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Accurate specification of the error statistics required for data assimilation remains an ongoing challenge, partly because their estimation is an underdetermined problem that requires statistical assumptions. Even with the common assumption that background and observation errors are uncorrelated, the problem remains underdetermined. One natural question that could arise is as follows: can the increasing amount of overlapping observations or other datasets help to reduce the total number of statistical assumptions, or do they introduce more statistical unknowns? In order to answer this question, this paper provides a conceptual view on the statistical error estimation problem for multiple collocated datasets, including a generalized mathematical formulation, an illustrative demonstration with synthetic data, and guidelines for setting up and solving the problem. It is demonstrated that the required number of statistical assumptions increases linearly with the number of datasets. However, the number of error statistics that can be estimated increases quadratically, allowing for an estimation of an increasing number of error cross-statistics between datasets for more than three datasets. The presented generalized estimation of full error covariance and cross-covariance matrices between datasets does not necessarily accumulate the uncertainties of assumptions among error estimations of multiple datasets.

Object GRB 221009A is the brightest gamma-ray burst (GRB) detected in more than 50 yr of study. In this paper, we present observations in the X-ray and optical domains obtained by the GRANDMA Collaboration and the Insight Collaboration. We study the optical afterglow with empirical fitting using the GRANDMA+HXMT-LE data sets augmented with data from the literature up to 60 days. We then model numerically using a Bayesian approach, and we find that the GRB afterglow, extinguished by a large dust column, is most likely behind a combination of a large Milky Way dust column and moderate low-metallicity dust in the host galaxy. Using the GRANDMA+HXMT-LE+XRT data set, we find that the simplest model, where the observed afterglow is produced by synchrotron radiation at the forward external shock during the deceleration of a top-hat relativistic jet by a uniform medium, fits the multiwavelength observations only moderately well, with a tension between the observed temporal and spectral evolution. This tension is confirmed when using the augmented data set. We find that the consideration of a jet structure (Gaussian or power law), the inclusion of synchrotron self-Compton emission, or the presence of an underlying supernova do not improve the predictions. Placed in the global context of GRB optical afterglows, we find that the afterglow of GRB 221009A is luminous but not extraordinarily so, highlighting that some aspects of this GRB do not deviate from the global known sample despite its extreme energetics and the peculiar afterglow evolution.

This contribution addresses the characterization of the model-error covariance matrix from the new theoretical perspective provided by the parametric Kalman filter method which approximates the covariance dynamics from the parametric evolution of a covariance model. The classical approach to obtain the modified equation of a dynamics is revisited to formulate a parametric modelling of the model-error covariance matrix which applies when the numerical model is dissipative compared with the true dynamics. As an illustration, the particular case of the advection equation is considered as a simple test bed. After the theoretical derivation of the predictability-error covariance matrices of both the nature and the numerical model, a numerical simulation is proposed which illustrates the properties of the resulting model-error covariance matrix.

The parametric Kalman filter (PKF) is a computationally efficient alternative method to the ensemble Kalman filter. The PKF relies on an approximation of the error covariance matrix by a covariance model with a space–time evolving set of parameters. This study extends the PKF to nonlinear dynamics using the diffusive Burgers equation as an application, focusing on the forecast step of the assimilation cycle. The covariance model considered is based on the diffusion equation, with the diffusion tensor and the error variance as evolving parameters. An analytical derivation of the parameter dynamics highlights a closure issue. Therefore, a closure model is proposed based on the kurtosis of the local correlation functions. Numerical experiments compare the PKF forecast with the statistics obtained from a large ensemble of nonlinear forecasts. These experiments strengthen the closure model and demonstrate the ability of the PKF to reproduce the tangent linear covariance dynamics, at a low numerical cost.

This paper discusses assimilation experiments of methane (CH4) and nitrous oxide (N2O) profiles retrieved from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). Here we focus on data versions 6 and 7 provided by the ESA processor. These data sets have been assimilated by the Belgian Assimilation System for Chemical ObsErvations (BASCOE). The CH4 and N2O retrieved profiles can oscillate, especially in the tropical lower stratosphere. Using the averaging kernels of the observations and a background error covariance matrix, which has previously been calibrated, allows the system to partly remedy this issue and provide assimilated fields that are more regular vertically. In general, there is a good agreement between the BASCOE analyses and independent observations from ACE–FTS (CH4 and N2O) and MLS (N2O), demonstrating the general good quality of CH4 and N2O retrievals provided by MIPAS ESA. Nevertheless, this study also identifies two issues in these data sets. First, time series of the observations show unexpected discontinuities due to an abrupt change in the gain of MIPAS band B, generally occurring after the instrument decontamination. Since the calibration is performed weekly, the abrupt change in the gain affects the measurements until the subsequent calibration is performed. Second, the correlations between BASCOE analyses and independent observations are poor in the lower stratosphere, especially in the tropics, probably due to the presence of outliers in the assimilated data. In this region, we recommend using MIPAS CH4 and N2O retrievals with caution.

We compare two optimized chemical data assimilation systems, one based on the ensemble Kalman filter (EnKF) and the other based on four-dimensional variational (4D-Var) data assimilation, using a comprehensive stratospheric chemistry transport model (CTM). This work is an extension of the Belgian Assimilation System for Chemical ObsErvations (BASCOE), initially designed to work with a 4D-Var data assimilation. A strict comparison of both methods in the case of chemical tracer transport was done in a previous study and indicated that both methods provide essentially similar results. In the present work, we assimilate observations of ozone, HCl, HNO3, H2O and N2O from EOS Aura-MLS data into the BASCOE CTM with a full description of stratospheric chemistry. Two new issues related to the use of the full chemistry model with EnKF are taken into account. One issue is a large number of error variance parameters that need to be optimized. We estimate an observation error variance parameter as a function of pressure level for each observed species using the Desroziers method. For comparison purposes, we apply the same estimate procedure in the 4D-Var data assimilation, where both scale factors of the background and observation error covariance matrices are estimated using the Desroziers method. However, in EnKF the background error covariance is modelled using the full chemistry model and a model error term which is tuned using an adjustable parameter. We found that it is adequate to have the same value of this parameter based on the chemical tracer formulation that is applied for all observed species. This is an indication that the main source of model error in chemical transport model is due to the transport. The second issue in EnKF with comprehensive atmospheric chemistry models is the noise in the cross-covariance between species that occurs when species are weakly chemically related at the same location. These errors need to be filtered out in addition to a localization based on distance. The performance of two data assimilation methods was assessed through an 8-month long assimilation of limb sounding observations from EOS Aura MLS. This paper discusses the differences in results and their relation to stratospheric chemical processes. Generally speaking, EnKF and 4D-Var provide results of comparable quality but differ substantially in the presence of model error or observation biases. If the erroneous chemical modelling is associated with moderately fast chemical processes, but whose lifetimes are longer than the model time step, then EnKF performs better, while 4D-Var develops spurious increments in the chemically related species. If, however, the observation biases are significant, then 4D-Var is more robust and is able to reject erroneous observations while EnKF does not.

An ensemble Kalman filter (EnKF) assimilation method is applied to the tracer transport using the same stratospheric transport model as in the four-dimensional variational (4D-Var) assimilation system BASCOE (Belgian Assimilation System for Chemical ObsErvations). This EnKF version of BASCOE was built primarily to avoid the large costs associated with the maintenance of an adjoint model. The EnKF developed in BASCOE accounts for two adjustable parameters: a parameter α controlling the model error term and a parameter r controlling the observational error. The EnKF system is shown to be markedly sensitive to these two parameters, which are adjusted based on the monitoring of a χ2 test measuring the misfit between the control variable and the observations. The performance of the EnKF and 4D-Var versions was estimated through the assimilation of Aura-MLS (microwave limb sounder) ozone observations during an 8-month period which includes the formation of the 2008 Antarctic ozone hole. To ensure a proper comparison, despite the fundamental differences between the two assimilation methods, both systems use identical and carefully calibrated input error statistics. We provide the detailed procedure for these calibrations, and compare the two sets of analyses with a focus on the lower and middle stratosphere where the ozone lifetime is much larger than the observational update frequency. Based on the observation-minus-forecast statistics, we show that the analyses provided by the two systems are markedly similar, with biases less than 5% and standard deviation errors less than 10% in most of the stratosphere. Since the biases are markedly similar, they most probably have the same causes: these can be deficiencies in the model and in the observation data set, but not in the assimilation algorithm nor in the error calibration. The remarkably similar performance also shows that in the context of stratospheric transport, the choice of the assimilation method can be based on application-dependent factors, such as CPU cost or the ability to generate an ensemble of forecasts.

Multi-year objective analyses (OA) on a high spatiotemporal resolution for the warm season period (1 May to 31 October) for ground-level ozone and for fine particulate matter (diameter less than 2.5 microns (PM2.5)) are presented. The OA used in this study combines model outputs from the Canadian air quality forecast suite with US and Canadian observations from various air quality surface monitoring networks. The analyses are based on an optimal interpolation (OI) with capabilities for adaptive error statistics for ozone and PM2.5 and an explicit bias correction scheme for the PM2.5 analyses. The estimation of error statistics has been computed using a modified version of the Hollingsworth–Lönnberg (H–L) method. The error statistics are "tuned" using a χ2 (chi-square) diagnostic, a semi-empirical procedure that provides significantly better verification than without tuning. Successful cross-validation experiments were performed with an OA setup using 90% of data observations to build the objective analyses and with the remainder left out as an independent set of data for verification purposes. Furthermore, comparisons with other external sources of information (global models and PM2.5 satellite surface-derived or ground-based measurements) show reasonable agreement. The multi-year analyses obtained provide relatively high precision with an absolute yearly averaged systematic error of less than 0.6 ppbv (parts per billion by volume) and 0.7 μg m−3 (micrograms per cubic meter) for ozone and PM2.5, respectively, and a random error generally less than 9 ppbv for ozone and under 12 μg m−3 for PM2.5. This paper focuses on two applications: (1) presenting long-term averages of OA and analysis increments as a form of summer climatology; and (2) analyzing long-term (decadal) trends and inter-annual fluctuations using OA outputs. The results show that high percentiles of ozone and PM2.5 were both following a general decreasing trend in North America, with the eastern part of the United States showing the most widespread decrease, likely due to more effective pollution controls. Some locations, however, exhibited an increasing trend in the mean ozone and PM2.5, such as the northwestern part of North America (northwest US and Alberta). Conversely, the low percentiles are generally rising for ozone, which may be linked to the intercontinental transport of increased emissions from emerging countries. After removing the decadal trend, the inter-annual fluctuations of the high percentiles are largely explained by the temperature fluctuations for ozone and to a lesser extent by precipitation fluctuations for PM2.5. More interesting is the economic short-term change (as expressed by the variation of the US gross domestic product growth rate), which explains 37% of the total variance of inter-annual fluctuations of PM2.5 and 15% in the case of ozone.

The formulation of the background error covariances represented in the spectral space is discussed in the context of univariate assimilation relying on a grid point model, leaving out all the aspects of balances between the different control variables needed in meteorological assimilation. The spectral transform operations are discussed in the case of a spherical harmonics basis and we stress that there is no need for an inverse spectral transform and of a Gaussian grid. The analysis increments are thus produced directly on the model grid. The practice of producing analysis increments on a horizontal Gaussian grid and then interpolating to an equally spaced grid is also shown to produce a degradation of the analysis. The method discussed in this paper allows the implementation of separable and non-separable spatial correlations. The separable formulation has been implemented in the Belgian Assimilation System for Chemical ObsErvations (BASCOE) and its impact on the assimilation of O3 observed by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) is shown. To promote the use of this method by other non-meteorological variational systems and in particular chemistry, the Fortran code developed is made available to the community.

Natural hazards, due to climate change, are particularly damaging in urban areas because of interdependencies of their networks. So, urban resilience has to face up to climate risks. The most impacting phenomenon is the urban heat island (UHI) effect. The storage capacity of heat is depending on shapes of buildings, public spaces, spatial organization, transport or even industrial activities. So, adaptive strategies for improving urban climate could be possible in different ways. In the framework of the French project Resilis, this study characterises urban vulnerability and resilience in terms of energy needs of buildings and outside urban comfort according to the IPCC carbon dioxide emission scenarios B2 and A2 for the period 2050–2100 for 10 French cities. The evolutions of four climate indicators in terms of heating and cooling needs and number of hours when the temperature is above 28 °C are then obtained for each city to analyse climate risks and their impacts in urban environment.

In 2003, strong energetic particle precipitation (EPP) events occurred producing massive amounts of ionization which affected the polar region significantly perturbing its chemical state down to the middle stratosphere. These events and their effects are generally left unaccounted for in current models of stratospheric chemistry and large differences between observations and models are then noted. In this study, we use a coupled 3-D stratospheric dynamical-chemical model and assimilation system to ingest MIPAS temperature and chemical observations. The goal is to gain further understanding of assimilation and monitoring processes during EPP events and their impacts on the stratospheric polar chemistry. Moreover, we investigate the feasibility of assimilating valid "outlier" observations associated with such events. We use OmF (Observation minus Forecast) residuals as they filter out phenomena well reproduced by the model (such as gas phase chemistry, transport, diurnal and seasonal cycles) thus revealing a clear trace of the EPP. Inspection of OmF statistics in both passive (without chemical assimilation) and active (with chemical assimilation) cases altogether provides a powerful diagnostic tool to assess the model and assimilation system. We also show that passive OmF can permit a satisfactory evaluation of the ozone partial column loss due to EPP effects. Results suggest a small but significant loss of 5–6 DU (Dobson Units) during an EPP-IE (EPP Indirect Effects) event in the Antarctic winter of 2003, and about only 1 DU for the SPE (Solar Proton Event) of October/November 2003. Despite large differences between the model and MIPAS chemical observations (NO2, HNO3, CH4 and O3), we demonstrate that a careful assimilation with only gas phase chemistry included in the model (i.e. no provision for EPP) and with relaxed quality control nearly eliminated the short-term bias and significantly reduced the standard deviation error of the constituents below 1 hPa.

Study Objectives: Pre- and early adolescence are believed to constitute periods of important age-related changes in sleep. However, much of the research on these presumed developmental changes has used cross-sectional data or subjective measures of sleep, limiting the quality of the evidence. In addition, little is known about the development of certain features of the sleep-wake cycle pertaining to regularity (e.g. weekend-weekday differences and intra-individual variability) or circadian rhythms (e.g. sleep midpoint)., Methods: This study examined the sleep trajectories of 128 typically developing youth (69 girls) from ages 8 to 12 years on four sleep characteristics: sleep onset, sleep offset, total sleep time (TST), and sleep midpoint. For each of these characteristics, actigraphy-derived estimates of typical (i.e. mean) sleep and sleep regularity were obtained at each time point. Multilevel growth curves were modeled., Results: Overall, the sleep-wake cycle significantly changed between 8 and 12 years. Mean sleep onset, offset and midpoint exhibited an ascending curvilinear growth pattern that shifted later with age, while mean TST decreased linearly. Weekend-weekday differences (social jetlag) for sleep offset and midpoint became more pronounced each year. Weekday TST was longer than weekend TST, though this difference became smaller over time. Finally, intra-individual variability increased over time for all sleep characteristics, with variability in TST ascending curvilinearly. Important between-person and sex differences were also observed., Conclusion: This study reveals the marked changes that occur in the sleep of typically developing pre- and early adolescents. We discuss the potential implications of these trajectories., (© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

We used a large national cohort in Canada to assess the incidence of acute myocardial infarction (AMI) and stroke hospitalizations in association with long-term exposure to fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ). The study population comprised 2.7 million respondents from the 2006 Canadian Census Health and Environment Cohort (CanCHEC), followed for incident hospitalizations of AMI or stroke between 2006 and 2016. We estimated 10-year moving average estimates of PM 2.5 , NO 2 , and O 3 , annually. We used Cox proportional hazards models to examine the associations adjusting for various covariates. For AMI, each interquartile range (IQR) increase in exposure was found to be associated with a hazard ratio of 1.026 (95% CI: 1.007-1.046) for PM 2.5 , 1.025 (95% CI: 1.001-1.050) for NO 2 , and 1.062 (95% CI: 1.041-1.084) for O 3 , respectively. Similarly, for stroke, an IQR increase in exposure was associated with a hazard ratio of 1.078 (95% CI: 1.052-1.105) for PM 2.5 , 0.995 (95% CI: 0.965-1.030) for NO 2 , and 1.055 (95% CI: 1.028-1.082) for O 3 , respectively. We found consistent evidence of positive associations between long-term exposures to PM 2.5 , and O 3 , and to a lesser degree NO 2 , with incident AMI and stroke hospitalizations., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Owing to their greater outdoor activity and ongoing lung development, children are particularly vulnerable to the harmful effects of exposure to fine particulate matter (PM 2.5 ) . However, the effects of PM 2.5 components are poorly understood. This study aimed to use a longitudinal birth cohort of children with physician-diagnosed incident asthma to investigate the effect of PM 2.5 components at birth on morbidity measured by health services utilization. Of 1277 Toronto Child Health Evaluation Questionnaire (T-CHEQ) participants, the study population included 362 children diagnosed with asthma who were followed for a mean of 13 years from birth until March 31, 2016, or loss-to-follow-up. Concentrations of PM 2.5 and its components were assigned based on participants' postal codes at birth. Study outcomes included counts of asthma, asthma-related, and all-cause health services use. Poisson regression in single-, two-, and multi-pollutant models was used to estimate rate ratios (RR) per interquartile range (IQR) increase of exposures. Covariates were included in all models to further adjust for potential confounding. The adjusted RR for sulfate (SO 4 ) and all-cause hospitalizations was statistically significant with RR = 2.23 (95% confidence interval [CI]: 1.25-3.96) in a multi-pollutant model with nitrogen dioxide (NO 2 ) and ozone (O 3 ). In multi-pollutant models with oxidants, the adjusted RRs for SO 4 of all-cause hospitalizations and emergency department (ED) visits were also statistically significant with RR = 2.31 (95% CI: 1.32-4.03) and RR = 1.39 (95% CI: 1.02-1.90), respectively. While unadjusted single-pollutant RRs for asthma-specific and asthma-related health services use with the SO 4 component of PM 2.5 were above one, none were statistically significant. This study found significant associations with exposure to SO 4 in PM 2.5 and all-cause acute care, chiefly for hospitalizations, in children with asthma., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Individual and neighbourhood-scale socioeconomic characteristics modify associations between exposure to air pollution and mortality. The role of stress, which may integrate effects of social and environmental exposures on health, is unknown. We examined whether an individual's perspective on their own well-being, as assessed using self-rated measures of stress and health, modifies the pollutant-mortality relationship., Methods: The Canadian Community Health Survey (CCHS)-mortality cohort includes respondents from surveys administered between 2001 and 2012 linked to vital statistics and postal codes from 1981 until 2016. Annual fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ) exposure estimates were attached to a sample of cohort members aged 30-89 years (n = 398,300 respondents/3,848,400 person-years). We examined whether self-rated stress, distress, mental health, and general health modified associations between long-term exposure to each pollutant (three-year moving average with one-year lag) and non-accidental mortality using Cox survival models, adjusted for individual- (i.e. socioeconomic and behavioural) and neighbourhood-scale covariates., Results: In fully-adjusted models, the relationship between exposure to pollutants and mortality was stronger among those with poor self-rated mental health, including a significant difference for NO 2 (hazard ratio (HR) = 1.15, 95% CI 1.06-1.25 per IQR) compared to those with very good/excellent mental health (HR = 1.05, 95% CI 1.01-1.08; Cochran's Q = 4.01; p < 0.05). Poor self-rated health was similarly associated with higher pollutant-associated HRs, but only in unadjusted models. Stress and distress did not modify pollutant-mortality associations., Conclusions: Poor self-rated mental and general health were associated with increased mortality attributed to exposure to ambient pollutants., (Crown Copyright © 2020. Published by Elsevier Inc. All rights reserved.)

Post-translational covalent modifications of histones play important roles in modulating chromatin structure and are involved in the control of multiple developmental processes in plants. Here we provide insight into the contribution of the histone lysine methyltransferase SET DOMAIN GROUP 8 (SDG8), implicated in histone H3 lysine 36 trimethylation (H3K36me3), in connection with RNA polymerase II (RNAPII) to enhance Arabidopsis immunity. We showed that even if the sdg8-1 loss-of-function mutant, defective in H3K36 methylation, displayed a higher sensitivity to different strains of the bacterial pathogen Pseudomonas syringae , effector-triggered immunity (ETI) still operated, but less efficiently than in the wild-type (WT) plants. In sdg8-1 , the level of the plant defense hormone salicylic acid (SA) was abnormally high under resting conditions and was accumulated similarly to WT at the early stage of pathogen infection but quickly dropped down at later stages. Concomitantly, the transcription of several defense-related genes along the SA signaling pathway was inefficiently induced in the mutant. Remarkably, albeit the defense genes PATHOGENESIS-RELATED1 ( PR1 ) and PR2 have retained responsiveness to exogenous SA, their inductions fade more rapidly in sdg8-1 than in WT. At chromatin, while global levels of histone methylations were found to be stable, local increases of H3K4 and H3K36 methylations as well as RNAPII loading were observed at some defense genes following SA-treatments in WT. In sdg8-1 , the H3K36me3 increase was largely attenuated and also the increases of H3K4me3 and RNAPII were frequently compromised. Lastly, we demonstrated that SDG8 could physically interact with the RNAPII C-terminal Domain, providing a possible link between RNAPII loading and H3K36me3 deposition. Collectively, our results indicate that SDG8, through its histone methyltransferase activity and its physical coupling with RNAPII, participates in the strong transcriptional induction of some defense-related genes, in particular PR1 and PR2 , to potentiate sustainable immunity during plant defense response to bacterial pathogen., (Copyright © 2020 Zhang, Ménard, Li, Coruzzi, Heitz, Shen and Berr.)

Rationale: There is growing evidence that air pollution may contribute to the development of childhood asthma and other allergic diseases. In this follow-up of the Toronto Child Health Evaluation Questionnaire (T-CHEQ) study, we examined associations between early life exposures to air pollution and incidence of asthma, allergic rhinitis and eczema from birth through adolescence., Methods: 1286 T-CHEQ participants were followed from birth until outcome (March 31, 2016) or loss to follow-up, with a mean of 17 years of follow-up. Concentrations of nitrogen dioxide (NO 2 ), ozone (O 3 ) and particulate matter with a 50% cut-off aerodynamic diameter of 2.5 µm (PM 2.5 ) from January 1, 1999 to December 31, 2012 were assigned to participants based on their postal codes at birth using ground observations, chemical/meteorological models, remote sensing and land-use regression models. Study outcomes included incidence of physician-diagnosed asthma, allergic rhinitis and eczema. Cox proportional hazard regression models were used to estimate hazard ratios per interquartile range of exposures and outcomes, adjusting for potential confounders., Results: Hazard ratios of 1.17 (95% CI 1.05-1.31) for asthma and 1.07 (95% CI 0.99-1.15) for eczema were observed for total oxidants (O 3 and NO 2 ) at birth. No significant increase in risk was found for PM 2.5 ., Conclusions: Exposures to oxidant air pollutants (O 3 and NO 2 ) but not PM 2.5 were associated with an increased risk of incident asthma and eczema in children. This suggests that improving air quality may contribute to the prevention of asthma and other allergic disease in childhood and adolescence., Competing Interests: Conflict of interest: T. To has nothing to disclose. Conflict of interest: J. Zhu has nothing to disclose. Conflict of interest: D. Stieb has nothing to disclose. Conflict of interest: N. Gray has nothing to disclose. Conflict of interest: I. Fong has nothing to disclose. Conflict of interest: L. Pinault has nothing to disclose. Conflict of interest: M. Jerrett reports grants from Health Canada, during the conduct of the study. Conflict of interest: A. Robichaud has nothing to disclose. Conflict of interest: R. Ménard has nothing to disclose. Conflict of interest: A. van Donkelaar has nothing to disclose. Conflict of interest: R.V. Martin reports grants from Health Canada, during the conduct of the study. Conflict of interest: P. Hystad has nothing to disclose. Conflict of interest: J.R. Brook has nothing to disclose. Conflict of interest: S. Dell has nothing to disclose., (The content of this work is copyright of the authors or their employers. Design and branding are copyright ©ERS 2020.)

Artemisinin is the most widely-used compound against malaria and plays a critical role in the treatment of malaria worldwide. Resistance to artemisinin emerged about a decade ago in Southeast Asia and it is paramount to prevent its spread or emergence in Africa. Artemisinin has a complex mode of action and can cause widespread injury to many components of the parasite. In this review, we outline the different metabolic pathways affected by artemisinin, including the unfolded protein response, protein polyubiquitination, proteasome, phosphatidylinositol-3-kinase, and the eukaryotic translation initiation factor 2α. Based on recently published data, we present a model of how these different pathways interplay and how mutations in K13, the main identified resistance marker, may help parasites survive under artemisinin pressure., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Objectives: To estimate the proportion of the Canadian population that is more susceptible to adverse effects of ozone (O 3 ) and fine particle (PM 2.5 ) air pollution exposure and how this varies by health region alongside ambient concentrations of O 3 and PM 2.5 ., Methods: Using data from the census, the Canadian Community Health Survey, vital statistics and published literature, we generated cross-sectional estimates for 2014 of the proportions of the Canadian population considered more susceptible due to age, chronic disease, pregnancy, outdoor work, socio-economic status, and diet. We also estimated 2010-2012 average concentrations of O 3 and PM 2.5 . Analyses were conducted nationally and for 110 health regions., Results: Restrictive criteria (age < 10 or ≥ 75; asthma, chronic obstructive pulmonary disease, heart disease, or diabetes; pregnancy) suggested that approximately one third of the Canadian population is more susceptible, while inclusive criteria (restrictive plus age 10-19 and 65-74, outdoor work, less than high school education, low vitamin C intake) increased this proportion to approximately two thirds. Across health regions, estimates ranged from 24.4% to 41.2% (restrictive) and 61.2% to 87.0% (inclusive). Ten health regions were in the highest quartile of both population susceptibility and O 3 or PM 2.5 concentrations, all of which were outside major urban centres., Conclusions: A substantial proportion of the Canadian population exhibits at least one risk factor that increases their susceptibility to adverse effects of O 3 and PM 2.5 exposure. Both risk communication and management interventions need to be increasingly targeted to regions outside large urban centres in the highest quartiles of both susceptibility and exposure.

Vaccines that target the preerythrocytic phase of malaria hold great promise as elimination tools since they are the sole vaccines that can achieve sterile protection against a challenge. This chapter focuses on preerythrocytic stage vaccines based on live attenuated parasites. It first summarizes the main conclusions that have emerged from studies in rodents, which compared various parasite attenuation methods, and then presents the vaccination regimens that are currently being tested in humans.

Background: Diabetes is infrequently coded as the primary cause of death but may contribute to cardiovascular disease (CVD) mortality in response to fine particulate matter (PM2.5) exposure. We analyzed all contributing causes of death to examine susceptibility of diabetics to CVD mortality from long-term exposure., Methods: We linked a subset of the 2001 Canadian Census Health and Environment Cohort (CanCHEC) with 10 years of follow-up to all causes of death listed on death certificates. We used survival models to examine the association between CVD deaths (n = 123,500) and exposure to PM2.5 among deaths that co-occurred with diabetes (n = 20,600) on the death certificate. More detailed information on behavioral covariates and diabetes status at baseline available in the Canadian Community Health Survey (CCHS)-mortality cohort (n = 12,400 CVD deaths, with 2,800 diabetes deaths) complemented the CanCHEC analysis., Results: Among CanCHEC subjects, comention of diabetes on the death certificate increased the magnitude of association between CVD mortality and PM2.5 (HR = 1.51 [1.39-1.65] per 10 μg/m) versus all CVD deaths (HR = 1.25 [1.21-1.29]) or CVD deaths without diabetes (HR = 1.20 [1.16-1.25]). Among CCHS subjects, diabetics who used insulin or medication (included as proxies for severity) had higher HR estimates for CVD deaths from PM2.5 (HR = 1.51 [1.08-2.12]) relative to the CVD death estimate for all respondents (HR = 1.31 [1.16-1.47])., Conclusions: Mention of diabetes on the death certificate resulted in higher magnitude associations between PM2.5 and CVD mortality, specifically among those who manage their diabetes with insulin or medication. Analyses restricted to the primary cause of death likely underestimate the role of diabetes in air pollution-related mortality. See video abstract at, http://links.lww.com/EDE/B408.