Dust exposure and the impact on hospital readmission of farming and wood industry workers for asthma and chronic obstructive pulmonary disease (COPD)

Objectives It is still not well established how occupational air pollutants affect the prognosis of asthma or chronic obstructive pulmonary disease (COPD). This study uses nationwide Danish registers and quantitative dust industry exposure matrices (IEM) for the farming and wood industries to estimate whether previous year dust exposure level impacts hospital readmissions for workers diagnosed with asthma or COPD. Methods We identified all individuals with a first diagnosis of either asthma (769 individuals) or COPD (342 individuals) between 1997 and 2007 and followed them until the next hospital admission for asthma or COPD, emigration, death or 31 December 2007. We included only individuals who worked in either the wood or farming industries at least one year during follow-up. We used logistic regression analysis to investigate associations between dust exposure level in the previous year and hospital readmission, adjusting for sex, age, time since first diagnosis, socioeconomic status, and labor force participation. Results Asthma readmissions for individuals with low and high dust exposure were increased [adjusted rate ratio (RR adj) 2.52, 95% confidence interval (CI) 1.45-4.40] and RR adj2.64 (95% CI 1.52-4.60), respectively. For COPD readmission, the risk estimates were RR adj1.36 (95% CI 0.57-3.23) for low and RR adj1.20 (95% CI 0.49-2.95) for high exposure level in the previous year. For asthma readmission, stratified analyses by type of dust exposure during follow-up showed increased risks for both wood dust [RR adj2.67 (95% CI 1.35-5.26) high exposure level] and farming dust [RR adj3.59 (95% CI 1.11-11.59) high exposure level]. No clear associations were seen for COPD readmissions. Conclusions This study indicates that exposure to wood or farm dust in the previous year increases the risk of hospital readmission for individuals with asthma but not for those with COPD

Associations between proximity to livestock farms, primary health care visits and self-reported symptoms

BACKGROUND: Living in a neighbourhood with a high density of livestock farms has been associated with adverse respiratory health effects, but less is known about healthcare utilisation. This study aimed at investigating the associations between livestock exposure and primary health care visits and self-reported symptoms. In addition, we examined the potentially confounding effect of distance from home to general practice. METHODS: Contact data between 2006 and 2009 were obtained from electronic medical records of 54,777 persons registered within 16 general practices in an area with a high density of livestock farms in the Netherlands. Data on self-reported symptoms were used from a cross-sectional sample of 531 patients in 2010. Livestock presence in a 500 m radius from home was computed using Geographic Information System data. RESULTS: In general, livestock exposure was associated with fewer contacts and self-reported symptoms for respiratory and other conditions. The number of poultry within 500 m was positively associated with the number of contacts. A longer distance to general practice was associated with fewer contacts, but did not confound associations. CONCLUSIONS: People living close to livestock farms less often see their general practitioner and report symptoms

A comparison of passive and active dust sampling methods for measuring airborne methicillin-resistant Staphylococcus aureus in pig farms

Methicillin-resistant strains of Staphylococcus aureus (MRSA) are resistant to most β-lactam antibiotics. Pigs are an important reservoir of livestock-associated MRSA (LA-MRSA), which is genetically distinct from both hospital and community-acquired MRSA. Occupational exposure to pigs on farms can lead to LA-MRSA carriage by workers. There is a growing body of research on MRSA found in the farm environment, the airborne route of transmission, and its implication on human health. This study aims to directly compare two sampling methods used to measure airborne MRSA in the farm environment; passive dust sampling with electrostatic dust fall collectors (EDCs), and active inhalable dust sampling using stationary air pumps with Gesamtstaubprobenahme (GSP) sampling heads containing Teflon filters. Paired dust samples using EDCs and GSP samplers, totaling 87 samples, were taken from 7 Dutch pig farms, in multiple compartments housing pigs of varying ages. Total nucleic acids of both types of dust samples were extracted and targets indicating MRSA (femA, nuc, mecA) and total bacterial count (16S rRNA) were quantified using quantitative real-time PCRs. MRSA could be measured from all GSP samples and in 94% of the EDCs, additionally MRSA was present on every farm sampled. There was a strong positive relationship between the paired MRSA levels found in EDCs and those measured on filters (Normalized by 16S rRNA; Pearson's correlation coefficient r = 0.94, Not Normalized; Pearson's correlation coefficient r = 0.84). This study suggests that EDCs can be used as an affordable and easily standardized method for quantifying airborne MRSA levels in the pig farm setting

Optimization of bacterial DNA and endotoxin extraction from settled airborne dust

Collecting and obtaining sufficient amount of airborne particles for multiple microbial component assessments can be challenging. A passive dust sampling device, the electrostatic dust fall collector (EDC) has been established for assessing airborne exposures including endotoxin and glucans. Recently, with advances in next-generation sequencing techniques, EDCs were used to collect microbial cells for DNA sequencing analysis to promote the study of airborne bacterial and fungal communities. However, low DNA yields have been problematic when employing passive sampling with EDC. To address this challenge, we attempted to increase the efficiency of extraction. We compared DNA extraction efficiency of bacterial components from EDCs captured on filters through filtration using five extraction techniques. By measuring the abundance, diversity and structure of bacterial communities using qPCR and amplicon sequencing targeting 16S rRNA genes, we found that two techniques outperformed the rest. Furthermore, we developed protocols to simultaneously extract both DNA and endotoxin from a single EDC cloth. Our technique promotes a high quality to price ratio and may be employed in large epidemiological studies addressing airborne bacterial exposure where a large number of samples is needed

A transcriptionally distinct CXCL13+CD103+CD8+ T-cell population is associated with B-cell recruitment and neoantigen load in human cancer

The chemokine CXCL13 mediates recruitment of B cells to tumors and is essential for the formation of tertiary lymphoid structures (TLSs). TLSs are thought to support antitumor immunity and are associated with improved prognosis. However, it remains unknown whether TLSs are formed in response to the general inflammatory character of the tumor microenvironment, or rather, are induced by (neo)antigen-specific adaptive immunity. We here report on the finding that the transforming growth factor beta (TGFβ)-dependent CD103+CD8+ tumor-infiltrating T-cell (TIL) subpopulation expressed and produced CXCL13. Accordingly, CD8+ T cells from peripheral blood activated in the presence of TGFβ upregulated CD103 and secreted CXCL13. Conversely, inhibition of TGFβ receptor signaling abrogated CXCL13 production. CXCL13+CD103+CD8+ TILs correlated with B-cell recruitment, TLSs, and neoantigen burden in six cohorts of human tumors. Altogether, our findings indicated that TGFβ plays a non-canonical role in coordinating immune responses against human tumors and suggest a potential role for CXCL13+CD103+CD8+ TILs in mediating B-cell recruitment and TLS formation in human tumors

Establishing farm dust as a useful viral metagenomic surveillance matrix

Farm animals may harbor viral pathogens, some with zoonotic potential which can possibly cause severe clinical outcomes in animals and humans. Documenting the viral content of dust may provide information on the potential sources and movement of viruses. Here, we describe a dust sequencing strategy that provides detailed viral sequence characterization from farm dust samples and use this method to document the virus communities from chicken farm dust samples and paired feces collected from the same broiler farms in the Netherlands. From the sequencing data, Parvoviridae and Picornaviridae were the most frequently found virus families, detected in 85-100% of all fecal and dust samples with a large genomic diversity identified from the Picornaviridae. Sequences from the Caliciviridae and Astroviridae familes were also obtained. This study provides a unique characterization of virus communities in farmed chickens and paired farm dust samples and our sequencing methodology enabled the recovery of viral genome sequences from farm dust, providing important tracking details for virus movement between livestock animals and their farm environment. This study serves as a proof of concept supporting dust sampling to be used in viral metagenomic surveillance

Ventilation and thermal conditions in secondary schools in the Netherlands: Effects of COVID-19 pandemic control and prevention measures

During the COVID-19 pandemic, the importance of ventilation was widely stressed and new protocols of ventilation were implemented in school buildings worldwide. In the Netherlands, schools were recommended to keep the windows and doors open, and after a national lockdown more stringent measures such as reduction of occupancy were introduced. In this study, the actual effects of such measures on ventilation and thermal conditions were investigated in 31 classrooms of 11 Dutch secondary schools, by monitoring the indoor and outdoor CO 2 concentration and air temperature, both before and after the lockdown. Ventilation rates were calculated using the steady-state method. Pre-lockdown, with an average occupancy of 17 students, in 42% of the classrooms the CO 2 concentration exceeded the upper limit of the Dutch national guidelines (800 ppm above outdoors), while 13% had a ventilation rate per person (VR p) lower than the minimum requirement (6 l/s/p). Post-lockdown, the indoor CO 2 concentration decreased significantly while for ventilation rates significant increase was only found in VR p, mainly caused by the decrease in occupancy (average 10 students). The total ventilation rate per classrooms, mainly induced by opening windows and doors, did not change significantly. Meanwhile, according to the Dutch national guidelines, thermal conditions in the classrooms were not satisfying, both pre- and post-lockdown. While opening windows and doors cannot achieve the required indoor environmental quality at all times, reducing occupancy might not be feasible for immediate implementation. Hence, more controllable and flexible ways for improving indoor air quality and thermal comfort in classrooms are needed

Establishing farm dust as a useful viral metagenomic surveillance matrix.

Farm animals may harbor viral pathogens, some with zoonotic potential which can possibly cause severe clinical outcomes in animals and humans. Documenting the viral content of dust may provide information on the potential sources and movement of viruses. Here, we describe a dust sequencing strategy that provides detailed viral sequence characterization from farm dust samples and use this method to document the virus communities from chicken farm dust samples and paired feces collected from the same broiler farms in the Netherlands. From the sequencing data, Parvoviridae and Picornaviridae were the most frequently found virus families, detected in 85-100% of all fecal and dust samples with a large genomic diversity identified from the Picornaviridae. Sequences from the Caliciviridae and Astroviridae familes were also obtained. This study provides a unique characterization of virus communities in farmed chickens and paired farm dust samples and our sequencing methodology enabled the recovery of viral genome sequences from farm dust, providing important tracking details for virus movement between livestock animals and their farm environment. This study serves as a proof of concept supporting dust sampling to be used in viral metagenomic surveillance