Citizen science in environmental health research: A comparison with conventional approaches and creation of a guidance tool issued from the LILAS initiative.

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.

A Gradient-Descent Optimization of CO2-CO-NOx Emissions over the Paris Megacity─The Case of the First SARS-CoV-2 Lockdown.

Urban greenhouse gas emissions monitoring is essential to assessing the impact of climate mitigation actions. Using atmospheric continuous measurements of air quality and carbon dioxide (CO2), we developed a gradient-descent optimization system to estimate emissions of the city of Paris. We evaluated our joint CO2-CO-NOx optimization over the first SARS-CoV-2 related lockdown period, resulting in a decrease in emissions by 40% for NOx and 30% for CO2, in agreement with preliminary estimates using bottom-up activity data yet lower than the decrease estimates from Bayesian atmospheric inversions (50%). Before evaluating the model, we first provide an in-depth analysis of three emission data sets. A general agreement in the totals is observed over the region surrounding Paris (known as Île-de-France) since all the data sets are constrained by the reported national and regional totals. However, the data sets show disagreements in their sector distributions as well as in the interspecies ratios. The seasonality also shows disagreements among emission products related to nonindustrial stationary combustion (residential and tertiary combustion). The results presented in this paper show that a multispecies approach has the potential to provide sectoral information to monitor CO2 emissions over urban areas enabled by the deployment of collocated atmospheric greenhouse gases and air quality monitoring stations.

The development of a rapid patient-derived xenograft model to predict chemotherapeutic drug sensitivity/resistance in malignant glial tumors.

BACKGROUND: High-grade gliomas (HGG) are aggressive brain tumors associated with short median patient survival and limited response to therapies, driving the need to develop tools to improve patient outcomes. Patient-derived xenograft (PDX) models, such as mouse PDX, have emerged as potential Avatar platforms for personalized oncology approaches, but the difficulty for some human grafts to grow successfully and the long time required for mice to develop tumors preclude their use for HGG. METHODS: We used a rapid and efficient ex-ovo chicken embryo chorioallantoic membrane (CAM) culture system to evaluate the efficacy of oncologic drug options for HGG patients. RESULTS: Implantation of fresh glioma tissue fragments from 59 of 60 patients, that include difficult-to-grow IDH-mutated samples, successfully established CAM tumor xenografts within 7 days, with a tumor take rate of 98.3%. These xenografts faithfully recapitulate the histological and molecular characteristics of the primary tumor, and the ability of individual fragments to form tumors was predictive of poor patient prognosis. Treatment of drug-sensitive or drug-resistant xenografts indicates that the CAM-glioma assay enables testing tumor sensitivity to temozolomide and carboplatin at doses consistent with those administered to patients. In a proof-of-concept study involving 14 HGG patients, we observed a correlation of 100% between the CAM xenograft response to temozolomide or carboplatin and the clinical response of patients. CONCLUSION: The CAM-glioma model is a fast and reliable assay that has the potential to serve as a complementary model to drug discovery and a real-time Avatar platform to predict the best treatment for HGG patients.

Simultaneous Monitoring of Atmospheric CH4, N2O, and H2O Using a Single Gas Sensor Based on Mid-IR Quartz-Enhanced Photoacoustic Spectroscopy.

An optical sensor based on external-cavity quantum cascade laser (EC-QCL) was developed for simultaneous triple-species monitoring of CH4, N2O, and H2O vapor using off-beam quartz-enhanced photoacoustic spectroscopy (OB-QEPAS). The EC-QCL wavelength was scanned over three neighboring absorption lines of CH4 (1260.81 cm-1), N2O (1261.06 cm-1), and H2O vapor (1261.58 cm-1) by tuning the grating of the EC-QCL with a piezoelectric actuator. Molecular relaxation effects impacting the generation of the QEPAS signals resulting from light absorption by CH4 and N2O molecules were investigated in the mid-infrared region near 8 µm. A theoretical model was introduced for the mid-infrared region, including the beneficial influence of water vapor. An enhancement of the QEPAS signals by a factor of 3 for CH4 in air and of 20% for N2O in air was observed in humidified samples compared to that in dry samples. The QEPAS measurement was scaled by the calibrated reference spectrometers; detection limits of 98 ppbv for CH4, 12 ppbv for N2O, and 750 ppmv for H2O vapor were obtained with a 1σ signal-to-noise ratio (SNR = 1) in humidified gas mixtures. Real-time Kalman filtering was applied to improve the measurement precision by a factor of approximately 4 while keeping the same temporal resolution, leading to measurement precisions of 60 ppbv for CH4, 10 ppbv for N2O, and 0.07% for H2O in the measurements of 1.99 ppmv CH4 and 312 ppbv N2O humidified with 2.8% H2O vapor, with a 1 s lock-in amplifier time constant and an equivalent bandwidth of 0.1 Hz.

Expression of ABCB1, ABCC1 and 3 and ABCG2 in glioblastoma and their relevance in relation to clinical survival surrogates.

PURPOSE: Glioblastoma (GBM) is the most common and aggressive malignant primary brain tumors in adults. Patients invariably relapse during or after first-line therapy and the median overall survival is 14.6 months. Such poor clinical response is partly ascribed to the activity of ATP-binding cassette (ABC) transporters. The activity of these proteins, severely reduces the amount of therapeutics that penetrates the tumor cells. We hypothesized that ABC transporter expression could correlate with survival surrogates. In this study, we assessed the expression of four commonly expressed ABC transporters in GBM samples and investigated if mRNA levels could serve as a prognostic biomarker. METHODS: Human specimens were analyzed by qPCR to assess ABCB1, ABCC1/3 and ABCG2 expression. Kaplan-Meier and multivariate analyses were then used to evaluate the correlation with overall survival (OS) and progression-free survival (PFS). RESULTS: Our cohort included 22 non-tumoral samples as well as 159 GBM tumor specimens. ABC transporters were significantly more expressed in GBM samples compared to non-tumoral tissue. Moreover ABCC1 and 3 mRNA expression were significantly increased at recurrence. Statistical analyses revealed that increased expression of either ABCC1 or ABCC3 did not confer a poorer prognosis. However, increased ABCC1 mRNA levels did correlate with a significantly shorter PFS. CONCLUSION: In this manuscript, the analyses we conducted suggest that the expression of the four ABC transporters evaluated would not be suitable prognostic biomarkers. We believe that, when estimating prognosis, the plethora of mechanisms implicated in chemoresistance should be analyzed as a multi-facetted entity rather than isolated units.

Development of an adverse outcome pathway for radiation-induced microcephaly via expert consultation and machine learning.

BACKGROUND: Brain development during embryogenesis and in early postnatal life is particularly complex and involves the interplay of many cellular processes and molecular mechanisms, making it extremely vulnerable to exogenous insults, including ionizing radiation (IR). Microcephaly is one of the most frequent neurodevelopmental abnormalities that is characterized by small brain size, and is often associated with intellectual deficiency. Decades of research span from epidemiological data on in utero exposure of the A-bomb survivors, to studies on animal and cellular models that allowed deciphering the most prominent molecular mechanisms leading to microcephaly. The Adverse Outcome Pathway (AOP) framework is used to organize, evaluate and portray the scientific knowledge of toxicological effects spanning different biological levels of organizations, from the initial interaction with molecular targets to the occurrence of a disease or adversity. In the present study, the framework was used in an attempt to organize the current scientific knowledge on microcephaly progression in the context of ionizing radiation (IR) exposure. This work was performed by a group of experts formed during a recent workshop organized jointly by the Multidisciplinary European Low Dose Initiative (MELODI) and the European Radioecology Alliance (ALLIANCE) associations to present the AOP approach and tools. Here we report on the development of a putative AOP for congenital microcephaly resulting from IR exposure based on discussions of the working group and we emphasize the use of a novel machine-learning approach to assist in the screening of the available literature to develop AOPs. CONCLUSION: The expert consultation led to the identification of crucial biological events for the progression of microcephaly upon exposure to IR, and highlighted current knowledge gaps. The machine learning approach was successfully used to screen the existing knowledge and helped to rapidly screen the body of evidence and in particular the epidemiological data. This systematic review approach also ensured that the analysis was sufficiently comprehensive to identify the most relevant data and facilitate rapid and consistent AOP development. We anticipate that as machine learning approaches become more user-friendly through easy-to-use web interface, this would allow AOP development to become more efficient and less time consuming.

Assessing the Effectiveness of an Urban CO2 Monitoring Network over the Paris Region through the COVID-19 Lockdown Natural Experiment.

The Paris metropolitan area, the largest urban region in the European Union, has experienced two national COVID-19 confinements in 2020 with different levels of restrictions on mobility and economic activity, which caused reductions in CO2 emissions. To quantify the timing and magnitude of daily emission reductions during the two lockdowns, we used continuous atmospheric CO2 monitoring, a new high-resolution near-real-time emission inventory, and an atmospheric Bayesian inverse model. The atmospheric inversion estimated the changes in fossil fuel CO2 emissions over the Greater Paris region during the two lockdowns, in comparison with the same periods in 2018 and 2019. It shows decreases by 42-53% during the first lockdown with stringent measures and by only 20% during the second lockdown when traffic reduction was weaker. Both lockdown emission reductions are mainly due to decreases in traffic. These results are consistent with independent estimates based on activity data made by the city environmental agency. We also show that unusual persistent anticyclonic weather patterns with north-easterly winds that prevailed at the start of the first lockdown period contributed a substantial drop in measured CO2 concentration enhancements over Paris, superimposed on the reduction of urban CO2 emissions. We conclude that atmospheric CO2 monitoring makes it possible to identify significant emission changes (>20%) at subannual time scales over an urban region.

Updated Mortality Analysis of SELTINE, the French Cohort of Nuclear Workers, 1968-2014.

Cohorts of nuclear workers are particularly relevant to study the health effects of protracted exposures to low doses at low dose-rates of ionizing radiation (IR). In France, a cohort of nuclear workers badge-monitored for external IR exposure has been followed-up for several decades. Its size and follow-up period have recently been extended. The present paper focuses on mortality from both cancer and non-cancer diseases in this cohort. The SELTINE cohort of nuclear workers employed by CEA, Orano, and EDF companies was followed-up for mortality from 1968 to 2014. Mortality in the cohort was compared to that in the French general population. Poisson regression methods were used to estimate excess relative rates of mortality per unit of cumulative dose of IR, adjusted for calendar year, age, company, duration of employment, and socioeconomic status. The cohort included 80,348 workers. At the end of the follow-up, the mean attained age was 63 years, and 15,695 deaths were observed. A strong healthy worker effect was observed overall. A significant excess of pleural cancer mortality was observed but not associated with IR dose. Death from solid cancers was positively but non-significantly associated with radiation. Death from leukaemia (excluding chronic lymphocytic leukaemia), dementia, and Alzheimer's disease were positively and significantly associated with IR dose. Estimated dose-risk relationships were consistent with those from other nuclear worker studies for all solid cancers and leukaemia but remained associated with large uncertainty. The association between IR dose and dementia mortality risk should be interpreted with caution and requires further investigation by other studies.

Bayesian Profile Regression to Deal With Multiple Highly Correlated Exposures and a Censored Survival Outcome. First Application in Ionizing Radiation Epidemiology.

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.

Associations between green space and preterm birth: Windows of susceptibility and interaction with air pollution.

BACKGROUND: Recent studies have reported inconsistent associations between maternal residential green space and preterm birth (PTB, born < 37 completed gestational weeks). In addition, windows of susceptibility during pregnancy have not been explored and potential interactions of green space with air pollution exposures during pregnancy are still unclear. OBJECTIVES: To evaluate the relationships between green space and PTB, identify windows of susceptibility, and explore potential interactions between green space and air pollution. METHODS: Birth certificate records for all births in California (2001-2008) were obtained. The Normalized Difference Vegetation Index (NDVI) was used to characterized green space exposure. Gestational age was treated as a time-to-event outcome; Cox proportional hazard models were applied to estimate the association between green space exposure and PTB, moderately PTB (MPTB, gestational age < 35 weeks), and very PTB (VPTB, gestational age < 30 weeks), after controlling for maternal age, race/ethnicity, education, and median household income. Month-specific green space exposure was used to identify potential windows of susceptibility. Potential interactions between green space and air pollution [fine particulate matter < 2.5 µm (PM2.5), nitrogen dioxide (NO2), and ozone (O3)] were examined on both additive and multiplicative scales. RESULTS: In total, 3,753,799 eligible births were identified, including 341,123 (9.09%) PTBs, 124,631 (3.32%) MPTBs, and 22,313 (0.59%) VPTBs. A reduced risk of PTB was associated with increases in residential NDVI exposure in 250 m, 500 m, 1000 m, and 2000 m buffers. In the 2000 m buffer, the association was strongest for VPTB [adjusted hazard ratio (HR) per interquartile range increase in NDVI: 0.959, 95% confidence interval (CI): 0.942-0.976)], followed by MPTB (HR = 0.970, 95% CI: 0.962-0.978) and overall PTB (HR = 0.972, 95% CI: 0.966-0.978). For PTB, green space during the 3rd - 5th gestational months had stronger associations than those in the other time periods, especially during the 4th gestational month (NDVI 2000 m: HR = 0.970, 95% CI: 0.965-0.975). We identified consistent positive additive and multiplicative interactions between decreasing green space and higher air pollution. CONCLUSION: This large study found that maternal exposure to residential green space was associated with decreased risk of PTB, MPTB, and VPTB, especially in the second trimester. There is a synergistic effect between low green space and high air pollution levels on PTB, indicating that increasing exposure to green space may be more beneficial for women with higher air pollution exposures during pregnancy.

Clinical and epidemiological observations on individual radiation sensitivity and susceptibility.

Purpose: To summarize existing knowledge and to understand individual response to radiation exposure, the MELODI Association together with CONCERT European Joint Programme has organized a workshop in March 2018 on radiation sensitivity and susceptibility.Methods: The workshop reviewed the current evidence on this matter, to inform the MELODI Strategic Research Agenda (SRA), to determine social and scientific needs and to come up with recommendations for suitable and feasible future research initiatives to be taken for the benefit of an improved medical diagnosis and treatment as well as for radiation protection.Results: The present paper gives an overview of the current evidence in this field, including potential effect modifiers such as age, gender, genetic profile, and health status of the exposed population, based on clinical and epidemiological observations.Conclusion: The authors conclude with the following recommendations for the way forward in radiation research: (a) there is need for large (prospective) cohort studies; (b) build upon existing radiation research cohorts; (c) use data from well-defined cohorts with good exposure assessment and biological material already collected; (d) focus on study quality with standardized data collection and reporting; (e) improve statistical analysis; (f) cooperation between radiobiology and epidemiology; and (g) take consequences of radiosensitivity and radiosusceptibility into account.

Relationships between greenness and low birth weight: Investigating the interaction and mediation effects of air pollution.

BACKGROUND: Associations between residential greenness and improved birth weight have been increasingly reported, but underlying mechanisms and interactions with other environmental exposures are still unclear. OBJECTIVES: To study the relationships between low birth weight (LBW, <2500 g), residential greenness, and the potential influence of air pollution in these relationships (interaction and mediation) in California, over the period 2001-2008. METHODS: Residential greenness around maternal homes was characterized using the Normalized Difference Vegetation Index (NDVI). Complementary indicators of air pollution exposure reflected its main components. Birth weight and maternal characteristics were obtained from birth certificate records. In this case-cohort study, associations between greenness and LBW were investigated using multi-level Poisson regression with random effect at the hospital level. We investigated potential interaction of greenness and air pollutants on both additive and multiplicative scales. Mediation analyses were conducted to estimate the potential contribution of local variations in air pollutant concentrations associated with greenness on LBW risk. RESULTS: In total 72,632 LBW cases were included. A reduction of LBW risk was associated with an increase in NDVI (adjusted risk ratio per inter-quartile range in NDVI: 0.963; 95% confidence interval: 0.947; 0.978). We observed no interaction between NDVI and air pollution on LBW risk. The estimated mediating effect of fine particulate matter in the impact of greenness on LBW was 12%. CONCLUSION: This large study confirms that residential greenness is associated with a reduced risk of LBW and suggests that greenness might benefit to LBW partly through a local reduction in air pollution.

Analysis of the association between ionizing radiation and mortality in uranium workers from five plants involved in the nuclear fuel production cycle in France.

PURPOSE: The aim is to investigate associations between mortality and exposure to ionizing radiation in a cohort of uranium workers with potential for internal and external radiation exposures. METHODS: Workers employed for at least 6 months between 1958 and 2006 in five plants involved in the French nuclear fuel cycle were included and followed up between 1968 and 2013. Cause-specific standardized mortality ratios were calculated. Analyses of associations between individual cumulative radiation dose (both internal and external, lagged by 5-15 years) and mortality were conducted using Poisson regression. RESULTS: The cohort includes 4541 workers. The mean cumulative external dose was 11.12 mGy. Mean cumulative internal doses ranged, depending on modelling hypotheses, from 0.05 to 0.09 mGy (liver) and from 4.22 to 10.90 mGy (lung). At the end of the follow-up, 838 workers were deceased and 28 lost to follow-up. A healthy worker effect was observed. The risk of prostate and lung cancers mortality was significantly higher for workers exposed to cumulative external dose above 50 mGy compared to non-exposed, but these associations were based only on three cases and became non-significant, although of similar magnitude, after adjustment for smoking. Associations with internal dose showed no consistent pattern. CONCLUSIONS: For the first time, a study was conducted in a French cohort of uranium workers with a complete reconstruction of internal dose. Results are preliminary and must be interpreted with caution because of the limited cohort size and significant sources of uncertainty. Future steps of this study will overcome these limitations.

Liposomal formulations of carboplatin injected by convection-enhanced delivery increases the median survival time of F98 glioma bearing rats.

BACKGROUND: Effectiveness of chemotherapy for treating glioblastoma (GBM) brain tumors is hampered by the blood-brain barrier which limits the entry into the brain of most drugs from the blood. To bypass this barrier, convection-enhanced delivery (CED) was proposed to directly inject drugs in tumor. However, the benefit of CED may be hampered when drugs diffuse outside the tumor to then induce neurotoxicity. Encapsulation of drugs into liposome aims at increasing tumor cells specificity and reduces neurotoxicity. However, the most appropriate liposomal formulation to inject drugs into brain tumor by CED still remains to be determined. In this study, four liposomal carboplatin formulations were prepared and tested in vitro on F98 glioma cells and in Fischer rats carrying F98 tumor implanted in the brain. Impact of pegylation on liposomal surface and relevance of positive or negative charge were assessed. RESULTS: The cationic non-pegylated (L1) and pegylated (L2) liposomes greatly improved the toxicity of carboplatin in vitro compared to free carboplatin, whereas only a modest improvement and even a reduction of efficiency were measured with the anionic non-pegylated (L3) and the pegylated (L4) liposomes. Conversely, only the L4 liposome significantly increased the median survival time of Fisher rats implanted with the F98 tumor, compared to free carboplatin. Neurotoxicity assays performed with the empty L4' liposome showed that the lipid components of L4 were not toxic. These results suggest that the positive charge on liposomes L1 and L2, which is known to promote binding to cell membrane, facilitates carboplatin accumulation in cancer cells explaining their higher efficacy in vitro. Conversely, negatively charged and pegylated liposome (L4) seems to diffuse over a larger distance in the tumor, and consequently significantly increased the median survival time of the animals. CONCLUSIONS: Selection of the best liposomal formulation based on in vitro studies or animal model can result in contradictory conclusions. The negatively charged and pegylated liposome (L4) which was the less efficient formulation in vitro showed the best therapeutic effect in animal model of GBM. These results support that relevant animal model of GBM must be considered to determine the optimal physicochemical properties of liposomal formulations.

Differential Expression and Clinical Significance of Transforming Growth Factor-Beta Isoforms in GBM Tumors.

Glioblastoma (GBM) represents the most common and aggressive malignant primary brain tumors in adults. Response to standard treatment is transitory and the survival of clinical trial cohorts are little more than 14 months. GBM are characterized by excessive proliferation, invasiveness, and radio-/chemoresistance features; which are strongly upregulated by transforming growth factor-beta (TGF-ß). We hypothesized that TGF-ß gene expression could correlate with overall survival (OS) and serve as a prognostic biomarker. TGF-ß1 and -ß2 expression were analyzed by qPCR in 159 GBM tumor specimens. Kaplan-Meier and multivariate analyses were used to correlate expression with OS and progression-free survival (PFS). In GBM, TGF-ß1 and -ß2 levels were 33- and 11-fold higher respectively than in non-tumoral samples. Kaplan-Meier and multivariate analyses revealed that high to moderate expressions of TGF-ß1 significantly conferred a strikingly poorer OS and PFS in newly diagnosed patients. Interestingly, at relapse, neither isoforms had meaningful impact on clinical evolution. We demonstrate that TGF-ß1 is the dominant isoform in newly diagnosed GBM rather than the previously acknowledged TGF-ß2. We believe our study is the first to unveil a significant relationship between TGF-ß1 expression and OS or PFS in newly diagnosed GBM. TGF-ß1 could serve as a prognostic biomarker or target affecting treatment planning and patient follow-up.

First mortality analysis in the French cohort of uranium millers (F-Millers), period 1968-2013.

PURPOSE: Epidemiological studies in cohorts of uranium millers can be informative to improve knowledge of the health effects of uranium, but are very rare. The aim of this study was to analyze, for the first time, mortality in a French cohort of uranium millers. METHODS: The F-Millers cohort includes permanent contract workers employed at least 6 months at French uranium milling plants. Vital status and causes of death were obtained from national registries between 1968 and 2013, in order to perform comparisons with French national and local mortality rates by computing standardized mortality ratios (SMRs) with 95% confidence intervals (95% CI). RESULTS: The cohort includes 1291 workers. The average duration of follow-up is 32.1 years. At the end of follow-up, 448 workers were deceased and 13 lost to follow-up. We observed a significant deficit of mortality for all causes combined when the national reference was considered (SMR 0.81; 95% CI [0.74;0.89]), but no significant difference when the local reference was considered (SMR 0.97; 95% CI [0.88;1.07]). Significant excesses were observed only in a subgroup of 552 workers hired at the manufacturing unit, mainly when the local reference was considered. CONCLUSION: No significant excess of mortality was observed at the scale of the full cohort. The cause-specific excesses of mortality observed in the subgroup of workers hired at the manufacturing unit were based on small number of cases, but would warrant further investigations. Undertaking analytical studies and combined analyses of cohorts of uranium millers would help to study the influence of potential risk factors and obtain more precise results.

PI3Kß Plays a Key Role in Apolipoprotein A-I-Induced Endothelial Cell Proliferation Through Activation of the Ecto-F1-ATPase/P2Y1 Receptors.

BACKGROUND/AIMS: High-density lipoproteins (HDL) exert multiple cardioprotective functions on the arterial wall, including the promotion of endothelial cell survival and proliferation. Among mechanism contributing to endothelial protection, it has been reported that apolipoprotein A-I (apoA-I), the major protein in HDL, binds and activates the endothelial ecto-F1-ATPase receptor. This generates extracellular ADP, which in turn promotes endothelial cell survival. In this study we aimed to further investigate the signaling pathway involved downstream of apoA-I-induced ecto-F1-ATPase activation. METHODS: In human umbilical vein endothelial cells (HUVECs), pharmacological and gene silencing approaches were used to study pathways involved downstream ecto-F1-ATPase activation by apoA-I. RESULTS: ApoA-I and HDL both induced Akt phosphorylation. F1-ATPase inhibitors such as inhibitory factor 1 and oligomycin completely blocked apoA-I-induced Akt phosphorylaton and significantly blocked HDL-induced phosphorylation, indicating that this signaling pathway is dependent on ecto-F1-ATPase activation by apoA-I. Further, we were able to specify roles for the P2Y1-ADPreceptor and the PI3Kß isoform in this pathway since pharmacological inhibition and silencing of these proteins dramatically inhibited apoA-I-induced Akt phosphorylation and cell proliferation. CONCLUSION: Altogether, these data highlight a key role of the P2Y1/PI3Kß axis in endothelial cell proliferation downstream of ecto-F1-ATPase activation by apoA-I. Pharmacological targeting of this pathway could represent a promising approach to enhance vascular endothelial protection.

Ionizing radiation biomarkers in epidemiological studies - An update.

Recent epidemiology studies highlighted the detrimental health effects of exposure to low dose and low dose rate ionizing radiation (IR): nuclear industry workers studies have shown increased leukaemia and solid tumour risks following cumulative doses of <100mSv and dose rates of <10mGy per year; paediatric patients studies have reported increased leukaemia and brain tumours risks after doses of 30-60mGy from computed tomography scans. Questions arise, however, about the impact of even lower doses and dose rates where classical epidemiological studies have limited power but where subsets within the large cohorts are expected to have an increased risk. Further progress requires integration of biomarkers or bioassays of individual exposure, effects and susceptibility to IR. The European DoReMi (Low Dose Research towards Multidisciplinary Integration) consortium previously reviewed biomarkers for potential use in IR epidemiological studies. Given the increased mechanistic understanding of responses to low dose radiation the current review provides an update covering technical advances and recent studies. A key issue identified is deciding which biomarkers to progress. A roadmap is provided for biomarker development from discovery to implementation and used to summarise the current status of proposed biomarkers for epidemiological studies. Most potential biomarkers remain at the discovery stage and for some there is sufficient evidence that further development is not warranted. One biomarker identified in the final stages of development and as a priority for further research is radiation specific mRNA transcript profiles.

Residential Exposure to Natural Background Radiation and Risk of Childhood Acute Leukemia in France, 1990-2009.

BACKGROUND: Exposures to high-dose ionizing radiation and high-dose rate ionizing radiation are established risk factors for childhood acute leukemia (AL). The risk of AL following exposure to lower doses due to natural background radiation (NBR) has yet to be conclusively determined. METHODS: AL cases diagnosed over 1990-2009 (9,056 cases) were identified and their municipality of residence at diagnosis collected by the National Registry of Childhood Cancers. The Geocap study, which included the 2,763 cases in 2002-2007 and 30,000 population controls, was used for complementary analyses. NBR exposures were modeled on a fine scale (36,326 municipalities) based on measurement campaigns and geological data. The power to detect an association between AL and dose to the red bone marrow (RBM) fitting UNSCEAR (United Nations Scientific Committee on the Effects of Atomic Radiation) predictions was 92%, 45% and 99% for exposure to natural gamma radiation, radon and total radiation, respectively. RESULTS: AL risk, irrespective of subtype and age group, was not associated with the exposure of municipalities to radon or gamma radiation in terms of yearly exposure at age reached, cumulative exposure or RBM dose. There was no confounding effect of census-based socio-demographic indicators, or environmental factors (road traffic, high voltage power lines, vicinity of nuclear plants) related to AL in the Geocap study. CONCLUSIONS: Our findings do not support the hypothesis that residential exposure to NBR increases the risk of AL, despite the large size of the study, fine scale exposure estimates and wide range of exposures over France. However, our results at the time of diagnosis do not rule out a slight association with gamma radiation at the time of birth, which would be more in line with the recent findings in the UK and Switzerland.

Biomarkers for Uranium Risk Assessment for the Development of the CURE (Concerted Uranium Research in Europe) Molecular Epidemiological Protocol.

Despite substantial experimental and epidemiological research, there is limited knowledge of the uranium-induce health effects after chronic low-dose exposures in humans. Biological markers can objectively characterize pathological processes or environmental responses to uranium and confounding agents. The integration of such biological markers into a molecular epidemiological study would be a useful approach to improve and refine estimations of uranium-induced health risks. To initiate such a study, Concerted Uranium Research in Europe (CURE) was established, and involves biologists, epidemiologists and dosimetrists. The aims of the biological work package of CURE were: 1. To identify biomarkers and biological specimens relevant to uranium exposure; 2. To define standard operating procedures (SOPs); and 3. To set up a common protocol (logistic, questionnaire, ethical aspects) to perform a large-scale molecular epidemiologic study in uranium-exposed cohorts. An intensive literature review was performed and led to the identification of biomarkers related to: 1. retention organs (lungs, kidneys and bone); 2. other systems/organs with suspected effects (cardiovascular system, central nervous system and lympho-hematopoietic system); 3. target molecules (DNA damage, genomic instability); and 4. high-throughput methods for the identification of new biomarkers. To obtain high-quality biological materials, SOPs were established for the sampling and storage of different biospecimens. A questionnaire was developed to assess potential confounding factors. The proposed strategy can be adapted to other internal exposures and should improve the characterization of the biological and health effects that are relevant for risk assessment.