Long-term exposure to air pollution and COVID-19 severity: A cohort study in Greater Manchester, United Kingdom.

Exposure to outdoor air pollution may affect incidence and severity of coronavirus disease 2019 (COVID-19). In this retrospective cohort based on patient records from the Greater Manchester Care Records, all first COVID-19 cases diagnosed between March 1, 2020 and May 31, 2022 were followed until COVID-19 related hospitalization or death within 28 days. Long-term exposure was estimated using mean annual concentrations of particulate matter with diameter ≤2.5 µm (PM2.5), ≤10 µm (PM10), nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2) and benzene (C6H6) in 2019 using a validated air pollution model developed by the Department for Environment, Food and Rural Affairs (DEFRA). The association of long-term exposure to air pollution with COVID-19 hospitalization and mortality were estimated using multivariate logistic regression models after adjusting for potential individual, temporal and spatial confounders. Significant positive associations were observed between PM2.5, PM10, NO2, SO2, benzene and COVID-19 hospital admissions with odds ratios (95% Confidence Intervals [CI]) of 1.27 (1.25-1.30), 1.15 (1.13-1.17), 1.12 (1.10-1.14), 1.16 (1.14-1.18), and 1.39 (1.36-1.42), (per interquartile range [IQR]), respectively. Significant positive associations were also observed between PM2.5, PM10, SO2, or benzene and COVID-19 mortality with odds ratios (95% CI) of 1.39 (1.31-1.48), 1.23 (1.17-1.30), 1.18 (1.12-1.24), and 1.62 (1.52-1.72), per IQR, respectively. Individuals who were older, overweight or obese, current smokers, or had underlying comorbidities showed greater associations between all pollutants of interest and hospital admission, compared to the corresponding groups. Long-term exposure to air pollution is associated with developing severe COVID-19 after a positive SARS-CoV-2 infection, resulting in hospitalization or death.

Based on network pharmacology and bioinformatics to analyze the mechanism of action of Astragalus membranaceus in the treatment of vitiligo and COVID-19.

Coronavirus disease 2019 (COVID-19) is spreading rapidly around the world. However, the treatment of vitiligo combined with COVID-19 has not been reported. Astragalus membranaceus (AM) has a therapeutic effect on patients with vitiligo and COVID-19. This study aims to discover its possible therapeutic mechanisms and provide potential drug targets. Using the Chinese Medicine System Pharmacological Database (TCMSP), GEO database and Genecards websites and other databases, AM target, vitiligo disease target, and COVID-19 related gene set were established. Then find the crossover genes by taking the intersection. Then use GO, KEGG enrichment analysis, and PPI network to discover its underlying mechanism. Finally, by importing drugs, active ingredients, crossover genes, and enriched signal pathways into Cytoscape software, a "drug-active ingredient-target signal pathway-" network is constructed. TCMSP screened and obtained 33 active ingredients including baicalein (MOL002714), NEOBAICALEIN (MOL002934), Skullcapflavone II (MOL002927), and wogonin (MOL000173), which acted on 448 potential targets. 1166 differentially expressed genes for vitiligo were screened by GEO. CIVID-19 related genes were screened by Genecards. Then by taking the intersection, a total of 10 crossover genes (PTGS2, CDK1, STAT1, BCL2L1, SCARB1, HIF1A, NAE1, PLA2G4A, HSP90AA1, and HSP90B1) were obtained. KEGG analysis found that it was mainly enriched in signaling pathways such as IL-17 signaling pathway, Th17 cell differentiation, Necroptosis, NOD-like receptor signaling pathway. Five core targets (PTGS2, STAT1, BCL2L1, HIF1A, and HSP90AA1) were obtained by analyzing the PPI network. The network of "active ingredients-crossover genes" was constructed by Cytoscape, and the 5 main active ingredients acting on the 5 core crossover genes acacetin, wogonin, baicalein, bis2S)-2-ethylhexyl) benzene-1,2-dicarboxylate and 5,2'-Dihydroxy-6,7,8-trimethoxyflavone. The core crossover genes obtained by PPI and the core crossover genes obtained by the "active ingredient-crossover gene" network are intersected to obtain the three most important core genes (PTGS2, STAT1, HSP90AA1). AM may act on PTGS2, STAT1, HSP90AA1, etc. through active components such as acacetin, wogonin, baicalein, bis2S)-2-ethylhexyl) benzene-1,2-dicarboxylate and 5,2'-Dihydroxy-6,7,8-trimethoxyflavone to activate IL-17 signaling pathway, Th17 cell differentiation, Necroptosis, NOD-like receptor signaling pathway, Kaposi sarcoma-associated herpesvirus infection, and VEGF signaling pathway and other signaling pathways to achieve the effect of treating vitiligo and COVID-19.

The impact of COVID-19 lockdown on air pollution in Europe and North America: a systematic review.

BACKGROUND: Multiple studies report reductions in air pollution associated with COVID-19 lockdowns. METHODS: We performed a systematic review of the changes observed in hazardous air pollutants known or suspected to be harmful to health, including nitrogen dioxide (NO2), nitrogen oxides (NOx), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3) and particulate matter (PM). We searched PubMed and Web of Science for studies reporting the associations of lockdowns with air pollutant changes during the COVID-19 pandemic in Europe and North America. RESULTS: One hundred nine studies were identified and analyzed. Several pollutants exhibited marked and sustained reductions. The strongest was NO2 (93% of 89 estimated changes were reductions) followed by CO (88% of 33 estimated pollutant changes). All NOx and benzene studies reported significant reductions although these were based on fewer than 10 estimates. About three-quarters of PM2.5 and PM10 estimates showed reductions and few studies reported increases when domestic fuel use rose during COVID-19 lockdowns. In contrast, O3 levels rose as NOx levels fell. SO2 and ammonia (NH3) had mixed results. In general, greater reductions appeared when lockdowns were more severe, as well as where baseline pollutant levels were higher, such as at low-elevation and in densely populated areas. Substantial and robust reductions in NO2, NO, CO, CO2, PM2.5, PM10, benzene and air quality index pollution occurred in association with COVID-19 lockdowns. O3 levels tended to increase, while SO2 and NH3 had mixed patterns. CONCLUSIONS: Our study shows the profound impact of human activity levels on air pollution and its potential avoidability.

Occurrence of and dermal exposure to benzene, toluene and styrene found in hand sanitizers from the United States.

Human exposure to carcinogenic volatile organic compounds (VOCs), such as benzene, from hand sanitizers is a topic of current concern. In light of the heavy use of hand sanitizers during the COVID-19 pandemic, determination of exposure to toxicants present in these products deserves attention. The US Food and Drug Administration (FDA) had set an interim limit for benzene in alcohol-based hand sanitizers at 2000 parts-per-billion (ppb). We determined the concentrations of and exposure to three VOCs namely, benzene, toluene and styrene, in 200 hand sanitizers using high-resolution gas chromatography coupled with high-resolution mass spectrometry (HRGC-HRMS). Benzene, toluene and styrene were found in 31%, 25% and 32%, respectively, of the samples analyzed at mean concentrations of 395 (range: 0.181-22,300), 164 (range: 0.074-20,700) and 61.3 ng/g (range: 0.082-4200 ng/g), respectively. Benzene was found at concentrations > 2000 ng/g (above the FDA interim limit) in 5% of the samples, representing 9 brands. The mean potential dermal exposure doses (DEDs) to benzene (children/teenagers: 34.6; adults: 24.7 ng/kg-bw/d) were higher than those for toluene (children/teenagers: 14.4; adults: 10.3 ng/kg-bw/d) and styrene (children/teenagers: 5.37; adults: 3.83 ng/kg-bw/d) in the 200 hand sanitizers analyzed. The estimated cancer risk from exposure to benzene in children/teenagers and adults from hand sanitizer use (at an estimated usage rate of 5 g/day) was greater than the one-in-a-million risk benchmark (1.0 × 10-6) for 10% and 9% of the samples, respectively. To the best of our knowledge, this is the first study to determine both the concentrations of and exposure risks to benzene, toluene and styrene present in hand sanitizers.

Assessing the impact of long-term exposure to nine outdoor air pollutants on COVID-19 spatial spread and related mortality in 107 Italian provinces.

This paper investigates the air quality in 107 Italian provinces in the period 2014-2019 and the association between exposure to nine outdoor air pollutants and the COVID-19 spread and related mortality in the same areas. The methods used were negative binomial (NB) regression, ordinary least squares (OLS) model, and spatial autoregressive (SAR) model. The results showed that (i) common air pollutants-nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5 and PM10)-were highly and positively correlated with large firms, energy and gas consumption, public transports, and livestock sector; (ii) long-term exposure to NO2, PM2.5, PM10, benzene, benzo[a]pyrene (BaP), and cadmium (Cd) was positively and significantly correlated with the spread of COVID-19; and (iii) long-term exposure to NO2, O3, PM2.5, PM10, and arsenic (As) was positively and significantly correlated with COVID-19 related mortality. Specifically, particulate matter and Cd showed the most adverse effect on COVID-19 prevalence; while particulate matter and As showed the largest dangerous impact on excess mortality rate. The results were confirmed even after controlling for eighteen covariates and spatial effects. This outcome seems of interest because benzene, BaP, and heavy metals (As and Cd) have not been considered at all in recent literature. It also suggests the need for a national strategy to drive down air pollutant concentrations to cope better with potential future pandemics.

Uncovering cryptic pockets in the SARS-CoV-2 spike glycoprotein.

The COVID-19 pandemic has prompted a rapid response in vaccine and drug development. Herein, we modeled a complete membrane-embedded SARS-CoV-2 spike glycoprotein and used molecular dynamics simulations with benzene probes designed to enhance discovery of cryptic pockets. This approach recapitulated lipid and host metabolite binding sites previously characterized by cryo-electron microscopy, revealing likely ligand entry routes, and uncovered a novel cryptic pocket with promising druggable properties located underneath the 617-628 loop. A full representation of glycan moieties was essential to accurately describe pocket dynamics. A multi-conformational behavior of the 617-628 loop in simulations was validated using hydrogen-deuterium exchange mass spectrometry experiments, supportive of opening and closing dynamics. The pocket is the site of multiple mutations associated with increased transmissibility found in SARS-CoV-2 variants of concern including Omicron. Collectively, this work highlights the utility of the benzene mapping approach in uncovering potential druggable sites on the surface of SARS-CoV-2 targets.