce a new Bayesian clustering algorithm for studying population structure using individually geo-referenced multilocus data sets. The algorithm is based on the concept of hidden Markov random field, which models the spatial dependencies at the cluster membership level. We argue that (i) a Markov chain Monte Carlo procedure can implement the algorithm efficiently, (ii) it can detect significant geographical discontinuities in allele frequencies and regulate the number of clusters, (iii) it can check whether the clusters obtained without the use of spatial priors are robust to the hypothesis of discontinuous geographical variation in allele frequencies, and (iv) it can reduce the number of loci required to obtain accurate assignments. We illustrate and discuss the implementation issues with the Scandinavian brown bear and the human CEPH diversity panel data set.