Extreme Humid-Heat Exposure and Mortality Among Patients Receiving Dialysis.

RATIONALE & OBJECTIVE: Exposure to extreme heat events has been linked to increased morbidity and mortality in the general population. Patients receiving maintenance dialysis may be vulnerable to greater risks from these events, but this is not well understood. We sought to characterize the association of extreme heat events and the risk of death among patients receiving dialysis in the United States. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: Data from the United States Renal Data System were used to identify adults living in US urban settlements prone to extreme heat who initiated maintenance dialysis between 1997 and 2016. EXPOSURE: An extreme heat event was defined as a time-updated heat index (a humid-heat metric) exceeding 40.6°C for ≥2 days or 46.1°C for ≥1 day. OUTCOME: Death. ANALYTICAL APPROACH: Cox proportional hazards regression to estimate the elevation in risk of death during a humid-heat event adjusted for age, sex, year of dialysis initiation, dialysis modality, poverty level, and climate region. Interactions between humid-heat and these same factors were explored. RESULTS: Among 945,251 adults in 245 urban settlements, the mean age was 63 years and 44% were female. During a median follow-up of 3.6 years, 498,049 adults were exposed to at least one of 7,154 extreme humid-heat events, and 500,025 deaths occurred. In adjusted models, there was an increased risk of death (hazard ratio 1.18; 95% confidence interval 1.15-1.20) during extreme humid-heat exposure. Relative mortality risk was higher among patients living in the Southeast (P<0.001) compared with the Southwest. LIMITATIONS: Possibility of exposure misclassification, did not account for land use and air pollution co-exposures. CONCLUSIONS: This study suggests that patients receiving dialysis face an increased risk of death during extreme humid-heat exposure.

Grouped mixtures of air pollutants and seasonal temperature anomalies and cardiovascular hospitalizations among U.S. Residents.

BACKGROUND: Air pollution is a recognized risk factor for cardiovascular disease (CVD). Temperature is also linked to CVD, with a primary focus on acute effects. Despite the close relationship between air pollution and temperature, their health effects are often examined separately, potentially overlooking their synergistic effects. Moreover, fewer studies have performed mixture analysis for multiple co-exposures, essential for adjusting confounding effects among them and assessing both cumulative and individual effects. METHODS: We obtained hospitalization records for residents of 14 U.S. states, spanning 2000-2016, from the Health Cost and Utilization Project State Inpatient Databases. We used a grouped weighted quantile sum regression, a novel approach for mixture analysis, to simultaneously evaluate cumulative and individual associations of annual exposures to four grouped mixtures: air pollutants (elemental carbon, ammonium, nitrate, organic carbon, sulfate, nitrogen dioxide, ozone), differences between summer and winter temperature means and their long-term averages during the entire study period (i.e., summer and winter temperature mean anomalies), differences between summer and winter temperature standard deviations (SD) and their long-term averages during the entire study period (i.e., summer and winter temperature SD anomalies), and interaction terms between air pollutants and summer and winter temperature mean anomalies. The outcomes are hospitalization rates for four prevalent CVD subtypes: ischemic heart disease, cerebrovascular disease, heart failure, and arrhythmia. RESULTS: Chronic exposure to air pollutant mixtures was associated with increased hospitalization rates for all CVD subtypes, with heart failure being the most susceptible subtype. Sulfate, nitrate, nitrogen dioxide, and organic carbon posed the highest risks. Mixtures of the interaction terms between air pollutants and temperature mean anomalies were associated with increased hospitalization rates for all CVD subtypes. CONCLUSIONS: Our findings identified critical pollutants for targeted emission controls and suggested that abnormal temperature changes chronically affected cardiovascular health by interacting with air pollution, not directly.

"All in One" Strategy for Achieving Superprotonic Conductivity by Incorporating Strong Acids into a Robust Imidazole-Linked Covalent Organic Framework.

The fabrication of solid-state proton-conducting electrolytes possessing both high performance and long-life reusability is significant but challenging. An "all-in-one" composite, H3PO4@PyTFB-1-SO3H, including imidazole, sulfonic acid, and phosphoric acid, which are essential for proton conduction, was successfully prepared by chemical post-modification and physical loading in the rationally pre-synthesized imidazole-based nanoporous covalent organic framework (COF), PyTFB-1. The resultant H3PO4@PyTFB-1-SO3H exhibits superhigh proton conductivity with its value even highly up to 1.15 × 10-1 S cm-1 at 353 K and 98% relative humidity (RH), making it one of the highest COF-based composites reported so far under the same conditions. Experimental studies and theoretical calculations further confirmed that the imidazole and sulfonic acid groups have strong interactions with the H3PO4 molecules and the synergistic effect of these three groups dramatically improves the proton conductivity properties of H3PO4@PyTFB-1-SO3H. This work demonstrated that by aggregating multiple proton carriers into one composite, effective proton-conducting electrolyte can be feasibly achieved.

Exposure-response associations between chronic exposure to fine particulate matter and risks of hospital admission for major cardiovascular diseases: population based cohort study.

OBJECTIVE: To estimate exposure-response associations between chronic exposure to fine particulate matter (PM2.5) and risks of the first hospital admission for major cardiovascular disease (CVD) subtypes. DESIGN: Population based cohort study. SETTING: Contiguous US. PARTICIPANTS: 59 761 494 Medicare fee-for-service beneficiaries aged ≥65 years during 2000-16. Calibrated PM2.5 predictions were linked to each participant's residential zip code as proxy exposure measurements. MAIN OUTCOME MEASURES: Risk of the first hospital admission during follow-up for ischemic heart disease, cerebrovascular disease, heart failure, cardiomyopathy, arrhythmia, valvular heart disease, thoracic and abdominal aortic aneurysms, or a composite of these CVD subtypes. A causal framework robust against confounding bias and bias arising from errors in exposure measurements was developed for exposure-response estimations. RESULTS: Three year average PM2.5 exposure was associated with increased relative risks of first hospital admissions for ischemic heart disease, cerebrovascular disease, heart failure, cardiomyopathy, arrhythmia, and thoracic and abdominal aortic aneurysms. For composite CVD, the exposure-response curve showed monotonically increased risk associated with PM2.5: compared with exposures ≤5 µg/m3 (the World Health Organization air quality guideline), the relative risk at exposures between 9 and 10 µg/m3, which encompassed the US national average of 9.7 µg/m3 during the study period, was 1.29 (95% confidence interval 1.28 to 1.30). On an absolute scale, the risk of hospital admission for composite CVD increased from 2.59% with exposures ≤5 µg/m3 to 3.35% at exposures between 9 and 10 µg/m3. The effects persisted for at least three years after exposure to PM2.5. Age, education, accessibility to healthcare, and neighborhood deprivation level appeared to modify susceptibility to PM2.5. CONCLUSIONS: The findings of this study suggest that no safe threshold exists for the chronic effect of PM2.5 on overall cardiovascular health. Substantial benefits could be attained through adherence to the WHO air quality guideline.

Long-term exposure to ambient PM2.5, particulate constituents and hospital admissions from non-respiratory infection.

The association between PM2.5 and non-respiratory infections is unclear. Using data from Medicare beneficiaries and high-resolution datasets of PM2.5 and its constituents across 39,296 ZIP codes in the U.S between 2000 and 2016, we investigated the associations between annual PM2.5, PM2.5 constituents, source-specific PM2.5, and hospital admissions from non-respiratory infections. Each standard deviation (3.7-µg m-3) increase in PM2.5 was associated with a 10.8% (95%CI 10.8-11.2%) increase in rate of hospital admissions from non-respiratory infections. Sulfates (30.8%), Nickel (22.5%) and Copper (15.3%) contributed the largest weights in the observed associations. Each standard deviation increase in PM2.5 components sourced from oil combustion, coal burning, traffic, dirt, and regionally transported nitrates was associated with 14.5% (95%CI 7.6-21.8%), 18.2% (95%CI 7.2-30.2%), 20.6% (95%CI 5.6-37.9%), 8.9% (95%CI 0.3-18.4%) and 7.8% (95%CI 0.6-15.5%) increases in hospital admissions from non-respiratory infections. Our results suggested that non-respiratory infections are an under-appreciated health effect of PM2.5.

From feedstock to digestion: Unraveling the impact of humic acid composition on anaerobic digestion.

In the anaerobic digestion (AD) process, the effects of humic acid (HA) derived from different feedstocks on AD are influenced by the variations in their structural composition and oxygen-containing functional groups. Thus, clarifying the structural differences of HA obtained from different feedstocks is crucial for understanding their impact on AD. In this study, the structure of five humic acids (HAs) derived from liquid digestate, food waste, silage corn straw, lignite and commercial HA, and their effects on AD were investigated. The study found that HA from food waste had more carboxyl groups, while straw-derived HA had more phenolic hydroxyl groups. Both types of HA had higher aromaticity and humification degree and showed significant inhibition effect on AD. HA from food waste had an average methanogenic inhibition rate of 43.5 % with 1 g/L HA added. In addition, commercial HA and HA derived from lignite had similar functional group types and aromaticity, with an average methanogenic inhibition rate of about 20 %. The study revealed that HAs with more carboxyl groups exhibited greater effectiveness in inhibiting AD, thereby confirming the influence of HA structures derived from different feedstocks on AD. In conclusion, this study provides valuable insights into the mechanism of HA effect on AD and offers guidance for future research focused on enhancing AD efficiency.

Tree-based machine learning model for visualizing complex relationships between biochar properties and anaerobic digestion.

The ideal conditions for anaerobic digestion experiments with biochar addition are challenging to thoroughly study due to different experimental purposes. Therefore, three tree-based machine learning models were developed to depict the intricate connection between biochar properties and anaerobic digestion. For the methane yield and maximum methane production rate, the gradient boosting decision tree produced R2 values of 0.84 and 0.69, respectively. According to feature analysis, digestion time and particle size had a substantial impact on the methane yield and production rate, respectively. When particle sizes were in the range of 0.3-0.5 mm and the specific surface area was approximately 290 m2/g, corresponding to a range of O content (>31%) and biochar addition (>20 g/L), the maximum promotion of methane yield and maximum methane production rate were attained. Therefore, this study presents new insights into the effects of biochar on anaerobic digestion through tree-based machine learning.

Measurement error correction for ambient PM2.5 exposure using stratified regression calibration: Effects on all-cause mortality.

BACKGROUND: Previous studies on the impact of measurement error for PM2.5 were mostly simulation studies, did not control for other pollutants, or used a single regression calibration model to correct for measurement error. However, the relationship between actual and error-prone PM2.5 concentration may vary by time and region. We aim to correct the measurement error of PM2.5 predictions using stratified regression calibration and investigate how the measurement error biases the association between PM2.5 and mortality in the Medicare Cohort. METHODS: The "gold-standard" measurements of PM2.5 were defined as daily monitoring data. We regressed daily monitoring PM2.5 on modeled PM2.5 using the simple linear regression by strata of season, elevation, census division and time period. Calibrated PM2.5 was calculated with stratum-specific calibration parameters ß0 (intercept) and ß1 (slope) for each strata and aggregated to annual level. Associations between calibrated and error-prone annual PM2.5 and all-cause mortality among Medicare beneficiaries were estimated with Quasi-Poisson regression models. RESULTS: Across 208 strata, the median of ß0 and ß1 were 0.62 (25% 0.0.20, 75% 1.06) and 0.93 (25% 0.87, 75% 0.99). From calibrated and error-prone PM2.5 data, we estimated that each 10 µg/m3 increase in PM2.5 was respectively associated with 4.9% (95%CI 4.6-5.2) and 4.6% (95%CI 4.4-4.9) increases in the mortality rate among Medicare beneficiaries, conditional on confounders. CONCLUSIONS: Regression calibration parameters of PM2.5 varied by time and region. Using error-prone measures of PM2.5 underestimated the association between PM2.5 and all-cause mortality. Modern exposure models produce relatively small bias.

Hurricanes and Mortality among Patients Receiving Dialysis.

BACKGROUND: Hurricanes are severe weather events that can disrupt power, water, and transportation systems. These disruptions may be deadly for patients requiring maintenance dialysis. We hypothesized that the mortality risk among patients requiring maintenance dialysis would be increased in the 30 days after a hurricane. METHODS: Patients registered as requiring maintenance dialysis in the United States Renal Data System who initiated treatment between January 1, 1997 and December 31, 2017 in one of 108 hurricane-afflicted counties were followed from dialysis initiation until transplantation, dialysis discontinuation, a move to a nonafflicted county, or death. Hurricane exposure was determined as a tropical cyclone event with peak local wind speeds ≥64 knots in the county of a patient's residence. The risk of death after the hurricane was estimated using time-varying Cox proportional hazards models. RESULTS: The median age of the 187,388 patients was 65 years (IQR, 53-75) and 43.7% were female. There were 27 hurricanes and 105,398 deaths in 529,339 person-years of follow-up on dialysis. In total, 29,849 patients were exposed to at least one hurricane. Hurricane exposure was associated with a significantly higher mortality after adjusting for demographic and socioeconomic covariates (hazard ratio, 1.13; 95% confidence interval, 1.05 to 1.22). The association persisted when adjusting for seasonality. CONCLUSIONS: Patients requiring maintenance dialysis have a higher mortality risk in the 30 days after a hurricane.

Evoked responses to note onsets and phrase boundaries in Mozart's K448.

Understanding the neural correlates of perception of hierarchical structure in music presents a direct window into auditory organization. To examine the hypothesis that high-level and low-level structures-i.e. phrases and notes-elicit different neural responses, we collected intracranial electroencephalography (iEEG) data from eight subjects during exposure to Mozart's K448 and directly compared Event-related potentials (ERPs) due to note onsets and those elicited by phrase boundaries. Cluster-level permutation tests revealed that note-onset-related ERPs and phrase-boundary-related ERPs were significantly different at [Formula: see text], 200, and 450 ms relative to note onset and phrase markers. We also observed increased activity in frontal brain regions when processing phrase boundaries. We relate these observations to (1) a process which syntactically binds notes together hierarchically to form larger phrases; (2) positive emotions induced by successful prediction of forthcoming phrase boundaries and violations of melodic expectations at phrase boundaries.

Ambient Air Pollution and Adverse Waitlist Events Among Lung Transplant Candidates.

BACKGROUND: Air pollution is associated with cardiopulmonary disease and death in the general population. Fine particulate matter (PM2.5) is particularly harmful due to its ability to penetrate into areas of gas exchange within the lungs. Persons with advanced lung disease are believed to be particularly susceptible to PM2.5 exposure, but only a few studies have examined the effect of exposure on this population. Here we investigate the association between PM2.5 exposure and adverse waitlist events among lung transplant (LT) candidates. METHODS: US registry data were used to identify LT candidates listed between January 1, 2010 and December 31, 2016. Annual PM2.5 concentration at year of listing was estimated for each candidate's ZIP Code using National Aeronautics and Space Administration's (NASA) Socioeconomic Data and Applications Center Global Annual PM2.5 Grids. We estimated crude and adjusted hazard ratios for adverse waitlist events, defined as death or removal, using Cox proportional hazards regression. RESULTS: Of the 15 075 included candidates, median age at listing was 60, 43.8% were female individuals, and 81.7% were non-Hispanic White. Median ZIP Code PM2.5 concentration was 9.06 µg/m3. When compared with those living in ZIP Codes with lower PM2.5 exposure (PM2.5 <10.53 µg/m3), candidates in ZIP Codes in the highest quartile of PM2.5 exposure (≥10.53 µg/m3) had 1.14-fold (95% confidence interval, 1.04-1.25) risk of adverse waitlist events. The result remained significant after adjusting for demographics, education, insurance, smoking, lung allocation score, body mass index, and blood type (hazard ratio, 1.17; 95% confidence interval, 1.07-1.29). CONCLUSIONS: Elevated ambient PM2.5 concentration was associated with adverse waitlist events among LT candidates. These findings highlight the impact of air pollution on clinical outcomes in this critically ill population.

Estimation of the Global Gap in Clinic Visits for Hypertension Care Between Patient Need and Physician Capacity.

[Figure: see text].

Ambient air pollution and posttransplant outcomes among kidney transplant recipients.

Fine particulate matter (PM2.5 ), a common form of air pollution which can induce systemic inflammatory response, is a risk factor for adverse health outcomes. Kidney transplant (KT) recipients are likely vulnerable to PM2.5 due to comorbidity and chronic immunosuppression. We sought to quantify the association between PM2.5 and post-KT outcomes. For adult KT recipients (1/1/2010-12/31/2016) in the Scientific Registry of Transplant Recipients, we estimated annual zip-code level PM2.5 concentrations at the time of KT using NASA's SEDAC Global PM2.5 Grids. We determined the associations between PM2.5 and delayed graft function (DGF) and 1-year acute rejection using logistic regression and death-censored graft failure (DCGF) and mortality using Cox proportional hazard models. All models were adjusted for sociodemographics, recipient, transplant, and ZIP code level confounders. Among 87 233 KT recipients, PM2.5 was associated with increased odds of DGF (OR = 1.59; 95% CI: 1.48-1.71) and 1-year acute rejection (OR = 1.31; 95% CI: 1.17-1.46) and increased risk of all-cause mortality (HR = 1.15; 95% CI: 1.07-1.23) but not DCGF (HR = 1.05; 95% CI: 0.97-1.51). In conclusion, PM2.5 was associated with higher odds of DGF and 1-year acute rejection and elevated risk of mortality among KT recipients. Our study highlights the importance of considering environmental exposure as risk factors for post-KT outcomes.

Ambient Air Pollution and Mortality among Older Patients Initiating Maintenance Dialysis.

BACKGROUND: Fine particulate matter (particulate matter with diameter <2.5 µm [PM2.5]) is associated with CKD progression and may impact the health of patients living with kidney failure. While older (aged ≥65 years) adults are most vulnerable to the impact of PM2.5, it is unclear whether older patients on dialysis are at elevated risk of mortality when exposed to fine particulate matter. METHODS: Older adults initiating dialysis (2010-2016) were identified from US Renal Data System (USRDS). PM2.5 concentrations were obtained from NASA's Socioeconomic Data and Application Center (SEDAC) Global Annual PM2.5 Grids. We investigated the association between PM2.5 and all-cause mortality using Cox proportional hazard models with linear splines [knot at the current Environmental Protection Agency (EPA) National Ambient Air Quality Standard for PM2.5 of 12 µg/m3] and robust variance. RESULTS: For older dialysis patients who resided in areas with high PM2.5, a 10 µg/m3 increase in PM2.5 was associated with 1.16-fold (95% CI: 1.08-1.25) increased risk of mortality; furthermore, those who were female (aHR = 1.26, 95% CI: 1.13-1.42), Black (aHR = 1.31, 95% CI: 1.09-1.59), or had diabetes as a primary cause of kidney failure (aHR = 1.25, 95% CI: 1.13-1.38) were most vulnerable to high PM2.5. While the mortality risk associated with PM2.5 was stronger at higher levels (aHR = 1.19, 95% CI: 1.08-1.32), at lower levels (≤12 µg/m3), PM2.5 was significantly associated with mortality risk (aHR = 1.04, 95% CI: 1.00-1.07) among patients aged ≥75 years (Pslope difference = 0.006). CONCLUSIONS: Older adults initiating dialysis who resided in ZIP codes with PM2.5 levels >12 µg/m3 are at increased risk of mortality. Those aged >75 were at elevated risk even at levels below the EPA Standard for PM2.5.

Model-based spatial-temporal mapping of opisthorchiasis in endemic countries of Southeast Asia.

Opisthorchiasis is an overlooked danger to Southeast Asia. High-resolution disease risk maps are critical but have not been available for Southeast Asia. Georeferenced disease data and potential influencing factor data were collected through a systematic review of literatures and open-access databases, respectively. Bayesian spatial-temporal joint models were developed to analyze both point- and area-level disease data, within a logit regression in combination of potential influencing factors and spatial-temporal random effects. The model-based risk mapping identified areas of low, moderate, and high prevalence across the study region. Even though the overall population-adjusted estimated prevalence presented a trend down, a total of 12.39 million (95% Bayesian credible intervals [BCI]: 10.10-15.06) people were estimated to be infected with O. viverrini in 2018 in four major endemic countries (i.e., Thailand, Laos, Cambodia, and Vietnam), highlighting the public health importance of the disease in the study region. The high-resolution risk maps provide valuable information for spatial targeting of opisthorchiasis control interventions.

Epidemiological Characteristics of Atrial Fibrillation in Southern China: Results from the Guangzhou Heart Study.

Precise prevalence of atrial fibrillation (AF) and the associated risk factors in southern China are rarely reported. This large population-based follow-up study, the Guangzhou Heart Study, was conducted from 2015 to 2017 to fill up this gap. Permanent residents aged 35 years and above in Guangzhou city were enrolled and demographic factors of participants were collected by a structured questionnaire. Examinations of physical, electrocardiographic and biochemical indicators were performed following a standard operation procedure designed prior to the field investigation. Descriptive statistics were used to evaluate basic characteristics of the study participants, and multivariate logistic regression model was performed to assess the AF prevalence-related factors. The detailed study design, the baseline characteristics and the prevalence of AF were reported here. In total, 12,013 residents were enrolled, and the percentage of participants from rural and urban areas was 53.92% and 46.08%, respectively. In total, 90.57% participants aged 40-79 years old and the proportion of women was more than men (64.98% vs. 35.02%). Overall, the prevalence of AF among the participants was 1.46%. Increasing age, male sex and widowed marital status were associated with higher AF prevalence (P-value < 0.05). The prevalence of AF increased with age and climbed to approximately 5% in residents aged 80 years and over. Residents with abnormal higher blood level of total cholesterol tended to have a lower AF prevalence but a higher prevalence of AF was observed in female participants with lower level of high density lipoprotein cholesterol land higher level uric acid (all P-value < 0.05). Personal illness such as hypertension, diabetes mellitus, dyslipidemia, myocardial infarction, heart failure, stroke and transient ischemic were significantly linked to the attack of AF (all P-value < 0.05). This study will be rich resource for investigating environmental exposure and individual genetic diathesis of AF and other common cardiovascular diseases in Chinese population.

Presence of an adsorbent cake layer improves the performance of gravity-driven membrane (GDM) filtration system.

Gravity-driven membrane (GDM) filtration is a promising decentralized drinking water treatment process. To improve the performance of GDM system, a thin layer of adsorbent was pre-deposited on the membrane surface prior to filtration (adsorbent-laden GDM system). The tested adsorbents include powdered activated carbon (PAC) and anion exchange resin (AER), and an unmodified GDM system and a SiO2-laden GDM system were used as controls. In the adsorbent-laden GDM systems, the adsorption of the PAC and AER increased the removal efficiency of natural organic matter by 7.2-43.5% and microcystin-LR, atrazine, and bisphenol A by 7.9-81.2%. The presence of adsorbent particles increased the amount of microorganisms in the cake layer and therefore increased the removal efficiency of assimilable organic matter (AOC) by 20.1-34.4%. In the adsorbent-laden GDM systems, the physically irrecoverable fouling decreased because of the reduction in membrane foulants by the adsorbent layer. However, the presence of adsorbent particles in the cake layer counteracted this effect and increased the physically recoverable fouling. Consequently, the pre-deposited adsorbent layers had only a limited effect on the stabilized flux (2.26-2.65 L/m2 h). A bilayer structure was found in the cake layer of the adsorbent-laden GDM systems via scanning electron microscopy (SEM), and the cake layer was looser in the presence of adsorbent particles. These results demonstrate that pre-depositing a thin layer of adsorbents on the membrane surface of the GDM system can significantly improve the quality of the permeate without decreasing the stabilized flux.

1-Acetyl-5-(4-fluoro-phen-yl)-2-sulfanyl-ideneimidazolidin-4-one.

In the title compound, C11H9FN2O2S, the 2-sulfanylideneimidazolidin-4-one moiety is essentially planar, with a maximum deviation of 0.0183 (14) Å. The mean plane of this moiety is approximately coplanar with the attached acetyl group and perpendicular to the benzene ring, making dihedral angles of 9.70 (14) and 86.70 (6)°, respectively. In the crystal, mol-ecules are linked by N-H⋯O hydrogen bonds between the amide NH and acetyl C=O groups, forming a C(6) chain along the a-axis direction.