Longer Lag Research Articles

Alpha-synuclein seed amplification assay longitudinal outcomes in Lewy body disease spectrum.

Evidence from neuropathological cohorts indicates that a CSF α-synuclein (α-syn) seed amplification assay (SAA) may provide quantitative kinetic parameters correlating with α-syn pathology burden in patients with Lewy body disease (LBD). Studies are needed to assess their longitudinal trend during the pre-symptomatic and clinical disease phases and their correlation with measures of disease progression. We aimed to assess the baseline α-syn CSF SAA kinetic parameters, their longitudinal variations and associations with clinical outcomes in a cohort of longitudinally repeatedly sampled Lewy Body disease patients, including clinically unimpaired (asymptomatic LBD) and neurologically impaired individuals. Participants from the prospective BioFINDER-1 study with longitudinal CSF collections (n=718) were screened by α-syn SAA. CSF samples were tested in four replicates blinded to clinical diagnoses. The number of positive replicates (Nrep), the time needed by the fluorescence signal to reach the threshold (Lag) and the highest intensity of the fluorescent signal (Imax). were analysed at baseline (time of first positive SAA) in all participants and longitudinally in those with at least two α-syn positive CSF samples available. One hundred ninety-six individuals (whole cohort) showing α-syn seeding activity were included. Of those, 170 participants tested positive by SAA in all available samples, while 26 converted from a negative to a positive test result during follow-up (LBD-converters), suggesting an early LBD stage. At baseline, LBD-converters showed lower Nrep (p=0.001) and a longer Lag (p=0.001) than subjects displaying α-syn seeding activity from the first available sample. Nrep increased longitudinally in the whole cohort (β=0.09, 95% confidence interval (95%CI) 0.06-0.12, p<0.001), in asymptomatic LBD (β=0.15, 95%CI 0.09-0.21, p<0.001) and Parkinson's disease individuals without dementia (β=0.07, 95%CI 0.02-0.12, p=0.01). The Lag decreased longitudinally in asymptomatic LBD (β=-0.24, 95%CI -0.42 - -0.06, p=0.008). Baseline Nrep predicted the subsequent appearance of dementia in the whole cohort (Hazard ratio (HR) 1.57, 95%CI 1.19-2.07, p=0.001) and the Parkinson's disease subgroup (HR 1.83, 95%CI 1.17-2.85, p=0.008). The difference between the Lag at each sampling and that at baseline was negatively associated with the appearance of dementia in the whole cohort (HR 0.76, 95%CI 0.59-0.99, p=0.04) and Parkinson's disease subgroup (HR 0.69, 95%CI 0.50-0.95, p=0.02). α-syn SAA parameters Nrep and Lag showed associations with the LBD stage and the development of dementia. Furthermore, their longitudinal variation is coherent with pathology progression over time. These data support the use of SAA kinetic parameters to monitor disease progression and therapeutic response.

A Dynamic Analysis of Sustainable Economic Growth and FDI Inflow in Saudi Arabia Using ARDL Approach and VECM Technique

This study investigates the relationship between sustainable economic growth and foreign direct investment (FDI) in Saudi Arabia from 1980 to 2023. The ARDL approach and VECM technique are employed to analyze the short-run and long-run dynamics. The short-run results show mixed effects. Sustainable economic growth has a positive impact on current and one-period lagged FDI but a negative impact on the two periods lagged. Trade openness and infrastructure negatively affect FDI in the short run. Interestingly, oil rents and real economic growth also have negative short-run impacts on FDI, but these effects become positive with a longer lag. Long-run analysis reveals a negative relationship between trade openness, infrastructure, and oil rents with FDI, suggesting a potential crowding-out effect. Trade openness has a positive long-run impact on most variables, including sustainable growth, FDI, real growth, and CO2 emissions. Oil rents also have a positive long-run impact on these variables. This study finds six bidirectional causal relationships in the short run, primarily between trade openness, infrastructure, oil rents, and FDI. Unidirectional causality runs from oil rents, trade openness, exchange rate, sustainable growth, and real growth to FDI and infrastructure. Additionally, CO2 emissions cause FDI, and trade openness causes sustainable growth. While sustainable economic growth benefits FDI in the long run, short-term policies regarding trade openness and infrastructure require reevaluation. Oil revenue and real economic growth may initially deter FDI, but this reverses in the long term. To attract sustainable FDI, policymakers should focus on long-term economic growth strategies and consider reforms in trade and infrastructure policies. A comprehensive FDI strategy that moves beyond oil dependence and leverages trade openness is crucial to long-term economic diversification.

Consumption of milk and other dairy products and incidence of Parkinson's disease: a prospective cohort study in French women.

Previous studies showed positive associations between milk intake and Parkinson's disease (PD) in men but not in women, but few studies were available in women. Due to the long prodromal PD phase, reverse causation represents a major threat to investigations of diet in PD; cohort studies with a long follow-up are needed. We investigated associations between intake of milk and other dairy products with PD incidence in women from the E3N cohort study (1993-2018). PD diagnoses were validated using medical records and drug claim databases. Diet was assessed via a dietary questionnaire. Hazard ratios (HR) were estimated using multivariable Cox regression models. Exposures were lagged by 5y in main analyses and longer lags in sensitivity analyses. We examined the impact of adjustment for premotor symptoms (constipation/depression). During a mean follow-up of 18.8y, 845 of 71,542 women developed PD. Main analyses showed a J-shaped association between total milk intake and PD (P-non linearity = 0.045), with a significant linear positive association among drinkers (HR/1-SD = 1.09, 95% CI = 1.01-1.18, P = 0.024), that was explained in secondary analyses by a different pattern of association for plain milk (alone or with cereals) and milk added to drinks (tea/coffee/chicory). PD incidence increased significantly with plain milk consumption (HR/1-SD = 1.08 [1.02-1.14], P = 0.014). A U-shaped relation was observed for milk added to drinks (P-non linearity = 0.038), with lower PD incidence in women with moderate consumption (HR = 0.77 [0.61-0.97], P = 0.030) and no difference between non-drinkers and those with the highest consumption (HR = 0.98 [0.79-1.21], P = 0.848). Findings were similar in analyses using longer lags and adjusted for constipation/depression. Consumption of other dairy products was not associated with PD. A J-shaped association between total milk intake and PD was explained by a different pattern of association for plain milk intake and milk added to drinks. Reverse causation is unlikely to explain a positive association of plain milk with PD incidence in women. The U-shaped relation for milk added to drinks could be explained by an interaction between milk and coffee/tea/chicory. Further studies are warranted to elucidate the underlying mechanisms.

What drives the variability in AGN? Explaining the UV-Xray disconnect through propagating fluctuations

ABSTRACT Intensive broad-band reverberation mapping campaigns have shown that AGN variability is significantly more complex than expected from disc reverberation of the variable X-ray illumination. The UV/optical variability is highly correlated and lagged, with longer lags at longer wavelengths as predicted, but the observed time-scales are longer than expected. Worse, the UV/optical light curves are not well correlated with the X-rays, which should drive them. Instead, we consider an intrinsically variable accretion disc, where slow mass accretion rate fluctuations are generated in the optical-UV disc, propagating down to modulate intrinsically faster X-ray variability from the central regions. We match our model to Fairall 9, a well-studied AGN with L ∼ 0.1LEdd, where the spectrum is dominated by the UV/EUV. Our model produces light curves where the X-rays and UV have very different fast variability, yet are well correlated on longer time-scales, as observed. It predicts that the intrinsic variability has optical/UV leading the X-rays, but including reverberation of the variable EUV from an inner wind produces a lagged bound-free continuum that matches the observed UV-optical lags. We conclude that optical/UV AGN variability is likely driven by intrinsic fluctuations within the disc, not X-ray reprocessing: the observed longer than expected lags are produced by reverberation of the EUV illuminating a wind, not by X-ray illumination of the disc: the increasing lag with increasing wavelength is produced by the increased contribution of the (constant lag) bound-free continuum to the spectrum, rather than indicating intrinsically larger reverberation distances for longer wavelengths.

Real-World Data Quality Framework for Oncology Time to Treatment Discontinuation Use Case: Implementation and Evaluation Study.

The importance of real-world evidence is widely recognized in observational oncology studies. However, the lack of interoperable data quality standards in the fragmented health information technology landscape represents an important challenge. Therefore, adopting validated systematic methods for evaluating data quality is important for oncology outcomes research leveraging real-world data (RWD). This study aims to implement real-world time to treatment discontinuation (rwTTD) for a systemic anticancer therapy (SACT) as a new use case for the Use Case Specific Relevance and Quality Assessment, a framework linking data quality and relevance in fit-for-purpose RWD assessment. To define the rwTTD use case, we mapped the operational definition of rwTTD to RWD elements commonly available from oncology electronic health record-derived data sets. We identified 20 tasks to check the completeness and plausibility of data elements concerning SACT use, line of therapy (LOT), death date, and length of follow-up. Using descriptive statistics, we illustrated how to implement the Use Case Specific Relevance and Quality Assessment on 2 oncology databases (Data sets A and B) to estimate the rwTTD of an SACT drug (target SACT) for patients with advanced head and neck cancer diagnosed on or after January 1, 2015. A total of 1200 (24.96%) of 4808 patients in Data set A and 237 (5.92%) of 4003 patients in Data set B received the target SACT, suggesting better relevance of the former in estimating the rwTTD of the target SACT. The 2 data sets differed with regard to the terminology used for SACT drugs, LOT format, and target SACT LOT distribution over time. Data set B appeared to have less complete SACT records, longer lags in incorporating the latest data, and incomplete mortality data, suggesting a lack of fitness for estimating rwTTD. The fit-for-purpose data quality assessment demonstrated substantial variability in the quality of the 2 real-world data sets. The data quality specifications applied for rwTTD estimation can be expanded to support a broad spectrum of oncology use cases.

Effects of Meteorological Factors on Asthma Hospital Visits in Haikou City, China

The effects of meteorological conditions on asthma in Haikou, a tropical city in China, are still unclear. This study aimed to determine the relationships between meteorological factors and the number of asthma hospital visits in Haikou. A Poisson generalized additive model combined with a distributed lag nonlinear model is used to model the nonlinear exposure–response relationship between the daily mean temperature and asthma hospital visits. The daily mean pressure and air quality are used as covariates and simultaneously control the mixed effects of holiday effects, weekend effects, and long-term trends. The results indicate that there is a significant statistical relationship between the daily mean temperature and asthma hospital visits, which shows an inverted J-shaped relationship. When the daily mean temperature is below the reference value (29.3 °C), the number of asthma patients increases considerably, and there is a marked lag in the prevalence of asthma. The longest lag is 9 days, and the most pronounced impact of the daily mean temperature on the number of asthma hospital visits can be found when the lag time is 1–4 days. When the daily mean temperature is 10 °C, the cumulative effect of the relative risk of asthma is 2.204, an increase of 120.4% (95% CI 1.294–3.755). If the daily mean temperature is below the 2.5th percentile value (14.8 °C), the relative risk significantly increases by more than 5.3% (95% CI 1.000–1.110), and the longest lasting impact time is 5 days. This indicates that increases in asthma hospital visits in Haikou, China, are significantly correlated with low-temperature weather. We suggest that preventive measures for asthma should take low-temperature weather into account. Additionally, we also found that extremely high temperatures have a certain impact on the increase in asthma hospital visits, but that the correlation is not significant.

Influence of air pollution on NSTEMI incidence and acute coronary syndrome mortality - the 10-year community-level analysis including 80 million patient-years. EP-PARTICLES study

Abstract Introduction During the last years, air pollution has emerged as an important modifiable cardiovascular risk factor. Most research focused on heavy-polluted agglomerations and big cities, neglecting its influence on cardiovascular health in smaller cities and villages. Purpose The study aimed to assess the spatio-temporal trends and the influence of air pollution on the non-ST-elevation myocardial infarction (NSTEMI) incidence and acute coronary syndrome (ACS) mortality in an urban and rural environment. Moreover, the study aimed to investigate whether there is a connection between the influence of air pollution on hospitalization and cause-specific mortality. Methods The analysis included data on 7 main air pollutants in 709 communities in Eastern Poland in 2011-2020. Mortality data were obtained from National Health Fund and daily air pollution concentrations for each community were obtained from National Public Health Institute. Time-stratified panel data Poisson regression techniques were used. The influence of each air pollutant was analysed at a single-day lag (0-6 days) and multi-day lag (0-1, 0-6, 0-30 days) and presented as an odds ratio (OR) with a 95% confidence interval (CI) for an increase in 10 μg/m3. Results Incidence of NSTEMI was associated with exposition to benzo-a-pyrene (BaP) on all analysed lag patterns (OR 1.121, 95% CI 1.075-1.168 for lag 0, OR 1.241, 95% CI 1.169-1.317 for lag 0-30) and to particulate matter with a diameter of &amp;lt;10 and &amp;lt;2.5 μm (PM10, PM2.5), CO and NO2 on the most of analysed lag patterns (OR 1.01, 95% CI 1.005-1.015 for PM10 on lag 0, OR 1.013, 95% CI 1.007-1.02 for PM2.5 on lag 0, OR 1.017, OR 1.002, 95% CI 1.001-1.003 for CO on lag 0, 95% CI 1.007-1.028 for NO2 on lag 0). O3 and SO2 had a protective influence on NSTEMI incidence on longer lags (OR 0.984, 95% CI 0.977-0.992 for O3 on lag 0-30, OR 0.978, 95% CI 0.963-0.993 for SO2 on lag 5) Mortality due to the ACS was associated with an increase in NO2 and CO concentrations on all lag patterns (OR 1.03, 95% CI 1.02-1.04 for NO2 on lag 0, OR 1.089, 95% CI 1.068-1.11 for NO2 on lag 0-30, OR 1.003, 95% CI 1.002-1.004 for CO on lag 0, OR 1.089, 95% CI 1.068-1.11 for CO on lag 0-30). PMs concentrations had a protective effect on ACS mortality on all lag patterns (OR 0.971, 95% CI 0.966-0.976 for PM10 on lag 0, OR 0.964, 95% CI 0.958-0.971 for PM2.5 on lag 0). Conclusions An increase in most of the major air pollutants concentrations have an influence on NSTEMI incidence. Different lag patterns for air pollutants suggest various mechanisms of detrimental effect. Cause-specific mortality analysis showed the results mostly opposite to incidence analysis. It suggests that a high rate of garbage codes may prevent high-quality population analysis focusing on cause-specific mortality. The development of air quality monitoring stations and the correct use of ICD-10 diagnoses may be crucial in drawing important conclusions from environmental studies.

The predictive effect of risk aversion on oil returns under different market conditions

This paper uses a new risk aversion index to investigate the predictive effect of risk aversion on oil returns under different market conditions. Moreover, we assess whether the US partisan conflict shapes the prediction of risk aversion for oil returns. Based on the quantile regressions of oil returns on lagged risk aversion changes, we find that risk aversion negatively predicts oil returns after oil financialization, and such a predictive effect is stronger under bearish market conditions. Also, we find that the negative predictive effect of risk aversion is weaker with increasing lags in bearish stages, but this negative effect does not last in bullish stages and even becomes positive at a longer lag. Finally, we find that the US partisan conflict mitigates the negative predictive effect of risk aversion on oil returns in the post-financialization period, and this mitigation is stronger in upward market conditions. Our findings provide novel insight into the determinants of oil prices from the perspective of investors' risk appetite.

Acute Effects of Ambient Air Pollution on Asthma Emergency Department Visits in Ten U.S. States.

Previous studies of short-term ambient air pollution exposure and asthma morbidity in the United States have been limited to a small number of cities and/or pollutants and with limited consideration of effects across ages. To estimate acute age group-specific effects of fine and coarse particulate matter (PM), major PM components, and gaseous pollutants on emergency department (ED) visits for asthma during 2005-2014 across the United States. We acquired ED visit and air quality data in regions surrounding 53 speciation sites in 10 states. We used quasi-Poisson log-linear time-series models with unconstrained distributed exposure lags to estimate site-specific acute effects of air pollution on asthma ED visits overall and by age group (1-4, 5-17, 18-49, 50-64, and y), controlling for meteorology, time trends, and influenza activity. We then used a Bayesian hierarchical model to estimate pooled associations from site-specific associations. Our analysis included asthma ED visits. We observed positive associations for multiday cumulative exposure to all air pollutants examined [e.g., 8-d exposure to : rate ratio of 1.016 with 95% credible interval (CI) of (1.008, 1.025) per increase, : 1.014 (95% CI: 1.007, 1.020) per increase, organic carbon: 1.016 (95% CI: 1.009, 1.024) per increase, and ozone: 1.008 (95% CI: 0.995, 1.022) per increase]. and ozone showed stronger effects at shorter lags, whereas associations of traffic-related pollutants (e.g., elemental carbon and oxides of nitrogen) were generally stronger at longer lags. Most pollutants had more pronounced effects on children ( y old) than adults; had strong effects on both children and the elderly ( y old); and ozone had stronger effects on adults than children. We reported positive associations between short-term air pollution exposure and increased rates of asthma ED visits. We found that air pollution exposure posed a higher risk for children and older populations. https://doi.org/10.1289/EHP11661.

Stringent response ensures the timely adaptation of bacterial growth to nutrient downshift

Timely adaptation to nutrient downshift is crucial for bacteria to maintain fitness during feast and famine cycle in the natural niche. However, the molecular mechanism that ensures the timely adaption of bacterial growth to nutrient downshift remains poorly understood. Here, we quantitatively investigated the adaptation of Escherichia coli to various kinds of nutrient downshift. We found that relA deficient strain, which is devoid of stringent response, exhibits a significantly longer growth lag than wild type strain during adapting to both amino acid downshift and carbon downshift. Quantitative proteomics show that increased (p)ppGpp level promotes the growth adaption of bacteria to amino acid downshift via triggering the proteome resource re-allocation from ribosome synthesis to amino acid biosynthesis. Such type of proteome re-allocation is significantly delayed in the relA-deficient strain, which underlies its longer lag than wild type strain during amino acid downshift. During carbon downshift, a lack of stringent response in relA deficient strain leads to disruption of the transcription-translation coordination, thus compromising the transcription processivity and further the timely expression of related catabolic operons for utilizing secondary carbon sources. Our studies shed light on the fundamental strategy of bacteria to maintain fitness under nutrient-fluctuating environments.

Apparent Temperature Modifies the Effects of Air Pollution on Cardiovascular Disease Mortality in Cape Town, South Africa

Cardiovascular disease (CVD) is the top cause of mortality and a main contributor to disability globally. The evidence so far is varied on whether cold or heat modifies the CVD effects of air pollution. Weather conditions and air pollution sources and levels are different in different countries. Studies in low-and middle-income countries are lacking. Mortality data were obtained from Statistics South Africa. Air pollution and meteorological data were obtained from the South African Weather Service. A time-stratified case–crossover epidemiological design was applied. The association between air pollutants (PM10, NO2 and SO2) and CVD mortality was investigated using conditional logistic regression models. Susceptibility by sex and age groups was investigated. In total, 54,356 CVD deaths were included in the 10-year study. The daily PM10, NO2 and SO2 levels exceeded the daily WHO guidelines on 463, 421 and 8 days of the 3652 days, respectively. Higher air pollution risks were observed in this study compared to those reported in meta-analyses. In general, the elderly and females seemed to be vulnerable to air pollutants, especially at high and moderate apparent temperature levels. Harvesting effects were observed at longer lags. The results can be used to develop an early warning system for the city.

Air pollution and dementia using longitudinal electronic health record data from the Indian Health Service

AbstractBackgroundAir pollution has been identified as an important risk factor for dementia in previous studies. As a unique population with a history of colonization, American Indians have long been disproportionately affected by air pollution. However, few studies have investigated the effects of air pollution on the risk of developing dementia in American Indians. This study aims to address this important knowledge gap.MethodCounty‐level average air pollution data in 2003‐2007 were downloaded from the land‐use regression models developed by the Center for Air, Climate, &amp; Energy Solutions (CACES) and merged with data from the Indian Health Service (IHS) National Data Warehouse and related electronic health record databases between fiscal year (FY) 2007‐2013. We assigned air pollution exposure to IHS users based on their county of residence and calculated 5‐year averages of PM2.5, O3, CO, and NO2 in each county. A total of 14,910 American Indians who were 65+ years old in FY2007, used IHS services at least once each year, and were dementia free between FY2007‐2009 were included in the main analysis. Cox proportional hazard models with age as the time scale were employed to examine the association of air pollution with dementia incidence, adjusting for potential confounders.ResultThe PM2.5 levels in the IHS counties were lower than those in all US counties during 2003‐2013, while the levels of other air pollutants were similar to the US (Figure 1). More dementia incident cases were found in IHS counties with higher O3 levels (Figure 2). In multivariable Cox regression models (Table1), we found a significant positive association between dementia and O3 with a hazard ratio (HR) of 1.26 (95% CI: 1.02‐1.55) per 1 ppb standardized O3, while the associations between dementia and PM2.5, and CO were not statistically significant. We found similar results in sensitivity analyses using longer lags between air pollution and dementia or replacing CO by NO2 in the regression model.ConclusionOur study suggests that exposure to O3 is associated with the higher risk of dementia in American Indians. Future efforts to reduce exposure to air pollution might help lower dementia risk in American Indian communities.

High spatial frequencies disrupt conscious visual recognition: evidence from an attentional blink paradigm

In this article, we tested the respective importance of low spatial frequencies (LSF) and high spatial frequencies (HSF) for conscious visual recognition of emotional stimuli by using an attentional blink paradigm. Thirty-eight participants were asked to identify and report two targets (happy faces) embedded in a rapid serial visual presentation of distractors (angry faces). During attentional blink, conscious perception of the second target (T2) is usually altered when the lag between the two targets is short (200–500 ms) but is restored at longer lags. The distractors between T1 and T2 were either non-filtered (broad spatial frequencies, BSF), low-pass filtered (LSF), or high-pass filtered (HSF). Assuming that prediction abilities could be at the root of conscious visual recognition, we expected that LSF distractors could result in a greater disturbance of T2 reporting than HSF distractors. Results showed that both LSF and HSF play a role in the emergence of exogenous consciousness in the visual system. Furthermore, HSF distractors strongly affected T1 and T2 reporting irrespective of the lag between targets, suggesting their role for facial emotion processing. We discuss these results with regards to other models of visual recognition. .

What do we know about the price spillover between green bonds and Islamic stocks and stock market indices?

This paper investigates the risk transmission, linkages, and directional predictability between green bonds, Islamic stocks, and other asset classes. Using daily data from November 2008 to August 2020, we use the Standard & Poor's (S&P) Green Bond Index to represent the green bond market and the Dow Jones Islamic World Index and the S&P Global Shariah Indices to represent Islamic stocks. The other asset classes considered include the S&P 500 Stock Composite, S&P 500 Bond, and S&P 500 Energy indices. This paper uses the novel quantile cross-spectral (coherency), the windowed scalogram difference (WSD), and the cross-quantilogram (CQ) correlation approaches. The results from the quantile coherency analysis reveal a negative spillover effect from green bond price returns to Islamic stocks in the long run, which indicates that the green bond market poses a long-run systemic risk to Islamic stocks. From the WSD analysis, the results show that the integration between green bonds and Islamic stocks, the S&P 500 Stock Composite, and the S&P 500 Bond index is weaker during volatile market conditions. The CQ correlation suggests that the dependency between green bonds and other asset returns is concentrated in the lower quantiles and that this dependency is weaker at longer lags. Our results underscore the significance of green bonds in investor portfolios as a new investment asset class.

Quantifying the associations of the air pollutant SO2 on outpatient visits for conjunctivitis in Hangzhou, China.

The aim of this study is to further investigate the single and cumulative associations of SO2 on outpatient visits for conjunctivitis. Data from outpatient visits, air pollutants, and meteorology was collected by the Eye Center of the Second Affiliated Hospital of the Zhejiang University School of Medicine, the Environmental Protection Department of Zhejiang Province, and the Meteorological Administration of Zhejiang Province from July 1, 2014, to November 30, 2019. A Poisson generalized linear regression model (PGLM), combined with a distributed lag nonlinear model (DLNM), was employed to analyze the association between SO2 and outpatient visits for conjunctivitis using PM2.5 and NO2 as covariates. Of the 539,649 outpatients for conjunctivitis recruited for analysis, 58.1% were female. Obvious single associations of SO2 were observed in outpatient visits for conjunctivitis, which is consistent with our previous results using a time-stratified case crossover design. A delay in the associations of SO2 on outpatient visits for conjunctivitis was further confirmed, with the longest lag being 12 days. The strongest lag effect was found at lag 0-11 with RR95th vs 25th = 1.30 (1.24, 1.37), and RR90h vs 25th = 1.23 (1.18, 1.28). Furthermore, the results showed that old people may be more sensitive to the associations of SO2 than adults and the younger ones. Our study provides the first evidence that outpatient visits for conjunctivitis are positively associated with both single and cumulative air pollutant SO2 exposure, suggesting that people especially elders had better to decrease outdoor activities when the SO2 concentration is above safe level.

Acute effects of ambient air pollution on asthma emergency department visits in 10 US states

Background: Ambient air pollution is a major risk factor for increased asthma morbidity. However, previous short-term health effect studies in the US have been limited to a small number of cities or pollutants. Objectives: This study examined acute age-specific effects of exposure to particulate matter (PM2.5, PM10), major PM2.5 components (elemental carbon [EC], organic carbon [OC], nitrate, sulfate), and gaseous pollutants (O3, NOx/NO2, SO2, CO) on emergency department (ED) visits for asthma during 2005-2014 in 10 US states (Arizona, California, Georgia, Maryland, Missouri, Nevada, New Jersey, New York, North Carolina, and Utah). Methods: We used quasi-Poisson log-linear time-series models with unconstrained distributed lags to estimate acute (8-day) effects of air pollution exposure on asthma ED visits at agency monitoring sites, controlling for meteorology, time, and influenza ED visits. We used a Bayesian hierarchical model to combine site-specific associations. We also conducted age-stratified analyses (aged 1-4, 5-17, 18-49, 50-64, and 65+). Results: We observed positive associations between 8-day exposure to particulate matter (e.g., PM2.5: rate ratio [RR] = 1.016, 95% confidence internal [CI] = [1.008, 1.025] per 6.21 &amp;#x3bc;g/m³ increase), major PM2.5 components (e.g., EC: RR of 1.010 [1.002, 1.018] per 0.52 &amp;#x3bc;g/m³), and gaseous pollutants (e.g., O3: RR of 1.048 [1.026, 1.070] per 0.02 ppm). Associations of traffic-related pollutants (NOx, CO, EC, and OC) were generally weaker for same day (lag 0) exposures than for exposures at longer lags before the ED visit; in contrast, PM and O3 showed strongest effects at lag day 0. Total and carbonaceous PM had more pronounced associations within younger age groups (aged 17 and below) than older age groups. Conclusions: This study reports associations between short-term air pollution exposure and increased risks of asthma ED visits. We found that short-term particular matter exposure posed a higher risk on children and adolescents than on adults.

A stable solid amine adsorbent with interconnected open-cell structure for rapid CO2 adsorption and CO2/CH4 separation

A novel stable porous solid amine adsorbent with three-dimensional interpenetrating network structure was prepared by polymerization of divinylbenzene using high internal phase emulsion (HIPE) template method, and followed by further introducing polyethyleneimine (PEI) by impregnation-crosslinking method. Fixed bed dynamic adsorption experiment proved that under wet condition, the former exhibited not only a higher capacity of 6.22 mmol/g but also a better adsorption kinetics process with faster adsorption rate and longer lag in breakthrough point, which makes it potential to be used in gas separation. In CO2/CH4 separation experiment, PolyHIPE-PE30-4 showed a CO2/CH4 separation selectivity of 253 at 298 K and 1 bar, and meanwhile exhibited an extra-high operating capacity. The pure methane productivity of PolyHIPE-PE30-4 was 24.1 mmol/g from CO2/CH4 (80:20, v/v) mixed gas, 4.5 times to that of PE30-4 gel (5.36 mmol/g). Significantly, PolyHIPE-PE30-4 could maintain an excellent regeneration performance after at least 7 cycles, while PolyHIPE-P30 exhibited a remarkably decrease in adsorption capacity after only three adsorption-desorption process in wet condition, demonstrating the advantage of impregnation-crosslinking method for amine functionalization. The superior CO2 adsorption capacity and regeneration stability, combined with its superior adsorption kinetics property make it a broad prospect in the field of CO2/CH4 separation.

Research on Monetary Policy Implementation and Industrial Structure Transformation Under COVID-19-Evidence From Eight Economic Zones in Mainland China.

The outbreak of COVID-19 has brought a serious impact on the economies of various countries, monetary policy needs to play a role in stimulating economic recovery when the economy encounters a serious negative impact. Since the recurrent outbreak of COVID-19 has caused great obstacles to the normal economic exchanges between countries, it has become particularly important to build the domestic market and optimize the industrial allocation at this time. This paper focuses on studying the dynamic impact of China's monetary policy implementation on the industrial structure during the pandemic. Based on the data of the eight major economic zones in Mainland China and the dataset containing many of China's macroeconomic variables, a SV-TVP-FAVAR model is established. The manuscript compares the time-varying effects of monetary policy tools on the industries at different stages before and after the epidemic. The study supported some interesting conclusions. (1) Either the quantitative or price-based monetary policy shocks have significant time-varying impacts on the industries in different economic zones. The impacts of monetary policy on the primary, secondary, and tertiary industries in each economic zone are uneven. (2) The developed Northern, Eastern, and Southern coastal economic zones in Mainland China are more sensitive to the changes in monetary policy. (3) COVID-19 has brought a tremendous negative shock on the economy, which has destroyed the original steady-state of the economic system and added more uncertainty to the regulatory effect of monetary policy. Compared with other periods in China's economic history that severely negatively impacted (the Southeast Asian financial crisis and the global economic crisis), industries in most economic zones under the COVID-19 epidemic have been affected by monetary policy for a longer lag time. Therefore, for the implementation of monetary policy, at the moment of COVID-19 epidemic, we should pay more attention to the dual-pillar role of macro-prudential regulation, further improve the process of China's interest rate reform, enrich the monetary toolbox, and implement differentiated monetary policies in line with the economic zone's position, to optimize the regional industrial structure, and promote long-term economic growth.

Combined Sewer Overflows and Gastrointestinal Illness in Atlanta, 2002-2013: Evaluating the Impact of Infrastructure Improvements.

Background:Combined sewer overflows (CSOs) discharge untreated sewage into surface and recreational water, often following heavy precipitation. Given projected increases in frequency and intensity of precipitation due to climate change, it is important to understand the health impacts of CSOs and mediating effects of sewerage systems.Objectives:In this study we estimate associations of CSO events and emergency department (ED) visits for gastrointestinal (GI) illness among City of Atlanta, Georgia, residents and explore how these associations vary with sewerage improvements.Methods:We estimate associations using Poisson generalized linear models, controlling for time trends. We categorized CSOs by overflow volume and assessed effects of CSO events prior to ED visits with 1-, 2- and 3-wk lags. Similarly, we evaluated effects of weekly cumulative precipitation greater than the 90th percentile at the same lags. We also evaluated effect modification by ZIP Code Tabulation Area (ZCTA)-level poverty and infrastructure improvement period using interaction terms.Results:Occurrence of a large volume CSO in the previous week was associated with a 9% increase in daily ED visits for GI illness. We identified significant interaction by ZCTA-level poverty, with stronger CSO–GI illness associations in low than high poverty areas. Among areas with low poverty, we observed associations at 1-wk and longer lags, following both large and lower volume CSO events. We did not observe significant interaction by infrastructure improvement period for CSO– nor precipitation–GI illness associations; however, the number of CSO events decreased from 2.31 per week before improvements to 0.49 after improvements.Discussion:Our findings suggest that CSOs contribute to acute GI illness burden in Atlanta and that the magnitude of this risk may be higher among populations living in areas of low poverty. We did not find a protective effect of sewerage system improvements. Nonetheless, observed reductions in CSO frequency may lower the absolute burden of GI illness attributable to these events. https://doi.org/10.1289/EHP10399

Analysis of Cause-Specific Mortality in Patients with Retinoblastoma.

Background Retinoblastoma (RB) is a rare pediatric tumor with a relatively favorable prognosis. However, RB is associated with cause-specific mortality, some of that should be of great importance to clinicians. In this study, we summarize the characteristics of cause-specific mortality from nontumor disease in patients with RB. Methods This retrospective case series study identified and analyzed cause-specific mortality in patients with RB. The information of cause-specific mortality of RB patients, including detailed clinical characteristics, diagnosis, treatment process, cause-specific mortality classification, and lag time, was assessed. Results A total of 12 eligible patients were selected from 264 patients who died among 3780 patients diagnosed with RB. The cause-specific mortality rate was 4.5% for all patients with RB who died and 0.3% for all patients with RB. The main nontumor cause-specific mortalities were diseases of the nervous, circulatory, and respiratory systems, which specifically included intracranial infection, cerebral hemorrhage, paraplegia, and respiratory failure. The longest lag time was 42 days from the last chemoradiotherapy or surgery. Conclusion Nontumor cause-specific mortality is an essential outcome of RB. Thus, intensive care and differentiation during management need to be taken seriously.