Sex differences in urinary levels of several biological indicators of exposure: a human volunteer study

The aim of the study was to quantify the variability on biological indicators of exposure between men and women for three well known solvents: methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1-trichloroethane. Another purpose was to explore the effect of selected CYP2E1 polymorphisms on the toxicokinetic profile. Controlled human exposures were carried out in a 12m(3) exposure chamber for each solvent separately, during 6h and at half of the threshold limit value. The human volunteers groups were composed of ten young men and fifteen young women, including ten women using hormonal contraceptive. An analysis of variance mainly showed an effect on the urinary levels of several biomarkers of exposure among women due to the use of hormonal contraceptive, with an increase of more than 50% in metabolites concentrations and a decrease of up to 50% in unchanged substances concentrations, suggesting an increase in their metabolism rate. The results also showed a difference due to the genotype CYP2E1*6, when exposed to methyl ethyl ketone, with a tendency to increase CYP2E1 activity when volunteers were carriers of the mutant allele. Our study suggests that not only physiological differences between men and women but also differences due to sex hormones levels can have an impact on urinary concentrations of several biomarkers of exposure. The observed variability due to sex among biological exposure indices can lead to misinterpretation of biomonitoring results. This aspect should have its place in the approaches for setting limits of occupational exposure. [Authors]

Digital holographic microscopy: a noninvasive contrast imaging technique allowing quantitative visualization of living cells with subwavelength axial accuracy.

We have developed a digital holographic microscope (DHM), in a transmission mode, especially dedicated to the quantitative visualization of phase objects such as living cells. The method is based on an original numerical algorithm presented in detail elsewhere [Cuche et al., Appl. Opt. 38, 6994 (1999)]. DHM images of living cells in culture are shown for what is to our knowledge the first time. They represent the distribution of the optical path length over the cell, which has been measured with subwavelength accuracy. These DHM images are compared with those obtained by use of the widely used phase contrast and Nomarski differential interference contrast techniques.

Monitoring of biological markers indicative of doping: the athlete biological passport

The athlete biological passport (ABP) was recently implemented in anti-doping work and is based on the individual and longitudinal monitoring of haematological or urine markers. These may be influenced by illicit procedures performed by some athletes with the intent to improve exercise performance. Hence the ABP is a valuable tool in the fight against doping. Actually, the passport has been defined as an individual and longitudinal observation of markers. These markers need to belong to the biological cascade influenced by the application of forbidden hormones or more generally, affected by biological manipulations which can improve the performance of the athlete. So far, the haematological and steroid profile modules of the ABP have been implemented in major sport organisations, and a further module is under development. The individual and longitudinal monitoring of some blood and urine markers are of interest, because the intraindividual variability is lower than the corresponding interindividual variability. Among the key prerequisites for the implementation of the ABP is its prospect to resist to the legal and scientific challenges. The ABP should be implemented in the most transparent way and with the necessary independence between planning, interpretation and result management of the passport. To ensure this, the Athlete Passport Management Unit (APMU) was developed and the WADA implemented different technical documents associated to the passport. This was carried out to ensure the correct implementation of a profile which can also stand the challenge of any scientific or legal criticism. This goal can be reached only by following strictly important steps in the chain of production of the results and in the management of the interpretation of the passport. Various technical documents have been then associated to the guidelines which correspond to the requirements for passport operation. The ABP has been completed very recently by the steroid profile module. As for the haematological module, individual and longitudinal monitoring have been applied and the interpretation cascade is also managed by a specific APMU in a similar way as applied in the haematological module. Thus, after exclusion of any possible pathology, specific variation from the individual norms will be then considered as a potential misuse of hormones or other modulators to enhance performance.

Visualization Resources for Iowa State University and the Iowa DOT: An Automated Design Model to Simulator Converter, November 2012

This project developed an automatic conversion software tool that takes input a from an Iowa Department of Transportation (DOT) MicroStation three-dimensional (3D) design file and converts it into a form that can be used by the University of Iowa’s National Advanced Driving Simulator (NADS) MiniSim. Once imported into the simulator, the new roadway has the identical geometric design features as in the Iowa DOT design file. The base roadway appears as a wireframe in the simulator software. Through additional software tools, textures and shading can be applied to the roadway surface and surrounding terrain to produce the visual appearance of an actual road. This tool enables Iowa DOT engineers to work with the universities to create drivable versions of prospective roadway designs. By driving the designs in the simulator, problems can be identified early in the design process. The simulated drives can also be used for public outreach and human factors driving research.

Visualization Resources for Iowa State University and the Iowa DOT: An Automated Design Model to Simulator Converter, November 2012

The creation of three-dimensional (3D) drawings for proposed designs for construction, re-construction and rehabilitation activities are becoming increasingly common for highway designers, whether by department of transportation (DOT) employees or consulting engineers. However, technical challenges exist that prevent the use of these 3D drawings/models from being used as the basis of interactive simulation. Use of driving simulation to service the needs of the transportation industry in the US lags behind Europe due to several factors, including lack of technical infrastructure at DOTs, cost of maintaining and supporting simulation infrastructure—traditionally done by simulation domain experts—and cost and effort to translate DOT domain data into the simulation domain.

Visualization Resources for Iowa State University and the Iowa DOT: An Automated Design Model to Simulator Converter, November 2012

The creation of three-dimensional (3D) drawings for proposed designs for construction, re-construction and rehabilitation activities are becoming increasingly common for highway designers, whether by department of transportation (DOT) employees or consulting engineers. However, technical challenges exist that prevent the use of these 3D drawings/models from being used as the basis of interactive simulation. Use of driving simulation to service the needs of the transportation industry in the US lags behind Europe due to several factors, including lack of technical infrastructure at DOTs, cost of maintaining and supporting simulation infrastructure—traditionally done by simulation domain experts—and cost and effort to translate DOT domain data into the simulation domain.

Biological activity of ectodysplasin A is conditioned by its collagen and heparan sulfate proteoglycan-binding domains.

Mutations in the TNF family ligand EDA1 cause X-linked hypohidrotic ectodermal dysplasia (XLHED), a condition characterized by defective development of skin appendages. The EDA1 protein displays a proteolytic processing site responsible for its conversion to a soluble form, a collagen domain, and a trimeric TNF homology domain (THD) that binds the receptor EDAR. In-frame deletions in the collagen domain reduced the thermal stability of EDA1. Removal of the collagen domain decreased its activity about 100-fold, as measured with natural and engineered EDA1-responsive cell lines. The collagen domain could be functionally replaced by multimerization domains or by cross-linking antibodies, suggesting that it functions as an oligomerization unit. Surprisingly, mature soluble EDA1 containing the collagen domain was poorly active when administered in newborn, EDA-deficient (Tabby) mice. This was due to a short stretch of basic amino acids located at the N terminus of the collagen domain that confers EDA1 with proteoglycan binding ability. In contrast to wild-type EDA1, EDA1 with mutations in this basic sequence was a potent inducer of tail hair development in vivo. Thus, the collagen domain activates EDA1 by multimerization, whereas the proteoglycan-binding domain may restrict the distribution of endogeneous EDA1 in vivo.

Age differences in biological monitoring of chemical exposure: a tentative description using a toxicokinetic model

AIM: Specific factors responsible for interindividual variability should be identified and their contribution quantified to improve the usefulness of biological monitoring. Among others, age is an easily identifiable determinant, which could play an important impact on biological variability. MATERIALS AND METHODS: A compartmental toxicokinetic model developed in previous studies for a series of metallic and organic compounds was applied to the description of age differences. Young male physiological and metabolic parameters, based on Reference Man information, were taken from preceding studies and were modified to take into account age based on available information about age differences. RESULTS: Numerical simulation using the kinetic model with the modified parameters indicates in some cases important differences due to age. The expected changes are mostly of the order of 10-20%, but differences up to 50% were observed in some cases. CONCLUSION: These differences appear to depend on the chemical and on the biological entity considered. Further work should be done to improve our estimates of these parameters, by considering for example uncertainty and variability in these parameters. [Authors]

A common biological basis of obesity and nicotine addiction.

Smoking influences body weight such that smokers weigh less than non-smokers and smoking cessation often leads to weight increase. The relationship between body weight and smoking is partly explained by the effect of nicotine on appetite and metabolism. However, the brain reward system is involved in the control of the intake of both food and tobacco. We evaluated the effect of single-nucleotide polymorphisms (SNPs) affecting body mass index (BMI) on smoking behavior, and tested the 32 SNPs identified in a meta-analysis for association with two smoking phenotypes, smoking initiation (SI) and the number of cigarettes smoked per day (CPD) in an Icelandic sample (N=34,216 smokers). Combined according to their effect on BMI, the SNPs correlate with both SI (r=0.019, P=0.00054) and CPD (r=0.032, P=8.0 × 10(-7)). These findings replicate in a second large data set (N=127,274, thereof 76,242 smokers) for both SI (P=1.2 × 10(-5)) and CPD (P=9.3 × 10(-5)). Notably, the variant most strongly associated with BMI (rs1558902-A in FTO) did not associate with smoking behavior. The association with smoking behavior is not due to the effect of the SNPs on BMI. Our results strongly point to a common biological basis of the regulation of our appetite for tobacco and food, and thus the vulnerability to nicotine addiction and obesity.

Characterization and classification of matrix effects in biological samples analyses.

An exhaustive classification of matrix effects occurring when a sample preparation is performed prior to liquid-chromatography coupled to mass spectrometry (LC-MS) analyses was proposed. A total of eight different situations were identified allowing the recognition of the matrix effect typology via the calculation of four recovery values. A set of 198 compounds was used to evaluate matrix effects after solid phase extraction (SPE) from plasma or urine samples prior to LC-ESI-MS analysis. Matrix effect identification was achieved for all compounds and classified through an organization chart. Only 17% of the tested compounds did not present significant matrix effects.

Using toxicokinetic modeling approach to determine biological reference values (BRVs) and to assess human exposure to pesticides

Exposure to various pesticides has been characterized in workers and the general population, but interpretation and assessment of biomonitoring data from a health risk perspective remains an issue. For workers, a Biological Exposure Index (BEI®) has been proposed for some substances, but most BEIs are based on urinary biomarker concentrations at Threshold Limit Value - Time Weighted Average (TLV-TWA) airborne exposure while occupational exposure can potentially occurs through multiple routes, particularly by skin contact (i.e.captan, chlorpyrifos, malathion). Similarly, several biomonitoring studies have been conducted to assess environmental exposure to pesticides in different populations, but dose estimates or health risks related to these environmental exposures (mainly through the diet), were rarely characterized. Recently, biological reference values (BRVs) in the form of urinary pesticide metabolites have been proposed for both occupationally exposed workers and children. These BRVs were established using toxicokinetic models developed for each substance, and correspond to safe levels of absorption in humans, regardless of the exposure scenario. The purpose of this chapter is to present a review of a toxicokinetic modeling approach used to determine biological reference values. These are then used to facilitate health risk assessments and decision-making on occupational and environmental pesticide exposures. Such models have the ability to link absorbed dose of the parent compound to exposure biomarkers and critical biological effects. To obtain the safest BRVs for the studied population, simulations of exposure scenarios were performed using a conservative reference dose such as a no-observed-effect level (NOEL). The various examples discussed in this chapter show the importance of knowledge on urine collections (i.e. spot samples and complete 8-h, 12-h or 24-h collections), sampling strategies, metabolism, relative proportions of the different metabolites in urine, absorption fraction, route of exposure and background contribution of prior exposures. They also show that relying on urinary measurements of specific metabolites appears more accurate when applying this approach to the case of occupational exposures. Conversely, relying on semi-specific metabolites (metabolites common to a category of pesticides) appears more accurate for the health risk assessment of environmental exposures given that the precise pesticides to which subjects are exposed are often unknown. In conclusion, the modeling approach to define BRVs for the relevant pesticides may be useful for public health authorities for managing issues related to health risks resulting from environmental and occupational exposures to pesticides.

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways.

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.