Malondialdehyde and anion patterns in exhaled breath condensate among subway workers

Rational Design and Application of Breath Sensors for Healthcare Monitoring

Biomarkers contained in human exhaled breath are closely related to certain diseases. As a noninvasive, portable, and efficient health diagnosis method, the breath sensor has received considerable attention in recent years for early disease screening and prevention due to its user-friendly and easy-accessible features. Although some key challenges have been addressed, its capability to precisely monitor specific biomarkers of interest and its physiological relevance to health metrics is still to be ascertained. In this context, we analyzed the rational design and recent advance of breath sensors for healthcare monitoring. This review begins with an introduction to exhaled breath biomarkers and their sensing technologies, such as chemoresistive, humidity-sensitive, electrochemical, and colorimetric principles. Then, a systematic overview of their emerging applications in early disease screening, drunk driving inspection, apnea monitoring, and exhaled breath condensate analysis are demonstrated. Finally, we discuss the challenges and opportunities of breath sensors for noninvasive healthcare monitoring. With the ongoing research efforts, the continuous breakthrough in breath sensors and their attractive applications is foreseeable in the future.

Metabolomics and proteomics in occupational medicine: a comprehensive systematic review

BACKGROUND

Occupational biomonitoring is essential for assessing health risks linked to workplace exposures. The use of 'omics' technologies, such as metabolomics and proteomics, has become crucial in detecting subtle biological alterations induced by occupational hazards, thereby opening novel avenues for biomarker discovery.

AIMS

This systematic review aims to evaluate the application of metabolomics and proteomics in occupational health.

METHODS

Following the PRISMA guidelines, we conducted a comprehensive search on PubMed, Scopus, and Web of Science for original human studies that use metabolomics or proteomics to assess occupational exposure biomarkers. The risk of bias was assessed by adapting the Cochrane Collaboration tool and the Newcastle-Ottawa Quality Assessment Scale.

RESULTS

Of 2311 initially identified articles, 85 met the eligibility criteria. These studies were mainly conducted in China, Europe, and the United States of America, covering a wide range of occupational exposures. The findings revealed that metabolomics and proteomics approaches effectively identified biomarkers related to chemical, physical, biomechanical, and psychosocial hazards. Analytical methods varied, with mass spectrometry-based techniques emerging as the most prevalent. The risk of bias was generally low to moderate, with specific concerns about exposure measurement and confounding factors.

CONCLUSIONS

Integrating metabolomics and proteomics in occupational health biomonitoring significantly advances our understanding of exposure effects and facilitates the development of personalized preventive interventions. However, challenges remain regarding the complexity of data analysis, biomarker specificity, and the translation of findings into preventive measures. Future research should focus on longitudinal studies and biomarker validation across diverse populations to improve the reliability and applicability of occupational health interventions.

A pilot study of the cardiopulmonary effects in healthy volunteers after exposure to high levels of PM2.5 in a New York City subway station

BACKGROUND

Subway systems are becoming increasingly common worldwide transporting large populations in major cities. PM2.5 concentrations have been demonstrated to be exceptionally high when underground, however. Studies on the impact of subway PM exposure on cardiopulmonary health in the United States are limited.

METHODS

Healthy volunteers in New York City were exposed to a 2-h visit on the 9th Street Station platform on the Port Authority Trans-Hudson train system. Blood pressure, heart rate variability (HRV), spirometry, and forced impulse oscillometry were measured, and urine, blood spot, and nasal swab biosamples were collected for cytokine analysis at the end of the 2-h exposure period. These endpoints were compared against individual control measurements collected after 2-h in a "clean" control space. In addition to paired comparisons, mixed effects models with subject as a random effect were employed to investigate the effect of the PM2.5 concentrations and visit type (i.e., subway vs. control).

RESULTS

Mean PM2.5 concentrations on the platform and during the control visit were 293.6 ± 65.7 (SD) and 4.6 ± 1.9 µg/m3, respectively. There was no change in any of the health metrics, but there was a non-significant trend for SDNN to be lower after subway exposure compared to control exposure. Total symptomatic scores did increase post-subway exposure compared to reported values prior to exposure or after the control visit. No significant changes in cytokine concentrations in any specimen type were observed. Mixed-effects models mostly corroborated these paired comparisons.

CONCLUSIONS

Acute exposures to PM on a subway platform do not cause measurable cardiopulmonary effects apart from reductions in HRV and increases in symptoms in healthy volunteers. These findings match other studies that found little to no changes in lung function and blood pressure after exposure in underground subway stations. Future work should still target potentially more vulnerable populations, such as individuals with asthma or those who spend increased time underground on the subway such as transit workers.

Metal and oxidative potential exposure through particle inhalation and oxidative stress biomarkers: a 2-week pilot prospective study among Parisian subway workers

OBJECTIVE

In this pilot study on subway workers, we explored the relationships between particle exposure and oxidative stress biomarkers in exhaled breath condensate (EBC) and urine to identify the most relevant biomarkers for a large-scale study in this field.

METHODS

We constructed a comprehensive occupational exposure assessment among subway workers in three distinct jobs over 10 working days, measuring daily concentrations of particulate matter (PM), their metal content and oxidative potential (OP). Individual pre- and post-shift EBC and urine samples were collected daily. Three oxidative stress biomarkers were measured in these matrices: malondialdehyde (MDA), 8-hydroxy-2'deoxyguanosine (8-OHdG) and 8-isoprostane. The association between each effect biomarker and exposure variables was estimated by multivariable multilevel mixed-effect models with and without lag times.

RESULTS

The OP was positively associated with Fe and Mn, but not associated with any effect biomarkers. Concentration changes of effect biomarkers in EBC and urine were associated with transition metals in PM (Cu and Zn) and furthermore with specific metals in EBC (Ba, Co, Cr and Mn) and in urine (Ba, Cu, Co, Mo, Ni, Ti and Zn). The direction of these associations was both metal- and time-dependent. Associations between Cu or Zn and MDAEBC generally reached statistical significance after a delayed time of 12 or 24 h after exposure. Changes in metal concentrations in EBC and urine were associated with MDA and 8-OHdG concentrations the same day.

CONCLUSION

Associations between MDA in both EBC and urine gave opposite response for subway particles containing Zn versus Cu. This diverting Zn and Cu pattern was also observed for 8-OHdG and urinary concentrations of these two metals. Overall, MDA and 8-OHdG responses were sensitive for same-day metal exposures in both matrices. We recommend MDA and 8-OHdG in large field studies to account for oxidative stress originating from metals in inhaled particulate matter.

Discriminative potential of exhaled breath condensate biomarkers with respect to chronic obstructive pulmonary disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) affecting 334 million people in the world remains a major cause of morbidity and mortality. Proper diagnosis of COPD is still a challenge and largely solely based on spirometric criteria. We aimed to investigate the potential of nitrosative/oxidative stress and related metabolic biomarkers in exhaled breath condensate (EBC) to discriminate COPD patients.

METHODS

Three hundred three participants were randomly selected from a 15,000-transit worker cohort within the Respiratory disease Occupational Biomonitoring Collaborative Project (ROBoCoP). COPD was defined using the Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria as post-bronchodilator ratio of Forced Expiratory Volume in 1st second to Forced Vital Capacity < 0.7 in spirometry validated by an experienced pulmonologist. Discriminative power of biomarker profiles in EBC was analyzed using linear discriminant analyses.

RESULTS

Amongst 300 participants with validated spirometry, 50.3% were female, 52.3 years old in average, 36.0% were current smokers, 12.7% ex-smokers with mean tobacco exposure of 15.4 pack-years. Twenty-one participants (7.0%) were diagnosed as COPD, including 19 new diagnoses, 12 of which with a mild COPD stage (GOLD 1). Amongst 8 biomarkers measured in EBC, combination of 2 biomarkers, Lactate and Malondialdehyde (MDA) significantly discriminated COPD subjects from non-COPD, with a 71%-accuracy, area under the receiver curve of 0.78 (p-value < 0.001), and a negative predictive value of 96%.

CONCLUSIONS

These findings support the potential of biomarkers in EBC, in particular lactate and MDA, to discriminate COPD patients even at a mild or moderate stage. These EBC biomarkers present a non-invasive and drugless technique, which can improve COPD diagnosis in the future.

Job Exposure Matrix, a Solution for Retrospective Assessment of Particle Exposure in a Subway Network and Their Long-Term Effects

INTRODUCTION

Health effects after long-term exposure to subway particulate matter (PM) remain unknown due to the lack of individual PM exposure data. This study aimed to apply the job exposure matrix (JEM) approach to retrospectively assess occupational exposure to PM in the Parisian subway.

METHODS

Job, the line and sector of the transport network, as well as calendar period were four JEM dimensions. For each combination of these dimensions, we generated statistical models to estimate the annual average PM10 concentration using data from an exhaustive inventory of the PM measurement campaigns conducted between 2004 and 2020 in the Parisian subway and historical data from the Parisian air pollution monitoring network. The resulting JEM and its exposure estimates were critically examined by experts using the uncertainty analysis framework.

RESULTS

The resulting JEM allows for the assignment of the estimated annual PM10 concentration to three types of professionals working in the subway: locomotive operators, station agents, and security guards. The estimates' precision and validity depend on the amount and quality of PM10 measurement data used in the job-, line-, and sector-specific models. Models using large amounts of personal exposure measurement data produced rather robust exposure estimates compared to models with lacunary data (i.e., in security guards). The analysis of uncertainty around the exposure estimates allows for the identification of the sources of uncertainty and parameters to be addressed in the future in order to refine and/or improve the JEM.

CONCLUSIONS

The JEM approach seems relevant for the retrospective exposure assessment of subway workers. When applied to available data on PM10, it allows for the estimation of this exposure in locomotive operators and station agents with an acceptable validity. Conversely, for security guards, the current estimates have insufficient validity to recommend their use in an epidemiological study. Therefore, the current JEM should be considered as a valid prototype, which shall be further improved using more robust measurements for some jobs. This JEM can also be further refined by considering additional exposure determinants.

Particulate matter concentration and composition in the New York City subway system

This study investigated the concentration and composition of particulate matter (PM2.5) in the New York City subway system. Realtime measurements, at a one-second cadence, and gravimetric measurements were performed inside train cars along 300 kilometers of nine subway lines, as well as on 333 platforms from 287 subway stations. The mean (±SD) PM2.5 concentration on the underground platforms was 142 ± 69 μg/m3 versus 29 ± 20 μg/m3 for aboveground stations. The average Concentrations inside train cars were 88 ± 14 μg/m3 when traveling through underground tunnels and platforms and 29 ± 31 μg/m3 while on aboveground tracks. The particle composition analysis of filtered samples was done using X-ray fluorescence (XRF), revealing that iron made up approximately 43% of the total PM2.5 mass on station platforms, around 126 times higher than the outdoor ambient iron concentration. Other trace elements include silicon, sulfur, copper, nickel, aluminum, calcium, barium, and manganese. Considering the very high iron content, the comparative analysis of the measured concentration versus the standards set by the Environmental Protection Agency (US EPA) is questionable since those limits are largely based on particulate matter from fossil fuel combustion. Health impact analysis of iron-based particles will complement the study results presented here.

A harmonized protocol for an international multicenter prospective study of nanotechnology workers: the NanoExplore cohort

Nanotechnology applications are fast-growing in many industrial fields. Consequently, health effects of engineered nanomaterials (ENMs) should be investigated. Within the EU-Life project NanoExplore, we developed a harmonized protocol of an international multicenter prospective cohort study of workers in ENM-producing companies. This article describes the development of the protocol, sample size calculation, data collection and management procedures and discusses its relevance with respect to research needs. Within this protocol, workers' ENM exposure will be assessed over four consecutive working days during the initial recruitment campaign and the subsequent follow-up campaigns. Biomonitoring using noninvasive sampling of exhaled breath condensate (EBC), exhaled air, and urine will be collected before and after 4-day exposure monitoring. Both exposure and effect biomarkers, will be quantified along with pulmonary function tests and diagnosed diseases reported using a standardized epidemiological questionnaire available in four languages. Until now, this protocol was implemented at seven companies in Switzerland, Spain and Italy. The protocol is well standardized, though sufficiently flexible to include company-specific conditions and occupational hygiene measures. The recruitment, to date, of 140 participants and collection of all data and samples, enabled us launching the first international cohort of nanotechnology workers. All companies dealing with ENMs could join the NanoExplore Consortium, apply this harmonized protocol and enter in the cohort, concieved as an open cohort. Its protocol meets all requirements of a hypotheses-driven prospective study, which will assess and reassess effects of ENM exposure on workers' health by updating the follow-up of the cohort. New hypothesis could be also considered.

Challenges in Quantifying 8-OHdG and 8-Isoprostane in Exhaled Breath Condensate

Exhaled breath condensate (EBC) has attracted substantial interest in the last few years, enabling the assessment of airway inflammation with a non-invasive method. Concentrations of 8-Hydroxydesoxyguanosine (8-OHdG) and 8-isoprostane in EBC have been suggested as candidate biomarkers for lung diseases associated with inflammation and oxidative stress. EBC is a diluted biological matrix and consequently, requires highly sensitive chemical analytic methods (picomolar range) for biomarker quantification. We developed a new liquid chromatography coupled to tandem mass spectrometry method to quantify 8-OHdG and 8-isoprostane in EBC simultaneously. We applied this novel biomarker method in EBC obtained from 10 healthy subjects, 7 asthmatic subjects, and 9 subjects with chronic obstructive pulmonary disease. Both biomarkers were below the limit of detection (LOD) despite the good sensitivity of the chemical analytical method (LOD = 0.5 pg/mL for 8-OHdG; 1 pg/mL for 8-isoprostane). This lack of detection might result from factors affecting EBC collections. These findings are in line with methodological concerns already raised regarding the reliability of EBC collection for quantification of 8-OHdG and 8-isoprostane. Precaution is therefore needed when comparing literature results without considering methodological issues relative to EBC collection and analysis. Loss of analyte during EBC collection procedures still needs to be resolved before using these oxidative stress biomarkers in EBC.