Estimating mean exposures from censored data: exposure to benzene in the Australian petroleum industry

A retrospective assessment of exposure to benzene was carried out for a nested case control study of lympho-haematopoietic cancers, including leukaemia, in the Australian petroleum industry. Each job or task in the industry was assigned a Base Estimate (BE) of exposure derived from task-based personal exposure assessments carried out by the company occupational hygienists. The BEs corresponded to the estimated arithmetic mean exposure to benzene for each job or task and were used in a deterministic algorithm to estimate the exposure of subjects in the study. Nearly all of the data sets underlying the BEs were found to contain some values below the limit of detection (LOD) of the sampling and analytical methods and some were very heavily censored; up to 95% of the data were below the LOD in some data sets. It was necessary, therefore, to use a method of calculating the arithmetic mean exposures that took into account the censored data. Three different methods were employed in an attempt to select the most appropriate method for the particular data in the study. A common method is to replace the missing (censored) values with half the detection limit. This method has been recommended for data sets where much of the data are below the limit of detection or where the data are highly skewed; with a geometric standard deviation of 3 or more. Another method, involving replacing the censored data with the limit of detection divided by the square root of 2, has been recommended when relatively few data are below the detection limit or where data are not highly skewed. A third method that was examined is Cohen's method. This involves mathematical extrapolation of the left-hand tail of the distribution, based on the distribution of the uncensored data, and calculation of the maximum likelihood estimate of the arithmetic mean. When these three methods were applied to the data in this study it was found that the first two simple methods give similar results in most cases. Cohen's method on the other hand, gave results that were generally, but not always, higher than simpler methods and in some cases gave extremely high and even implausible estimates of the mean. It appears that if the data deviate substantially from a simple log-normal distribution, particularly if high outliers are present, then Cohen's method produces erratic and unreliable estimates. After examining these results, and both the distributions and proportions of censored data, it was decided that the half limit of detection method was most suitable in this particular study.

Deployment of DGT units in marine waters to assess the environmental risk from a deep sea tailings outfall

Measurements of total, filterable and DGT-labile concentrations of nine metals (Al, Cd, Cr, Cu, Fe, Pb, Mn, Ni and Zn) have been made at five sites up to 4.2km from a deep sea tailings outfall operated by Lihir Gold Ltd. at Lihir Island, Papua New Guinea. At each site, pairs of DGT units (one containing a 0.4mm and the other a 0.8mm diffusive gel layer) were deployed at three depths (50–70; 105–130; 135–155m) for 4–7 days. Comparison of predicted water column DGT-labile metal concentrations in field deployments showed the 0.8mm DGT units were relatively enriched in metals, with the effect being greatest closer to the outfall for Pb and Mn and least for Fe, Cr, Ni and Zn. The most likely explanation for this is that in addition to simple ion diffusion, kinetic factors associated with ageing or desorption processes govern release of metals from iron and aluminium oxyhydroxide colloids which diffuse through the gels. The thicker gels have a longer residence time over which metals can be released for adsorption. This model explains why enrichment is most pronounced near the outfall; more distant sites have lower colloid concentrations because of the longer time for coagulation to increase particle sizes to the extent they cannot enter the gels. Total and filterable metal (FM) concentrations were frequently below the limits of detection (LOD) achievable by conventional ICP-AES (1–52gL⁻¹) and this limited their usefulness for assessing environmental risk and for metal speciation determination. Because of its pre-concentration step DGT gave metal concentrations above their LODs and these decreased exponentially with distance from the outfall. Concentrations of DGT–labile metal fell below Australian water quality guidelines for protection of 99% of marine organisms within 0.13km of the outfall for Cd, Cr and Ni and below that for protection of 95% of marine organisms within 0.4, 0.7 and 3.6km for lead, zinc and copper, respectively.

A biomimetic sensor for the detection of lead in water.

The monitoring of lead (II) ions (Pb(2+)) in water is essential for both human health and the environment. Herein, a simple yet innovative biosensor for Pb(2+) detection is presented. The sensor is developed by the self-assembly of gold nanoparticles (GNPs) core-satellite structure using naturally occurring tripeptide glutathione (GSH) as linker. The addition of Pb(2+) caused a red-to-blue color change and the localized surface plasmon resonance (LSPR) band was shifted to ca. 650nm. The limit of detection (LOD) is found to be 47.6nM (9.9ppb) by UV-vis spectroscopy with high selectivity against other heavy metals. This method offers a new strategy for heavy metal detection using functionalized GNPs.

Application of dried blood spots to determine vitamin D status in a large nutritional study with unsupervised sampling: the Food4Me project

An efficient and robust method to measure vitamin D (25-hydroxy vitamin D3 (25(OH)D3) and 25-hydroxy vitamin D2 in dried blood spots (DBS) has been developed and applied in the pan-European multi-centre, internet-based, personalised nutrition intervention study Food4Me. The method includes calibration with blood containing endogenous 25(OH)D3, spotted as DBS and corrected for haematocrit content. The methodology was validated following international standards. The performance characteristics did not reach those of the current gold standard liquid chromatography-MS/MS in plasma for all parameters, but were found to be very suitable for status-level determination under field conditions. DBS sample quality was very high, and 3778 measurements of 25(OH)D3 were obtained from 1465 participants. The study centre and the season within the study centre were very good predictors of 25(OH)D3 levels (P<0·001 for each case). Seasonal effects were modelled by fitting a sine function with a minimum 25(OH)D3 level on 20 January and a maximum on 21 July. The seasonal amplitude varied from centre to centre. The largest difference between winter and summer levels was found in Germany and the smallest in Poland. The model was cross-validated to determine the consistency of the predictions and the performance of the DBS method. The Pearson's correlation between the measured values and the predicted values was r 0·65, and the sd of their differences was 21·2 nmol/l. This includes the analytical variation and the biological variation within subjects. Overall, DBS obtained by unsupervised sampling of the participants at home was a viable methodology for obtaining vitamin D status information in a large nutritional study.

Counter-pressure-assisted ITP with electrokinetic injection under field-amplified conditions for bacterial analysis

Counter-pressure was used to extend the duration of field-amplified sample injection in isotachophoresis (FASI-ITP) in order to improve the detection of bacterial cells. Using 0.51-μm negatively charged encapsulated fluorescent beads as a model, the counter-pressure, injection and separation voltages, and times were optimized. Using 6-min 8,963-Pa counter-pressure FASI-ITP injections at −12 kV followed by mobilization of the ITP band with continued injection at −6 kV, the limit of detection (LOD) for Escherichia coli was improved to 78 cells/mL, a factor of 4 when compared with FASI-ITP without counter-pressure.

Performance analysis of a field-effect-transistor based aptasensor

Prostate cancer is one of the most diagnosed cancers which leads to a considerable number of deaths due to the lack of early and sensitive detection. This paper presents an aptamer functionalized field effect (FET) based biosensor for the detection of prostate cancer. Prostate specific antigen (PSA) is considered as the biomarker for prostate cancer whose detection is confirmed by attaching aptamers onto the sensor surface. Through the modelling and numerical simulation, the paper aims to evaluate and predict the performance parameters such as sensitivity, settling time, and limit of detection (LOD) of a label-free FET based electronic biosensor. Various sensor parameters such as structure (i.e., geometry), type of the FET (e.g., nanowire FET, spherical FET, ion-selective FET, and magnetic particle) radius of the FET channel and incubation time are optimized and analyzed. In addition, concentration of analyte biomolecules, diffusion coefficients and affinity to the receptor molecules are also investigated to determine the optimize performance parameters.