Intake of nitrate and nitrite and the risk of gastric cancer: a prospective cohort study.

The association between the intake of nitrate or nitrite and gastric cancer risk was investigated in a prospective cohort study started in 1986 in the Netherlands, of 120,852 men and women aged 55-69 years. At baseline, data on dietary intake, smoking habits and other covariates were collected by means of a self-administered questionnaire. For data analysis, a case-cohort approach was used, in which the person-years at risk were estimated from a randomly selected subcohort (1688 men and 1812 women). After 6.3 years of follow-up, 282 microscopically confirmed incident cases of stomach cancer were detected: 219 men and 63 women. We did not find a higher risk of gastric cancer among people with a higher nitrate intake from food [rate ratio (RR) highest/lowest quintile = 0.80, 95% CI 0.47-1.37, trend-P = 0.18], a higher nitrate intake from drinking water (RR highest/lowest quintile = 0.88, 95% CI 0.59-1.32, trend-P = 0.39) or a higher intake of nitrite (RR highest/lowest quintile = 1.44, 95% CI 0.95-2.18, trend-P = 0.24). Rate ratios for gastric cancer were also computed for each tertile of nitrate intake from foods within tertiles of vitamin C intake and intake of beta-carotene, but no consistent pattern was found. Therefore, our study does not support a positive association between the intake of nitrate or nitrite and gastric cancer risk

Volumetric measurement of pulmonary nodules at low-dose chest CT: effect of reconstruction setting on measurement variability

To assess volumetric measurement variability in pulmonary nodules detected at low-dose chest CT with three reconstruction settings. The volume of 200 solid pulmonary nodules was measured three times using commercially available semi-automated software of low-dose chest CT data-sets reconstructed with 1 mm section thickness and a soft kernel (A), 2 mm and a soft kernel (B), and 2 mm and a sharp kernel (C), respectively. Repeatability coefficients of the three measurements within each setting were calculated by the Bland and Altman method. A three-level model was applied to test the impact of reconstruction setting on the measured volume. The repeatability coefficients were 8.9, 22.5 and 37.5% for settings A, B and C. Three-level analysis showed that settings A and C yielded a 1.29 times higher estimate of nodule volume compared with setting B (P = 0.03). The significant interaction among setting, nodule location and morphology demonstrated that the effect of the reconstruction setting was different for different types of nodules. Low-dose CT reconstructed with 1 mm section thickness and a soft kernel provided the most repeatable volume measurement. A wide, nodule-type-dependent range of agreement between volume measurements with different reconstruction settings suggests strict consistency is required for serial CT studies

A case study of neurodevelopmental risks from combined exposures to lead, methyl-mercury, inorganic arsenic, polychlorinated biphenyls, polybrominated diphenyl ethers and fluoride

We performed a mixture risk assessment (MRA) case study of dietary exposure to the food contaminants lead, methylmercury, inorganic arsenic (iAs), fluoride, non-dioxin-like polychlorinated biphenyls (NDL-PCBs) and polybrominated diphenyl ethers (PBDEs), all substances associated with declines in cognitive abilities measured as IQ loss. Most of these chemicals are frequently measured in human biomonitoring studies. A component-based, personalised modified reference point index (mRPI) approach, in which we expressed the exposures and potencies of our chosen substances as lead equivalent values, was applied to perform a MRA for dietary exposures. We conducted the assessment for four different age groups (toddlers, children, adolescents, and women aged 18–45 years) in nine European countries. Populations in all countries considered exceeded combined tolerable levels at median exposure levels. NDL-PCBs in fish, other seafood and dairy, lead in grains and fruits, methylmercury in fish and other seafoods, and fluoride in water contributed most to the combined exposure. We identified uncertainties for the likelihood of co-exposure, assessment group membership, endpoint-specific reference values (ESRVs) based on epidemiological (lead, methylmercury, iAs, fluoride and NDL-PCBs) and animal data (PBDE), and exposure data. Those uncertainties lead to a complex pattern of under- and overestimations, which would require probabilistic modelling based on expert knowledge elicitation for integration of the identified uncertainties into an overall uncertainty estimate. In addition, the identified uncertainties could be used to refine future MRA for cognitive decline.European Union’s Horizon 2020 research and innovation programme under grant agreement number 874583—the Advancing Tools for Human Early Lifecourse Exposome Research and Translation (ATHLETE) project. The author Mousumi Chatterjee is grateful for a Daphne Jackson Trust (UK) fellowship. The authors would like to thank EFSA providing the food consumption databases, data owners for giving permission to use the data, and Gerda van Donkersgoed and Matthijs Sam (RIVM) for organising the food consumption data and chemical concentration data

The LSST DESC data challenge 1: Generation and analysis of synthetic images for next-generation surveys

Data Challenge 1 (DC1) is the first synthetic data set produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST data set. DC1 is comprised of r-band observations of 40 deg2 to 10 yr LSST depth. We present each stage of the simulation and analysis process: (a) generation, by synthesizing sources from cosmological N-body simulations in individual sensor-visit images with different observing conditions; (b) reduction using a development version of the LSST Science Pipelines; and (c) matching to the input cosmological catalogue for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star-galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: (i) survey properties have an impact of 50 per cent of the statistical uncertainty for the scales and models used in DC1; (ii) a selection to eliminate artefacts in the catalogues is necessary to avoid biases in the measured clustering; and (iii) the presence of bright objects has a significant impact (2-6) in the estimated power spectra at small scales (> 1200), highlighting the impact of blending in studies at small angular scales in LSST

Intra-Household Work Timing: The Effect on Joint Activities and the Demand for Child Care

This study examines whether couples time their work hours and how this work timing influences child care demand and the time that spouses jointly spend on leisure, household chores, and child care. By using an innovative matching strategy, this study identifies the timing of work hours that cannot be explained by factors other than the partners' potential to communicate about the timing of their work. The main findings are that couples with children create less overlap in their work times and this effect is more pronounced the younger the children. We find evidence for a togetherness preference of spouses, but only for childless couples. Work timing also influences the joint time that is spent on household chores, but the effect is small. Finally, work timing behaviour affects the demand for informal child care, but not the demand for formal child care

The MCRA toolbox of models and data to support chemical mixture risk assessment

A model and data toolbox is presented to assess risks from combined exposure to multiple chemicals using probabilistic methods. The Monte Carlo Risk Assessment (MCRA) toolbox, also known as the EuroMix toolbox, has more than 40 modules addressing all areas of risk assessment, and includes a data repository with data collected in the EuroMix project. This paper gives an introduction to the toolbox and illustrates its use with examples from the EuroMix project. The toolbox can be used for hazard identification, hazard characterisation, exposure assessment and risk characterisation. Examples for hazard identification are selection of substances relevant for a specific adverse outcome based on adverse outcome pathways and QSAR models. Examples for hazard characterisation are calculation of benchmark doses and relative potency factors with uncertainty from dose response data, and use of kinetic models to perform in vitro to in vivo extrapolation. Examples for exposure assessment are assessing cumulative exposure at external or internal level, where the latter option is needed when dietary and non-dietary routes have to be aggregated. Finally, risk characterisation is illustrated by calculation and display of the margin of exposure for single substances and for the cumulation, including uncertainties derived from exposure and hazard characterisation estimates.</p

A new ultrafast and high-throughput mass spectrometric approach for the therapeutic drug monitoring of the multi-targeted anti-folate pemetrexed in plasma from lung cancer patients

An analytical assay has been developed and validated for ultrafast and high-throughput mass spectrometric determination of pemetrexed concentrations in plasma using matrix assisted laser desorption/ionization–triple quadrupole–tandem mass spectrometry. Patient plasma samples spiked with the internal standard methotrexate were measured by multiple reaction monitoring. The detection limit was 0.4 fmol/μL, lower limit of quantification was 0.9 fmol/μL, and upper limit of quantification was 60 fmol/μL, respectively. Overall observed pemetrexed concentrations in patient samples ranged between 8.7 (1.4) and 142.7 (20.3) pmol/μL (SD). The newly developed mass spectrometric assay is applicable for (routine) therapeutic drug monitoring of pemetrexed concentrations in plasma from non-small cell lung cancer patients

Differences between Men and Women in Treatment and Outcome after Traumatic Brain Injury

Traumatic brain injury (TBI) is a significant cause of disability, but little is known about sex and gender differences after TBI. We aimed to analyze the association between sex/gender, and the broad range of care pathways, treatment characteristics, and outcomes following mild and moderate/severe TBI. We performed mixed-effects regression analyses in the prospective multi-center Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, stratified for injury severity and age, and adjusted for baseline characteristics. Outcomes were various care pathway and treatment variables, and 6-month measures of functional outcome, health-related quality of life (HRQoL), post-concussion symptoms (PCS), and mental health symptoms. The study included 2862 adults (36% women) with mild (mTBI; Glasgow Coma Scale [GCS] score 13-15), and 1333 adults (26% women) with moderate/severe TBI (GCS score 3-12). Women were less likely to be admitted to the intensive care unit (ICU; odds ratios [OR] 0.6, 95% confidence interval [CI]: 0.4-0.8) following mTBI. Following moderate/severe TBI, women had a shorter median hospital stay (OR 0.7, 95% CI: 0.5-1.0). Following mTBI, women had poorer outcomes; lower Glasgow Outcome Scale Extended (GOSE; OR 1.4, 95% CI: 1.2-1.6), lower generic and disease-specific HRQoL, and more severe PCS, depression, and anxiety. Among them, women under age 45 and above age 65 years showed worse 6-month outcomes compared with men of the same age. Following moderate/severe TBI, there was no difference in GOSE (OR 0.9, 95% CI: 0.7-1.2), but women reported more severe PCS (OR 1.7, 95% CI: 1.1-2.6). Men and women differ in care pathways and outcomes following TBI. Women generally report worse 6-month outcomes, but the size of differences depend on TBI severity and age. Future studies should examine factors that explain these differences.</p

Overview on legislation and scientific approaches for risk assessment of combined exposure to multiple chemicals: the potential EuroMix contribution

This article reviews the current legislative requirements for risk assessment of combined exposure to multiple chemicals via multiple exposure routes, focusing on human health and particularly on food-related chemicals. The aim is to identify regulatory needs and current approaches for this type of risk assessment as well as challenges of the implementation of appropriate and harmonized guidance at international level. It provides an overview of the current legal requirements in the European Union (EU), the United States and Canada. Substantial differences were identified in the legal requirements for risk assessment of combined exposure to multiple chemicals and its implementation between EU and non-EU countries and across several regulatory sectors. Frameworks currently proposed and in use for assessing risks from combined exposure to multiple chemicals via multiple routes and different durations of exposure are summarized. In order to avoid significant discrepancies between regulatory sectors or countries, the approach for assessing risks of combined exposure should be based on similar principles for all types of chemicals. OECD and EFSA identified the development of harmonized methodologies for combined exposure to multiple chemicals as a key priority area. The Horizon 2020 project “EuroMix” aims to contribute to the further development of internationally harmonized approaches for such risk assessments by the development of an integrated test strategy using in vitro and in silico tests verified for chemical mixtures based on more appropriate data on potential combined effects. These approaches and testing strategies should be integrated in a scientifically based weight of evidence approach to account for complexity and uncertainty, to improve risk assessment