Low Exposure Range Research Articles

Suicide and Transportation Noise: A Prospective Cohort Study from Switzerland.

Although plausible from a pathophysiological point of view, robust evidence for effects of transportation noise on mental health remains scarce. Meanwhile, psychiatric diseases are among the most prevalent noncommunicable diseases worldwide, and suicide as a mortality outcome highly connected to mental disorders presents a pressing public health issue. The aim of this study was to investigate the association between source-specific transportation noise, particulate matter (PM) air pollution, residential greenness, and suicide by means of a nationwide cohort study. Road traffic, railway and aircraft noise exposure as well as exposure to air pollution [PM with aerodynamic diameter ()] and greenness [normalized difference vegetation index (NDVI)] were linked to 5.1 million adults (age 15 y and older) in the Swiss National Cohort, accounting for their address history. Mean noise exposure in 5-y periods was calculated. Individuals were followed for up to 15 y (2001-2015). Time-varying Cox regression models were applied to deaths by suicide (excluding assisted suicide). Models included all three noise sources, , and NDVI plus individual and spatial covariates, including socioeconomic status. Effect modification by sex, age, socioeconomic indicators, and degree of urbanization was explored. During the follow-up, there were 11,265 suicide deaths (10.4% poisoning, 33.3% hanging, 28.7% firearms, 14.7% falls). Road traffic and railway noise were associated with total suicides [hazard ratios: 1.040; 95% confidence interval (CI): 1.015, 1.065; and 1.022 (95% CI: 1.004, 1.041) per 10 dB day-evening-night level (Lden)], whereas for aircraft noise, a risk increase starting from 50 dB was masked by an inverse association in the very low exposure range (30-40 dB). Associations were stronger for females than males. The results were robust to adjustment for residential greenness and air pollution. In this longitudinal, nationwide cohort study, we report a robust association between exposure to road traffic and railway noise and risk of death by suicide after adjusting for exposure to air pollution and greenness. These findings add to the growing body of evidence that mental health disorders may be related to chronic transportation noise exposure. https://doi.org/10.1289/EHP11587.

Incident dementia and long-term exposure to constituents offine particle air pollution: A national cohort study in the United States.

Growing evidence suggests that fine particulate matter (PM2.5) likely increases the risks of dementia, yet little is known about the relative contributions of different constituents. Here, we conducted a nationwide population-based cohort study (2000 to 2017) by integrating the Medicare Chronic Conditions Warehouse database and two independently sourced datasets of high-resolution PM2.5 major chemical composition, including black carbon (BC), organic matter (OM), nitrate (NO3-), sulfate (SO42-), ammonium (NH4+), and soil dust (DUST). To investigate the impact of long-term exposure to PM2.5 constituents on incident all-cause dementia and Alzheimer's disease (AD), hazard ratios for dementia and AD were estimated using Cox proportional hazards models, and penalized splines were used to evaluate potential nonlinear concentration-response (C-R) relationships. Results using two exposure datasets consistently indicated higher rates of incident dementia and AD for an increased exposure to PM2.5 and its major constituents. An interquartile range increase in PM2.5 mass was associated with a 6 to 7% increase in dementia incidence and a 9% increase in AD incidence. For different PM2.5 constituents, associations remained significant for BC, OM, SO42-, and NH4+ for both end points (even after adjustments of other constituents), among which BC and SO42- showed the strongest associations. All constituents had largely linear C-R relationships in the low exposure range, but most tailed off at higher exposure concentrations. Our findings suggest that long-term exposure to PM2.5 is significantly associated with higher rates of incident dementia and AD and that SO42-, BC, and OM related to traffic and fossil fuel combustion might drive the observed associations.

Incident Dementia and Long‐Term Exposure to Constituents of U.S. Fine Particle Air Pollution: A National Cohort Study

AbstractBackgroundGrowing evidence suggests that PM2.5 likely increases the risks of neurological disorders, yet little is known about the relative contributions of different constituents. Understanding constituent‐specific effects are critical to targeting emission reductions of specific sources with the greatest health protection.MethodWe conducted a nationwide population‐based cohort study (2000‐2017), by integrating the Medicare Chronic Conditions Warehouse database and two sets of high‐resolution, multiple‐species, air pollution datasets to investigate the impact of long‐term exposure to PM2.5 constituents on incident dementia and Alzheimer’s disease (AD). and home health‐care claims. Hazard ratios for dementia and AD were estimated using single‐ and multi‐constituent Cox proportional hazards models, and penalized splines were used to evaluate potential nonlinear concentration‐response relationships.ResultsOf the 18.5 million dementia and 19.2 million AD individuals within these cohorts, 31.5% and 14.6% developed dementia and AD events, respectively. From the single‐pollutant models, an interquartile range (IQR) increase in PM2.5 mass was associated with an increase in dementia incidence ranging between 6‐7% using two exposure datasets. For different PM2.5 constituents, associations remained significant in black carbon (BC), organic matter (OM), sulfate (SO4 2−), and ammonium (NH4 +). Incident dementia was observed to have the strongest association with increases in exposure to SO4 2− and BC (10‐11% increase and 4‐6% per IQR increase, respectively). Effect estimates for AD were even larger. For both endpoints, all constituents had largely linear concentration‐response relationships in the low exposure range, but most tailed off at high exposure concentrations, particularly for AD.ConclusionOur study suggests that long‐term exposure to PM2.5 is significantly associated with increased incident dementia and AD, and that the different PM2.5 constituents may elicit differential neurotoxicity. Reduction of PM2.5 emissions, especially for the main sources of BC and SO4 2−, may reduce the burden of dementia or AD in the aging US population.

Estimation of the Exposure-Response Relation between Benzene and Acute Myeloid Leukemia by Combining Epidemiologic, Human Biomarker, and Animal Data.

Chemical risk assessment can benefit from integrating data across multiple evidence bases, especially in exposure-response curve (ERC) modeling when data across the exposure range are sparse. We estimated the ERC for benzene and acute myeloid leukemia (AML), by fitting linear and spline-based Bayesian meta-regression models that included summary risk estimates from non-AML and nonhuman studies as prior information. Our complete dataset included six human AML studies, three human leukemia studies, 10 human biomarker studies, and four experimental animal studies. A linear meta-regression model with intercept best predicted AML risks after cross-validation, both for the full dataset and AML studies only. Risk estimates in the low exposure range [<40 parts per million (ppm)-years] from this model were comparable, but more precise when the ERC was derived using all available data than when using AML data only. Allowing for between-study heterogeneity, RRs and 95% prediction intervals (95% PI) at 5 ppm-years were 1.58 (95% PI, 1.01-3.22) and 1.44 (95% PI, 0.85-3.42), respectively. Integrating the available epidemiologic, biomarker, and animal data resulted in more precise risk estimates for benzene exposure and AML, although the large between-study heterogeneity hampers interpretation of these results. The harmonization steps required to fit the Bayesian meta-regression model involve a range of assumptions that need to be critically evaluated, as they seem crucial for successful implementation. By describing a framework for data integration and explicitly describing the necessary data harmonization steps, we hope to enable risk assessors to better understand the advantages and assumptions underlying a data integration approach.See related commentary by Keil, p. 695.

Bayesian benchmark dose analysis for inorganic arsenic in drinking water associated with bladder and lung cancer using epidemiological data

Abundant epidemiological evidence has shown that there is a strong causal relationship between long-term exposure to inorganic arsenic (iAs) through drinking water and a few types of cancer (e.g., lung and bladder cancer). Traditionally, a linear low-dose extrapolation assumption was applied in risk assessment for iAs which resulted in a relatively conservative cancer risk estimate. Growing biological evidence suggests that the mode of action of iAs-induced cancer follows a threshold process (e.g., sufficient concentration of trivalent arsenic is required to disrupt normal cellular function). In this study, we applied the benchmark dose (BMD) methodology to model the relationship between the relative risk of bladder and lung cancer and the iAs concentration in drinking water using the high-quality epidemiological data reported in recently published papers, with a special focus on the low exposure range (i.e., <150 μg/L). Because of its biological plausibility and statistical flexibility, the Hill model has been chosen to model the data under a Bayesian framework. A Bayesian hierarchal model together with a bootstrap method for exposure estimation were applied to quantify uncertainty from various sources, including the within-study, between-study, and exposure uncertainties. Dose-response assessment results obtained from a number of alternative model structures and methods consistently demonstrate a threshold type dose-response curve with a threshold in the range between 40–60 μg/L of iAs concentration in drinking water. The BMD for iAs in drinking water associated with 0.1 % increase in relative risk of bladder cancer is 42.2 μg/L (BMDL 39.2 μg/L); for 0.05 % increase, the BMD is 41.6 μg/L (BMDL 38.6 μg/L). For lung cancer, the two counterpart BMD estimates are 57.0 μg/L (BMDL 43.6 μg/L) and 55.7 μg/L (BMDL 42.5 μg/L) for 0.1 % and 0.05 % increase, respectively. These analyses provide additional statistical support for a non-linear dose response for cancer risk from inorganic arsenic which may have important policy implications.

Low Doses of Psilocybin and Ketamine Enhance Motivation and Attention in Poor Performing Rats: Evidence for an Antidepressant Property.

Long term benefits following short-term administration of high psychedelic doses of serotonergic and dissociative hallucinogens, typified by psilocybin and ketamine respectively, support their potential as treatments for psychiatric conditions such as major depressive disorder. The high psychedelic doses induce perceptual experiences which are associated with therapeutic benefit. There have also been anecdotal reports of these drugs being used at what are colloquially referred to as “micro” doses to improve mood and cognitive function, although currently there are recognized limitations to their clinical and preclinical investigation. In the present studies we have defined a low dose and plasma exposure range in rats for both ketamine (0.3–3 mg/kg [10–73 ng/ml]) and psilocybin/psilocin (0.05–0.1 mg/kg [7–12 ng/ml]), based on studies which identified these as sub-threshold for the induction of behavioral stereotypies. Tests of efficacy were focused on depression-related endophenotypes of anhedonia, amotivation and cognitive dysfunction using low performing male Long Evans rats trained in two food motivated tasks: a progressive ratio (PR) and serial 5-choice (5-CSRT) task. Both acute doses of ketamine (1–3 mg/kg IP) and psilocybin (0.05–0.1 mg/kg SC) pretreatment increased break point for food (PR task), and improved attentional accuracy and a measure of impulsive action (5-CSRT task). In each case, effect size was modest and largely restricted to test subjects characterized as “low performing”. Furthermore, both drugs showed a similar pattern of effect across both tests. The present studies provide a framework for the future study of ketamine and psilocybin at low doses and plasma exposures, and help to establish the use of these lower concentrations of serotonergic and dissociative hallucinogens both as a valid scientific construct, and as having a therapeutic utility.

A causal exposure response function with local adjustment for confounding: Estimating health effects of exposure to low levels of ambient fine particulate matter.

In the last two decades, ambient levels of air pollution have declined substantially. At the same time, the Clean Air Act mandates that the National Ambient Air Quality Standards (NAAQS) must be routinely assessed to protect populations based on the latest science. Therefore, researchers should continue to address the following question: is exposure to levels of air pollution below the NAAQS harmful to human health? Furthermore, the contentious nature surrounding environmental regulations urges us to cast this question within a causal inference framework. Several parametric and semi-parametric regression approaches have been used to estimate the exposure-response (ER) curve between long-term exposure to ambient air pollution concentrations and health outcomes. However, most of the existing approaches are not formulated within a formal framework for causal inference, adjust for the same set of potential confounders across all levels of exposure, and do not account for model uncertainty regarding covariate selection and the shape of the ER. In this paper, we introduce a Bayesian framework for the estimation of a causal ER curve called LERCA (Local Exposure Response Confounding Adjustment), which a) allows for different confounders and different strength of confounding at the different exposure levels; and b) propagates model uncertainty regarding confounders' selection and the shape of the ER. Importantly, LERCA provides a principled way of assessing the observed covariates' confounding importance at different exposure levels, providing researchers with important information regarding the set of variables to measure and adjust for in regression models. Using simulation studies, we show that state of the art approaches perform poorly in estimating the ER curve in the presence of local confounding. LERCA is used to evaluate the relationship between long-term exposure to ambient PM2.5, a key regulated pollutant, and cardiovascular hospitalizations for 5,362 zip codes in the continental U.S. and located near a pollution monitoring site, while adjusting for a potentially varying set of confounders across the exposure range. Our data set includes rich health, weather, demographic, and pollution information for the years of 2011-2013. The estimated exposure-response curve is increasing indicating that higher ambient concentrations lead to higher cardiovascular hospitalization rates, and ambient PM2.5 was estimated to lead to an increase in cardiovascular hospitalization rates when focusing at the low exposure range. Our results indicate that there is no threshold for the effect of PM2.5 on cardiovascular hospitalizations.

Sexual Patterns Among Medical Students - A Bioethical Look

There are few empirical studies on the teaching of human sexuality in medical curricula, lacking in knowledge of how sexuality is taught, what content is used and how it is offered. The emergence of sexuality for a significant portion of university students occurs in college, which increases the importance of sexual education for this group, even though it constitutes only a small portion of our younger population. This is especially important for health students who should address the issue with their future patients. This research aimed to establish sexual differences between students of both sexes in an entire class of medical students. Evaluating the prevalence of sexual behaviors and sexual dysfunctions in this community was investigated, and finally the sexual patterns of students from a bioethical point of view were analyzed. General and specific questionnaires for both genders were used to evaluate and confront them. As a result, 120 questionnaires were applied in a 3rd year medical class of public universities of a northeastern Brazilian state, representing 100% of the sample. According to the Sexual Exposure Index (SEI), 35% of females predominated in the low risk exposure range. The male gender predominated in the medium exposure range, corresponding to 24.16% of the total target population. Applying the chi-squared test for group B versus A there was a p=8x10-4, X2=15 and OR=1.7. Finally, there is a need to approach this theme in the agenda for inserting it in the curriculum, but more studies are needed to apply this model.

Acute and chronic effects of ambient fine particulate matter on preterm births in Beijing, China: A time-series model

Accumulating evidence suggests that short- and long-term exposure to ambient fine particulate matter ≤ 2.5 μm (PM2.5) during pregnancy is associated with preterm births, yet the results are inconsistent, and the shape of the exposure-response curve is unclear, partially due to the limited studies conducted in areas with high air pollution. Our study evaluated the association between ambient PM2.5 concentration and preterm births in Beijing, China.Daily preterm birth data were collected from a hospital in Beijing during 2006 to 2013; a time-series of daily PM2.5 concentrations during the same period is assembled with measured data at three monitoring sites in Beijing. An extension of the Poisson regression and a time-series model were applied to simultaneously estimate the acute and chronic effects of exposure to PM2.5, with mutual adjustment for short- and long-term exposure as well as for confounders.During the study period, the PM2.5 concentration was 70.4 ± 60.6 μg/m3 and was found to be associated with an increased risk of preterm birth. In the study cohort, a 0.52% (95% confidence interval, CI: 0.09%, 0.96%) and 3.13% (95%CI: 1.92%, 4.35%) increase in preterm births was estimated for each 10-μg/m3 increase in short- and long-term exposure, respectively. This association was significantly modified by season (p < 0.05). With mutual adjustments for short- and long-term exposure, a more robust association (3.16%, 95% CI: 1.95%, 4.39%; per 10-μg/m3 increment in PM2.5) was observed for chronic effects. The exposure–response relationships for both short- and long-term exposure were linear, without a threshold, over the relatively low exposure range and flattened out at higher concentration levels. The maximum effect for long-term exposure to PM2.5 (33.6%) was much greater than that for short-term exposure (19.9%). These findings indicate that air quality improvements over a long period could yield significant health benefits.

Risks, risk assessment and risk competence in toxicology.

Understanding the toxic effects of xenobiotics requires sound knowledge of physiology and biochemistry. The often described lack of understanding pharmacology/toxicology is therefore primarily caused by the general absence of the necessary fundamental knowledge. Since toxic effects depend on exposure (or dosage) assessing the risks arising from toxic substances also requires quantitative reasoning. Typically public discussions nearly always neglect quantitative aspects and laypersons tend to disregard dose-effect-relationships. One of the main reasons for such disregard is the fact that exposures often occur at extremely low concentrations that can only be perceived intellectually but not by the human senses. However, thresholds in the low exposure range are often scientifically disputed. At the same time, ignorance towards known dangers is wide-spread. Thus, enhancing the risk competence of laypersons will have to be initially restricted to increasing the awareness of existing problems.

The relationship between population-level exposure to alcohol advertising on television and brand-specific consumption among underage youth in the US.

We investigated the population-level relationship between exposure to brand-specific advertising and brand-specific alcohol use among US youth. We conducted an internet survey of a national sample of 1031 youth, ages 13-20, who had consumed alcohol in the past 30 days. We ascertained all of the alcohol brands respondents consumed in the past 30 days, as well as which of 20 popular television shows they had viewed during that time period. Using a negative binomial regression model, we examined the relationship between aggregated brand-specific exposure to alcohol advertising on the 20 television shows [ad stock, measured in gross rating points (GRPs)] and youth brand-consumption prevalence, while controlling for the average price and overall market share of each brand. Brands with advertising exposure on the 20 television shows had a consumption prevalence about four times higher than brands not advertising on those shows. Brand-level advertising elasticity of demand varied by exposure level, with higher elasticity in the lower exposure range. The estimated advertising elasticity of 0.63 in the lower exposure range indicates that for each 1% increase in advertising exposure, a brand's youth consumption prevalence increases by 0.63%. At the population level, underage youths' exposure to brand-specific advertising was a significant predictor of the consumption prevalence of that brand, independent of each brand's price and overall market share. The non-linearity of the observed relationship suggests that youth advertising exposure may need to be lowered substantially in order to decrease consumption of the most heavily advertised brands.

Risk Estimation with Epidemiologic Data When Response Attenuates at High-Exposure Levels

BackgroundIn occupational studies, which are commonly used for risk assessment for environmental settings, estimated exposure–response relationships often attenuate at high exposures. Relative risk (RR) models with transformed (e.g., log- or square root–transformed) exposures can provide a good fit to such data, but resulting exposure–response curves that are supralinear in the low-dose region may overestimate low-dose risks. Conversely, a model of untransformed (linear) exposure may underestimate risks attributable to exposures in the low-dose region.MethodsWe examined several models, seeking simple parametric models that fit attenuating exposure–response data well. We have illustrated the use of both log-linear and linear RR models using cohort study data on breast cancer and exposure to ethylene oxide.ResultsLinear RR models fit the data better than do corresponding log-linear models. Among linear RR models, linear (untransformed), log-transformed, square root–transformed, linear-exponential, and two-piece linear exposure models all fit the data reasonably well. However, the slopes of the predicted exposure–response relations were very different in the low-exposure range, which resulted in different estimates of the exposure concentration associated with a 1% lifetime excess risk (0.0400, 0.00005, 0.0016, 0.0113, and 0.0100 ppm, respectively). The linear (in exposure) model underestimated the categorical exposure–response in the low-dose region, whereas log-transformed and square root–transformed exposure models overestimated it.ConclusionAlthough a number of models may fit attenuating data well, models that assume linear or nearly linear exposure–response relations in the low-dose region of interest may be preferred by risk assessors, because they do not depend on the choice of a point of departure for linear low-dose extrapolation and are relatively easy to interpret.

Age and Gender Modifies Dose-response Relationship Between Tubewell Arsenic Exposure and Toenail Arsenic Concentration

S-29A7-2 Background/Aims: Although arsenic exposure from drinking water has been significantly associated with toenail arsenic (As) concentrations in adults, similar association in young adults and children, particularly at low exposure range, remains unknown. Thus, we tested a hypothesis that the dose response in adolescents and children due to As intake from drinking tube-well water and toenail As concentration is linear without threshold. Methods: In an As-endemic area of Bangladesh, all members of 50 families (n = 254) were enrolled in a prospective, repeated measures biomonitoring study. Inorganic As intake from drinking water was examined for its ability to predict the toenail As. Samples of drinking water and toenails were collected every 3 months during a 4-year period and analyzed for As using inductively coupled plasma-mass spectrometry. As concentrations in toenail were modeled using linear mixed effects models with regression splines. Results: As concentrations in drinking water varied by >1000-fold among the 254 persons (range, below detection limit—751.50 μg/L). Overall, the shape of the dose response was S-shape, with 3 distinct coefficients of association at low (<10 μg/L), medium (10–200 μg/L), and high (200–751.50 μg/L) exposure range. Water intake at medium As concentration range was associated with an 80% increase toenail As concentrations (P = 0.02). However, high water As exposure range was associated with 21% increase in toenail As concentration (P > 0.05). Furthermore, while no association was observed at the low range of water-level As concentration among boy <18 years of age, same range of exposure was associated with 68% higher toenail As level among girls <18 years old. Conclusion: Present results suggest that the dose-response relationship between tube-well As concentration and toenail concentration might significantly differ by age group, gender, and concentration range.

Flexible Meta-Regression to Assess the Shape of the Benzene–Leukemia Exposure–Response Curve

BackgroundPrevious evaluations of the shape of the benzene–leukemia exposure–response curve (ERC) were based on a single set or on small sets of human occupational studies. Integrating evidence from all available studies that are of sufficient quality combined with flexible meta-regression models is likely to provide better insight into the functional relation between benzene exposure and risk of leukemia.ObjectivesWe used natural splines in a flexible meta-regression method to assess the shape of the benzene–leukemia ERC.MethodsWe fitted meta-regression models to 30 aggregated risk estimates extracted from nine human observational studies and performed sensitivity analyses to assess the impact of a priori assessed study characteristics on the predicted ERC.ResultsThe natural spline showed a supralinear shape at cumulative exposures less than 100 ppm-years, although this model fitted the data only marginally better than a linear model (p = 0.06). Stratification based on study design and jackknifing indicated that the cohort studies had a considerable impact on the shape of the ERC at high exposure levels (> 100 ppm-years) but that predicted risks for the low exposure range (< 50 ppm-years) were robust.ConclusionsAlthough limited by the small number of studies and the large heterogeneity between studies, the inclusion of all studies of sufficient quality combined with a flexible meta-regression method provides the most comprehensive evaluation of the benzene–leukemia ERC to date. The natural spline based on all data indicates a significantly increased risk of leukemia [relative risk (RR) = 1.14; 95% confidence interval (CI), 1.04–1.26] at an exposure level as low as 10 ppm-years.

Low noise signal-to-noise ratio enhancing readout circuit for current-mediated active pixel sensors

Diagnostic digital fluoroscopic applications continuously expose patients to low doses of x-ray radiation, posing a challenge to both the digital imaging pixel and readout electronics when amplifying small signal x-ray inputs. Traditional switch-based amorphous silicon imaging solutions, for instance, have produced poor signal-to-noise ratios (SNRs) at low exposure levels owing to noise sources from the pixel readout circuitry. Current-mediated amorphous silicon pixels are an improvement over conventional pixel amplifiers with an enhanced SNR across the same low-exposure range, but whose output also becomes nonlinear with increasing dosage. A low-noise SNR enhancing readout circuit has been developed that enhances the charge gain of the current-mediated active pixel sensor (C-APS). The solution takes advantage of the current-mediated approach, primarily integrating the signal input at the desired frequency necessary for large-area imaging, while adding minimal noise to the signal readout. Experimental data indicates that the readout circuit can detect pixel outputs over a large bandwidth suitable for real-time digital diagnostic x-ray fluoroscopy. Results from hardware testing indicate that the minimum achievable C-APS output current that can be discerned at the digital fluoroscopic output from the enhanced SNR readout circuit is 0.341nA. The results serve to highlight the applicability of amorphous silicon current-mediated pixel amplifiers for large-area flat panel x-ray imagers.

Perceptibility curve test for conventional and colour-coded radiographs

A colour scale has been developed as a complement to the grey scale in radiographs. The aim of the present study was to compare colour-coded with conventional black-and-white radiographs in terms of the perceptibility curve test. Twelve digital radiographs were exposed on a test object from low to high exposures and recorded using the DIXI system (Planmeca Oy, Helsinki, Finland). An aluminium test object was used containing ten object details in the form of holes with depths ranging from 0.03 mm to 0.30 mm in steps of 0.03+/-0.01 mm. The new colour scale was used to transform the conventional black-and-white radiographs into colour radiographs by specially designed software. Ten observers were asked to analyse four sets of radiographs, i.e. colour-coded and black-and-white radiographs, and reversed colour-coded and reversed black-and-white radiographs. The object detail having the lowest perceptible contrast in each radiograph was registered for each observer. Perceptibility curves were plotted based on the mean value of observer data. Results from the perceptibility curve test showed that the information in colour-coded radiographs was at least as good as that in black-and-white radiographs. In fact, in the lower exposure range, colour-coded radiographs exhibited better perception than conventional black-and-white radiographs. Radiographs that are colour-coded with the applied colour scale may be used as an alternative to conventional black-and-white radiographs.

Proposal for single and mixture biological exposure limits for sevoflurane and nitrous oxide at low occupational exposure levels.

Assessment of individual exposures to sevoflurane plus nitrous oxide (N(2)O) by biological monitoring of unmodified analytes in post-shift urine of exposed personnel. Anaesthetics in urine and breathing area were monitored in 124 subjects in 11 operating theatres. Passive samplers were collected after 2.5-7 h of exposure, at the same time as post-shift urinary samples, to evaluate the individual time-weighted average (TWA) exposures to sevoflurane and N(2)O. A static headspace sampler coupled with a gas chromatograph mass spectrometer was used for analytical determinations (sensitivity sufficient to reveal biological/environmental exposures of 0.1 microg/l(urine) and 50 ppb for sevoflurane, and 1 microg/l(urine) and 80 ppb for N(2)O). Median (range) post-shift urinary and environmental values were 1.2 microg/l(urine) (0.1-5.0) and 0.4 ppm (0.05-3.0) for sevoflurane ( n=107) and 10.9 microg/l(urine) (0.5-74.9) and 8.6 ppm (0.2-123.4) for N(2)O ( n=121) (all low-exposure range). At log-log regression, urinary levels closely correlated with environmental data (sevoflurane, r(2)=0.7538; N(2)O, r(2)=0.8749). Biological equivalent limits (BELs) based on National Institute for Occupational Safety and Health (NIOSH) TWA exposure limits, calculated as means of regression slope and y-intercept, were 3.6 microg/l(urine) for sevoflurane (corresponding to 2 ppm) and 22.3 microg/l(urine) for N(2)O (corresponding to 25 ppm). Individual "mixture BELs", which we calculated by applying the American Conference of Governmental Industrial Hygienists (ACGIH) threshold limit value (TLV) mix formula to biomarker values and using the obtained NIOSH-based BELs as a reference, closely correlated with mixture TLVs (rho=0.816, Lin's concordance test). CONCLUSIONS. We propose urinary sevoflurane as a new, specific, internal dose biomarker for routine biological monitoring of personal exposures among operating-theatre personnel, and use of reliable "mixture BELs" to provide safer levels of internal exposure for workers exposed to mixtures of sevoflurane and N(2)O, and conceivably also to other mixtures of toxicants with possible additive effects.

The electronic structure and magnetism of NO adsorbed on Fe(1 0 0) surfaces

The electronic structure and magnetism of the NO adsorbed on Fe(1 0 0) surfaces was investigated using spin-polarized metastable deexcitation spectroscopy (SPMDS) and ultraviolet photoelectron spectroscopy (He I). It was indicated that the energy levels of the occupied and unoccupied orbitals of the NO 2π derived state were contiguous in the low exposure range to NO up to 1.0 L. As the NO coverage increased, these two parts of the 2π derived state split and the split width became larger. In the SPMDS measurements, the change of the spin asymmetry induced by the NO adsorption was observed. It is indicated that the NO adsorbate was not ferromagnetically ordered.

Conventional and predicted perceptibility curves for contrast-enhanced direct digital intraoral radiographs.

To construct Perceptibility Curves (PCs) for contrast-enhanced digital intraoral radiographs. Radiographs of a test object having holes of increasing depths were exposed using three digital systems, the CDR (Schick Technologies, Long Island, NY, USA), the Dixel (J Morita MFG, Kyoto, Japan) and the Sens-A-Ray (Regam Medical Systems, Sundsvall, Sweden). The radiographs were contrast-enhanced and PCs constructed in the conventional way using 10 observers. Predicted PCs were calculated and compared with observer data. The PCs showed that contrast enhancement is effective for the perception of small contrast details, especially in the low exposure range. Predicted PCs demonstrated excellent agreement with observer data. Contrast enhancement should be advantageous in digital radiography. The effects of contrast enhancement on PCs may be predicted without previous knowledge of observer performance.

Spin-resolved electronic structure of the outermost surface in the H 2O/Na/Fe(0 0 1) coadsorption system: spin-polarized metastable deexcitation spectroscopy study

The spin-resolved electronic structure of the outermost surface on the coadsorption system of H 2O and Na on an Fe(0 0 1) surface was investigated using spin-polarized metastable deexcitation spectroscopy (SPMDS). H 2O exposure on Fe(0 0 1) resulted in oxygen adsorption, where the SPMDS spectra and the observed spin polarization at the outermost surface were quite similar to those in O/Fe(0 0 1). In contrast, OH adsorption was observed when the Na-precovered Fe(0 0 1) surface was exposed to H 2O. The change of the spin polarization was found at the both SPMDS peak positions of Na 3s and OH 1π on the Na/Fe(0 0 1) surface during the exposure to H 2O. The change of the spin polarization at the Na 3s and OH 1π peak occurred simultaneously in the low exposure range (0–0.3 L), where polarization at Na 3s (OH 1π) changed to the positive (negative) direction. The observed behavior of the spin polarization is interpreted to indicate that the electron transfer from Na 3s to the partially vacant 1π orbital of OH, where the dominant transferred electrons are thought to have anti-parallel spins to the magnetized Fe substrate in this low exposure range.