Towards a consensus view on understanding nanomaterials hazards and managing exposure

The aim of this article is to present an overview of salient issues of exposure, characterisation and hazard assessment of nanomaterials as they emerged from the consensus-building of experts undertaken within the four year European Commission coordination project NanoImpactNet. The approach adopted is to consolidate and condense the findings and problem-identification in such a way as to identify knowledge-gaps and generate a set of interim recommendations of use to industry, regulators, research bodies and funders. The categories of recommendation arising from the consensual view address: significant gaps in vital factual knowledge of exposure, characterisation and hazards; the development, dissemination and standardisation of appropriate laboratory protocols; address a wide range of technical issues in establishing an adequate risk assessment platform; the more efficient and coordinated gathering of basic data; greater inter-organisational cooperation; regulatory harmonization; the wider use of the life-cycle approaches; and the wider involvement of all stakeholders in the discussion and solution-finding efforts for nanosafety.

Predictive analysis and mapping of indoor radon concentrations in Switzerland

It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

Risk factors of sunburns from occupational sun exposure in outdoor workers

Question: Outdoor workers can be exposed to intense ultraviolet (UV) solar radiation likely to results to sunburns. As sunburn is an important risk factor for skin cancer, in particular melanoma, we investigated the causes of occupational sunburns (OS) in French outdoor workers. Methods: A population-based survey was conducted in May-June 2012 through computer-assisted telephonic interviews in population 25 to 69 years of age. History of sunburn from occupational exposure within the year preceding interview was collected. We analysed the risk of OS in multivariate logistic regression. Results: Out of 1442 individuals who declared having an occupational exposure to solar UV radiation, 403 (27.9%) reported a sunburn from occupational exposure in the year preceding the interview. Sunburns were more frequent in women (30% vs. 26.4% in men although not significant p = 0.14), in younger workers (p = 0.0099), in sensitive phototype (40% in phototype I/II vs. 23% in phototype III/IV, p < 0.001) and in workers taking lunch outdoor (p = 0.0355). Some occupations were more associated with OS (more than 30%): health occupations, managing, research/engineering, construction workers and culture/art/social sciences workers. In multivariate analysis, risk factors for OS are phototype (I vs. IV, OR = 4.30 95% CI [2.65-6.98]), sunburn during leisure time (OR = 3.46 95% CI [2.62-4.59]), seasonality of exposure (seasonal vs. constant exposure OR = 1.36 95% CI [1.02-1.81] and annual UVA exposure (OR for 10J/m² daily average increment 1.08 95% CI [1.02-1.14]). In multivariate analysis the type of occupation was not associated with increased OS. Conclusion: Sunburns from occupation was also observed in non sensitive population, phototype IV, which shows that outdoor workers are potentially exposed to intense UV radiations. This study suggests that prevention should target UV sensitive outdoor workers as well as those cumulating intense UV exposure.

Solid-phase microextraction as short-term sampling technique for BTEX occupational exposure

Solid phase microextraction (SPME) has been widely used for many years in various applications, such as environmental and water samples, food and fragrance analysis, or biological fluids. The aim of this study was to suggest the SPME method as an alternative to conventional techniques used in the evaluation of worker exposure to benzene, toluene, ethylbenzene, and xylene (BTEX). Polymethylsiloxane-carboxen (PDMS/CAR) showed as the most effective stationary phase material for sorbing BTEX among other materials (polyacrylate, PDMS, PDMS/divinylbenzene, Carbowax/divinylbenzene). Various experimental conditions were studied to apply SPME to BTEX quantitation in field situations. The uptake rate of the selected fiber (75 μm PDMS/CAR) was determined for each analyte at various concentrations, relative humidities, and airflow velocities from static (calm air) to dynamic (>200 cm/s) conditions. The SPME method also was compared with the National Institute of Occupational Safety and Health method 1501. Unlike the latter, the SPME approach fulfills the new requirement for the threshold limit value-short term exposure limit (TLV-STEL) of 2.5 ppm for benzene (8 mg/m3).

Vancomycin exposure from active calcium sulfate bone filler

Objective: Bone cements and substitutes are commonly used in surgery to deliver antibiotics locally. The objective of this study was to assess the systemic absorption and disposition of vancomycin in patients treated with active calcium sulfate bone filler and to predict systemic concentrations under various conditions. Method: 277 blood samples were taken from 42 patients receiving vancomycin in bone cement during surgery. Blood samples were collected from 3h to 10 days after implantation. Vancomycin was measured by immunoenzymatic assay. Population pharmacokinetic (PK) analysis was performed using NONMEM to assess average estimates and variability of PK parameters. Based on the final model, simulations with various doses and renal function levels were performed. Results: The patients were 64 ± 20 years old, their body weight was 81 ± 22 kg and Cockcroft-Gault creatinine clearance (CLcr) 98 ± 55 mL/min. Vancomycin doses ranged from 200 mg to 6000 mg and implantation sites were hip (n=16), tibia (10) or others (16). Concentration profiles remained low and consistent with absorption rate-limited first-order release, while showing prominent variability. Mean clearance (CL) was 3.87 L/h (CV 35%), absorption rate constant (ka) 0.004 h-1 (66%) and volume of distribution (V) 9.5 L. Simulations with up to 8000 mg vancomycin implant showed systemic concentrations exceeding 20 mg/L for 3.5 days in 43% of the patients with CLcr 15 mL/min, whereas 7% of the patients with normal renal function had a concentration above 20 mg/L for 1.1 days. Subtherapeutic concentrations (0.4-4 mg/L) were predicted during a median of 22 days in patients with normal renal function and 4000 mg vancomycin implant, with limited influence of dose or renal function. Conclusion: Vancomycin-laden calcium sulfate implant does not raise toxicity concern. Selection of resistant bacteria, such as Enterococcus and Staphylococcus species, might however be a concern, as simulations show persistent subtherapeutic systemic concentrations during 3 to 4 weeks in these patients.

Particle exposure scenarios for research and production activities involving nanomaterials

Nanomaterials with structures in the nanoscale (1 to 100 nm) often have chemical, physical and bioactive characteristics different from those of larger entities of the same material. This is interesting for industry but raises questions about the health of exposed people. However, little is known so far about the exposure of workers to inhalable airborne nanomaterials. We investigated several activities in research laboratories and industry to learn about relevant exposure scenarios. Work process analyses were combined with measurements of airborne particle mass concentrations and number−size distributions. Background levels in research settings were mostly low, while in industrial production, levels were sometimes elevated, especially in halls near busy roads or in the presence of diesel fork lifts without particle filters. Peak levels were found in an industrial setting dealing with powders (up to 80,000 particles/cm³ and up to 15 mg/m³). Mostly low concentrations were found for activities involving liquid applications. However, centrifugation and lyophilization of nanoparticle containing solutions resulted in very high particle number concentrations (up to 300,000 particles/cm³), whereas no increases were seen for the same activities conducted with nanoparticle−free liquids. No significant increases of particle concentrations were found for processes involving nanoparticles bound to surfaces. Also no increases were observed in laboratories that were visualizing properties and structures of small amounts of nanomaterials. Conclusion: When studying exposure scenarios for airborne nanomaterials, the focus should not only be on processes involving nano−powders, but also on processes involving intensively treated nanoparticle−containing liquids. Acknowledgement: We thank Chantal Imhof, MSc and Guillaume Ferraris, MSc for their contributions.

Reflections on Partial Least Squares Path Modeling

The purpose of the present article is to take stock of a recent exchange in Organizational Research Methods between critics (Rönkkö & Evermann, 2013) and proponents (Henseler et al., 2014) of partial least squares path modeling (PLS-PM). The two target articles were centered around six principal issues, namely whether PLS-PM: (1) can be truly characterized as a technique for structural equation modeling (SEM); (2) is able to correct for measurement error; (3) can be used to validate measurement models; (4) accommodates small sample sizes; (5) is able to provide null hypothesis tests for path coefficients; and (6) can be employed in an exploratory, model-building fashion. We summarize and elaborate further on the key arguments underlying the exchange, drawing from the broader methodological and statistical literature in order to offer additional thoughts concerning the utility of PLS-PM and ways in which the technique might be improved. We conclude with recommendations as to whether and how PLS-PM serves as a viable contender to SEM approaches for estimating and evaluating theoretical models.

Contribution of fine particulate matter sources to indoor exposure in bars, restaurants, and cafes

This study investigated the contribution of sources and establishment characteristics, on the exposure to fine particulate matter (PM(2.5)) in the non-smoking sections of bars, cafes, and restaurants in central Zurich. PM(2.5)-exposure was determined with a nephelometer. A random sample of hospitality establishments was investigated on all weekdays, from morning until midnight. Each visit lasted 30 min. Numbers of smokers and other sources, such as candles and cooking processes, were recorded, as were seats, open windows, and open doors. Ambient air pollution data were obtained from public authorities. Data were analysed using robust MM regression. Over 14 warm, sunny days, 102 establishments were measured. Average establishment PM(2.5) concentrations were 64.7 microg/m(3) (s.d. = 73.2 microg/m(3), 30-min maximum 452.2 microg/m(3)). PM(2.5) was significantly associated with the number of smokers, percentage of seats occupied by smokers, and outdoor PM. Each smoker increased PM(2.5) on average by 15 microg/m(3). No associations were found with other sources, open doors or open windows. Bars had more smoking guests and showed significantly higher concentrations than restaurants and cafes. Smokers were the most important PM(2.5)-source in hospitality establishments, while outdoor PM defined the baseline. Concentrations are expected to be even higher during colder, unpleasant times of the year. PRACTICAL IMPLICATIONS: Smokers and ambient air pollution are the most important sources of fine airborne particulate matter (PM(2.5)) in the non-smoking sections of bars, restaurants, and cafes. Other sources do not significantly contribute to PM(2.5)-levels, while opening doors and windows is not an efficient means of removing pollutants. First, this demonstrates the impact that even a few smokers can have in affecting particle levels. Second, it implies that creating non-smoking sections, and using natural ventilation, is not sufficient to bring PM(2.5) to levels that imply no harm for employees and non-smoking clients. [Authors]

Self-potentials in partially saturated media: the importance of explicit modeling of electrode effects

Self-potential (SP) data are of interest to vadose zone hydrology because of their direct sensitivity to water flow and ionic transport. There is unfortunately little consensus in the literature about how to best model SP data under partially saturated conditions, and different approaches (often supported by one laboratory data set alone) have been proposed. We argue that this lack of agreement can largely be traced to electrode effects that have not been properly taken into account. A series of drainage and imbibition experiments were considered in which we found that previously proposed approaches to remove electrode effects were unlikely to provide adequate corrections. Instead, we explicitly modeled the electrode effects together with classical SP contributions using a flow and transport model. The simulated data agreed overall with the observed SP signals and allowed decomposing the different signal contributions to analyze them separately. After reviewing other published experimental data, we suggest that most of them include electrode effects that have not been properly taken into account. Our results suggest that previously presented SP theory works well when considering the modeling uncertainties presently associated with electrode effects. Additional work is warranted to not only develop suitable electrodes for laboratory experiments but also to assure that associated electrode effects that appear inevitable in longer term experiments are predictable, so that they can be incorporated into the modeling framework.

In vivo 13C NMR spectroscopy and metabolic modeling in the brain: a practical perspective.

In vivo 13C NMR spectroscopy has the unique capability to measure metabolic fluxes noninvasively in the brain. Quantitative measurements of metabolic fluxes require analysis of the 13C labeling time courses obtained experimentally with a metabolic model. The present work reviews the ingredients necessary for a dynamic metabolic modeling study, with particular emphasis on practical issues.