Physiologicomathematical model for studying human exposure to organic solvents: kinetics of blood/tissue n-hexane concentrations and of 2,5-hexanedione in urine

The Pathological Links between Adiposity and the Carpal Tunnel Syndrome

An association between obesity and carpal tunnel syndrome is found in many epidemiological studies. Therefore, there is a need to evaluate the physiopathological links that could explain the association between these two entities. Ectopic adipose tissue is responsible for metabolic syndrome and inflammation, and is a major risk factor for diabetes and cardiovascular diseases. Taking these elements into consideration, we conducted an extensive literature revision of the subject, considering as ectopic fat-related mechanisms the following: (a) the direct compression and the association with the metabolic syndrome of the fat deposition around the wrist, (b) the insulin resistance, dyslipidemia, inflammatory, and oxidative mechanisms related to the central deposition of the fat, (c) the impaired muscle contraction and metabolism related to myosteatosis. Each section presents the cellular pathways which are modified by the ectopic deposition of the adipose tissue and the impact in the pathogeny of the carpal tunnel syndrome. In conclusion, the experimental and clinical data support the epidemiological findings. Efforts to reduce the obesity epidemics will improve not only cardio-metabolic health but will reduce the burden of the disability-free life expectancy due to the carpal tunnel syndrome.

Role of Physiologically Based Kinetic modelling in addressing environmental chemical mixtures - A review

•

The availability and applicability of Physiologically Based Kinetic (PBK) models for mixtures is reviewed.

•

PBK models can support risk assessment of mixtures by incorporating the toxicokinetic processes.

•

Quantitative structure-activity relationship (QSAR) models can be used to fill data gaps in PBK modelling.

•

PBK models for mixtures can be improved by including various types of interactions.

The role of Physiologically Based Kinetic (PBK) modelling in assessing mixture toxicology has been growing for the last three decades. It has been widely used to investigate and address interactions in mixtures. This review describes the current state-of-the-art of PBK models for chemical mixtures and to evaluate the applications of PBK modelling for mixtures with emphasis on their role in chemical risk assessment. A total of 35 mixture PBK models were included after searching web resources (Scopus, PubMed, Web of Science, and Google Scholar), screening for duplicates, and excluding articles based on eligibility criteria. Binary mixtures and volatile organic compounds accounted for two-thirds of the chemical mixtures identified. The most common exposure route and modelled system were found to be inhalation and rats respectively. Twenty two (22) models were for binary mixtures, 5 for ternary mixtures, 3 for quaternary mixtures, and 5 for complex mixtures. Both bottom-up and top-down PBK modelling approaches are described. Whereas bottom-up approaches are based on a series of binary interactions, top-down approaches are based on the lumping of mixture components. Competitive inhibition is the most common type of interaction among the various types of mixtures, and usually becomes a concern at concentrations higher than environmental exposure levels. It leads to reduced biotransformation that either means a decrease in the amount of toxic metabolite formation or an increase in toxic parent chemical accumulation. The consequence is either lower or higher toxicity compared to that estimated for the mixture based on the additivity principle. Therefore, PBK modelling can play a central role in predicting interactions in chemical mixture risk assessment.

Concentration of trichloroethylene in breast milk and household water from Nogales, Arizona

The United States Environmental Protection Agency has identified quantification of trichloroethylene (TCE), an industrial solvent, in breast milk as a high priority need for risk assessment. Water and milk samples were collected from 20 households by a lactation consultant in Nogales, Arizona. Separate water samples (including tap, bottled, and vending machine) were collected for all household uses: drinking, bathing, cooking, and laundry. A risk factor questionnaire was administered. Liquid-liquid extraction with diethyl ether was followed by GC-MS for TCE quantification in water. Breast milk underwent homogenization, lipid hydrolysis, and centrifugation prior to extraction. The limit of detection was 1.5 ng/mL. TCE was detected in 7 of 20 mothers' breast milk samples. The maximum concentration was 6 ng/mL. TCE concentration in breast milk was significantly correlated with the concentration in water used for bathing (ρ = 0.59, p = 0.008). Detection of TCE in breast milk was more likely if the infant had a body mass index <14 (RR = 5.2, p = 0.02). Based on average breast milk consumption, TCE intake for 5% of the infants may exceed the proposed U.S. EPA Reference Dose. Results of this exploratory study warrant more in depth studies to understand risk of TCE exposures from breast milk intake.

Environmental and occupational exposure to benzene by analysis of breath and blood

Benzene exposure of chemical workers was studied, during the entire workshift, by continuous monitoring of workplace benzene concentration, and 16 hours after the end of the workshift by the measurement of alveolar and blood benzene concentrations and excretion of urinary phenol. Exposure of hospital staff was studied by measuring benzene concentrations in the alveolar and blood samples collected during the hospital workshift. Instantaneous environmental air samples were also collected, at the moment of the biological sampling, for all the subjects tested. A group of 34 chemical workers showed an eight hour exposure to benzene, as a geometric mean, of 1.12 micrograms/l which corresponded, 16 hours after the end of the workshift, to a geometric mean benzene concentration of 70 ng/l in the alveolar air and 597 ng/l in the blood. Another group of 27 chemical workers (group A) turned out to be exposed to an indeterminable eight hour exposure to benzene that corresponded, the morning after, to a geometric mean benzene concentration of 28 ng/l in the alveolar air and 256 ng/l in the blood. The group of hospital staff (group B) had a benzene concentration of 14 ng/l in the alveolar air and 269 ng/l in the blood. Instantaneous environmental samples showed that in the infirmaries the geometric mean benzene concentration was 58 ng/l during the examination of the 34 chemical workers, 36 ng/l during the examination of the 27 chemical workers (group A), and 5 ng/l during the examination of the 19 subjects of the hospital staff (group B). Statistical analysis showed that the alveolar and blood benzene concentrations in the 34 workers exposed to 1.12 microgram/l of benzene differed significantly from those in groups A and B. It was found, moreover, that the alveolar and blood benzene concentrations were higher in the smokers in groups A and B but not in the smokers in the group of 34 chemical workers. The slope of the linear correlation between the alveolar and the instantaneous environmental benzene concentrations suggested a benzene alveolar retention of about 55%. Blood and alveolar benzene concentrations showed a highly significant correlation and the blood/air partition coefficient, obtained from the slope of the regression line, was 7.4. In the group of the 34 chemical workers no correlation was found between the TWA benzene exposure and the urinary phenol excretion.