Internal arsenite bioassay calibration using multiple reporter cell lines

Bioassays with bioreporter bacteria are usually calibrated with analyte solutions of known concentrations that are analysed along with the samples of interest. This is done as bioreporter output (the intensity of light, fluorescence or colour) does not only depend on the target concentration, but also on the incubation time and physiological activity of the cells in the assay. Comparing the bioreporter output with standardized colour tables in the field seems rather difficult and error-prone. A new approach to control assay variations and improve application ease could be an internal calibration based on the use of multiple bioreporter cell lines with drastically different reporter protein outputs at a given analyte concentration. To test this concept, different Escherichia coli-based bioreporter strains expressing either cytochrome c peroxidase (CCP, or CCP mutants) or β-galactosidase upon induction with arsenite were constructed. The reporter strains differed either in the catalytic activity of the reporter protein (for CCP) or in the rates of reporter protein synthesis (for β-galactosidase), which, indeed, resulted in output signals with different intensities at the same arsenite concentration. Hence, it was possible to use combinations of these cell lines to define arsenite concentration ranges at which none, one or more cell lines gave qualitative (yes/no) visible signals that were relatively independent of incubation time or bioreporter activity. The discriminated concentration ranges would fit very well with the current permissive (e.g. World Health Organization) levels of arsenite in drinking water (10 µg l−1).

The QUASAR reproducibility study, Part II: Results from a multi-center Arterial Spin Labeling test-retest study.

Arterial Spin Labeling (ASL) is a method to measure perfusion using magnetically labeled blood water as an endogenous tracer. Being fully non-invasive, this technique is attractive for longitudinal studies of cerebral blood flow in healthy and diseased individuals, or as a surrogate marker of metabolism. So far, ASL has been restricted mostly to specialist centers due to a generally low SNR of the method and potential issues with user-dependent analysis needed to obtain quantitative measurement of cerebral blood flow (CBF). Here, we evaluated a particular implementation of ASL (called Quantitative STAR labeling of Arterial Regions or QUASAR), a method providing user independent quantification of CBF in a large test-retest study across sites from around the world, dubbed "The QUASAR reproducibility study". Altogether, 28 sites located in Asia, Europe and North America participated and a total of 284 healthy volunteers were scanned. Minimal operator dependence was assured by using an automatic planning tool and its accuracy and potential usefulness in multi-center trials was evaluated as well. Accurate repositioning between sessions was achieved with the automatic planning tool showing mean displacements of 1.87+/-0.95 mm and rotations of 1.56+/-0.66 degrees . Mean gray matter CBF was 47.4+/-7.5 [ml/100 g/min] with a between-subject standard variation SD(b)=5.5 [ml/100 g/min] and a within-subject standard deviation SD(w)=4.7 [ml/100 g/min]. The corresponding repeatability was 13.0 [ml/100 g/min] and was found to be within the range of previous studies.

Biodiversity of amoebae and amoeba-associated bacteria in water treatment plants.

In this study, we enlarged our previous investigation focusing on the biodiversity of chlamydiae and amoebae in a drinking water treatment plant, by the inclusion of two additional plants and by searching also for the presence of legionellae and mycobacteria. Autochthonous amoebae were recovered onto non-nutritive agar, identified by 18S rRNA gene sequencing, and screened for the presence of bacterial endosymbionts. Bacteria were also searched for by Acanthamoeba co-culture. From a total of 125 samples, we recovered 38 amoebae, among which six harboured endosymbionts (three chlamydiae and three legionellae). In addition, we recovered by amoebal co-culture 11 chlamydiae, 36 legionellae (no L. pneumophila), and 24 mycobacteria (all rapid-growers). Two plants presented a similar percentage of samples positive for chlamydiae (11%), mycobacteria (20%) and amoebae (27%), whereas in the third plant the number of recovered bacteria was almost twice higher. Each plant exhibited a relatively high specific microbiota. Amoebae were mainly represented by various Naegleria species, Acanthamoeba species and Hartmannella vermiformis. Parachlamydiaceae were the most abundant chlamydiae (8 strains in total), and in this study we recovered a new genus-level strain, along with new chlamydiae previously reported. Similarly, about 66% of the recovered legionellae and 47% of the isolated mycobacteria could represent new species. Our work highlighted a high species diversity among legionellae and mycobacteria, dominated by putative new species, and it confirmed the presence of chlamydiae in these artificial water systems.

Estimating traveltimes and groundwater flow patterns using 3D time-lapse crosshole ERT imaging of electrical resistivity fluctuations induced by infiltrating river water

The infiltration of river water into aquifers is of high relevance to drinking-water production and is a key driver of biogeochemical processes in the hyporheic and riparian zone, but the distribution and quantification of the infiltrating water are difficult to determine using conventional hydrological methods (e.g., borehole logging and tracer tests). By time-lapse inverting crosshole ERT (electrical resistivity tomography) monitoring data, we imaged groundwater flow patterns driven by river water infiltrating a perialpine gravel aquifer in northeastern Switzerland. This was possible because the electrical resistivity of the infiltrating water changed during rainfall-runoff events. Our time-lapse resistivity models indicated rather complex flow patterns as a result of spatially heterogeneous bank filtration and aquifer heterogeneity. The upper part of the aquifer was most affected by the river infiltrate, and the highest groundwater velocities and possible preferential flow occurred at shallow to intermediate depths. Time series of the reconstructed resistivity models matched groundwater electrical resistivity data recorded on borehole loggers in the upper and middle parts of the aquifer, whereas the resistivity models displayed smaller variations and delayed responses with respect to the logging data. in the lower part. This study demonstrated that crosshole ERT monitoring of natural electrical resistivity variations of river infiltrate could be used to image and quantify 3D bank filtration and aquifer dynamics at a high spatial resolution.

Stochastic inversion of tracer test and electrical geophysical data to estimate hydraulic conductivities.

Quantifying the spatial configuration of hydraulic conductivity (K) in heterogeneous geological environments is essential for accurate predictions of contaminant transport, but is difficult because of the inherent limitations in resolution and coverage associated with traditional hydrological measurements. To address this issue, we consider crosshole and surface-based electrical resistivity geophysical measurements, collected in time during a saline tracer experiment. We use a Bayesian Markov-chain-Monte-Carlo (McMC) methodology to jointly invert the dynamic resistivity data, together with borehole tracer concentration data, to generate multiple posterior realizations of K that are consistent with all available information. We do this within a coupled inversion framework, whereby the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration. To minimize computational expense, a facies-based subsurface parameterization is developed. The Bayesian-McMC methodology allows us to explore the potential benefits of including the geophysical data into the inverse problem by examining their effect on our ability to identify fast flowpaths in the subsurface, and their impact on hydrological prediction uncertainty. Using a complex, geostatistically generated, two-dimensional numerical example representative of a fluvial environment, we demonstrate that flow model calibration is improved and prediction error is decreased when the electrical resistivity data are included. The worth of the geophysical data is found to be greatest for long spatial correlation lengths of subsurface heterogeneity with respect to wellbore separation, where flow and transport are largely controlled by highly connected flowpaths.

How Accurate Are Blood (or Breath) Tests for Identifying Self-Reported Heavy Drinking Among People with Alcohol Dependence?

AIMS: Managing patients with alcohol dependence includes assessment for heavy drinking, typically by asking patients. Some recommend biomarkers to detect heavy drinking but evidence of accuracy is limited. METHODS: Among people with dependence, we assessed the performance of disialo-carbohydrate-deficient transferrin (%dCDT, ≥1.7%), gamma-glutamyltransferase (GGT, ≥66 U/l), either %dCDT or GGT positive, and breath alcohol (> 0) for identifying 3 self-reported heavy drinking levels: any heavy drinking (≥4 drinks/day or >7 drinks/week for women, ≥5 drinks/day or >14 drinks/week for men), recurrent (≥5 drinks/day on ≥5 days) and persistent heavy drinking (≥5 drinks/day on ≥7 consecutive days). Subjects (n = 402) with dependence and current heavy drinking were referred to primary care and assessed 6 months later with biomarkers and validated self-reported calendar method assessment of past 30-day alcohol use. RESULTS: The self-reported prevalence of any, recurrent and persistent heavy drinking was 54, 34 and 17%. Sensitivity of %dCDT for detecting any, recurrent and persistent self-reported heavy drinking was 41, 53 and 66%. Specificity was 96, 90 and 84%, respectively. %dCDT had higher sensitivity than GGT and breath test for each alcohol use level but was not adequately sensitive to detect heavy drinking (missing 34-59% of the cases). Either %dCDT or GGT positive improved sensitivity but not to satisfactory levels, and specificity decreased. Neither a breath test nor GGT was sufficiently sensitive (both tests missed 70-80% of cases). CONCLUSIONS: Although biomarkers may provide some useful information, their sensitivity is low the incremental value over self-report in clinical settings is questionable.

Safer-drinking strategies used by chronically homeless individuals with alcohol dependence.

Chronically homeless individuals with alcohol dependence experience severe alcohol-related consequences. It is therefore important to identify factors that might be associated with reduced alcohol-related harm, such as the use of safer-drinking strategies. Whereas effectiveness of safer-drinking strategies has been well-documented among young adults, no studies have explored this topic among more severely affected populations, such as chronically homeless individuals with alcohol dependence. The aims of this study were thus to qualitatively and quantitatively document safer-drinking strategies used in this population. Participants (N=31) were currently or formerly chronically homeless individuals with alcohol dependence participating in a pilot study of extended-release naltrexone and harm-reduction counseling. At weeks 0 and 8, research staff provided a list of safer-drinking strategies for participants to endorse. Implementation of endorsed safer-drinking strategies was recorded at the next appointment. At both time points, strategies to buffer the effects of alcohol on the body (e.g., eating prior to and during drinking) were most highly endorsed, followed by changing the manner in which one drinks (e.g., spacing drinks), and reducing alcohol consumption. Quantitative analyses indicated that all participants endorsed safer-drinking strategies, and nearly all strategies were implemented (80-90% at weeks 0 and 8, respectively). These preliminary findings indicate that chronically homeless people with alcohol dependence use strategies to reduce harm associated with their drinking. Larger randomized controlled trials are needed to test whether interventions that teach safer-drinking strategies may reduce overall alcohol-related harm in this population.