Environmental Risk Assessment of Time-Variable Toxicant Exposure with Toxicokinetic-Toxicodynamic Modeling of Sublethal Endpoints and Moving Time Windows: A Case Study with Ceriodaphnia dubia.

Toxicokinetic-toxicodynamic (TKTD) modeling has received increasing attention in terms of the regulatory environmental risk assessment of chemicals. This type of mechanistic model can integrate all available data from individual-level bioassays into a single framework and enable refined risk assessments by extrapolating from laboratory results to time-variable exposure scenarios, based, for instance, on surface water exposure modeling (e.g.

Impact of the antidepressant Bupropion on the Dynamic Energy Budget of Daphnia magna.

Psychiatric drugs are considered among the emerging contaminants of concern in ecological risk assessment, due to their potential to disrupt homeostasis in aquatic organisms. Bupropion is an antidepressant that acts by selective reuptake inhibition of norepinephrine and dopamine. Little is known about this compound's effects on aquatic organisms, despite being detected in significant concentrations in both water and biota close to waste-water treatment plants and densely populated areas.

Connecting Suborganismal Data to Bioenergetic Processes: Killifish Embryos Exposed to a Dioxin-Like Compound.

A core challenge for ecological risk assessment is to integrate molecular responses into a chain of causality to organismal or population-level outcomes. Bioenergetic theory may be a useful approach for integrating suborganismal responses to predict organismal responses that influence population dynamics. We describe a novel application of dynamic energy budget (DEB) theory in the context of a toxicity framework (adverse outcome pathways [AOPs]) to make quantitative predictions of chemical exposures to individuals, starting from suborganismal data.

Dynamic Energy Budget models: fertile ground for understanding resource allocation in plants in a changing world.

Climate change is having dramatic effects on the diversity and distribution of species. Many of these effects are mediated by how an organism's physiological patterns of resource allocation translate into fitness through effects on growth, survival and reproduction. Empirically, resource allocation is challenging to measure directly and so has often been approached using mathematical models, such as Dynamic Energy Budget (DEB) models.

Comparison of the performance and reliability between improved sampling strategies for polynomial chaos expansion.

As uncertainty and sensitivity analysis of complex models grows ever more important, the difficulty of their timely realizations highlights a need for more efficient numerical operations. Non-intrusive Polynomial Chaos methods are highly efficient and accurate methods of mapping input-output relationships to investigate complex models. There is substantial potential to increase the efficacy of the method regarding the selected sampling scheme.

E3-ligase knock down revealed differential titin degradation by autopagy and the ubiquitin proteasome system.

The sarcomere protein titin is a major determinant of cardiomyocyte stiffness and ventricular distensibility. The constant mechanical stress on titin requires well-controlled protein quality control, the exact mechanisms of which have not yet been fully elucidated. Here, we analyzed E3-ligases potentially responsible for cardiac titin ubiquitination and specifically studied the involvement of the autophagosomal system in titin degradation.

Improving the Screening Analysis of Pesticide Metabolites in Human Biomonitoring by Combining High-Throughput Incubation and Automated LC-HRMS Data Processing.

There is a current need to monitor human exposure to a large number of pesticides and other chemicals of emerging concern (CECs). This requires screening analysis with high confidence for these compounds and their metabolites in complex matrices, which is hampered by the fact that no reference standards are available for most metabolites. We address this challenge by a high-throughput workflow based on incubation of pesticides (or other CECs) with human liver S9, followed by solid-phase extraction, liquid chromatography-high-resolution mass spectrometry (LC-HRMS) analysis, and automated data processing to generate a database (retention time, precursor /, and MS spectral library) for the annotation in human samples.

Synthesis of (R)-mandelic acid and (R)-mandelic acid amide by recombinant E. coli strains expressing a (R)-specific oxynitrilase and an arylacetonitrilase.

Objectives: Chiral 2-hydroxycarboxylic acids and 2-hydroxycarboxamides are valuable synthons for the chemical industry.

Results: The biocatalytic syntheses of (R)-mandelic acid and (R)-mandelic acid amide by recombinant Escherichia coli clones were studied. Strains were constructed which simultaneously expressed a (R)-specific oxynitrilase (hydroxynitrile lyase) from the plant Arabidopsis thaliana together with the arylacetonitrilase from the bacterium Pseudomonas fluorescens EBC191.

Symbolic Aggregate Approximation Improves Gap Filling in High-Resolution Mass Spectrometry Data Processing.

Nontargeted mass spectrometry (MS) is widely used in life sciences and environmental chemistry to investigate large sets of samples. A major problem for larger-scale MS studies is data gaps or missing values in aligned data sets. The main causes for these data gaps are the absence of the compound from the sample, issues related to chromatography or mass spectrometry (for example, broad peaks, early eluting peaks, ion suppression, low ionization efficiency), and issues related to software (mainly limitations of peak detection algorithms).

Conventional and nano-copper pesticides are equally toxic to the estuarine amphipod Leptocheirus plumulosus.

Modern nano-engineered pesticides have great promise for agriculture due to their extended, low dose release profiles that are intended to increase effectiveness but reduce environmental harm. Whether nanopesticides, including copper (Cu) formulations, cause reduced levels of toxicity to non-target aquatic organisms is unclear but important to assess. Predicting how aquatic species respond to incidental exposure to Cu-based nanopesticides is challenging because of the expected very low concentrations in the environment, and the two forms of exposure that may occur, namely to Cu ions and Cu nanoparticles.

Unraveling longitudinal pollution patterns of organic micropollutants in a river by non-target screening and cluster analysis.

The pollution of aquatic ecosystems with complex and largely unknown mixtures of organic micropollutants is not sufficiently addressed with current monitoring strategies based on target screening methods. In this study, we implemented an open-source workflow based on non-target screening to unravel longitudinal pollution patterns of organic micropollutants along a river course. The 47 km long Holtemme River, a tributary of the Bode River (both Saxony-Anhalt, Germany), was used as a case study.

A Data Set of 255,000 Randomly Selected and Manually Classified Extracted Ion Chromatograms for Evaluation of Peak Detection Methods.

Non-targeted mass spectrometry (MS) has become an important method over recent years in the fields of metabolomics and environmental research. While more and more algorithms and workflows become available to process a large number of non-targeted data sets, there still exist few manually evaluated universal test data sets for refining and evaluating these methods. The first step of non-targeted screening, peak detection and refinement of it is arguably the most important step for non-targeted screening.

Proton radiation effects on carrier transport in diamond radiation detectors.

Diamond, a highly radiation-resistant material, is considered a nearly ideal material for radiation detection, particularly in high-energy physics. In this study, radiation damage from high-energy proton beams was induced in diamond crystals to determine exposure lifetime in detectors made from this material; the effects were investigated using non-destructive x-ray techniques and through the FLUKA simulation package. Two diamond detectors were irradiated by an 800 MeV proton beam at different fluence rates, and the real-time current response was recorded to observe degradation in the signal over time.

REGULATION OF REPRODUCTIVE PROCESSES WITH DYNAMIC ENERGY BUDGETS.

1. The simple bioenergetic models in the family of Dynamic Energy Budget (DEB) consist of a small number of state equations quantifying universal processes, such as feeding, maintenance, development, reproduction and growth. Linking these organismal level processes to underlying suborganismal mechanisms at the molecular, cellular and organ level constitutes a major challenge for predictive ecological risk assessments.

Non-targeted mercapturic acid screening in urine using LC-MS/MS with matrix effect compensation by postcolumn infusion of internal standard (PCI-IS).

While the targeted analysis of mercapturic acid (MA) metabolites in human urine is used to assess exposure to selected chemicals, this compound class has only rarely been addressed in non-target screening utilizing diagnostic neutral loss liquid chromatography tandem mass spectrometry (LC-MS/MS). Additionally, this type of analysis is severely affected by matrix effects (MEs) causing poor comparability of samples and distortion of signal intensities. However, MEs have been neglected in urinary MA non-target screening so far.

Towards a holistic and solution-oriented monitoring of chemical status of European water bodies: how to support the EU strategy for a non-toxic environment?

The definition of priority substances (PS) according to the Water Framework Directive (WFD) helped to remove many of these chemicals from the market and to reduce their concentrations in the European water bodies. However, it could not prevent that many of these chemicals have been replaced by others with similar risks. Today, monitoring of the PS-based chemical status according to WFD covers only a tiny fraction of toxic risks, extensively ignores mixture effects and lacks incentives and guidance for abatement.

An all-diamond X-ray position and flux monitor using nitrogen-incorporated ultra-nanocrystalline diamond contacts.

Diamond X-ray detectors with conducting nitrogen-incorporated ultra-nanocrystalline diamond (N-UNCD) films as electrodes were fabricated to measure X-ray beam flux and position. Structural characterization and functionality tests were performed for these devices. The N-UNCD films grown on unseeded diamond substrates were compared with N-UNCD films grown on a seeded silicon substrate.

Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment.

A working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS) explored the feasibility of integrating 2 complementary approaches relevant to ecological risk assessment. Adverse outcome pathway (AOP) models provide "bottom-up" mechanisms to predict specific toxicological effects that could affect an individual's ability to grow, reproduce, and/or survive from a molecular initiating event. Dynamic energy budget (DEB) models offer a "top-down" approach that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources.

Water transport through tall trees: A vertically explicit, analytical model of xylem hydraulic conductance in stems.

Trees grow by vertically extending their stems, so accurate stem hydraulic models are fundamental to understanding the hydraulic challenges faced by tall trees. Using a literature survey, we showed that many tree species exhibit continuous vertical variation in hydraulic traits. To examine the effects of this variation on hydraulic function, we developed a spatially explicit, analytical water transport model for stems.

Performance of combined fragmentation and retention prediction for the identification of organic micropollutants by LC-HRMS.

In nontarget screening, structure elucidation of small molecules from high resolution mass spectrometry (HRMS) data is challenging, particularly the selection of the most likely candidate structure among the many retrieved from compound databases. Several fragmentation and retention prediction methods have been developed to improve this candidate selection. In order to evaluate their performance, we compared two in silico fragmenters (MetFrag and CFM-ID) and two retention time prediction models (based on the chromatographic hydrophobicity index (CHI) and on log D).

A dynamic bioenergetic model for coral-Symbiodinium symbioses and coral bleaching as an alternate stable state.

Coral reef ecosystems owe their ecological success - and vulnerability to climate change - to the symbiotic metabolism of corals and Symbiodinium spp. The urgency to understand and predict the stability and breakdown of these symbioses (i.e.

Host-Symbiont Interaction Model Explains Non-monotonic Response of Soybean Growth and Seed Production to Nano-CeO Exposure.

Recent nanotoxicity studies have demonstrated non-monotonic dose-response mechanisms for planted soybean that have a symbiotic relationship with bacteroids in their root nodules: reduction of growth and seed production was greater for low, as compared to high, exposures. To investigate mechanistic underpinnings of the observed patterns, we formulated an energy budget model coupled to a toxicokinetic module describing bioaccumulation, and two toxicodynamic modules describing toxic effects on host plant and symbionts. By fitting data on plants exposed to engineered CeO nanoparticles to the newly formulated model, we show that the non-monotonic patterns can be explained as the interaction of two, individually monotonic, dose-response processes: one for the plant and the other for the symbiont.

Photosynthetic efficiency predicts toxic effects of metal nanomaterials in phytoplankton.

High Throughput Screening (HTS) using in vitro assessments at the subcellular level has great promise for screening new chemicals and emerging contaminants to identify high-risk candidates, but their linkage to ecological impacts has seldom been evaluated. We tested whether a battery of subcellular HTS tests could be used to accurately predict population-level effects of engineered metal nanoparticles (ENPs) on marine phytoplankton, important primary producers that support oceanic food webs. To overcome well-known difficulties of estimating ecologically meaningful toxicity parameters, we used novel Dynamic Energy Budget and Toxicodynamic (DEBtox) modeling techniques to evaluate impacts of ENPs on population growth rates.