Suchergebnisse

Engineered nanomaterials (ENMs) raise questions among the scientific community and public health authorities about their potential risks to human health. Studying a prospective cohort of workers exposed to ENMs would be considered the gold standard for identifying potential health effects of nanotechnology and confirming the 'no effect' levels derived from cellular and animal models. However, because only small, cross-sectional studies have been conducted in the past 5 years, questions remain about the health risks of ENMs. This essay addresses the scientific, methodological, political and regulatory issues that make epidemiological research in nanotechnology-exposed communities particularly complex. Scientific challenges include the array of physicochemical parameters and ENM production conditions, the lack of universally accepted definitions of ENMs and nanotechnology workers, and the lack of information about modes of action, target organs and likely dose– response functions of ENMs. Standardisation of data collection and harmonisation of research protocols are needed to eliminate misclassification of exposures and health effects. Forming ENM worker cohorts from a combination of smaller cohorts and overcoming selection bias are also challenges. National or international registries for monitoring the exposures and health of ENM workers would be helpful for epidemiological studies, but the creation of such a registry and ENM worker cohorts will require political support and dedicated funding at the national and international levels. Public authorities and health agencies should consider carrying out an ENM awareness campaign to educate and engage all stakeholders and concerned communities in discussion of such a project.

Abstract
Exposure to metal oxides nanomaterials (NMs) might trigger adverse health effects. NMs can generate Oxidative Stress (OS), causing redox effects detectable in urine through suitable biomarkers. We evaluated the cross-sectional association of urinary OS biomarkers with urinary metal concentrations, using data collected in the multicenter international study NanoExplore. One hundred forty-one workers were recruited at three R&D and four industrial facilities employing NMs in different processes (paints/coating[PC];construction chemicals[CC]). Only 129 workers had complete data and, based on the personal work-shift exposure to NMs, they were classified as unexposed workers (n=41), workers with negligible/low exposure (n=37), and with moderate/high exposure (n=51). OS biomarkers (IsoP,MDA,TAP) and metals (27Al,47Ti,52Cr,118Sn) were quantified in urine samples collected before and after exposure monitoring campaign (2-4 work-shifts). Between-group comparisons were performed with non-parametric tests according to the data distribution. Highly exposed workers had significantly higher pro-oxidant (IsoP and MDA,p<0.005) and antioxidant (TAP,p<0.05) biomarkers concentrations. 47Ti,118Sn and 29Si were significantly higher in CC workers (p<0.005). IsoP and TAP were positively associated with 29Si (both p<0.001), 47Ti (p=0.036,p=0.003), 52Cr (p=0.048,p=0.003) and 118Sn (p=0.047,p=0.022). The ongoing analyses will assess the potential mediation role of OS and metal biomarkers. Occupational exposure to NMs can represent an underestimated hazard for people handling NMs products, increasing OS and potentially beginning pathological processes. Although the health significance of such findings needs to be further elucidated, the assessment of metals in urine may represent a useful tool for estimating the body burden of NMs long-term exposure.

Abstract
We aimed at analyzing dose-response relationship between occupational exposure to a mixture of nanomaterials (NMs) and effect biomarkers measured according to the NanoExplore protocol in exhaled breath condensate (EBC, local pulmonary level)) and urine (systemic level) of 141 workers. Two exposure metrics: particle number concentration (PNC) and lung deposited surface area (LDSA) were monitored using DiSCMini for 2-4 8h-workshifts. Biological samples were collected twice, before and after exposure monitoring. We assumed that current or short-term exposure to NMs is associated in a linear dose-response manner to the effect biomarker concentration. We analyzed each biomarker separately, using the multilevel mixed-effects interval regression models to properly manage the biomarker concentrations the LOD or in the interval between the LOD and the limit of quantification. We used directed acyclic graphs to identify all potential confounders: age, smoking status, medication status, and study center. Center and the participant's ID were modeled as random effect variables. For IL-10, IL-1β and TNF-α in EBC we observed consistent positive dose-response relationships with both PNC and LDSA. For urinary Total Antioxidant Power the relationship was consistently negative. For MDA, KL-6, hs-CRP or NOTyr in EBC and urinary MDA and 8-Isoprostane, no relationship was found. These results suggest an activation of the innate immune response rather than oxidative stress as the main effect of the mixture of NM investigated. This study offers new insights into the dose-response relationship between exposure to NMs and possible indicators of early and long-term biological alterations in the cohort of recruited workers.