EFFECT OF TEN DAYS HIGH-INTENSITY TRAINING ON DNA DAMAGE

The purpose of this study was to examine the effects of ten days high-intensity training on human PBMC DNA damage. 20 subjects were randomly assigned into two groups (n=10). The intervention group was performing daily cycle training for ten days, while the control group did not exercise at all. Blood samples were analysed the day before training starts in the morning after the last session and after four days of recovery. Daily training was quantified using the TRIMP the RPE scale and lactate concentration. Also the differences in the overall well-being was measured using the MDBF Two-way ANOVA showed no significant differences between the groups in DNA damage. Results have shown that the stress, initiated by the training was not represented in the PBMC

High-Intensity Interval Training Decreases Resting Urinary Hypoxanthine Concentration in Young Active Men—A Metabolomic Approach

High-intensity interval training (HIIT) is known to improve performance and skeletal muscle energy metabolism. However, whether the body’s adaptation to an exhausting short-term HIIT is reflected in the resting human metabolome has not been examined so far. Therefore, a randomized controlled intervention study was performed to investigate the effect of a ten-day HIIT on the resting urinary metabolome of young active men. Fasting spot urine was collected before (−1 day) and after (+1 day; +4 days) the training intervention and 65 urinary metabolites were identified by liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy. Metabolite concentrations were normalized to urinary creatinine and subjected to univariate statistical analysis. One day after HIIT, no overall change in resting urinary metabolome, except a significant difference with decreasing means in urinary hypoxanthine concentration, was documented in the experimental group. As hypoxanthine is related to purine degradation, lower resting urinary hypoxanthine levels may indicate a training-induced adaptation in purine nucleotide metabolism

A systemic large-scale assessment of risks from pesticide use for different organism groups in the United States of America and Germany based on a labeled property graph

Ecotoxicology is the science that researches effects of toxicants on biological entities. Following the famous toxicological principle formulated 1538 by von Hohenheim, known as Paracelsus, thereby generally all chemicals are able to act as toxicants. Unlike human toxicology that focuses on toxic effects on individuals and populations of one species, Homo sapiens, ecotoxicology is not constrained in its scope of biological entities. It is interested in toxic effects on individuals and populations of any species (excluding humans), and on communities and entire ecosystems (Walker et al., 2012; Köhler & Triebskorn, 2013; Newman 2014). One example of where the ecological foundation of ecotoxicology manifests itself are indirect effects, which are effects on biological entities that are not directly caused by chemicals but instead are mediated by ecological interactions and environmental conditions (Walker et al., 2012). With this large scope, ecotoxicology is an inter- and multidisciplinary science that links chemical, biological and environmental knowledge. With millions of species and at least 100,000 chemicals that potentially interact with them in the environment (Wang et al., 2021), ecotoxicology has a large ground to cover. Among these sheer numbers, there are some groups that are of special importance regarding their potential environmental impact. Pesticides are one group of chemicals that have a large, if not the largest, ecotoxicological relevance: they are toxic for biological entities, sometimes in very low concentrations , and they are used in large amounts and globally (Bernhardt et al., 2017). The high toxicity of pesticides, much higher than that of most other groups of chemicals, is a result of their intended use: they are designed to reduce detrimental effects of, e.g., insects, plants or fungi on agriculture by controlling respective populations, often, and in the sense of their Latin name, through induced lethality (Walker et al., 2012). However, they act not specific enough to be toxic only for the intended species that are considered pests, but also show toxicity towards species living in habitats next to pesticide-treated areas. The widespread agricultural use of pesticides, on the other hand, is a result of their work-and-cost-efficiency for securing yields, but also results in exposure of ecosystems at a global scale (Sharma et al., 2019). In summary, pesticides can be abstractly seen as toxicity intentionally applied to agricultural areas, unintentionally also exposing organisms in non-agricultural areas to toxicity. The risks of pesticide use for ecosystems have led major jurisdictions, like the United States of America (US) and the European Union (EU), to enact elaborated regulatory processes that require a registration of pesticides prior use (EFSA, 2013; EPA, 2011; Stehle & Schulz, 2015b). A by-product of these registration processes are regulatory threshold levels (RTL) which can be used for scientific risk analysis outside the regulatory process (Stehle & Schulz, 2015a). The RTL for an organism group is basically derived from the most sensitive effect concentrations found in standardized toxicity tests for species representative for the group, multiplied by a safety factor, although specifics differ among regulatory processes. Conceptually, they mark the threshold that separates environmental concentrations associated with acceptable risk (concentrations below the RTL) from concentrations associated with unacceptable risk (concentrations above the RTL). Due to the high degree of procedural standardization in the derivation of RTLs, they have been found as a good measure to make the toxicities of different pesticides comparable, and they were employed in a series of studies to characterize environmental pesticide concentrations (e.g., Stehle & Schulz, 2015a; Stehle et al., 2018; Wolfram et al., 2018; Wolfram et al., 2021; Schulz et al., 2021, also, in Appendix B; Bub et al., 2023, also, in Appendix C). RTL reflect, for instance, that insecticides show regulatory unacceptable concentrations towards fish between 3 ng/L (deltamethrin, a pyrethroid) and 110 mg/L (imidacloprid, a neonicotinoid), a range of nine orders of magnitude. At the same, imidacloprid is very toxic to pollinators (RTL of 1.52 ng/organism), while more than 95% of all of the insecticides, with regulatory unacceptable concentrations among insecticides ranging as high as 1,6 mg/organism, indicating a toxicity six orders of magnitude lower than that of imidacloprid. At large-scales, ecotoxicology deals with pesticide impacts on a national (e.g., Bub et al., 2023; Douglas & Tooker, 2015; Hallmann et al., 2014; Schulz et al., 2021; Stehle et al., 2019; Wolfram et al., 2018), continental (Wolfram et al., 2021) or the global scale (Stehle & Schulz, 2015a; Stehle et al., 2018). This maximization of considered scale is in line with the general tendency of ecotoxicology towards larger scales, but generally requires new methodological and conceptual approaches. Historically, individual chemicals and groups of chemicals have been identified that mark, caused by their immense release into the environment, main disruptors of processes in the Earth system, like greenhouses gases for the climate change, chlorofluorocarbons for the depletion of the atmosphere’s ozone layer, dichlorodiphenyl-trichloroethane and other organochlorides for bioaccumulation in food webs and declines in bird populations, etc., but for other phenomena, like declines in biodiversity or numbers of insect species (Outhwaite et al., 2020; Seibold et al., 2019; Vörösmarty et al., 2010), the active part of chemical pollution is only understood to a much lesser extent. There are indicators that pesticides may play a major role This dissertation contributes to the research of large-scale risks of pesticide use, and of large-scale ecotoxicology in general, in several ways (Figure 1). In Chapter 2, it presents a labeled property graph, the MAGIC graph (Meta-Analysis of the Global Impact of Chemicals graph), as a solution to the methodological issues that arise when increasing amounts of data from more and more sources are combined for analysis (Bub et al., 2019; also, in Appendix A). The MAGIC graph is able to link chemical information from different sources, even if these sources use different nomenclatures. This enables analyses that incorporate toxicological data, like thousands of RTLs (for different organism groups and jurisdictions) for hundreds of pesticides, and information on pesticide use and chemical classes. The MAGIC graph is implemented in a way that allows it to be organically extended by additional chemical, biological and environmental data, and eventually scaled to all chemicals of environmental interest. Chapter 3 shows, how the combination of the linked pesticide data with a systemic consideration of pesticide use supports the interpretation of pesticide risks in the US (Schulz et al., 2021; also, in Appendix B). This systemic approach includes a new measure, the total applied toxicity (TAT), which integrates used pesticide amounts and pesticide toxicities, and the consideration of pesticide use as a complex system whose state and evolution can be visualized in phase-space plots. The combination of the described methods and concepts led to a novel view on pesticide risks in the US and can provide a framework for future ecotoxicological research at large scales. Chapter 4 displays the results of the methods and concepts of the US pesticide risk analysis applied to Germany (Bub et al., 2023; also, in Appendix C). A pesticide risk analysis of Germany is of special importance in the context of the EU’s goal to drastically reduce pesticide risks (European Commission, 2020) and Germany being one of the important agricultural producers in the EU. A comparison of the results for Germany to those for the US did also allow to evaluate the impact of scale and differing RTLs, information that can help other ecotoxicological large-scale assessments. Chapter 5 adds a conclusion and an outlook

An NMR-Based Approach to Identify Urinary Metabolites Associated with Acute Physical Exercise and Cardiorespiratory Fitness in Healthy Humans—Results of the KarMeN Study

Knowledge on metabolites distinguishing the metabolic response to acute physical exercise between fit and less fit individuals could clarify mechanisms and metabolic pathways contributing to the beneficial adaptations to exercise. By analyzing data from the cross-sectional KarMeN (Karlsruhe Metabolomics and Nutrition) study, we characterized the acute effects of a standardized exercise tolerance test on urinary metabolites of 255 healthy women and men. In a second step, we aimed to detect a urinary metabolite pattern associated with the cardiorespiratory fitness (CRF), which was determined by measuring the peak oxygen uptake (VO2peak) during incremental exercise. Spot urine samples were collected pre- and post-exercise and 47 urinary metabolites were identified by nuclear magnetic resonance (NMR) spectroscopy. While the univariate analysis of pre-to-post-exercise differences revealed significant alterations in 37 urinary metabolites, principal component analysis (PCA) did not show a clear separation of the pre- and post-exercise urine samples. Moreover, both bivariate correlation and multiple linear regression analyses revealed only weak relationships between the VO2peak and single urinary metabolites or urinary metabolic pattern, when adjusting for covariates like age, sex, menopausal status, and lean body mass (LBM). Taken as a whole, our results show that several urinary metabolites (e.g., lactate, pyruvate, alanine, and acetate) reflect acute exercise-induced alterations in the human metabolism. However, as neither pre- and post-exercise levels nor the fold changes of urinary metabolites substantially accounted for the variation of the covariate-adjusted VO2peak, our results furthermore indicate that the urinary metabolites identified in this study do not allow to draw conclusions on the individual’s physical fitness status. Studies investigating the relationship between the human metabolome and functional variables like the CRF should adjust for confounders like age, sex, menopausal status, and LBM

Modeling Regulatory Threshold Levels for Pesticides in Surface Waters from Effect Databases

Regulatory threshold levels (RTL) represent robust benchmarks for assessing risks of pesticides, e.g., in surface waters. However, comprehensive scientific risk evaluations comparing RTL to measured environmental concentrations (MEC) of pesticides in surface waters were yet restricted to a low number of pesticides, as RTL are only available after extensive review of regulatory documents. Thus, the aim of the present study was to model RTL equivalents (RTLe) for aquatic organisms from publicly accessible ecotoxicological effect databases. We developed a model that applies validity criteria in accordance with official US EPA review guidelines and validated the model against a set of manually retrieved RTL (n = 49). Model application yielded 1283 RTLe (n = 676 for pesticides, plus 607 additional RTLe for other use types). In a case study, the usability of RTLe was demonstrated for a set of 27 insecticides by comparing RTLe and RTL exceedance rates for 3001 MEC from US surface waters. The provided dataset enables thorough risk assessments of surface water exposure data for a comprehensive number of substances. Especially regions without established pesticide regulations may benefit from this dataset by using it as a baseline information for pesticide risk assessment and for the identification of priority substances or potential high-risk regions

Graphing Ecotoxicology: The MAGIC Graph for Linking Environmental Data on Chemicals

Assessing the impact of chemicals on the environment and addressing subsequent issues are two central challenges to their safe use. Environmental data are continuously expanding, requiring flexible, scalable, and extendable data management solutions that can harmonize multiple data sources with potentially differing nomenclatures or levels of specificity. Here, we present the methodological steps taken to construct a rule-based labeled property graph database, the “Meta-analysis of the Global Impact of Chemicals„ (MAGIC) graph, for potential environmental impact chemicals (PEIC) and its subsequent application harmonizing multiple large-scale databases. The resulting data encompass 16,739 unique PEICs attributed to their corresponding chemical class, stereo-chemical information, valid synonyms, use types, unique identifiers (e.g., Chemical Abstract Service registry number CAS RN), and others. These data provide researchers with additional chemical information for a large amount of PEICs and can also be publicly accessed using a web interface. Our analysis has shown that data harmonization can increase up to 98% when using the MAGIC graph approach compared to relational data systems for datasets with different nomenclatures. The graph database system and its data appear more suitable for large-scale analysis where traditional (i.e., relational) data systems are reaching conceptional limitations

Data from: Irisin, physical activity and fitness status in healthy humans: no association under resting conditions in a cross-sectional study

Regular physical activity and physical fitness are closely related to a positive health status in humans. In this context, the muscle becomes more important due to its function as an endocrine organ. Muscle tissue secretes "myokines" in response to physical activity and it is speculated that these myokines are involved in physical activity induced positive health effects. Recently, the newly discovered myokine Irisin thought to be secreted by the muscle in response to physical activity and might be related to the health inducing effect by inducing browning of white adipose tissue. Speculating that myokines at least partly mediate exercise related health effects one would assume that regular physical activity and physical fitness are associated with resting Irisin concentrations in healthy humans. To investigate the association between resting Irisin concentration and either short-term physical activity, habitual physical activity, or physical fitness, data of 300 healthy participants from the cross-sectional KarMeN-study were analyzed. By applying different activity measurements we determined short-term and habitual physical activity, as well as physical fitness. Fasting serum samples were collected to determine resting Irisin concentrations by Enzyme-linked Immunosorbent Assay. Multivariate linear regression analysis served to investigate associations of the individual physical activity parameters with Irisin concentrations. Therefore, lean body mass and total fat mass (both determined by dual-energy X-ray absorptiometry) as well as age and parameters of glucose metabolism were included as confounders in multivariate linear regression analysis. Results showed that Irisin serum concentrations were not related to measures of physical activity and physical fitness in healthy humans under resting conditions, irrespective of the applied methods. Therefore we assume that if physical activity related effects are partly induced by myokines, permanently increased Irisin serum concentration may not be necessary to induce health-related exercise effects

Irisin, physical activity and fitness status in healthy humans: No association under resting conditions in a cross-sectional study

Regular physical activity and physical fitness are closely related to a positive health status in humans. In this context, the muscle becomes more important due to its function as an endocrine organ. Muscle tissue secretes “myokines” in response to physical activity and it is speculated that these myokines are involved in physical activity induced positive health effects. Recently, the newly discovered myokine Irisin thought to be secreted by the muscle in response to physical activity and might be related to the health inducing effect by inducing browning of white adipose tissue. Speculating that myokines at least partly mediate exercise related health effects one would assume that regular physical activity and physical fitness are associated with resting Irisin concentrations in healthy humans. To investigate the association between resting Irisin concentration and either short-term physical activity, habitual physical activity, or physical fitness, data of 300 healthy participants from the cross-sectional KarMeN-study were analyzed. By applying different activity measurements we determined short-term and habitual physical activity, as well as physical fitness. Fasting serum samples were collected to determine resting Irisin concentrations by Enzyme-linked Immunosorbent Assay. Multivariate linear regression analysis served to investigate associations of the individual physical activity parameters with Irisin concentrations. Therefore, lean body mass and total fat mass (both determined by dual-energy X-ray absorptiometry) as well as age and parameters of glucose metabolism were included as confounders in multivariate linear regression analysis. Results showed that Irisin serum concentrations were not related to measures of physical activity and physical fitness in healthy humans under resting conditions, irrespective of the applied methods. Therefore we assume that if physical activity related effects are partly induced by myokines, permanently increased Irisin serum concentration may not be necessary to induce health-related exercise effects

Large monitoring datasets reveal high probabilities for intermittent occurrences of pesticides in European running waters

Abstract Many studies have investigated short-term peak concentrations of pesticides in surface waters resulting from agricultural uses. However, we lack information to what extent pesticides reoccur over medium (> 4 days) and longer time periods (> 10 days). We use here large-scale pesticide monitoring data from across Europe (~ 15 mil. measurements, i.e., quantified concentrations in water at > 17,000 sites for 474 pesticide compounds) to evaluate the degree to which pesticides were not only detected once, but in sequences of a compound repeatedly quantified in the same area (0.015 km2) within 4–30 days. Reoccurrence was observed at ~ 18% of sites for > 76% of compounds, ~ 40% of which not a priori considered to chronically expose aquatic ecosystems. We calculated a probability of reoccurrence (POR) over medium-term (4–7 days) and long-term (8–30 days) time periods for ~ 360 pesticides. Relative PORs (ratio between long-term and medium-term POR) revealed three occurrence patterns: ephemeral, intermittent and permanent. While fungicides dominated intermittently occurring substances, aligning with application strategies and physico-chemical properties, neonicotinoids and legacy pesticides were among substances permanently occurring. The results of this study shed new light on previously underestimated longer-term occurrence of many pesticides in aquatic environments (35% of investigated substances occurring intermittently or permanently were previously not considered to pollute the aquatic environment chronically), entailing new challenges for chronic risk assessments and the evaluation of pesticide effects on aquatic biodiversity