Neuromuscular electrical stimulation prevents muscle disuse atrophy during leg immobilization in humans

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this recordAIM: Short periods of muscle disuse, due to illness or injury, result in substantial skeletal muscle atrophy. Recently, we have shown that a single session of neuromuscular electrical stimulation (NMES) increases muscle protein synthesis rates. The aim was to investigate the capacity for daily NMES to attenuate muscle atrophy during short-term muscle disuse. METHODS: Twenty-four healthy, young (23 ± 1 year) males participated in the present study. Volunteers were subjected to 5 days of one-legged knee immobilization with (NMES; n = 12) or without (CON; n = 12) supervised NMES sessions (40-min sessions, twice daily). Two days prior to and immediately after the immobilization period, CT scans and single-leg one-repetition maximum (1RM) strength tests were performed to assess quadriceps muscle cross-sectional area (CSA) and leg muscle strength respectively. Furthermore, muscle biopsies were taken to assess muscle fibre CSA, satellite cell content and mRNA and protein expression of selected genes. RESULTS: In CON, immobilization reduced quadriceps CSA by 3.5 ± 0.5% (P < 0.0001) and muscle strength by 9 ± 2% (P < 0.05). In contrast, no significant muscle loss was detected following immobilization in NMES although strength declined by 7 ± 3% (P < 0.05). Muscle MAFbx and MuRF1 mRNA expression increased following immobilization in CON (P < 0.001 and P = 0.07 respectively), whereas levels either declined (P < 0.01) or did not change in NMES, respectively. Immobilization led to an increase in muscle myostatin mRNA expression in CON (P < 0.05), but remained unchanged in NMES. CONCLUSION: During short-term disuse, NMES represents an effective interventional strategy to prevent the loss of muscle mass, but it does not allow preservation of muscle strength. NMES during disuse may be of important clinical relevance in both health and disease

Plan for development of case studies - Deliverable Report AD 15.1 WP 15 - Mixtures, HBM and human health risk

This deliverable describes the activities in task 15.3 leading up to the development of cases studies for mixture health effects and outlines the proposed case studies. The proposed case studies are: · Developmental neurotoxicity beyond polybrominated diphenylethers · Heavy metals and nephrotoxicity · Anti-androgenic chemicals and male reproductive health · Chromium (VI), nickel and polycyclic aromatic hydrocarbons and lung cancer · Addressing exposure misclassification in mixture studies The Addendum provides further details about multi-year perspective and timing, as well as detailed budgetary aspects per case study.HBM4EU- Grant agreement 733032 HORIZON2020 Programmeinfo:eu-repo/semantics/publishedVersio

Pesticide exposure among Czech adults and children from the CELSPAC-SPECIMEn cohort: Urinary biomarker levels and associated health risks

Current-use pesticides (CUP) are extensively applied in both agricultural and urban settings. Exposure occurs mainly via the dietary pathway; however, other pathways such as inhalation or skin contact are also important. In this study, urinary levels of 12 CUP metabolites were investigated among 110 parent-child pairs during two seasons of 2020. Metabolites of pyrethroids (3-PBA, t/c-DCCA), chlorpyrifos (TCPY), and tebuconazole (TEB-OH) were detected in more than 60% of the samples. Chlorpyrifos metabolite was found at the highest concentration and tebuconazole was detected in almost all samples. CUP urinary metabolite levels were significantly higher in children in comparison to adults, except for tebuconazole, which was similar in both groups. In children, winter samples had significantly higher concentrations of pyrethroid and chlorpyrifos metabolites in comparison to the summer samples, but in adults, only chlorpyrifos metabolite concentrations were higher in the winter. No association between CUP urinary metabolite levels and proximity/surface of agricultural areas around residences was observed. Based on our findings, we suspect that CUP exposure is mainly driven by diet and that the effect of environmental exposure is less significant. Daily Intakes were estimated with three possible scenarios considering the amount of the metabolite excreted in urine and were compared to Acceptable Daily Intake values. Using a realistic scenario, exposure to chlorpyrifos exhibited the highest health risk, but still within a safe level. The Acceptable Daily Intake was exceeded only in one child in the case of cypermethrin. The cumulative risk assessment of pesticide mixtures having an effect on the nervous system, based on the total margin of exposure calculations, did not indicate any risk. The overall risk associated with pesticide exposure in the observed population was low. However, the risk observed using the worst-case scenario suggests the need for continuous evaluation of human exposure to such compounds, especially in children

Urinary pesticide mixture patterns and exposure determinants in the adult population from the Netherlands and Switzerland : Application of a suspect screening approach

INTRODUCTION: Non-occupational sources of pesticide exposure may include domestic pesticide usage, diet, occupational exposure of household members, and agricultural activities in the residential area. We conducted a study with the ambition to characterize pesticide mixture patterns in a sample of the adult population of the Netherlands and Switzerland, using a suspect screening approach and to identify related exposure determinants. METHODS: A total of 105 and 295 adults participated in the Dutch and Swiss studies, respectively. First morning void urine samples were collected and analyzed in the same laboratory. Harmonized questionnaires about personal characteristics, pesticide-related activities, and diet were administered. Detection rates and co-occurrence patterns were calculated to explore internal pesticide exposure patterns. Censored linear and logistic regression models were constructed to investigate the association between exposure and domestic pesticide usage, consumption of homegrown and organic foods, household members' exposure, and distance to agricultural and forest areas. RESULTS: From the 37 detected biomarkers, 3 (acetamiprid (-CH2), chlorpropham (4-HSA), and flonicamid (-C2HN)) were detected in ≥40% of samples. The most frequent combination of biomarkers (acetamiprid-flonicamid) was detected in 22 (5.5%) samples. Regression models revealed an inverse association between high organic vegetable and fruit consumption and exposure to acetamiprid, chlorpropham, propamocarb (+O), and pyrimethanil (+O + SO3). Within-individual correlations in repeated samples (summer/winter) from the Netherlands were low (≤0.3), and no seasonal differences in average exposures were observed in Switzerland. CONCLUSION: High consumption of organic fruit and vegetables was associated with lower pesticide exposure. In the two countries, detection rates and co-occurrence were typically low, and within-person variability was high. Our study results provide an indication for target biomarkers to include in future studies aimed at quantifying urinary exposure levels in European adult populations

Pesticide exposure among Czech adults and children from the CELSPAC-SPECIMEn cohort: Urinary biomarker levels and associated health risks

Current-use pesticides (CUP) are extensively applied in both agricultural and urban settings. Exposure occurs mainly via the dietary pathway; however, other pathways such as inhalation or skin contact are also important. In this study, urinary levels of 12 CUP metabolites were investigated among 110 parent-child pairs during two seasons of 2020. Metabolites of pyrethroids (3-PBA, t/c-DCCA), chlorpyrifos (TCPY), and tebuconazole (TEB-OH) were detected in more than 60% of the samples. Chlorpyrifos metabolite was found at the highest concentration and tebuconazole was detected in almost all samples. CUP urinary metabolite levels were significantly higher in children in comparison to adults, except for tebuconazole, which was similar in both groups. In children, winter samples had significantly higher concentrations of pyrethroid and chlorpyrifos metabolites in comparison to the summer samples, but in adults, only chlorpyrifos metabolite concentrations were higher in the winter. No association between CUP urinary metabolite levels and proximity/surface of agricultural areas around residences was observed. Based on our findings, we suspect that CUP exposure is mainly driven by diet and that the effect of environmental exposure is less significant. Daily Intakes were estimated with three possible scenarios considering the amount of the metabolite excreted in urine and were compared to Acceptable Daily Intake values. Using a realistic scenario, exposure to chlorpyrifos exhibited the highest health risk, but still within a safe level. The Acceptable Daily Intake was exceeded only in one child in the case of cypermethrin. The cumulative risk assessment of pesticide mixtures having an effect on the nervous system, based on the total margin of exposure calculations, did not indicate any risk. The overall risk associated with pesticide exposure in the observed population was low. However, the risk observed using the worst-case scenario suggests the need for continuous evaluation of human exposure to such compounds, especially in children

Identification of Real-Life Mixtures Using Human Biomonitoring Data: A Proof of Concept Study

Human health risk assessment of chemical mixtures is complex due to the almost infinite number of possible combinations of chemicals to which people are exposed to on a daily basis. Human biomonitoring (HBM) approaches can provide inter alia information on the chemicals that are in our body at one point in time. Network analysis applied to such data may provide insight into real-life mixtures by visualizing chemical exposure patterns. The identification of groups of more densely correlated biomarkers, so-called "communities", within these networks highlights which combination of substances should be considered in terms of real-life mixtures to which a population is exposed. We applied network analyses to HBM datasets from Belgium, Czech Republic, Germany, and Spain, with the aim to explore its added value for exposure and risk assessment. The datasets varied in study population, study design, and chemicals analysed. Sensitivity analysis was performed to address the influence of different approaches to standardise for creatinine content of urine. Our approach demonstrates that network analysis applied to HBM data of highly varying origin provides useful information with regards to the existence of groups of biomarkers that are densely correlated. This information is relevant for regulatory risk assessment, as well as for the design of relevant mixture exposure experiments

A large scale multi-laboratory suspect screening of pesticide metabolites in human biomonitoring: From tentative annotations to verified occurrences

Within the Human Biomonitoring for Europe initiative (HBM4EU), a study to determine new biomarkers of exposure to pesticides and to assess exposure patterns was conducted. Human urine samples (N = 2,088) were collected from five European regions in two different seasons. The objective of the study was to identify pesticides and their metabolites in collected urine samples with a harmonized suspect screening approach based on liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) applied in five laboratories. A combined data processing workflow included comprehensive data reduction, correction of mass error and retention time (RT) drifts, isotopic pattern analysis, adduct and elemental composition annotation, finalized by a mining of the elemental compositions for possible annotations of pesticide metabolites. The obtained tentative annotations (n = 498) were used for acquiring representative data-dependent tandem mass spectra (MS2) and verified by spectral comparison to reference spectra generated from commercially available reference standards or produced through human liver S9 in vitro incubation experiments. 14 parent pesticides and 71 metabolites (including 16 glucuronide and 11 sulfate conjugates) were detected. Collectively these related to 46 unique pesticides. For the remaining tentative annotations either (i) no data-dependent MS2 spectra could be acquired, (ii) the spectral purity was too low for sufficient matching, or (iii) RTs indicated a wrong annotation, leaving potential for more pesticides and/or their metabolites being confirmed in further studies. Thus, the reported results are reflecting only a part of the possible pesticide exposure

Approaches to identify exposure to real-life chemical mixtures in the general population

Humans are exposed to large number of chemicals from various sources in their environment. Current risk assessment approaches often focus on single chemicals, sources or routes, not accounting for possible combinations of chemicals and overlooking potential additional risks associated with chemical mixtures. This thesis focusses on how to accurately measure and describe exposure patterns of chemical mixtures in the general population. Measuring exposure to chemical mixtures in real-life situations at a population level is a complex task. The preferably individual measurements can be obtained either externally (e.g. silicone wristbands) or internally (human biomonitoring). In my thesis, chemical mixtures are described as combinations of manufactured chemicals that co-occur within the same individual or sample. My thesis revolves around three different approaches to identify chemical mixtures in the general population. 1) The first approach focusses on describing co-occurrence patterns of chemicals in existing human biomonitoring datasets, combining a graphical correlation network model with a clustering algorithm. This method visualizes and summarizes these co-occurrence patterns by identifying highly correlated groups or clusters of chemicals. We demonstrated that presenting biomonitoring data in networks facilitates the identification of exposure patterns that contribute to the observed exposure levels in the samples. The application of community detection with a clustering algorithm was instrumental in identifying patterns within and between chemical families. 2) The second approach involves measuring chemical mixtures at individual level, employing external and internal measurements. 3) The third approach refers to the analytical measurement of chemical mixtures in urine samples, for which a suspect screening approach based on high resolution mass spectrometry was applied, enabling detection of a broad range of biomarkers in a single sample. The second and third approach were applied on pesticides, as an example of a mixture of chemicals. By utilization of wristbands we were able to detect multiple pesticides over a longer period of time, reflecting highly individual exposure profiles. It was demonstrated that a harmonized pan-European sample collection, combined with suspect screening provided valuable new insights into the presence of pesticide mixture exposure in the European population. Forty pesticide biomarkers corresponding to 29 different pesticides were confidently identified across six countries. Some variation but no consistent pattern in the probability of detection of pesticide biomarkers was observed based on residential location or season of urine sampling. Pesticide mixture patterns in the adult populations of the Netherlands and Switzerland were analyzed by their semi-quantitative levels. Urinary concentrations of the two most frequently detected pesticides (acetamiprid and chlorpropham) showed an inverse association with high organic vegetable and fruit consumption. In both countries, detection rates and co-occurrence of pesticides in the same urine sample were typically low. This thesis highlights the importance of understanding and measuring the mixture of chemicals we encounter. Knowledge of what these mixtures are helps us to figure out the risks to human health. I recommend to incorporate the approaches of this thesis in future studies to learn more about human exposure to chemical mixtures, and that research and sharing data is conducted in a harmonized way