Oxygen limitation may affect the temperature and size dependence of metabolism in aquatic ectotherms.

Both oxygen and temperature are fundamental factors determining metabolic performance, fitness, ecological niches, and responses of many aquatic organisms to climate change. Despite the importance of physical and physiological constraints on oxygen supply affecting aerobic metabolism of aquatic ectotherms, ecological theories such as the metabolic theory of ecology have focused on the effects of temperature rather than oxygen. This gap currently impedes mechanistic models from accurately predicting metabolic rates (i.e., oxygen consumption rates) of aquatic organisms and restricts predictions to resting metabolism, which is less affected by oxygen limitation. Here, we expand on models of metabolic scaling by accounting for the role of oxygen availability and temperature on both resting and active metabolic rates. Our model predicts that oxygen limitation is more likely to constrain metabolism in larger, warmer, and active fish. Consequently, active metabolic rates are less responsive to temperature than are resting metabolic rates, and metabolism scales to body size with a smaller exponent whenever temperatures or activity levels are higher. Results from a metaanalysis of fish metabolic rates are consistent with our model predictions. The observed interactive effects of temperature, oxygen availability, and body size predict that global warming will limit the aerobic scope of aquatic ectotherms and may place a greater metabolic burden on larger individuals, impairing their physiological performance in the future. Our model reconciles the metabolic theory with empirical observations of oxygen limitation and provides a formal, quantitative framework for predicting both resting and active metabolic rate and hence aerobic scope of aquatic ectotherms.

A Generalized Physiologically Based Kinetic Model for Fish for Environmental Risk Assessment of Pharmaceuticals.

An increasing number of pharmaceuticals found in the environment potentially impose adverse effects on organisms such as fish. Physiologically based kinetic (PBK) models are essential risk assessment tools, allowing a mechanistic approach to understanding chemical effects within organisms. However, fish PBK models have been restricted to a few species, limiting the overall applicability given the countless species. Moreover, many pharmaceuticals are ionizable, and fish PBK models accounting for ionization are rare. Here, we developed a generalized PBK model, estimating required parameters as functions of fish and chemical properties. We assessed the model performance for five pharmaceuticals (covering neutral and ionic structures). With biotransformation half-lives (HLs) from EPI Suite, 73 and 41% of the time-course estimations were within a 10-fold and a 3-fold difference from measurements, respectively. The performance improved using experimental biotransformation HLs (87 and 59%, respectively). Estimations for ionizable substances were more accurate than any of the existing species-specific PBK models. The present study is the first to develop a generalized fish PBK model focusing on mechanism-based parameterization and explicitly accounting for ionization. Our generalized model facilitates its application across chemicals and species, improving efficiency for environmental risk assessment and supporting an animal-free toxicity testing paradigm.

Ibuprofen exposure in Europe; ePiE as an alternative to costly environmental monitoring.

The EU Water Framework Directive and Priority Substance Directive provide a framework to identify substances that potentially pose a risk to surface waters and provide a legal basis whereby member states are required to monitor and comply with environmental quality standards (EQSs) set for those substances. The cost and effort to continuously measure and analyse real world concentrations in all water bodies across Europe are high. Establishing the reliability of environmental exposure models to predict concentrations of priority substances is key, both to fill data gaps left by monitoring campaigns, and to predict the outcomes of actions that might be taken to reduce exposure. In this study, we aimed to validate the ePiE model for the pharmaceutical ibuprofen by comparing predictions made using the best possible consumption data with measured river concentrations. The results demonstrate that the ePiE model makes useful, conservative exposure predictions for ibuprofen, typically within a factor of 3 of mean measured values. This exercise was performed across a number of basins within Europe, representative of varying conditions, including consumption rates, population densities and climates. Incorporating specific information pertaining to the basin or country being assessed, such as custom WWTP removal rates, was found to improve the realism and accuracy of predictions. We found that the extrapolation of consumption data between countries should be kept to a minimum when modelling the exposure of pharmaceuticals, with the per capita consumption of ibuprofen varying by nearly a factor of 10.

Rewilding the Sea with Domesticated Seagrass.

It is well known that seagrass meadows sequester atmospheric carbon dioxide, protect coasts, provide nurseries for global fisheries, and enhance biodiversity. Large-scale restoration of lost seagrass meadows is urgently needed to revive these planetary ecosystem services, but sourcing donor material from natural meadows would further decline them. Therefore, we advocate the domestication and mariculture of seagrasses in order to produce the large quantities of seed needed for successful rewilding of the sea with seagrass meadows. We provide a roadmap for our proposed solution and show that 44% of seagrass species have promising reproductive traits for domestication and rewilding by seeds. The principle of partially domesticating species to enable subsequent large-scale rewilding may form a successful shortcut to restore threatened keystone species and their vital ecosystem services.

Internal and Maternal Distribution of Persistent Organic Pollutants in Sea Turtle Tissues: A Meta-Analysis.

We aimed to identify patterns in the internal distribution of persistent organic pollutants (POPs) and assess contributing factors using sea turtles and their offspring as a case study of a long-lived wildlife species. We systematically synthesized 40 years of data and developed a lipid database to test whether lipid-normalized POP concentrations are equal among tissues as expected under steady state for lipophilic compounds. Results supported equal partitioning among tissues with high blood flow or perfusion including the heart, kidney, muscle, and lung. Observed differences in the brain, fat, and blood plasma, however, suggest the physiological influence of the blood-brain barrier, limited perfusion, and protein content, respectively. Polybrominated diphenyl ethers partitioned comparably to legacy POPs. Polycyclic aromatic hydrocarbons, meanwhile, partitioned more into the lung, colon, and muscle compared to the liver under chronic and acute field exposure. Partitioning ratios of individual POPs among tissues were significantly related to the lipophilicity of compounds (as estimated by Kow) in half of the observed cases, and significant differences between juveniles and adults underscore physiological differences across life stages. The comprehensive tissue partitioning patterns presented here provide a quantitative basis to support comparative assessments of POP pollution derived from biomonitoring among multiple tissues.

Do initial concentration and activated sludge seasonality affect pharmaceutical biotransformation rate constants?

Pharmaceuticals find their way to the aquatic environment via wastewater treatment plants (WWTPs). Biotransformation plays an important role in mitigating environmental risks; however, a mechanistic understanding of involved processes is limited. The aim of this study was to evaluate potential relationships between first-order biotransformation rate constants (kb) of nine pharmaceuticals and initial concentration of the selected compounds, and sampling season of the used activated sludge inocula. Four-day bottle experiments were performed with activated sludge from WWTP Groesbeek (The Netherlands) of two different seasons, summer and winter, spiked with two environmentally relevant concentrations (3 and 30 nM) of pharmaceuticals. Concentrations of the compounds were measured by LC-MS/MS, microbial community composition was assessed by 16S rRNA gene amplicon sequencing, and kb values were calculated. The biodegradable pharmaceuticals were acetaminophen, metformin, metoprolol, terbutaline, and phenazone (ranked from high to low biotransformation rates). Carbamazepine, diatrizoic acid, diclofenac, and fluoxetine were not converted. Summer and winter inocula did not show significant differences in microbial community composition, but resulted in a slightly different kb for some pharmaceuticals. Likely microbial activity was responsible instead of community composition. In the same inoculum, different kb values were measured, depending on initial concentration. In general, biodegradable compounds had a higher kb when the initial concentration was higher. This demonstrates that Michealis-Menten kinetic theory has shortcomings for some pharmaceuticals at low, environmentally relevant concentrations and that the pharmaceutical concentration should be taken into account when measuring the kb in order to reliably predict the fate of pharmaceuticals in the WWTP. KEY POINTS: • Biotransformation and sorption of pharmaceuticals were assessed in activated sludge. • Higher initial concentrations resulted in higher biotransformation rate constants for biodegradable pharmaceuticals. • Summer and winter inocula produced slightly different biotransformation rate constants although microbial community composition did not significantly change.

Towards a systematic method for assessing the impact of chemical pollution on ecosystem services of water systems.

Chemical pollution impinges on the quality of water systems and the ecosystem services (ESs) they provide. Expression of ESs in monetary units has become an essential tool for sustainable ecosystem management. However, the impact of chemical pollution on ESs is rarely quantified, and ES valuation often focuses on individual services without considering the total services provided by the ecosystem. The purpose of the study was to develop a stepwise approach to quantify the impact of sediment pollution on the total ES value provided by water systems. Thereby, we calculated the total ES value loss as a function of the multi-substance potentially affected fraction of species at the HC50 level (msPAF(HC50)). The function is a combination of relationships between, subsequently: the msPAF(HC50), diversity, productivity and total ES value. Regardless of the inherent differences between terrestrial and aquatic ecosystems, an increase of diversity generally corresponded to an increase in productivity with curvilinear or linear effects. A positive correlation between productivity and total values of ESs of biomes was observed. The combined relationships showed that 1% msPAF(HC50) corresponded to on average 0.5% (0.05-1.40%) of total ES value loss. The ES loss due to polluted sediments in the Waal-Meuse river estuary (the Netherlands) and Flemish waterways (Belgium) was estimated to be 0.3-5 and 0.6-10 thousand 2007$/ha/yr, respectively. Our study presents a novel methodology to assess the impact of chemical exposure on diversity, productivity, and total value that ecosystems provide. With sufficient monitoring data, our generic methodology can be applied for any chemical and region of interest and help water managers make informed decisions on cost-effective measures to remedy pollution. Acknowledging that the ES loss estimates as a function of PAF(HC50) are crude, we explicitly discuss the uncertainties in each step for further development and application of the methodology.

Bioconcentration of Organotin Cations during Molting Inhibits Heterocypris incongruens Growth.

The densely populated North Sea region encompasses catchments of rivers such as Scheldt and Meuse. Herein, agricultural, industrial, and household chemicals are emitted, transported by water, and deposited in sediments, posing ecological risks. Though sediment monitoring is often costly and time-intensive, modeling its toxicity to biota has received little attention. Due to high complexity of interacting variables that induce overall toxicity, monitoring data only sporadically validates current models. Via a range of concepts, we related bio-physicochemical constituents of sediment in Flanders to results from toxicity bioassays performed on the ostracod Heterocypris incongruens. Depending on the water body, we explain up to 90% of the variance in H. incongruens growth. Though variable across Flanders' main water bodies, organotin cations and ammonia dominate the observed toxicity according to toxic unit (TU) assessments. Approximately 10% relates to testing conditions/setups, species variabilities, incoherently documented pollutant concentrations, and/or bio-physicochemical sediment properties. We elucidated the influence of organotin cations and ammonia relative to other metal(oxides) and biocides. Surprisingly, the tributylin cation appeared ∼1000 times more toxic to H. incongruens as compared to "single-substance" bioassays for similar species. We inferred indirect mixture effects between organotin, ammonia, and phosphate. Via chemical speciation calculations, we observed strong physicochemical and biological interactions between phosphate and organotin cations. These interactions enhance bioconcentration and explain the elevated toxicity of organotin cations. Our study aids water managers and policy makers to interpret monitoring data on a mechanistic basis. As sampled sediments differ, future modeling requires more emphasis on characterizing and parametrizing the interactions between bioassay constituents. We envision that this will aid in bridging the gap between testing in the laboratory and field observations.

Thermochemical unification of molecular descriptors to predict radical hydrogen abstraction with low computational cost.

Chemistry describes transformation of matter with reaction equations and corresponding rate constants. However, accurate rate constants are not always easy to get. Here we focus on radical oxidation reactions. Analysis of over 500 published rate constants of hydroxyl radicals led us to hypothesize that a modified linear free-energy relationship (LFER) could be used to predict rate constants speedily, reliably and accurately. LFERs correlate the Gibbs activation-energy with the Gibbs energy of reaction. We calculated the latter as the sum of one-electron transfer and, if appropriate, proton transfer. We parametrized specific transition state effects to orbital delocalizability and the polarity of the reactant. The calculation time for 500 reactions is less than 8 hours on a standard desktop-PC. Rate constants were also calculated for hydrogen and methyl radicals; these controls show that the predictions are applicable to a broader set of oxidizing radicals. An accuracy of 30-40% (standard deviation) with reference to reported experimental values was found suitable for the screening of complex chemical systems for possibly relevant reactions. In particular, potentially relevant reactions can be singled out and scrutinized in detail when prioritizing chemicals for environmental risk assessment.

Deriving Field-Based Ecological Risks for Bird Species.

Ecological risks (ERs) of pollutants are typically assessed using species sensitivity distributions (SSDs), based on effect concentrations obtained from bioassays with unknown representativeness for field conditions. Alternatively, monitoring data relating breeding success in bird populations to egg concentrations may be used. In this study, we developed a procedure to derive SSDs for birds based on field data of egg concentrations and reproductive success. As an example, we derived field-based SSDs for p, p'-DDE and polychlorinated biphenyls (PCBs) exposure to birds. These SSDs were used to calculate ERs for these two chemicals in the American Great Lakes and the Arctic. First, we obtained field data of p, p'-DDE and PCBs egg concentrations and reproductive success from the literature. Second, these field data were used to fit exposure-response curves along the upper boundary (right margin) of the response's distribution (95th quantile), also called quantile regression analysis. The upper boundary is used to account for heterogeneity in reproductive success induced by other external factors. Third, the species-specific EC10/50s obtained from the field-based exposure-response curves were used to derive SSDs per chemical. Finally, the SSDs were combined with specific exposure data for both compounds in the two areas to calculate the ER. We found that the ERs of combined exposure to these two chemicals were a factor of 5-35 higher in the Great Lakes compared to Arctic regions. Uncertainty in the species-specific exposure-response curves and related SSDs was mainly caused by the limited number of field exposure-response data for bird species. With sufficient monitoring data, our method can be used to quantify field-based ecological risks for other chemicals, species groups, and regions of interest.

Development of a PBPK Model for Silver Accumulation in Chub Infected with Acanthocephalan Parasites.

Simultaneous presence of metals and parasites in fish might lead to potential risks to human health. Parasites might influence metal accumulation and disturb detoxification in fish, thereby affecting biomarkers of fish responses as well as metal biomagnification in humans. It is, therefore, of importance to take into account parasite infection when investigating metal accumulation in fish. However, mechanisms of metal accumulation and distribution in fish-parasite systems are not integrated into current approaches. The present study proposes a new physiologically based pharmacokinetic model for mechanistic simulation of metal partitioning between intestinal parasites and their hosts. As a particular case, Ag accumulation in the system of chub Squalius cephalus and the acanthocephalan Pomphorhynchus tereticollis was investigated. As a novelty, fish cardiac output and organ-specific blood flow distribution were incorporated in our model. This approach distinguishes the current model from the ones developed previously. It also facilitates model extrapolation and application to varying conditions. In general, the model explained Ag accumulation in the system well, especially in chub gill, storage (including skin, muscle, and carcass), and liver. The highest concentration of Ag was found in the liver. The accumulation of Ag in the storage, liver, and gill compartments followed a similar pattern, i.e., increasing during the exposure and decreasing during the depuration. The model also generated this observed trend. However, the model had a weaker performance for simulating Ag accumulation in the intestine and the kidney. Silver accumulation in these organs was less evident with considerable variations.

Dietary Toxicity Thresholds and Ecological Risks for Birds and Mammals Based on Species Sensitivity Distributions.

Species sensitivity distributions (SSDs) are commonly used in regulatory procedures and ecological risk assessments. Yet, most toxicity threshold and risk assessment studies are based on invertebrates and fish. In the present study, no observed effect concentrations (NOECs) specific to birds and mammals were used to derive SSDs and corresponding hazardous concentrations for 5% of the species (HC5 values). This was done for 41 individual substances as well as for subsets of substances aggregated based on their toxic Mode of Action (MoA). In addition, potential differences in SSD parameters (mean and standard deviation) were investigated in relation to MoA and end point (growth, reproduction, and survival). The means of neurotoxic and respirotoxic compounds were significantly lower than those of narcotics, whereas no differences were found between end points. The standard deviations of the SSDs were similar across MoA's and end points. Finally, the SSDs obtained were used in a case study by calculating Ecological Risks (ER) and multisubstance Potentially Affected Fractions of species (msPAF) based on 19 chemicals in 10 Northwestern European estuaries and coastal areas. The assessment showed that the risks were all below 2.6 × 10-2. However, the calculated risks underestimate the actual risks of chemicals in these areas because the potential impacts of substances that were not measured in the field or for which no SSD was available were not included in the risk assessment. The SSDs obtained can be used in regulatory procedures and for assessing the impacts of contaminants on birds and mammals from fish contaminants monitoring programs.

Calcifying species sensitivity distributions for ocean acidification.

Increasing CO2 atmospheric levels lead to increasing ocean acidification, thereby enhancing calcium carbonate dissolution of calcifying species. We gathered peer-reviewed experimental data on the effects of acidified seawater on calcifying species growth, reproduction, and survival. The data were used to derive species-specific median effective concentrations, i.e., pH50, and pH10, via logistic regression. Subsequently, we developed species sensitivity distributions (SSDs) to assess the potentially affected fraction (PAF) of species exposed to pH declines. Effects on species growth were observed at higher pH than those on species reproduction (mean pH10 was 7.73 vs 7.63 and mean pH50 was 7.28 vs 7.11 for the two life processes, respectively) and the variability in the sensitivity of species increased with increasing number of species available for the PAF (pH10 standard deviation was 0.20, 0.21, and 0.33 for survival, reproduction, and growth, respectively). The SSDs were then applied to two climate change scenarios to estimate the increase in PAF (ΔPAF) by future ocean acidification. In a high CO2 emission scenario, ΔPAF was 3 to 10% (for pH50) and 21 to 32% (for pH10). In a low emission scenario, ΔPAF was 1 to 4% (for pH50) and 7 to 12% (for pH10). Our SSDs developed for the effect of decreasing ocean pH on calcifying marine species assemblages can also be used for comparison with other environmental stressors.

Toxicokinetic toxicodynamic (TKTD) modeling of Ag toxicity in freshwater organisms: whole-body sodium loss predicts acute mortality across aquatic species.

ToxicoKinetic ToxicoDynamic (TKTD) models are considered essential tools to further advance acute toxicity prediction of metals for a range of species and exposure conditions, but they are currently underutilized. We present a mechanistic TKTD model for acute toxicity prediction of silver (Ag) in freshwater organisms. In this new approach, we explicitly link relevant TKTD processes to species (physiological) characteristics, which facilitates model application to other untested freshwater organisms. The model quantifies the reduction in whole-body sodium concentration over time as a function of the target site inhibition over time, the target site density and the species-specific sodium turnover rate. Freshwater species are assumed to die instantly when they have lost a critical amount of their initial whole-body sodium concentration. Results show that mortality is significantly related to sodium loss (r(2) = 0.86) for various aquatic organisms and exposure durations. The model accurately predicts lethal effect concentrations for different freshwater organisms, including Daphnia magna, rainbow trout and juvenile crayfish, and is able to capture the observed size-specific variation of nearly 2 orders of magnitude in empirical LC50s.

Modeling the impacts of multiple environmental stress factors on estuarine copepod populations.

Many studies have focused on natural stress factors that shape the spatial and temporal distribution of calanoid copepods, but bioassays have shown that copepods are also sensitive to a broad range of contaminants. Although both anthropogenic and natural stress factors are obviously at play in natural copepod communities, most studies consider only one or the other. In the present investigation, we modeled the combined impact of both anthropogenic and natural stress factors on copepod populations. The model was applied to estimate Eurytemora affinis densities in the contaminated Scheldt estuary and the relatively uncontaminated Darß-Zingst estuary in relation to temperature, salinity, chlorophyll a, and sediment concentrations of cadmium, copper, and zinc. The results indicated that temperature was largely responsible for seasonal fluctuations of E. affinis densities. Our model results further suggested that exposure to zinc and copper was largely responsible for the reduced population densities in the contaminated estuary. The model provides a consistent framework for integrating and quantifying the impacts of multiple anthropogenic and natural stress factors on copepod populations. It facilitates the extrapolation of laboratory experiments to ecologically relevant end points pertaining to population viability.

Multimedia modeling of engineered nanoparticles with SimpleBox4nano: model definition and evaluation.

Screening level models for environmental assessment of engineered nanoparticles (ENP) are not generally available. Here, we present SimpleBox4Nano (SB4N) as the first model of this type, assess its validity, and evaluate it by comparisons with a known material flow model. SB4N expresses ENP transport and concentrations in and across air, rain, surface waters, soil, and sediment, accounting for nanospecific processes such as aggregation, attachment, and dissolution. The model solves simultaneous mass balance equations (MBE) using simple matrix algebra. The MBEs link all concentrations and transfer processes using first-order rate constants for all processes known to be relevant for ENPs. The first-order rate constants are obtained from the literature. The output of SB4N is mass concentrations of ENPs as free dispersive species, heteroaggregates with natural colloids, and larger natural particles in each compartment in time and at steady state. Known scenario studies for Switzerland were used to demonstrate the impact of the transport processes included in SB4N on the prediction of environmental concentrations. We argue that SB4N-predicted environmental concentrations are useful as background concentrations in environmental risk assessment.

Mechanistically-based QSARs to describe metabolic constants in mammals.

Biotransformation is one of the processes which influence the bioaccumulation of chemicals. The enzymatic action of metabolism involves two processes, i.e. the binding of the substrate to the enzyme followed by a catalytic reaction, which are described by the Michaelis-Menten constant (Km) and the maximum rate (Vmax). Here, we developed Quantitative Structure-Activity Relationships (QSARs) for Log(1/Km) and LogVmax for substrates of four enzyme classes. We focused on oxidations catalysed by alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), flavin-containing monooxygenase (FMO) and cytochrome P450 (CYP) in mammals. The chemicals investigated were xenobiotics, including alcohols, aldehydes, pesticides and drugs. We applied general linear models for this purpose, employing descriptors related to partitioning, geometric characteristics, and electronic properties of the substrates, which can be interpreted mechanistically. The explained variance of the QSARs varied between 20% and 70%, and it was larger for Log(1/Km) than for LogVmax. The increase of 1/Km with compound logP and size suggests that weak interactions are important, e.g. by substrate binding via desolvation processes. The importance of electronic factors for 1/Km was described in relation to the catalytic mechanism of the enzymes. Vmax was particularly influenced by electronic properties, such as dipole moment and energy of the lowest unoccupied molecular orbital. This can be explained by the nature of the catalysis, characterised by the cleavage and formation of covalent or ionic bonds (strong interactions). The present study may be helpful to understand the underlying principles of the chemical specific activity of four important oxidising enzymes.

Towards process-based modelling and parameterisation of bioaccumulation in humans across PFAS congeners.

Per- and polyfluoroalkyl substances (PFAS) are a large class of stable toxic chemicals which have ended up in the environment and in organisms in significant concentrations. Toxicokinetic models are needed to facilitate extrapolation of bioaccumulation data across PFAS congeners and species. For the present study, we carried out an inventory of accumulation processes specific for PFAS, deviating from traditional Persistent Organic Pollutants (POPs). In addition, we reviewed toxicokinetic models on PFAS reported in literature, classifying them according to the number of compartments distinguished as a one-compartment model (1-CM), two-compartment model (2- CM) or a multi-compartment model, (multi-CM) as well as the accumulation processes included and the parameters used. As the inventory showed that simple 1-CMs were lacking, we developed a generic 1-CM of ourselves to include PFAS specific processes and validated the model for legacy perfluoroalkyl acids. Predicted summed elimination constants were accurate for long carbon chains (>C6), indicating that the model properly represented toxicokinetic processes for most congeners. Results for urinary elimination rate constants were mixed, which might be caused by the exclusion of reabsorption processes (renal reabsorption, enterohepatic circulation). The 1-CM needs to be improved further in order to better predict individual elimination pathways. Besides that, more data on PFAS-transporter specific processes are needed to extrapolate across PFAS congeners and species.

Predicting the oral uptake efficiency of chemicals in mammals: combining the hydrophilic and lipophilic range.

Environmental risk assessment requires models for estimating the bioaccumulation of untested compounds. So far, bioaccumulation models have focused on lipophilic compounds, and only a few have included hydrophilic compounds. Our aim was to extend an existing bioaccumulation model to estimate the oral uptake efficiency of pollutants in mammals for compounds over a wide K(ow) range with an emphasis on hydrophilic compounds, i.e. compounds in the lower K(ow) range. Usually, most models use octanol as a single surrogate for the membrane and thus neglect the bilayer structure of the membrane. However, compounds with polar groups can have different affinities for the different membrane regions. Therefore, an existing bioaccumulation model was extended by dividing the diffusion resistance through the membrane into an outer and inner membrane resistance, where the solvents octanol and heptane were used as surrogates for these membrane regions, respectively. The model was calibrated with uptake efficiencies of environmental pollutants measured in different mammals during feeding studies combined with human oral uptake efficiencies of pharmaceuticals. The new model estimated the uptake efficiency of neutral (RMSE=14.6) and dissociating (RMSE=19.5) compounds with logK(ow) ranging from -10 to +8. The inclusion of the K(hw) improved uptake estimation for 33% of the hydrophilic compounds (logK(ow)<0) (r(2)=0.51, RMSE=22.8) compared with the model based on K(ow) only (r(2)=0.05, RMSE=34.9), while hydrophobic compounds (logK(ow)>0) were estimated equally by both model versions with RMSE=15.2 (K(ow)&K(hw)) and RMSE=15.7 (K(ow) only). The model can be used to estimate the oral uptake efficiency for both hydrophilic and hydrophobic compounds.

Relationships between absorption efficiency of elements in mammals and chemical properties.

Oral absorption efficiency is an important factor to consider in human risk assessment and varies widely between elements. Linking absorption efficiency to chemical properties facilitates the understanding of underlying processes and enables extrapolation across elements. In our study, oral absorption efficiency in humans was predicted for a number of elements based on their ionization energy and electronegativity. Data on oral absorption efficiency in humans were retrieved via a literature survey. A model was developed based on the assumption that ionic species readily react with biotic ligands. Accordingly, ionization energy was presumed to represent the reactivity and absorption of atoms in the gastrointestinal tract. The coefficients of the model were parameterized by fitting the quantitative relationship between absorption efficiency and ionization energy to data collected from well-standardized studies. Generally, absorption efficiency was strongly related to ionization energy, explaining 94% of the variability in absorption efficiency between elements reported by the International Commission on Radiological Protection (ICRP). In addition, the absorption efficiencies predicted based on ionization energy were within a factor of two of those given by the ICRP (ME = -0.05; RMSE = 0.31). However, the model is not applicable to alkaline metals and molybdenum because of the uniquely high solubility of their compounds or the flexible electron configuration of these elements. Approximately 56% of the variability in absorption efficiency between elements could be explained by electronegativity. These strong relationships between absorption efficiency and ionization energy and, to a lesser extent, electronegativity indicate potential for extrapolation across elements using atomic properties.