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All normal somatic cells are thought to acquire mutations, but understanding of the rates, patterns, causes and consequences of somatic mutations in normal cells is limited. The uterine endometrium adopts multiple physiological states over a lifetime and is lined by a gland-forming epithelium 1 , 2 . Here, using whole-genome sequencing, we show that normal human endometrial glands are clonal cell populations with total mutation burdens that increase at about 29 base substitutions per year and that are many-fold lower than those of endometrial cancers. Normal endometrial glands frequently carry ‘driver’ mutations in cancer genes, the burden of which increases with age and decreases with parity. Cell clones with drivers often originate during the first decades of life and subsequently progressively colonize the epithelial lining of the endometrium. Our results show that mutational landscapes differ markedly between normal tissues—perhaps shaped by differences in their structure and physiology—and indicate that the procession of neoplastic change that leads to endometrial cancer is initiated early in life. Whole-genome sequencing of normal human endometrial glands shows that most are clonal cell populations and frequently carry cancer driver mutations that occur early in life, and that parity has a protective effect.

Encouraging neighbourhood social mix has been a major goal of urban policy and planning in a number of different countries. This book draws together a range of case studies by international experts to assess the impacts of social mix policies and the degree to which they might represent gentrification by stealth.

Surface ozone is a secondary air pollutant produced during the atmospheric photochemical degradation of emitted volatile organic compounds (VOCs) in the presence of sunlight and nitrogen oxides (NOx). Temperature directly influences ozone production through speeding up the rates of chemical reactions and increasing the emissions of VOCs, such as isoprene, from vegetation. In this study, we used an idealised box model with different chemical mechanisms (Master Chemical Mechanism, MCMv3.2; Common Representative Intermediates, CRIv2; Model for OZone and Related Chemical Tracers, MOZART-4; Regional Acid Deposition Model, RADM2; Carbon Bond Mechanism, CB05) to examine the non-linear relationship between ozone, NOx and temperature, and we compared this to previous observational studies. Under high-NOx conditions, an increase in ozone from 20 to 40°C of up to 20ppbv was due to faster reaction rates, while increased isoprene emissions added up to a further 11ppbv of ozone. The largest inter-mechanism differences were obtained at high temperatures and high-NOx emissions. CB05 and RADM2 simulated more NOx-sensitive chemistry than MCMv3.2, CRIv2 and MOZART-4, which could lead to different mitigation strategies being proposed depending on the chemical mechanism. The increased oxidation rate of emitted VOC with temperature controlled the rate of Ox production; the net influence of peroxy nitrates increased net Ox production per molecule of emitted VOC oxidised. The rate of increase in ozone mixing ratios with temperature from our box model simulations was about half the rate of increase in ozone with temperature observed over central Europe or simulated by a regional chemistry transport model. Modifying the box model set-up to approximate stagnant meteorological conditions increased the rate of increase of ozone with temperature as the accumulation of oxidants enhanced ozone production through the increased production of peroxy radicals from the secondary degradation of emitted VOCs. The box model simulations approximating stagnant conditions and the maximal ozone production chemical regime reproduced the 2ppbv increase in ozone per degree Celsius from the observational and regional model data over central Europe. The simulated ozone-temperature relationship was more sensitive to mixing than the choice of chemical mechanism. Our analysis suggests that reductions in NOx emissions would be required to offset the additional ozone production due to an increase in temperature in the future.

Background Ambient air pollution poses a major risk for the development and aggravation of respiratory diseases. Evidence suggests that even in low-level air pollution environments there is a risk for an increase in adverse respiratory symptoms. We examined whether variations in daily air pollution levels of nitrogen dioxide, ozone, or particulate matter in Berlin, Germany were associated with hospital admissions of chronic obstructive pulmonary disease (COPD) and asthma patients in a time series analysis. Methods We calculated single and multi-pollutant models, investigated possible lags in effect, and analysed the influence of meteorological variables on the results. Data from January 2005 through December 2015 were used to quantify the concentration–response. Results The risk ratio for asthma patients to be hospitalised on the same day of NO 2 exposure was 1.101 per 10 µg/m 3 NO 2 increase (95% CI: 1.013 to 1.195), for COPD patients 1.123 (95% CI: 1.081 to 1.168). Neither the exposure to ozone (95% CI: 0.904 to 1.020), PM 10 (95% CI: 0.990 to 1.127), nor PM 2.5 (95% CI: 0.981 to 1.148) was associated with an increased risk ratio for asthma patients to be hospitalised . Risk ratios for the hospital admission of COPD patients were also not increased due to ozone (95% CI: 0.981 to 1.033), PM 10 (95% CI: 0.988 to 1.032), or PM 2.5 (95% CI: 0.966 to 1.019) exposure. The presented risk ratios and confidence intervals relate to the day of exposure. We found no increased hospitalisation risks with a delayed occurrence on subsequent days. Conclusions A quantifiable, statistically significant increase in risk for asthma and COPD exacerbations owing to NO 2 exposure at levels well below European regulatory limit values was observed.

The Coloboma mouse carries a ∼2 cM deletion encompassing the SNAP25 gene and has a hyperactive phenotype similar to that of ADHD. Such mice are 3 fold more active compared to their control littermates. Genetic association studies support a role for allelic variants of the human SNAP25 gene in predisposing to ADHD. We performed association analysis across the SNAP25 gene in 1,107 individuals (339 ADHD trios). To assess the functional relevance of the SNAP25-ADHD associated allele, we performed quantitative PCR on post-mortem tissue derived from the inferior frontal gyrus of 89 unaffected adults. Significant associations with the A allele of SNP rs362990 (χ(2) = 10, p-corrected = 0.019, OR = 1.5) and three marker haplotypes (rs6108461, rs362990 and rs362998) were observed. Furthermore, a significant additive decrease in the expression of the SNAP25 transcript as a function of the risk allele was also observed. This effect was detected at the haplotype level, where increasing copies of the ADHD-associated haplotype reduced the expression of the transcript. Our data show that DNA variation at SNAP25 confers risk to ADHD and reduces the expression of the transcript in a region of the brain that is critical for the regulation of attention and inhibition.

With NO2 limit values being frequently exceeded in European cities, complying with the European air quality regulations still poses a problem for many cities. Traffic is typically a major source of NOx emissions in urban areas. High-resolution chemistry transport modelling can help to assess the impact of high urban NOx emissions on air quality inside and outside of urban areas. However, many modelling studies report an underestimation of modelled NOx and NO2 compared with observations. Part of this model bias has been attributed to an underestimation of NOx emissions, particularly in urban areas. This is consistent with recent measurement studies quantifying underestimations of urban NOx emissions by current emission inventories, identifying the largest discrepancies when the contribution of traffic NOx emissions is high. This study applies a high-resolution chemistry transport model in combination with ambient measurements in order to assess the potential underestimation of traffic NOx emissions in a frequently used emission inventory. The emission inventory is based on officially reported values and the Berlin–Brandenburg area in Germany is used as a case study. The WRF-Chem model is used at a 3 km × 3 km horizontal resolution, simulating the whole year of 2014. The emission data are downscaled from an original resolution of ca. 7 km × 7 km to a resolution of 1 km × 1 km. An in-depth model evaluation including spectral decomposition of observed and modelled time series and error apportionment suggests that an underestimation in traffic emissions is likely one of the main causes of the bias in modelled NO2 concentrations in the urban background, where NO2 concentrations are underestimated by ca. 8 µg m−3 (−30 %) on average over the whole year. Furthermore, a diurnal cycle of the bias in modelled NO2 suggests that a more realistic treatment of the diurnal cycle of traffic emissions might be needed. Model problems in simulating the correct mixing in the urban planetary boundary layer probably play an important role in contributing to the model bias, particularly in summer. Also taking into account this and other possible sources of model bias, a correction factor for traffic NOx emissions of ca. 3 is estimated for weekday daytime traffic emissions in the core urban area, which corresponds to an overall underestimation of traffic NOx emissions in the core urban area of ca. 50 %. Sensitivity simulations for the months of January and July using the calculated correction factor show that the weekday model bias can be improved from −8.8 µg m−3 (−26 %) to −5.4 µg m−3 (−16 %) in January on average in the urban background, and −10.3 µg m−3 (−46 %) to −7.6 µg m−3 (−34 %) in July. In addition, the negative bias of weekday NO2 concentrations downwind of the city in the rural and suburban background can be reduced from −3.4 µg m−3 (−12 %) to −1.2 µg m−3 (−4 %) in January and from −3.0 µg m−3 (−22 %) to −1.9 µg m−3 (−14 %) in July. The results and their consistency with findings from other studies suggest that more research is needed in order to more accurately understand the spatial and temporal variability in real-world NOx emissions from traffic, and apply this understanding to the inventories used in high-resolution chemical transport models.

We present an evaluation of the online regional model WRF-Chem over Europe with a focus on ground-level ozone (O3) and nitrogen oxides (NOx). The model performance is evaluated for two chemical mechanisms, MOZART-4 and RADM2, for year-long simulations. Model-predicted surface meteorological variables (e.g., temperature, wind speed and direction) compared well overall with surface-based observations, consistent with other WRF studies. WRF-Chem simulations employing MOZART-4 as well as RADM2 chemistry were found to reproduce the observed spatial variability in surface ozone over Europe. However, the absolute O3 concentrations predicted by the two chemical mechanisms were found to be quite different, with MOZART-4 predicting O3 concentrations up to 20 µgm-3 greater than RADM2 in summer. Compared to observations, MOZART-4 chemistry overpredicted O3 concentrations for most of Europe in the summer and fall, with a summertime domain-wide mean bias of +10 µgm-3 against observations from the AirBase network. In contrast, RADM2 chemistry generally led to an underestimation of O3 over the European domain in all seasons. We found that the use of the MOZART-4 mechanism, evaluated here for the first time for a European domain, led to lower absolute biases than RADM2 when compared to ground-based observations. The two mechanisms show relatively similar behavior for NOx, with both MOZART-4 and RADM2 resulting in a slight underestimation of NOx compared to surface observations. Further investigation of the differences between the two mechanisms revealed that the net midday photochemical production rate ofO3 in summer is higher for MOZART-4 than for RADM2 for most of the domain. The largest differences in O3 production can be seen over Germany, where net O3 production in MOZART-4 is seen to be higher than in RADM2 by 1.8 ppbh-1 (3.6 µgm-3h-1) or more. We also show that while the two mechanisms exhibit similar NOx sensitivity, RADM2 is approximately twice as sensitive to increases in anthropogenic VOC emissions as MOZART-4. Additionally, we found that differences in reaction rate coefficients for inorganic gas-phase chemistry in MOZART-4 vs. RADM2 accounted for a difference of 8 µgm-3, or 40 % of the summertime difference in O3 predicted by the two mechanisms. Differences in deposition and photolysis schemes explained smaller differences in O3. Our results highlight the strong dependence of modeled surface O3 over Europe on the choice of gas-phase chemical mechanism, which we discuss in the context of overall uncertainties in prediction of ground-level O3 and its associated health impacts (via the health-related metrics MDA8 and SOMO35).

In this study 1 year of ceilometer measurements taken in the Kathmandu Valley, Nepal, in the framework of the SusKat project (A Sustainable Atmosphere for the Kathmandu Valley) were analysed to investigate the diurnal variation of the mixing layer height (MLH) and its dependency on the meteorological conditions. In addition, the impact of the MLH on the temporal variation and the magnitude of the measured black carbon concentrations are analysed for each season. Based on the assumption that black carbon aerosols are vertically well mixed within the mixing layer and the finding that the mixing layer varies only little during night time and morning hours, black carbon emission fluxes are estimated for these hours and per month. Even though this method is relatively simple, it can give an observationally based first estimate of the black carbon emissions in this region, especially illuminating the seasonal cycle of the emission fluxes. The monthly minimum median MLH values typically range between 150 and 200 m during night and early morning hours, the monthly maximum median values between 625 m in July and 1460 m in March. Seasonal differences are not only found in the absolute MLHs, but also in the duration of the typical daytime maximum ranging between 2 and 3 h in January and 6–7 h in May. During the monsoon season a diurnal cycle has been observed with the smallest amplitude (typically between 400 and 500 m), with the lowest daytime mixing height of all seasons (maximum monthly median values typically between 600 and 800 m), and also the highest night-time and early morning mixing height of all seasons (minimum monthly median values typically between 200 and 220 m). These characteristics can mainly be explained with the frequently present clouds and the associated reduction in incoming solar radiation and outgoing longwave radiation. In general, the black carbon concentrations show a clear anticorrelation with MLH measurements, although this relation is less pronounced in the monsoon season. The daily evolution of the black carbon diurnal cycle differs between the seasons, partly due to the different meteorological conditions including the MLH. Other important reasons are the different main emission sources and their diurnal variations in the individual seasons. The estimation of the black carbon emission flux for the morning hours show a clear seasonal cycle with maximum values in December to April. Compared to the emission flux values provided by different emission databases for this region, the estimated values here are considerably higher. Several possible sources of uncertainty are considered, and even the absolute lower bound of the emissions based on our methodology is higher than in most emissions datasets, providing strong evidence that the black carbon emissions for this region have likely been underestimated in modelling studies thus far.

Germ cell tumours (GCTs) are a collection of benign and malignant neoplasms derived from primordial germ cells. They are uniquely able to recapitulate embryonic and extraembryonic tissues, which carries prognostic and therapeutic significance. The developmental pathways underpinning GCT initiation and histogenesis are incompletely understood. Here, we study the relationship of histogenesis and clonal diversification in GCTs by analysing the genomes and transcriptomes of 547 microdissected histological units. We find no correlation between genomic and histological heterogeneity. However, we identify unifying features including the retention of fetal developmental transcripts across tissues, expression changes on chromosome 12p, and a conserved somatic evolutionary sequence of whole genome duplication followed by clonal diversification. While this pattern is preserved across all GCTs, the developmental timing of the duplication varies between prepubertal and postpubertal cases. In addition, tumours of younger children exhibit distinct substitution signatures which may lend themselves as potential biomarkers for risk stratification. Our findings portray the extensive diversification of GCT tissues and genetic subclones as randomly distributed, while identifying overarching transcriptional and genomic features. The molecular characterisation of germ cell tumours (GCT) is necessary to understand their development and histological diversification. Here, the authors use whole-genome and transcriptome sequencing of GCTs across distinct histologies to reveal their somatic evolution and clonal diversification, as well as identify several putative biomarkers for treatment stratification.