Cisplatin in the era of PARP inhibitors and immunotherapy.

Platinum compounds such as cisplatin, carboplatin and oxaliplatin are widely used in chemotherapy. Cisplatin induces cytotoxic DNA damage that blocks DNA replication and gene transcription, leading to arrest of cell proliferation. Although platinum therapy alone is effective against many tumors, cancer cells can adapt to the treatment and gain resistance. The mechanisms for cisplatin resistance are complex, including low DNA damage formation, high DNA repair capacity, changes in apoptosis signaling pathways, rewired cell metabolisms, and others. Drug resistance compromises the clinical efficacy and calls for new strategies by combining cisplatin with other therapies. Exciting progress in cancer treatment, particularly development of poly (ADP-ribose) polymerase (PARP) inhibitors and immune checkpoint inhibitors, opened a new chapter to combine cisplatin with these new cancer therapies. In this Review, we discuss how platinum synergizes with PARP inhibitors and immunotherapy to bring new hope to cancer patients.

Pan-cancer mutational signature surveys correlated mutational signature with geospatial environmental exposures and viral infections.

Background: Cancer has been disproportionally affecting minorities. Genomic-based cancer disparity analyses have been less common than conventional epidemiological studies. In the past decade, mutational signatures have been established as characteristic footprints of endogenous or exogenous carcinogens. Methods: Integrating datasets of diverse cancer types from The Cancer Genome Atlas and geospatial environmental risks of the registry hospitals from the United States Environmental Protection Agency, we explored mutational signatures from the aspect of racial disparity concerning pollutant exposures. The raw geospatial environmental exposure data were refined to 449 air pollutants archived and modeled from 2007 to 2017 and aggregated to the census county level. Additionally, hepatitis B and C viruses and human papillomavirus infection statuses were incorporated into analyses for skin cancer, cervical cancer, and liver cancer. Results: Mutation frequencies of key oncogenic genes varied substantially between different races. These differences were further translated into differences in mutational signatures. Survival analysis revealed that the increased pollution level is associated with worse survival. The analysis of the oncogenic virus revealed that aflatoxin, an affirmed carcinogen for liver cancer, was higher in Asian liver cancer patients than in White patients. The aflatoxin mutational signature was exacerbated by hepatitis infection for Asian patients but not for White patients, suggesting a predisposed genetic or genomic disadvantage for Asians concerning aflatoxin. Conclusions: Environmental pollutant exposures increase a mutational signature level and worsen cancer prognosis, presenting a definite adverse risk factor for cancer patients.

Application of artificial intelligence in quantifying lung deposition dose of black carbon in people with exposure to ambient combustion particles.

BACKGROUND: Understanding lung deposition dose of black carbon is critical to fully reconcile epidemiological evidence of combustion particles induced health effects and inform the development of air quality metrics concerning black carbon. Macrophage carbon load (MaCL) is a novel cytology method that quantifies lung deposition dose of black carbon, however it has limited feasibility in large-scale epidemiological study due to the labor-intensive manual counting. OBJECTIVE: To assess the association between MaCL and episodic elevation of combustion particles; to develop artificial intelligence based counting algorithm for MaCL assay. METHODS: Sputum slides were collected during episodic elevation of ambient PM2.5 (n = 49, daily PM2.5 > 10 µg/m3 for over 2 weeks due to wildfire smoke intrusion in summer and local wood burning in winter) and low PM2.5 period (n = 39, 30-day average PM2.5 < 4 µg/m3) from the Lovelace Smokers cohort. RESULTS: Over 98% individual carbon particles in macrophages had diameter <1 µm. MaCL levels scored manually were highly responsive to episodic elevation of ambient PM2.5 and also correlated with lung injury biomarker, plasma CC16. The association with CC16 became more robust when the assessment focused on macrophages with higher carbon load. A Machine-Learning algorithm for Engulfed cArbon Particles (MacLEAP) was developed based on the Mask Region-based Convolutional Neural Network. MacLEAP algorithm yielded excellent correlations with manual counting for number and area of the particles. The algorithm produced associations with ambient PM2.5 and plasma CC16 that were nearly identical in magnitude to those obtained through manual counting. IMPACT STATEMENT: Understanding lung black carbon deposition is crucial for comprehending health effects of combustion particles. We developed "Machine-Learning algorithm for Engulfed cArbon Particles (MacLEAP)", the first artificial intelligence algorithm for quantifying airway macrophage black carbon. Our study bolstered the algorithm with more training images and its first use in air pollution epidemiology. We revealed macrophage carbon load as a sensitive biomarker for heightened ambient combustion particles due to wildfires and residential wood burning.

Industrial air pollution and low birth weight in New Mexico, USA.

In recent decades, the low birth weight (LBW) rate in New Mexico has consistently exceeded the Unites States average. Maternal exposure to air pollution during pregnancy may be a significant contributor to LBW in offspring. This study investigated the links between maternal residential exposure to air pollution from industrial sources and the risk of LBW in offspring. The analysis included 22,375 LBW cases and 233,340 controls. It focused on 14 common chemicals listed in the Toxic Release Inventory (TRI) and monitoring datasets, which have abundant monitoring samples. The Emission Weighted Proximity Model (EWPM) was used to calculate maternal air pollution exposure intensity. Adjusted odds ratios (adjORs) were calculated using binary logistic regressions to examine the association between maternal residential air pollution exposure and LBW, while controlling for potential confounders, such as the maternal age, race/ethnicity, gestational age, prenatal care, education level, consumption of alcohol during pregnancy, public health regions, child's sex, and the year of birth. Multiple comparison correction was applied using the False Discovery Rate approach. The results showed that maternal residential exposure to 1,2,4-trimethylbenzene, benzene, chlorine, ethylbenzene, and styrene had significant positive associations with LBW in offspring, with adjusted odds ratios ranging from 1.10 to 1.13. These five chemicals remained as significant risk factors after dividing the estimated exposure intensities into four categories. In addition, significant linear trends were found between LBW and maternal exposure to each of the five identified chemicals. Furthermore, 1,2,4-trimethylbenzene was identified as a risk factor to LBW for the first time. The findings of this study should be confirmed through additional epidemiological, biological, and toxicological studies.

Maternal exposure to metal components of PM2.5 and low birth weight in New Mexico, USA.

Infants with low birth weight (LBW) are more likely to have health problems than normal weight infants. In studies examining the associations between particulate matter (PM) exposures and LBW, there is a tendency to focus on PM2.5 as a whole. However, insufficient information is available regarding the effects of different components of PM2.5 on birth weight. This study identified the associations between maternal exposure to 10 metal components of PM2.5 and LBW in offspring based on small area (divided by population size) level data in New Mexico, USA, from 2012 to 2016. This study used a pruned feed-forward neural network (pruned-FNN) approach to estimate the annual average exposure index to each metal component in each small area. The linear regression model was employed to examine the association between maternal PM2.5 metal exposures and LBW rate in small areas, adjusting for the female percentage and race/ethnicity compositions, marriage status, and educational level in the population. An interquartile range increase in maternal exposure to mercury and chromium of PM2.5 increased LBW rate by 0.43% (95% confidence interval (CI): 0.18-0.68%) and 0.63% (95% CI: 0.15-1.12%), respectively. These findings suggest that maternal exposure to metal components of air pollutants may increase the risk of LBW in offspring. With no similar studies in New Mexico, this study also posed great importance because of a higher LBW rate in New Mexico than the national average. These findings provide critical information to inform further epidemiological, biological, and toxicological studies.

Disproportionate impact of COVID-19 severity and mortality on hospitalized American Indian/Alaska Native patients.

Epidemiological data across the United States of America illustrate health disparities in COVID-19 infection, hospitalization, and mortality by race/ethnicity. However, limited information is available from prospective observational studies in hospitalized patients, particularly for American Indian or Alaska Native (AI/AN) populations. Here, we present risk factors associated with severe COVID-19 and mortality in patients (4/2020-12/2021, n = 475) at the University of New Mexico Hospital. Data were collected on patient demographics, infection duration, laboratory measures, comorbidities, treatment(s), major clinical events, and in-hospital mortality. Severe disease was defined by COVID-related intensive care unit requirements and/or death. The cohort was stratified by self-reported race/ethnicity: AI/AN (30.7%), Hispanic (47.0%), non-Hispanic White (NHW, 18.5%), and Other (4.0%, not included in statistical comparisons). Despite similar timing of infection and comparable comorbidities, admission characteristics for AI/AN patients included younger age (P = 0.02), higher invasive mechanical ventilation requirements (P = 0.0001), and laboratory values indicative of more severe disease. Throughout hospitalization, the AI/AN group also experienced elevated invasive mechanical ventilation (P < 0.0001), shock (P = 0.01), encephalopathy (P = 0.02), and severe COVID-19 (P = 0.0002), consistent with longer hospitalization (P < 0.0001). Self-reported AI/AN race/ethnicity emerged as the highest risk factor for severe COVID-19 (OR = 3.19; 95% CI = 1.70-6.01; P = 0.0003) and was a predictor of in-hospital mortality (OR = 2.35; 95% CI = 1.12-4.92; P = 0.02). Results from this study highlight the disproportionate impact of COVID-19 on hospitalized AI/AN patients, who experienced more severe illness and associated mortality, compared to Hispanic and NHW patients, even when accounting for symptom onset and comorbid conditions. These findings underscore the need for interventions and resources to address health disparities in the COVID-19 pandemic.

Site-specific Atg13 methylation-mediated autophagy regulates epithelial inflammation in PM2.5-induced pulmonary fibrosis.

Fine particulate matters (PM2.5) increased the risk of pulmonary fibrosis. However, the regulatory mechanisms of lung epithelium in pulmonary fibrosis remained elusive. Here we developed PM2.5-exposure lung epithelial cells and mice models to investigate the role of autophagy in lung epithelia mediating inflammation and pulmonary fibrosis. PM2.5 exposure induced autophagy in lung epithelial cells and then drove pulmonary fibrosis by activation of NF-κB/NLRP3 signaling pathway. PM2.5-downregulated ALKBH5 protein expression promotes m6A modification of Atg13 mRNA at site 767 in lung epithelial cells. Atg13-mediated ULK complex positively regulated autophagy and inflammation in epithelial cells with PM2.5 treatment. Knockout of ALKBH5 in mice further accelerated ULK complex-regulated autophagy, inflammation and pulmonary fibrosis. Thus, our results highlighted that site-specific m6A methylation on Atg13 mRNA regulated epithelial inflammation-driven pulmonary fibrosis in an autophagy-dependent manner upon PM2.5 exposure, and it provided target intervention strategies towards PM2.5-induced pulmonary fibrosis.

Computational risk modeling of underground coal mines based on NIOSH employment demographics.

Objective: To investigate the feasibility of predicting the risk of underground coal mine operations using data from the National Institute for Occupational Safety and Health (NIOSH). Methods: A total of 22,068 data entries from 3,982 unique underground coal mines from 1990 to 2020 were extracted from the NIOSH mine employment database. We defined the risk index of a mine as the ratio between the number of injuries and the size of the mine. Several machine learning models were used to predict the risk of a mine based on its employment demographics (i.e., number of underground employees, number of surface employees, and coal production). Based on these models, a mine was classified into a "low-risk" or "high-risk" category and assigned with a fuzzy risk index. Risk probabilities were then computed to generate risk profiles and identify mines with potential hazards. Results: NIOSH mine demographic features yielded a prediction performance with an AUC of 0.724 (95% CI 0.717-0.731) based on the last 31-years' mine data and an AUC of 0.738 (95% CI: 0.726, 0.749) on the last 16-years' mine data. Fuzzy risk score shows that risk is greatest in mines with an average of 621 underground employees and a production of 4,210,150 tons. The ratio of tons/employee maximizes the risk at 16,342.18 tons/employee. Conclusion: It is possible to predict the risk of underground coal mines based on their employee demographics and optimizing the allocation and distribution of employees in coal mines can help minimize the risk of accidents and injuries.

Maternal exposure to metal components of PM2.5 and low birth weight in New Mexico, USA.

Infants with low birth weight (LBW) are more likely to have health problems than normal weight infants. In studies examining the associations between particulate matter (PM) exposures and LBW, there is a tendency to focus on PM 2.5 as a whole. However, insufficient information is available regarding the effects of different components of PM 2.5 on birth weight. This study identified the associations between maternal exposure to 10 metal components of PM 2.5 and LBW in offspring based on small area (divided by population size) level data in New Mexico, USA, from 2012 to 2016. This study used a pruned feed-forward neural network (pruned-FNN) approach to estimate the annual average exposure index to each metal component in each small area. The linear regression model was employed to examine the association between maternal PM 2.5 metal exposures and LBW rate in small areas, adjusting for the female percentage and race/ethnicity compositions, marriage status and educational level in the population. An interquartile range increase in maternal exposure to mercury and chromium of PM 2.5 increased LBW rate by 0.43% (95% confidence interval (CI): 0.18%-0.68%) and 0.63% (95% CI: 0.15%-1.12%), respectively. These findings suggest that maternal exposure to metal components of air pollutants may increase the risk of LBW in offspring. With no similar studies in New Mexico, this study also posed great importance because of a higher LBW rate in New Mexico than the national average. These findings provide critical information to inform further epidemiological, biological, and toxicological studies.

Alterations to biomarkers related to long-term exposure to diesel exhaust at concentrations below occupational exposure limits in the European Union and the USA.

BACKGROUND: We previously found that occupational exposure to diesel engine exhaust (DEE) was associated with alterations to 19 biomarkers that potentially reflect the mechanisms of carcinogenesis. Whether DEE is associated with biological alterations at concentrations under existing or recommended occupational exposure limits (OELs) is unclear. METHODS: In a cross-sectional study of 54 factory workers exposed long-term to DEE and 55 unexposed controls, we reanalysed the 19 previously identified biomarkers. Multivariable linear regression was used to compare biomarker levels between DEE-exposed versus unexposed subjects and to assess elemental carbon (EC) exposure-response relationships, adjusted for age and smoking status. We analysed each biomarker at EC concentrations below the US Mine Safety and Health Administration (MSHA) OEL (<106 µg/m3), below the European Union (EU) OEL (<50 µg/m3) and below the American Conference of Governmental Industrial Hygienists (ACGIH) recommendation (<20 µg/m3). RESULTS: Below the MSHA OEL, 17 biomarkers were altered between DEE-exposed workers and unexposed controls. Below the EU OEL, DEE-exposed workers had elevated lymphocytes (p=9E-03, false discovery rate (FDR)=0.04), CD4+ count (p=0.02, FDR=0.05), CD8+ count (p=5E-03, FDR=0.03) and miR-92a-3p (p=0.02, FDR=0.05), and nasal turbinate gene expression (first principal component: p=1E-06, FDR=2E-05), as well as decreased C-reactive protein (p=0.02, FDR=0.05), macrophage inflammatory protein-1ß (p=0.04, FDR=0.09), miR-423-3p (p=0.04, FDR=0.09) and miR-122-5p (p=2E-03, FDR=0.02). Even at EC concentrations under the ACGIH recommendation, we found some evidence of exposure-response relationships for miR-423-3p (ptrend=0.01, FDR=0.19) and gene expression (ptrend=0.02, FDR=0.19). CONCLUSIONS: DEE exposure under existing or recommended OELs may be associated with biomarkers reflective of cancer-related processes, including inflammatory/immune response.

Association between diesel exhaust exposure and mitochondrial DNA methylation.

OBJECTIVES: Diesel exhaust is an established human carcinogen, however the mechanisms by which it leads to cancer development are not fully understood. Mitochondrial dysfunction is an established contributor to carcinogenesis. Recent studies have improved our understanding of the role played by epigenetic modifications in the mitochondrial genome on tumorigenesis. In this study, we aim to evaluate the association between diesel engine exhaust (DEE) exposure with mitochondrial DNA (mtDNA) methylation levels in workers exposed to DEE. METHODS: The study population consisted of 53 male workers employed at a diesel engine manufacturing facility in Northern China who were routinely exposed to diesel exhaust in their occupational setting, as well as 55 unexposed male control workers from other unrelated factories in the same geographic area. Exposure to DEE, elemental carbon, organic carbon, and particulate matter (PM2.5) were assessed. mtDNA methylation for CpG sites (CpGs) from seven mitochondrial genes (D-Loop, MT-RNR1, MT-CO2, MT-CO3, MT-ATP6, MT-ATP8, MT-ND5) was measured in blood samples. Linear regression models were used to estimate the associations between DEE, elemental carbon, organic carbon and PM2.5 exposures with mtDNA methylation levels, adjusting for potential confounders. RESULTS: DEE exposure was associated with decreased MT-ATP6 (difference = -35.6%, P-value = 0.019) and MT-ATP8 methylation (difference = -30%, P-value = 0.029) compared to unexposed controls. Exposures to elemental carbon, organic carbon, and PM2.5 were also significantly and inversely associated with methylation in MT-ATP6 and MT-ATP8 genes (all P-values < 0.05). CONCLUSIONS: Our findings suggest that DEE exposure perturbs mtDNA methylation, which may be of importance for tumorigenesis.

Exposure to diesel engine exhaust and alterations to the Cys34/Lys525 adductome of human serum albumin.

We investigated whether exposure to carcinogenic diesel engine exhaust (DEE) was associated with altered adduct levels in human serum albumin (HSA) residues. Nano-liquid chromatography-high resolution mass spectrometry (nLC-HRMS) was used to measure adducts of Cys34 and Lys525 residues in plasma samples from 54 diesel engine factory workers and 55 unexposed controls. An untargeted adductomics and bioinformatics pipeline was used to find signatures of Cys34/Lys525 adductome modifications. To identify adducts that were altered between DEE-exposed and unexposed participants, we used an ensemble feature selection approach that ranks and combines findings from linear regression and penalized logistic regression, then aggregates the important findings with those determined by random forest. We detected 40 Cys34 and 9 Lys525 adducts. Among these findings, we found evidence that 6 Cys34 adducts were altered between DEE-exposed and unexposed participants (i.e., 841.75, 851.76, 856.10, 860.77, 870.43, and 913.45). These adducts were biologically related to antioxidant activity.

Wood smoke exposure affects lung aging, quality of life, and all-cause mortality in New Mexican smokers.

BACKGROUND: The role of wood smoke (WS) exposure in the etiology of chronic obstructive pulmonary disease (COPD), lung cancer (LC), and mortality remains elusive in adults from countries with low ambient levels of combustion-emitted particulate matter. This study aims to delineate the impact of WS exposure on lung health and mortality in adults age 40 and older who ever smoked. METHODS: We assessed health impact of self-reported "ever WS exposure for over a year" in the Lovelace Smokers Cohort using both objective measures (i.e., lung function decline, LC incidence, and deaths) and two health related quality-of-life questionnaires (i.e., lung disease-specific St. George's Respiratory Questionnaire [SGRQ] and the generic 36-item short-form health survey). RESULTS: Compared to subjects without WS exposure, subjects with WS exposure had a more rapid decline of FEV1 (- 4.3 ml/s, P = 0.025) and FEV1/FVC ratio (- 0.093%, P = 0.015), but not of FVC (- 2.4 ml, P = 0.30). Age modified the impacts of WS exposure on lung function decline. WS exposure impaired all health domains with the increase in SGRQ scores exceeding the minimal clinically important difference. WS exposure increased hazard for incidence of LC and death of all-cause, cardiopulmonary diseases, and cancers by > 50% and shortened the lifespan by 3.5 year. We found no evidence for differential misclassification or confounding from socioeconomic status for the health effects of WS exposure. CONCLUSIONS: We identified epidemiological evidence supporting WS exposure as an independent etiological factor for the development of COPD through accelerating lung function decline in an obstructive pattern. Time-to-event analyses of LC incidence and cancer-specific mortality provide human evidence supporting the carcinogenicity of WS exposure.

Lung Effects of Household Air Pollution.

Biomass fuel smoke, secondhand smoke, and oxides of nitrogen are common causes of household air pollution (HAP). Almost 2.4 billion people worldwide use solid fuels for cooking and heating, mostly in low- and middle-income countries. Wood combustion for household heating is also common in many areas of high-income countries, and minorities are particularly vulnerable. HAP in low- and middle-income countries is associated with asthma, acute respiratory tract infections in adults and children, chronic obstructive pulmonary disease, lung cancer, tuberculosis, and respiratory mortality. Although wood smoke exposure levels in high-income countries are typically lower than in lower-income countries, it is similarly associated with accelerated lung function decline, higher prevalence of airflow obstruction and chronic bronchitis, and higher all-cause and respiratory cause-specific mortality. Household air cleaners with high-efficiency particle filters have mixed effects on asthma and chronic obstructive pulmonary disease outcomes. Biomass fuel interventions in low-income countries include adding chimneys to cookstoves, improving biomass fuel combustion stoves, and switching fuel to liquid petroleum gas. Still, the impact on health outcomes is inconsistent. In high-income countries, strategies for reducing biomass fuel-related HAP are centered on community-level woodstove changeout programs, although the results are again inconsistent. In addition, initiatives to encourage home smoking bans have mixed success in households with children. Environmental solutions to reduce HAP have varying success in reducing pollutants and health problems. Improved understanding of indoor air quality factors and actions that prevent degradation or improve polluted indoor air may lead to enhanced environmental health policies, but health outcomes must be rigorously examined.

Early natural menopause is associated with poor lung health and increased mortality among female smokers.

BACKGROUND: Early natural menopause has been regarded as a biomarker of reproductive and somatic aging. Cigarette smoking is the most harmful factor for lung health and also an established risk factor for early menopause. Understanding the effect of early menopause on health outcomes in middle-aged and older female smokers is important to develop preventive strategies. OBJECTIVE: This study aimed to examine the associations of early menopause with multiple lung health and aging biomarkers, lung cancer risk, and all-cause and cause-specific mortality in postmenopausal women who were moderate or heavy smokers. STUDY DESIGN: This study was conducted on postmenopausal women with natural (n=1038) or surgical (n=628) menopause from the Pittsburgh Lung Screening Study. The Pittsburgh Lung Screening Study is a community-based research cohort of current and former smokers, screened with low-dose computed tomography and followed up for lung cancer. Early menopause was defined as occurring before 45 years of age. The analyses were stratified by menopause types because of the different biological and medical causes of natural and surgical menopause. Statistical methods included linear model, generalized linear model, linear mixed-effects model, and time-to-event analysis. RESULTS: The average age of the 1666 female smokers was 59.4±6.7 years, with 1519 (91.2%) of the population as non-Hispanic Whites and 1064 (63.9%) of the population as current smokers at baseline. Overall, 646 (39%) women reported early menopause, including 198 (19.1%) women with natural menopause and 448 (71.3%) women with surgical menopause (P<.001). Demographic variables did not differ between early and nonearly menopause groups, regardless of menopause type. Significant associations were identified between early natural menopause and higher risk of wheezing (odds ratio, 1.65; P<.01), chronic bronchitis (odds ratio, 1.73; P<.01), and radiographic emphysema (odds ratio, 1.70; P<.001) and lower baseline lung spirometry in an obstructive pattern (-104.8 mL/s for forced expiratory volume in the first second with P<.01, -78.6 mL for forced vital capacity with P=.04, and -2.1% for forced expiratory volume in the first second-to-forced vital capacity ratio with P=.01). In addition, early natural menopause was associated with a more rapid decline of forced expiratory volume in the first second-to-forced vital capacity ratio (-0.16% per year; P=.01) and incident airway obstruction (odds ratio, 2.02; P=.04). Furthermore, women early natural menopause had a 40% increased risk of death (P=.023), which was mainly driven by respiratory diseases (hazard ratio, 2.32; P<.001). Mediation analyses further identified that more than 33.3% of the magnitude of the associations between early natural menopause and all-cause and respiratory mortality were explained by baseline forced expiratory volume in the first second. Additional analyses in women with natural menopause identified that the associations between continuous smoking and subsequent lung cancer risk and cancer mortality were moderated by early menopause status, and females with early natural menopause who continued smoking had the worst outcomes (hazard ratio, >4.6; P<.001). This study did not find associations reported above in female smokers with surgical menopause. CONCLUSION: Early natural menopause was found to be a risk factor for malignant and nonmalignant lung diseases and mortality in middle-aged and older female smokers. These findings have strong public health relevance as preventive strategies, including smoking cessation and chest computed tomography screening, should target this population (ie, female smokers with early natural menopause) to improve their postmenopausal health and well-being.

Elevated SARS-CoV-2 in peripheral blood and increased COVID-19 severity in American Indians/Alaska Natives.

Epidemiological data across the United States show health disparities in COVID-19 infection, hospitalization, and mortality by race/ethnicity. While the association between elevated SARS-CoV-2 viral loads (VLs) (i.e. upper respiratory tract (URT) and peripheral blood (PB)) and increased COVID-19 severity has been reported, data remain largely unavailable for some disproportionately impacted racial/ethnic groups, particularly for American Indian or Alaska Native (AI/AN) populations. As such, we determined the relationship between SARS-CoV-2 VL dynamics and disease severity in a diverse cohort of hospitalized patients. Results presented here are for study participants (n = 94, ages 21-88 years) enrolled in a prospective observational study between May and October 2020 who had SARS-CoV-2 viral clades 20A, C, and G. Based on self-reported race/ethnicity and sample size distribution, the cohort was stratified into two groups: (AI/AN, n = 43) and all other races/ethnicities combined (non-AI/AN, n = 51). SARS-CoV-2 VLs were quantified in the URT and PB on days 0-3, 6, 9, and 14. The strongest predictor of severe COVID-19 in the study population was the mean VL in PB (OR = 3.34; P = 2.00 × 10-4). The AI/AN group had the following: (1) comparable co-morbidities and admission laboratory values, yet more severe COVID-19 (OR = 4.81; P = 0.014); (2) a 2.1 longer duration of hospital stay (P = 0.023); and (3) higher initial and cumulative PB VLs during severe disease (P = 0.025). Moreover, self-reported race/ethnicity as AI/AN was the strongest predictor of elevated PB VLs (ß = 1.08; P = 6.00 × 10-4) and detection of SARS-CoV-2 in PB (hazard ratio = 3.58; P = 0.004). The findings presented here suggest a strong relationship between PB VL (magnitude and frequency) and severe COVID-19, particularly for the AI/AN group.

Circulatory metabolites trigger ex vivo arterial endothelial cell dysfunction in population chronically exposed to diesel exhaust.

BACKGROUND: Chronic exposure to diesel exhaust has a causal link to cardiovascular diseases in various environmental and occupational settings. Arterial endothelial cell function plays an important role in ensuring proper maintenance of cardiovascular homeostasis and the endothelial cell dysfunction by circulatory inflammation is a hallmark in cardiovascular diseases. Acute exposure to diesel exhaust in controlled exposure studies leads to artery endothelial cells dysfunction in previous study, however the effect of chronic exposure remains unknown. RESULTS: We applied an ex vivo endothelial biosensor assay for serum samples from 133 diesel engine testers (DETs) and 126 non-DETs with the aim of identifying evidence of increased risk for cardiovascular diseases. Environmental monitoring suggested that DETs were exposed to high levels of diesel exhaust aerosol (282.3 µg/m3 PM2.5 and 135.2 µg/m3 elemental carbon). Surprisingly, chronic diesel exhaust exposure was associated with a pro-inflammatory phenotype in the ex vivo endothelial cell model, in a dose-dependent manner with CCL5 and VCAM as most affected genes. This dysfunction was not mediated by reduction in circulatory pro-inflammatory factors but significantly associated with a reduction in circulatory metabolites cGMP and an increase in primary DNA damage in leucocyte in a dose-dependent manner, which also explained a large magnitude of association between diesel exhaust exposure and ex vivo endothelial biosensor response. Exogenous cGMP addition experiment further confirmed the induction of ex vivo biosensor gene expressions in endothelial cells treated with physiologically relevant levels of metabolites cGMP. CONCLUSION: Serum-borne bioactivity caused the arterial endothelial cell dysfunction may attribute to the circulatory metabolites based on the ex vivo biosensor assay. The reduced cGMP and increased polycyclic aromatic hydrocarbons metabolites-induced cyto/geno-toxic play important role in the endothelial cell dysfunction of workers chronic exposure to diesel exhaust.

Genetic Associations and Architecture of Asthma-COPD Overlap.

BACKGROUND: Some people have characteristics of both asthma and COPD (asthma-COPD overlap), and evidence suggests they experience worse outcomes than those with either condition alone. RESEARCH QUESTION: What is the genetic architecture of asthma-COPD overlap, and do the determinants of risk for asthma-COPD overlap differ from those for COPD or asthma? STUDY DESIGN AND METHODS: We conducted a genome-wide association study in 8,068 asthma-COPD overlap case subjects and 40,360 control subjects without asthma or COPD of European ancestry in UK Biobank (stage 1). We followed up promising signals (P < 5 × 10-6) that remained associated in analyses comparing (1) asthma-COPD overlap vs asthma-only control subjects, and (2) asthma-COPD overlap vs COPD-only control subjects. These variants were analyzed in 12 independent cohorts (stage 2). RESULTS: We selected 31 independent variants for further investigation in stage 2, and discovered eight novel signals (P < 5 × 10-8) for asthma-COPD overlap (meta-analysis of stage 1 and 2 studies). These signals suggest a spectrum of shared genetic influences, some predominantly influencing asthma (FAM105A, GLB1, PHB, TSLP), others predominantly influencing fixed airflow obstruction (IL17RD, C5orf56, HLA-DQB1). One intergenic signal on chromosome 5 had not been previously associated with asthma, COPD, or lung function. Subgroup analyses suggested that associations at these eight signals were not driven by smoking or age at asthma diagnosis, and in phenome-wide scans, eosinophil counts, atopy, and asthma traits were prominent. INTERPRETATION: We identified eight signals for asthma-COPD overlap, which may represent loci that predispose to type 2 inflammation, and serious long-term consequences of asthma.

Risk of Acute Lung Injury after Esophagectomy.

To develop a new approach for identifying acute lung injury (ALI) in surgical ward setting and to assess incidence rate, clinical outcomes, and risk factors for ALI cases after esophagectomy. We also compare the degree of lung injury between operative and non-operative sides. Consecutive esophageal cancer patients (n=1022) who underwent esophagectomy from Dec 2012 to Nov 2018 in our hospital were studied. An approach for identifying ALI was proposed that integrated radiographic assessment of lung edema (RALE) score to quantify degree of lung edema. Stepwise logistic regression identified risk factors for postoperative ALI incidence. The degree of bilateral lung injury was compared using the RALE score. The approach for identifying ALI in surgical ward setting was defined as acute onset, PaO2/FiO2≤300 mmHg, bilateral opacities on bedside chest radiograph with a RALE score≥16, and exclusion of cardiogenic pulmonary edema. Incidence rate of ALI was estimated to be 9.7%. ALI diagnosis was associated with multiple clinical complications, prolonged hospital stay, higher medical bills, and higher perioperative mortality. Nine risk factors including BMI, ASA class, DLCO%, duration of surgery, neutrophil percentage, high-density lipoprotein, and electrolyte disorders were identified. The RALE score of the lung lobes of the operative side was higher than the non-operative side. A new approach for identifying ALI in esophageal cancer patients receiving esophagectomy was proposed and several risk factors were identified. ALI is common and has severe outcomes. The lung lobes on the operative side are more likely to be affected than the non-operative side.