Exhaled breath condensate as a matrix for combustion-based nanoparticle exposure and health effect evaluation.
BACKGROUND
Health assessment and medical surveillance of workers exposed to combustion nanoparticles are challenging. The aim was to evaluate the feasibility of using exhaled breath condensate (EBC) from healthy volunteers for (1) assessing the lung deposited dose of combustion nanoparticles and (2) determining the resulting oxidative stress by measuring hydrogen peroxide (H(2)O(2)) and malondialdehyde (MDA).


METHODS
Fifteen healthy nonsmoker volunteers were exposed to three different levels of sidestream cigarette smoke under controlled conditions. EBC was repeatedly collected before, during, and 1 and 2 hr after exposure. Exposure variables were measured by direct reading instruments and by active sampling. The different EBC samples were analyzed for particle number concentration (light-scattering-based method) and for selected compounds considered oxidative stress markers.


RESULTS
Subjects were exposed to an average airborne concentration up to 4.3×10(5) particles/cm(3) (average geometric size ∼60-80 nm). Up to 10×10(8) particles/mL could be measured in the collected EBC with a broad size distribution (50(th) percentile ∼160 nm), but these biological concentrations were not related to the exposure level of cigarette smoke particles. Although H(2)O(2) and MDA concentrations in EBC increased during exposure, only H2O2 showed a transient normalization 1 hr after exposure and increased afterward. In contrast, MDA levels stayed elevated during the 2 hr post exposure.


CONCLUSIONS
The use of diffusion light scattering for particle counting proved to be sufficiently sensitive to detect objects in EBC, but lacked the specificity for carbonaceous tobacco smoke particles. Our results suggest two phases of oxidation markers in EBC: first, the initial deposition of particles and gases in the lung lining liquid, and later the start of oxidative stress with associated cell membrane damage. Future studies should extend the follow-up time and should remove gases or particles from the air to allow differentiation between the different sources of H(2)O(2) and MDA.
1 Institute for Work and Health (IST) , CH-1066 Epalinges-Lausanne, Switzerland .
Jean-Jacques
JJ
Sauvain
Magdalena Sánchez Sandoval
MS
Hohl
Pascal
P
Wild
Jacques André
JA
Pralong
Michael
M
Riediker
D000328:Adult; D015415:Biomarkers / Q000378:metabolism; D001944:Breath Tests / Q000379:methods; D004781:Environmental Exposure / Q000009:adverse effects; D045853:Exhalation; D005240:Feasibility Studies; D064368:Healthy Volunteers; D006801:Humans; D006861:Hydrogen Peroxide / Q000378:metabolism; D008027:Light; D008168:Lung / Q000187:drug effects* / Q000378:metabolism / Q000503:physiopathology; D008297:Male; D008315:Malondialdehyde / Q000378:metabolism; D053758:Nanoparticles; D018384:Oxidative Stress / Q000187:drug effects*; D011237:Predictive Value of Tests; D012542:Scattering, Radiation; D013557:Switzerland; D013997:Time Factors; D014028:Tobacco Smoke Pollution / Q000009:adverse effects*; D055815:Young Adult
D015415:Biomarkers; D014028:Tobacco Smoke Pollution; D008315:Malondialdehyde; D006861:Hydrogen Peroxide
acrolein; cigarette smoke; exhaled breath condensate; hydrogen peroxide; malondialdehyde; nanoparticle tracking analysis