15 research outputs found
Association between ambient particulate matter concentration and fetal growth restriction stratified by maternal employment
Background
Fetal growth has been known to be associated with particulate matter (PM) air pollution during gestation. Given that regular working may deviate outdoor air pollution exposure, the association between air pollution and fetal growth restriction can be different across maternal working status. This study was to assess possible effect modification by maternal employment in the association between exposure to PM during pregnancy and fetal growth restriction.
Methods
Using hourly PM less than or equal to 10 and 2.5 μm in diameter (PM10 and PM2.5) regulatory monitoring data for 2001–2012 and 2008–2012, respectively, and birth certificate data for 2002–2012, we computed maternal exposures with district-level averages of PM10 and PM2.5 during one year before birth, entire pregnancy, and the 1st, 2nd and 3rd trimesters. The outcomes of fetal growth restriction were assessed by small for gestational age (SGA, weighted <10th percentile in the same gestational age) as well as low birth weight (LBW, < 2.5 kg) at term. We performed logistic regression to examine the association between PM and each of fetal growth restriction outcomes adjusting for individual risk factors. For effect modification by maternal employment, we estimated adjusted odds ratio (OR) of SGA or LBW for interquartile (IQR) increases in PM10 or PM2.5 stratified by employed and non-employed mothers. We also computed relative excess risk due to interaction (RERI) to investigate additive interaction.
Results
Among 824,011 singleton term births, 34.0% (279,856) were employed and 66.0% (544,155) were non-employed mothers. Proportions of LBW were 1.5% in employed and 1.6% in non-employed (P < 0.001). SGA occurred in 12.7% of employed and 12.8% of non- employed (P = 0.124) mothers. For non-employed mothers, we observed increased odds of SGA per IQR increase in PM10 for one year before birth (OR = 1.02, 95% confidence intervals (CI): 1.00–1.04, P = 0.028). ORs of SGA for full pregnancy period and the 3rd trimester were also positive but did not reach statistical significance. We did not observe positive association for PM2.5. RERI was not significant both for PM10 and PM2.5.
Conclusions
We did not observe evidence of effect modification by maternal employment in the association between ambient PM and fetal growth restriction. Future studies using more refined exposure measures should confirm this finding.This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2013R1A6A3A04059017, 2016R1D1A1B03933410, 2018R1A2B6004608 and 2018R1D1A1B07048821) and the National Cancer Center of Korea (NCC-1810220-01). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscrip
Transcriptional control of hydrogen peroxide homeostasis regulates ground tissue patterning in the Arabidopsis root
In multicellular organisms, including higher plants, asymmetric cell divisions (ACDs) play a crucial role in generating distinct cell types. The Arabidopsis root ground tissue initially has two layers: endodermis (inside) and cortex (outside). In the mature root, the endodermis undergoes additional ACDs to produce the endodermis itself and the middle cortex (MC), located between the endodermis and the pre-existing cortex. In the Arabidopsis root, gibberellic acid (GA) deficiency and hydrogen peroxide (H2O2) precociously induced more frequent ACDs in the endodermis for MC formation. Thus, these findings suggest that GA and H2O2 play roles in regulating the timing and extent of MC formation. However, details of the molecular interaction between GA signaling and H2O2 homeostasis remain elusive. In this study, we identified the PEROXIDASE 34 (PRX34) gene, which encodes a class III peroxidase, as a molecular link to elucidate the interconnected regulatory network involved in H2O2- and GA-mediated MC formation. Under normal conditions, prx34 showed a reduced frequency of MC formation, whereas the occurrence of MC in prx34 was restored to nearly WT levels in the presence of H2O2. Our results suggest that PRX34 plays a role in H2O2-mediated MC production. Furthermore, we provide evidence that SCARECROW-LIKE 3 (SCL3) regulates H2O2 homeostasis by controlling transcription of PRX34 during root ground tissue maturation. Taken together, our findings provide new insights into how H2O2 homeostasis is achieved by SCL3 to ensure correct radial tissue patterning in the Arabidopsis root
Bias-free solar hydrogen production at 19.8???mA???cm???2 using perovskite photocathode and lignocellulosic biomass
Solar hydrogen production is one of the ultimate technologies needed to realize a carbon-neutral, sustainable society. However, an energy-intensive water oxidation half-reaction together with the poor performance of conventional inorganic photocatalysts have been big hurdles for practical solar hydrogen production. Here we present a photoelectrochemical cell with a record high photocurrent density of 19.8???mA???cm???2 for hydrogen production by utilizing a high-performance organic???inorganic halide perovskite as a panchromatic absorber and lignocellulosic biomass as an alternative source of electrons working at lower potentials. In addition, value-added chemicals such as vanillin and acetovanillone are produced via the selective depolymerization of lignin in lignocellulosic biomass while cellulose remains close to intact for further utilization. This study paves the way to improve solar hydrogen productivity and simultaneously realize the effective use of lignocellulosic biomass
State-of-the-art methods for exposure-health studies: Results from the exposome data challenge event
The exposome recognizes that individuals are exposed simultaneously to a multitude of different environmental factors and takes a holistic approach to the discovery of etiological factors for disease. However, challenges arise when trying to quantify the health effects of complex exposure mixtures. Analytical challenges include dealing with high dimensionality, studying the combined effects of these exposures and their interactions, integrating causal pathways, and integrating high-throughput omics layers. To tackle these challenges, the Barcelona Institute for Global Health (ISGlobal) held a data challenge event open to researchers from all over the world and from all expertises. Analysts had a chance to compete and apply state-of-the-art methods on a common partially simulated exposome dataset (based on real case data from the HELIX project) with multiple correlated exposure variables (P > 100 exposure variables) arising from general and personal environments at different time points, biological molecular data (multi-omics: DNA methylation, gene expression, proteins, metabolomics) and multiple clinical phenotypes in 1301 mother–child pairs. Most of the methods presented included feature selection or feature reduction to deal with the high dimensionality of the exposome dataset. Several approaches explicitly searched for combined effects of exposures and/or their interactions using linear index models or response surface methods, including Bayesian methods. Other methods dealt with the multi-omics dataset in mediation analyses using multiple-step approaches. Here we discuss features of the statistical models used and provide the data and codes used, so that analysts have examples of implementation and can learn how to use these methods. Overall, the exposome data challenge presented a unique opportunity for researchers from different disciplines to create and share state-of-the-art analytical methods, setting a new standard for open science in the exposome and environmental health field
Variable Selection in Presence of Strong Collinearity with Application to Environmental Mixtures
Variable selection has become an essential element of high dimensional statistical modeling to yield parsimonious models while keeping high prediction accuracy. High dimensionality often induces collinearity problems. For instance, studies of environmental mixtures include a large number of pollutants that are strongly inter-correlated. Regularized variable selection methods such as LASSO are popular for statistical variable selection, however, these methods often do not perform well in presence of strong collinearity in terms of selection and prediction. To address these challenges a novel method, namely COrrelation LeaRNing for variable Selection (COLRNS), is developed that is based on iterative correlation learning for cluster detection and variable selection. The COLRNS is further extended to COLRNS Generalized Linear Model (COLRNS-GLM) to be applicable in a generalized linear regression setting. The performance of the methods is evaluated through an extensive set of simulations and real-world applications to environmental mixtures data. The results show that the methods effectively identify a set of influential predictors, improve prediction accuracy, and reduce error in parameter estimation in most simulation scenarios and data applications under strong collinearity in high dimensional data
IGF-1 Upregulates Biglycan and Decorin by Increasing Translation and Reducing ADAMTS5 Expression
Proteoglycan (PG) is a glycosaminoglycan (GAG)-conjugated protein essential for maintaining tissue strength and elasticity. The most abundant skin PGs, biglycan and decorin, have been reported to decrease as skin ages. Insulin-like growth factor-1 (IGF-1) is important in various physiological functions such as cell survival, growth, and apoptosis. It is well known that the serum level of IGF-1 decreases with age. Therefore, we investigated whether and how IGF-1 affects biglycan and decorin. When primary cultured normal human dermal fibroblasts (NHDFs) were treated with IGF-1, protein levels of biglycan and decorin increased, despite no difference in mRNA expression. This increase was not inhibited by transcription blockade using actinomycin D, suggesting that it is mediated by IGF-1-induced enhanced translation. Additionally, both mRNA and protein expression of ADAMTS5, a PG-degrading enzyme, were decreased in IGF-1-treated NHDFs. Knockdown of ADAMTS5 via RNA interference increased protein expression of biglycan and decorin. Moreover, mRNA and protein expression of ADAMTS5 increased in aged human skin tissues compared to young tissue. Overall, IGF-1 increases biglycan and decorin, which is achieved by improving protein translation to increase synthesis and preventing ADAMTS5-mediated degradation. This suggests a new role of IGF-1 as a regulator for biglycan and decorin in skin aging process
IGF-1 Upregulates Biglycan and Decorin by Increasing Translation and Reducing ADAMTS5 Expression
Proteoglycan (PG) is a glycosaminoglycan (GAG)-conjugated protein essential for maintaining tissue strength and elasticity. The most abundant skin PGs, biglycan and decorin, have been reported to decrease as skin ages. Insulin-like growth factor-1 (IGF-1) is important in various physiological functions such as cell survival, growth, and apoptosis. It is well known that the serum level of IGF-1 decreases with age. Therefore, we investigated whether and how IGF-1 affects biglycan and decorin. When primary cultured normal human dermal fibroblasts (NHDFs) were treated with IGF-1, protein levels of biglycan and decorin increased, despite no difference in mRNA expression. This increase was not inhibited by transcription blockade using actinomycin D, suggesting that it is mediated by IGF-1-induced enhanced translation. Additionally, both mRNA and protein expression of ADAMTS5, a PG-degrading enzyme, were decreased in IGF-1-treated NHDFs. Knockdown of ADAMTS5 via RNA interference increased protein expression of biglycan and decorin. Moreover, mRNA and protein expression of ADAMTS5 increased in aged human skin tissues compared to young tissue. Overall, IGF-1 increases biglycan and decorin, which is achieved by improving protein translation to increase synthesis and preventing ADAMTS5-mediated degradation. This suggests a new role of IGF-1 as a regulator for biglycan and decorin in skin aging process
Selective Electrochemical Depolymerization of Lignin in Lignocellulosic Biomass with Polyoxometalate Catalyst
Cox proportional hazards models with left truncation and time-varying coefficient: Application of age at event as outcome in cohort studies
When analyzing time-to-event cohort data, two different ways of choosing a time scale have been discussed in the literature: time-on-study or age at onset of disease. One advantage of choosing the latter is interpretability of the hazard ratio as a function of age. To handle the analysis of age at onset in a principled manner, we present an analysis of the Cox Proportional Hazards model with time-varying coefficient for left-truncated and right-censored data. In the analysis of Northern Manhattan Study (NOMAS) with age at onset of stroke as outcome, we demonstrate that well-established risk factors may be important only around a certain age span and less established risk factors can have a strong effect in a certain age span
Associations between fiber intake and Body Mass Index (BMI) among African-American women participating in a randomized weight loss and maintenance trial
Introduction African-American women are at increased risk for obesity, and therefore it is important to identify dietary factors that have the potential to prevent weight gainwithin this population. The purpose of the current study was to examine associations between daily fiber intake and Body Mass Index (BMI) over the course of an 18-month weight loss intervention for African-American women. Methods Anthropometric measures and the Block Food Frequency Questionnaire were administered at baseline, 6-month, and 18-month follow-up between 2008 and 2010. A mixed-effects linear regression model with random intercept and time slope was used to model associations between fiber consumption and BMI controlling for time trend. Results Associations between fiber consumption and BMI were significantly different over time (β̂Fiber∗Time=−0.07,p‐value=0.003 role= presentation style= box-sizing: border-box; margin: 0px; padding: 0px; display: inline-block; line-height: normal; font-size: 16.2px; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; position: relative; \u3e‐β̂Fiber∗Time=−0.07,p‐value=0.003). There was no association between fiber intake and BMI at baseline; however, there was a significant inverse relation between fiber consumption and BMI at 6 months, and the association was even stronger at 18 months. Conclusions Results from this study suggest that dietary fiber consumption may be particularly important within weight loss interventions tailored for African-American women