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Respiratory sensitization is a complex immunological process eventually leading to hypersensitivity following re-exposure to the chemical. A frequent consequence is occupational asthma, which may occur after long latency periods. Although chemical-induced respiratory hypersensitivity has been known for decades, there are currently no comprehensive and validated approaches available for the prospective identification of chemicals that induce respiratory sensitization, while the expectations of new approach methodologies (NAMs) are high. A great hope is that due to a better understanding of the molecular key events, new methods can be developed now. However, this is a big challenge due to the different chemical classes to which respiratory sensitizers belong, as well as because of the complexity of the response and the late manifestation of symptoms. In this review article, the current information on respiratory sensitization related processes is summarized by introducing it in the available adverse outcome pathway (AOP) concept. Potentially useful models for prediction are discussed. Knowledge gaps and gaps of regulatory concern are identified. [ABSTRACT FROM AUTHOR]

Abstract Simulation educators are often requested to provide multidisciplinary and/or interprofessional simulation training in response to critical incidents. Current perspectives on patient safety focus on learning from failure, success and everyday variation. An international collaboration has led to the development of an accessible and practical framework to guide the implementation of appropriate simulation-based responses to clinical events, integrating quality improvement, simulation and patient safety methodologies to design appropriate and impactful responses. In this article, we describe a novel five-step approach to planning simulation-based interventions after any events that might prompt simulation-based learning in healthcare environments. This approach guides teams to identify pertinent events in healthcare, involve relevant stakeholders, agree on appropriate change interventions, elicit how simulation can contribute to them and share the learning without aggravating the second victim phenomenon. The framework is underpinned by Deming’s System of Profound Knowledge, the Model for Improvement and translational simulation. It aligns with contemporary socio-technical models in healthcare, by emphasising the role of clinical teams in designing adaptation and change for improvement, as well as encouraging collaborations to enhance patient safety in healthcare. For teams to achieve this adaptive capacity that realises organisational goals of continuous learning and improvement requires the breaking down of historical silos through the creation of an infrastructure that formalises relationships between service delivery, safety management, quality improvement and education. This creates opportunities to learn by design, rather than chance, whilst striving to close gaps between work as imagined and work as done.

Respiratory sensitization is a complex immunological process eventually leading to hypersensitivity following re-exposure to the chemical. A frequent consequence is occupational asthma, which may occur after long latency periods. Although chemical-induced respiratory hypersensitivity has been known for decades, there are currently no comprehensive and validated approaches available for the prospective identification of chemicals that induce respiratory sensitization, while the expectations of new approach methodologies (NAMs) are high. A great hope is that due to a better understanding of the molecular key events, new methods can be developed now. However, this is a big challenge due to the different chemical classes to which respiratory sensitizers belong, as well as because of the complexity of the response and the late manifestation of symptoms. In this review article, the current information on respiratory sensitization related processes is summarized by introducing it in the available adverse outcome pathway (AOP) concept. Potentially useful models for prediction are discussed. Knowledge gaps and gaps of regulatory concern are identified.

Abstract Background Since air pollution and physical inactivity pose major public health risks, switching from cars to alternatives like public transport, cycling, and walking is important. Therefore, it is beneficial to identify key events for changes of mode choice. Methods We examined the association between risk perception and mode choice during the temporary closure of a road bridge between two major German cities in early 2020 using binary and multinomial regression models. Results 679 people participated in the survey. We found that 22% of car users switched to alternatives. The higher the perceived health risk from traffic-related air pollution, the more likely car users switched to alternatives (odds ratio [OR] = 1.76, 95% CI [1.14, 2.71]). Discussion Attitude, subjective norm and perceived behavioral control were associated with maintaining but not with switching transport modes. In conclusion, the closure of a main road bridge may present a key event. To explain mode choice, risk perception is a potential extension to the theory of planned behavior.

Background: Since air pollution and physical inactivity pose major public health risks, switching from cars to alternatives like public transport, cycling, and walking is important. Therefore, it is beneficial to identify key events for changes of mode choice. Methods: We examined the association between risk perception and mode choice during the temporary closure of a road bridge between two major German cities in early 2020 using binary and multinomial regression models. Results: 679 people participated in the survey. We found that 22% of car users switched to alternatives. The higher the perceived health risk from traffic-related air pollution, the more likely car users switched to alternatives (odds ratio [OR] = 1.76, 95% CI [1.14, 2.71]). Discussion: Attitude, subjective norm and perceived behavioral control were associated with maintaining but not with switching transport modes. In conclusion, the closure of a main road bridge may present a key event. To explain mode choice, risk perception is a potential extension to the theory of planned behavior. [ABSTRACT FROM AUTHOR]

The detection of key events and identification of the events' context have been widely studied to detect key events from large volumes of online news and identify trends in such events. In this paper, we propose a Key News Event Detection and Context Method based on graphic convolving, clustering, and summarizing methods. Our method has three main contributions: (1) We propose the use of position vectors as time-embedding feature representations and concatenate semantic and time-embedding features as node features of the graph to distinguish different nodes of the graph. Additionally, a temporal nonlinear function was constructed using time embedding to objectively describe the effect of time on the degree of association between nodes. (2) We update the graph nodes using a graph convolutional neural network to extract deep semantic information about individual nodes of a high-quality phrase graph, thereby improving the clustering capability of graph-based key event detection. (3) We apply a summary generation algorithm to a subset of news data for each key event. Lastly, we validated the effectiveness of our proposed method by applying it to the 2014 Ebola dataset. The experimental results indicate that our proposed method can effectively detect key events from news documents with high precision and completeness while naturally generating the event context of key events, as compared to EvMine and other existing methods. [ABSTRACT FROM AUTHOR]

For over a decade, New Approach Methodologies (NAMs) such as structure-activity/read-across, -omics technologies, and Adverse Outcome Pathway (AOP), have been considered within regulatory communities as alternative sources of chemical and biological information potentially relevant to human health risk assessment. Integration of NAMs into applications such as chemical mixtures risk assessment has been limited due to the lack of validation of qualitative and quantitative application to adverse health outcomes in vivo, and acceptance by risk assessors. However, leveraging existent hazard and dose–response information, including NAM-based data, for mixture component chemicals across one or more levels of biological organization using novel approaches such as AOP 'footprinting' proposed herein, may significantly advance mixtures risk assessment. AOP footprinting entails the systematic stepwise profiling and comparison of all known or suspected AOPs involved in a toxicological effect at the level of key event (KE). The goal is to identify key event(s) most proximal to an adverse outcome within each AOP suspected of contributing to a given health outcome at which similarity between mixture chemicals can be confidently determined. These key events are identified as the 'footprint' for a given AOP. This work presents the general concept, and a hypothetical example application, of AOP footprinting as a key methodology for the integration of NAM data into mixtures risk assessment. [ABSTRACT FROM AUTHOR]

The concept of the adverse outcome pathway (AOP) has recently gained significant attention as to its potential for incorporation of mechanistic biological information into the assessment of adverse health outcomes following ionizing radiation (IR) exposure. This work is an account of the activities of an international expert group formed specifically to develop an AOP for IR-induced leukemia. Group discussions were held during dedicated sessions at the international AOP workshop jointly organized by the MELODI (Multidisciplinary European Low Dose Initiative) and the ALLIANCE (European Radioecology Alliance) associations to consolidate knowledge into a number of biological key events causally linked by key event relationships and connecting a molecular initiating event with the adverse outcome. Further knowledge review to generate a weight of evidence support for the Key Event Relationships (KERs) was undertaken using a systematic review approach. An AOP for IR-induced acute myeloid leukemia was proposed and submitted for review to the OECD-curated AOP-wiki (aopwiki.org). The systematic review identified over 500 studies that link IR, as a stressor, to leukemia, as an adverse outcome. Knowledge gap identification, although requiring a substantial effort via systematic review of literature, appears to be one of the major added values of the AOP concept. Further work, both within this leukemia AOP working group and other similar working groups, is warranted and is anticipated to produce highly demanded products for the radiation protection research community. [ABSTRACT FROM AUTHOR]

The Organisation for Economic Co-operation and Development (OECD), through its Chemical Safety Programme, is delegated to ensure the safety of humans and wildlife from harmful toxicants. To support these needs, initiatives to increase the efficiency of hazard identification and risk management are under way. Amongst these, the adverse outcome pathway (AOP) approach integrates information on biological knowledge and test methodologies (both established and new) to support regulatory decision making. AOPs collate biological knowledge from different sources, assess lines of evidence through considerations of causality, and undergo rigorous peer-review before being subsequently endorsed by the OECD. It is envisioned that the OECD AOP Development Programme will transform the toxicity testing paradigm by leveraging the strengths of mechanistic and modeling based approaches and enhance the utility of high throughput screening assays. Since its launch, in 2012, the AOP Development Programme has matured with a greater number of AOPs endorsed, and the attraction of new scientific disciplines (e.g. the radiation field). Recently, a radiation and chemical (Rad/Chem) AOP Joint Topical Group has been formed by the OECD Nuclear Energy Agency High-level Group on Low-dose Research (HLG-LDR) under the auspices of the Committee on Radiological Protection and Public Health (CRPPH). The topical group will work to evolve the development and use of the AOP framework in radiation research and regulation. As part of these efforts, the group will bring awareness and understanding on the program, as it has matured from the chemical perspective. In this context, this paper provides the radiation community with a high-level overview of the OECD AOP Development Programme, including examples of application using knowledge gleaned from the field of chemical toxicology, and their work toward regulatory implementation. Although the drivers for developing AOPs in chemical sector differ from that of the radiation field, the principles and transparency of the approach can benefit both scientific disciplines. By providing perspectives and an understanding of the evolution of the OECD AOP Development Programme including case examples and work toward quantitative AOP development, it may motivate the expansion and implementation of AOPs in the radiation field. [ABSTRACT FROM AUTHOR]

The purpose of toxicology is to protect human health and the environment. To support this, the Organisation for Economic Co-operation and Development (OECD), operating via its Extended Advisory Group for Molecular Screening and Toxicogenomics (EAGMST), has been developing the Adverse Outcome Pathway (AOP) approach to consolidate evidence for chemical toxicity spanning multiple levels of biological organization. The knowledge transcribed into AOPs provides a structured framework to transparently organize data, examine the weight of evidence of the AOP, and identify causal relationships between exposure to stressors and adverse effects of regulatory relevance. The AOP framework has undergone substantial maturation in the field of hazard characterization of chemicals over the last decade, and has also recently gained attention from the radiation community as a means to advance the mechanistic understanding of human and ecological health effects from exposure to ionizing radiation at low dose and low dose-rates. To fully exploit the value of such approaches for facilitating risk assessment and management in the field of radiation protection, solicitation of experiences and active cooperation between chemical and radiation communities are needed. As a result, the Radiation and Chemical (Rad/Chem) AOP joint topical group was formed on June 1, 2021 as part of the initiative from the High Level Group on Low Dose Research (HLG-LDR). HLG-LDR is overseen by the OECD Nuclear Energy Agency (NEA) Committee on Radiation Protection and Public Health (CRPPH). The main aims of the joint AOP topical group are to advance the use of AOPs in radiation research and foster broader implementation of AOPs into hazard and risk assessment. With global representation, it serves as a forum to discuss, identify and develop joint initiatives that support research and take on regulatory challenges. The Rad/Chem AOP joint topical group will specifically engage, promote, and implement the use of the AOP framework to: (a) organize and evaluate mechanistic knowledge relevant to the protection of human and ecosystem health from radiation; (b) identify data gaps and research needs pertinent to expanding knowledge of low dose and low dose-rate radiation effects; and (c) demonstrate utility to support risk assessment by developing radiation-relevant case studies. It is envisioned that the Rad/Chem AOP joint topical group will actively liaise with the OECD EAGMST AOP developmental program to collectively advance areas of common interest and, specifically, provide recommendations for harmonization of the AOP framework to accommodate non-chemical stressors, such as radiation. [ABSTRACT FROM AUTHOR]

The National Research Council's vision of using adverse outcome pathways (AOPs) as a framework to assist with toxicity assessment for regulatory requirements of chemical assessment has continued to gain traction since its release in 2007. The need to expand the AOP knowledge base has gained urgency, with the U.S. Environmental Protection Agency's directive to eliminate reliance on animal toxicity testing by 2035. To meet these needs, our goal was to elucidate the AOP for male-rat-specific kidney cancer. Male-rat-specific kidney tumors occur through the ability of structurally diverse substances to induce α2u-globulin nephropathy (α2u-N), a well-studied mode of action (MoA) not relevant in humans that results in kidney tumor formation in male rats. An accepted AOP may help facilitate the differentiation from other kidney tumors MoAs. Following identification and review of relevant in vitro and in vivo literature, both the MIE and subsequent KEs were identified. Based on the weight of evidence from the various resources, the confidence in this AOP is high. Uses of this AOP include hazard identification, development of in vitro assays to determine if the MoA is through α2u-N and not relevant to humans resulting in decreased use of animals, and regulatory applications. [ABSTRACT FROM AUTHOR]

The detection of key events and identification of the events’ context have been widely studied to detect key events from large volumes of online news and identify trends in such events. In this paper, we propose a Key News Event Detection and Context Method based on graphic convolving, clustering, and summarizing methods. Our method has three main contributions: (1) We propose the use of position vectors as time-embedding feature representations and concatenate semantic and time-embedding features as node features of the graph to distinguish different nodes of the graph. Additionally, a temporal nonlinear function was constructed using time embedding to objectively describe the effect of time on the degree of association between nodes. (2) We update the graph nodes using a graph convolutional neural network to extract deep semantic information about individual nodes of a high-quality phrase graph, thereby improving the clustering capability of graph-based key event detection. (3) We apply a summary generation algorithm to a subset of news data for each key event. Lastly, we validated the effectiveness of our proposed method by applying it to the 2014 Ebola dataset. The experimental results indicate that our proposed method can effectively detect key events from news documents with high precision and completeness while naturally generating the event context of key events, as compared to EvMine and other existing methods.

For over a decade, New Approach Methodologies (NAMs) such as structure-activity/read-across, -omics technologies, and Adverse Outcome Pathway (AOP), have been considered within regulatory communities as alternative sources of chemical and biological information potentially relevant to human health risk assessment. Integration of NAMs into applications such as chemical mixtures risk assessment has been limited due to the lack of validation of qualitative and quantitative application to adverse health outcomes in vivo, and acceptance by risk assessors. However, leveraging existent hazard and dose–response information, including NAM-based data, for mixture component chemicals across one or more levels of biological organization using novel approaches such as AOP ‘footprinting’ proposed herein, may significantly advance mixtures risk assessment. AOP footprinting entails the systematic stepwise profiling and comparison of all known or suspected AOPs involved in a toxicological effect at the level of key event (KE). The goal is to identify key event(s) most proximal to an adverse outcome within each AOP suspected of contributing to a given health outcome at which similarity between mixture chemicals can be confidently determined. These key events are identified as the ‘footprint’ for a given AOP. This work presents the general concept, and a hypothetical example application, of AOP footprinting as a key methodology for the integration of NAM data into mixtures risk assessment.

Significant advances have been made in the development of Adverse Outcome Pathways (AOPs) over the last decade, mainly focused on the toxicity mechanisms of chemicals. These AOPs, although relevant to manufactured nanomaterials (MNs), do not currently capture the reported roles of size-associated properties of MNs on toxicity. Moreover, some AOs of relevance to airborne exposures to MNs such as lung inflammation and fibrosis shown in animal studies may not be targeted in routine regulatory decision making. The primary objective of the present study was to establish an approach to advance the development of AOPs of relevance to MNs using existing, publicly available, nanotoxicology literature. A systematic methodology was created for curating, organizing and applying the available literature for identifying key events (KEs). Using a case study approach, the study applied the available literature to build the biological plausibility for 'tissue injury', a KE of regulatory relevance to MNs. The results of the analysis reveal the various endpoints, assays and specific biological markers used for assessing and reporting tissue injury. The study elaborates on the limitations and opportunities of the current nanotoxicology literature and provides recommendations for the future reporting of nanotoxicology results that will expedite not only the development of AOPs for MNs but also aid in application of existing data for decision making. [ABSTRACT FROM AUTHOR]

• BMR defined based on definition of RAIU considered abnormal in medical literature. • Bayesian hierarchical modeling was used to account for the repeated measures. • The beta distribution used for the modeling correctly reflected the bounding of RAIU. • BMDL was 0.03 mg/kg-day. Several exposure limits for perchlorate have been developed based on an early key event, inhibition of radioactive iodide uptake (RAIU) by the thyroid. These assessments have used a variety of definitions of the point of departure. The current assessment revisited the modeling for inhibition of RAIU, using state of the science methods. Bayesian hierarchical modeling was used to account for the repeated measures on the same individuals in the key dataset, and the underlying Beta distribution used for the modeling correctly reflected the bounding of RAIU between 0 and 1. We defined the BMR as a point value of 8% RAIU (rather than a change in RAIU), based on descriptions in the medical literature that RAIU below this value is considered abnormal. Because a definition of the BMR based on the mean response would correspond to about 50% of the population with a response below the BMR at the benchmark dose, we used a hybrid definition of the BMR. That is, the BMD was defined as the dose at which it was estimated that there would be a 10% extra risk in the population of having RAIU of 8% or lower. The resulting point of departure based on the BMDL was 0.03 mg/kg-day. [ABSTRACT FROM AUTHOR]

• Key events in a mode of action can inform risk model shape. • Flexible approaches to modifying risk model shape are demonstrated and discussed. • Benzene leukemia risk models can incorporate information on hematotoxicity and genetic toxicity. Occupational exposure to benzene at levels of 10 ppm or more has been associated with increased risk of acute myeloid leukaemia (AML). The mode of action (MOA) for AML development leading to mortality is anticipated to include multiple earlier key events, which can be observed in hematotoxicity and genetic toxicity in peripheral blood of exposed workers. Prevention of these early events would lead to prevention of the apical, adverse outcomes, the morbidity and mortality caused by the myelodysplastic syndromes (MDS) and AML. Incorporation of key event information should modify the risk model, but few modification approaches have been suggested. To that end, two approaches to risk model modification are described that use sub-linear and segmented linear increases in risk below key events, while maintaining a linear increase in AML mortality risk beginning at 2 ppm, the lowest observed adverse effect concentration (LOAEC) identified for hemato- and geno- toxicity in high quality studies of human occupational exposure. Below 2 ppm two different modification approaches to quantitative risk models were applied: a continuously decreasing slope model and a segmented modification in slope. These two approaches provide greater flexibility to incorporate MOA information in risk model development and selection. [ABSTRACT FROM AUTHOR]

Traditional methods for cancer risk assessment are resource-intensive, retrospective, and not feasible for the vast majority of environmental chemicals. In this study, we investigated whether quantitative genomic data from short-term studies may be used to set protective thresholds for potential tumorigenic effects. We hypothesized that gene expression biomarkers measuring activation of the key early events in established pathways for rodent liver cancer exhibit cross-chemical thresholds for tumorigenesis predictive for liver cancer risk. We defined biomarker thresholds for 6 major liver cancer pathways using training sets of chemicals with short-term genomic data (3–29 days of exposure) from the TG-GATES (n  = 77 chemicals) and DrugMatrix (n  = 86 chemicals) databases and then tested these thresholds within and between datasets. The 6 pathway biomarkers represented genotoxicity, cytotoxicity, and activation of xenobiotic, steroid, and lipid receptors (aryl hydrocarbon receptor, constitutive activated receptor, estrogen receptor, and peroxisome proliferator-activated receptor α). Thresholds were calculated as the maximum values derived from exposures without detectable liver tumor outcomes. We identified clear response values that were consistent across training and test sets. Thresholds derived from the TG-GATES training set were highly predictive (97%) in a test set of independent chemicals, whereas thresholds derived from the DrugMatrix study were 96%–97% predictive for the TG-GATES study. Threshold values derived from an abridged gene list (2/biomarker) also exhibited high predictive accuracy (91%–94%). These findings support the idea that early genomic changes can be used to establish threshold estimates or "molecular tipping points" that are predictive of later-life health outcomes. [ABSTRACT FROM AUTHOR]

• Reviewed cell-based, and organism-based alternative models for DNT. • Provided an overview of current state of the science on DNT AOPs. • Identified common key events of AOPs that could serve as endpoints for DNT testing using alternative methods. • Proposed a streamlined screening strategy. Developmental neurotoxicity (DNT) is an important endpoint for the safety assessment of chemicals. However, the current in vivo animal model for DNT assessment is resource-intensive and may not fully capture all mechanisms that may be relevant to DNT in humans. As a result, there is a growing need for more reliable, time- and cost-efficient approaches for DNT evaluation. Toward this end, many stem/progenitor cell-based in vitro models and alternative organism-based models are becoming available with the potential for high throughput screening of DNT. Meanwhile, with advances in the knowledgebase of DNT molecular mechanisms and the identification of DNT-related adverse outcome pathways (AOP) there is potential to develop a mechanism-based integrated testing strategy for DNT assessment. This review summarizes the state of science regarding currently available human stem/progenitor cell-based in vitro models and alternative organism-based models that could be used for DNT testing. In addition, the current knowledge regarding DNT AOPs is reviewed to identify common key events that could serve as critical endpoints to assess multiple AOPs that underlie DNT. Following the identification of common key events, a streamlined strategy is proposed using alternative models to assess the DNT potential of chemicals as an early screening approach for chemicals in development. [ABSTRACT FROM AUTHOR]

The amino acid derivative reactivity assay (ADRA) is a novel in chemico alternative to animal testing for assessment of skin sensitization potential. The conventional ADRA protocol stipulates that test chemical solutions should be prepared to a specific molar concentration, allowing only for use of test chemicals with known molecular weights. Since many potential test substances are prepared by weight concentration or contain multiple unknown chemicals, this study was conducted to verify if it is possible to accurately assess the sensitization potential of test chemical solutions prepared at a specific weight concentration. (1) Test chemical solutions for 82 chemicals were prepared at four different weight concentrations. Results were evaluated for agreement with in vivo results. (2) A liquid mixture comprising ten different non-sensitizers was prepared at 1 mg/mL. Ten different sensitizers of varying sensitization potencies were added individually to this mixture. The resulting pseudobinary mixtures were tested to confirm that the sensitizers could be detected. (1) The accuracies for test chemical solutions prepared at 0.5 and 0.2 mg/mL were 87.8% and 86.6%, respectively, which were roughly equivalent to the accuracy of 86.6% achieved with a solution prepared at the conventional molar concentration of 1 mM. In contrast, the accuracies for solutions prepared at 0.1 and 0.05 mg/mL were 82.9% and 74.4%, respectively, both of which were lower than that obtained with the conventional method. (2) Sensitizers added to the liquid mixture at 0.5 mg/mL were all correctly detected. Preparing test chemical solutions at a weight concentration of 0.5 mg/mL decreased false negatives and increased false positives while improving prediction accuracy, which suggests that the sensitization potential of mixtures can also be assessed with this method. [ABSTRACT FROM AUTHOR]

Chemical risk assessment remains entrenched in chronic toxicity tests that set safety thresholds based on animal pathology or fitness. Chronic tests are resource expensive and lack mechanistic insight. Discovering a chemical's mode-of-action can in principle provide predictive molecular biomarkers for a toxicity endpoint. Furthermore, since molecular perturbations precede pathology, early-response molecular biomarkers may enable shorter, more resource efficient testing that can predict chronic animal fitness. This study applied untargeted metabolomics to attempt to discover early-response metabolic biomarkers that can predict reproductive fitness of Daphnia magna, an internationally-recognized test species. First, we measured the reproductive toxicities of cadmium, 2,4-dinitrophenol and propranolol to individual Daphnia in 21-day OECD toxicity tests, then measured the metabolic profiles of these animals using mass spectrometry. Multivariate regression successfully discovered putative metabolic biomarkers that strongly predict reproductive impairment by each chemical, and for all chemicals combined. The non-chemical-specific metabolic biomarkers were then applied to metabolite data from Daphnia 24-h acute toxicity tests and correctly predicted that significant decreases in reproductive fitness would occur if these animals were exposed to cadmium, 2,4-dinitrophenol or propranolol for 21 days. While the applicability of these findings is limited to three chemicals, they provide proof-of-principle that early-response metabolic biomarkers of chronic animal fitness can be discovered for regulatory toxicity testing. [ABSTRACT FROM AUTHOR]

This article provides insight into the intensified media attention for fake news in Dutch newspaper articles between May 2016 and April 2017 from the perspective of Vasterman's (2005) theory of media hypes. It was found that speculations about the election of Donald Trump as president of the United States as a result of the spread of fake news caused a news wave. This news wave consists mainly of meta news and contains few news articles about the disclosure of fake news. The news production ismainly driven bymeta news and by news about qualifications of the media as 'fake news'. This article calls for further research into the media attention for fake news in other media than newspapers in the Netherlands as well as in other countries. [ABSTRACT FROM AUTHOR]

This paper examines the mode use of students before and after starting their working lives and analyses the influencing factors. We aim to improve our understanding of travel behaviour change based on a theoretical framework extending the Theory of Planned Behaviour (ToPB), namely the Requirements, Opportunities, Abilities (ROA) approach, and the concept of habits and key events. The paper focuses on (i) how former university students adjust their travel behaviour when their working life starts and (ii) what are the most important factors explaining these changes. With a three-wave online panel, we show that indeed many graduate workers start commuting by car and fewer travel by public transport. To explain mode change, we identified classical factors from the ToPB (subjective norm, perceived behavioural control, attitudes) as well as several requirements (more flexibility, dress code), opportunities (changed car availability, parking situation, connection to public transport) and abilities (financial, commuting distance) and, moreover, habits. As a result, we could show influences resulting from changed attitudes, changes in personal requirements as well as changes in mode options. Habit consequently decreases the probability of mode change. We draw some policy implications from the results highlighting the importance of the provision of rail-bound public transport and giving recommendations on travel demand management. [ABSTRACT FROM AUTHOR]

Recent developments have prompted the transition of empirically based testing of late stage toxicity in animals for a range of different endpoints including neurotoxicity to more efficient and predictive mechanistically based approaches with greater emphasis on measurable key events early in the progression of disease. The adverse outcome pathway (AOP) has been proposed as a simplified organizational construct to contribute to this transition by linking molecular initiating events and earlier (more predictive) key events at lower levels of biological organization to disease outcomes. As such, AOPs are anticipated to facilitate the compilation of information to increase mechanistic understanding of pathophysiological pathways that are responsible for human disease. In this review, the sequence of key events resulting in adverse outcome (AO) defined as parkinsonian motor impairment and learning and memory deficit in children, triggered by exposure to environmental chemicals has been briefly described using the AOP framework. These AOPs follow convention adopted in an Organization for Economic Cooperation and Development (OECD) AOP development program, publically available, to permit tailored application of AOPs for a range of different purposes. Due to the complexity of disease pathways, including neurodegenerative disorders, a specific symptom of the disease (e.g. parkinsonian motor deficit) is considered as the AO in a developed AOP. Though the description is necessarily limited by the extent of current knowledge, additional characterization of involved pathways through description of related AOPs interlinked into networks for the same disease has potential to contribute to more holistic and mechanistic understanding of the pathophysiological pathways involved, possibly leading to the mechanism-based reclassification of diseases, thus facilitating more personalized treatment. [ABSTRACT FROM AUTHOR]

Algae are key components of aquatic food chains. Consequently, they are internationally recognised test species for the environmental safety assessment of chemicals. However, existing algal toxicity test guidelines are not yet optimized to discover molecular modes of action, which require highly-replicated and carefully controlled experiments. Here, we set out to develop a robust, miniaturised and scalable Chlamydomonas reinhardtii toxicity testing approach tailored to meet these demands. We primarily investigated the benefits of synchronised cultures for molecular studies, and of exposure designs that restrict chemical volatilisation yet yield sufficient algal biomass for omics analyses. Flow cytometry and direct-infusion mass spectrometry metabolomics revealed significant and time-resolved changes in sample composition of synchronised cultures. Synchronised cultures in sealed glass vials achieved adequate growth rates at previously unachievably-high inoculation cell densities, with minimal pH drift and negligible chemical loss over 24-h exposures. Algal exposures to a volatile test compound (chlorobenzene) yielded relatively high reproducibility of metabolic phenotypes over experimental repeats. This experimental test system extends existing toxicity testing formats to allow highly-replicated, omics-driven, mode-of-action discovery.

Microplastics are a contaminant of emergent concern in the environment, however, to date there is a limited understanding on their movement within organisms and the response of organisms. In the current study zebrafish embryos at different development stages were exposed to 700 nm fluorescent polystyrene (PS) particles and the response pathway after exposure was investigated using imaging and transcriptomics. Our results show limited spreading of particles within the larvae after injection during the blastula stage. This is in contrast to injection of PS particles in the yolk of 2-day old embryos, which resulted in redistribution of the PS particles throughout the bloodstream, and accumulation in the heart region. Although injection was local, the transcriptome profiling showed strong responses of zebrafish embryos exposed to PS particle, indicating a systemic response. We found several biological pathways activated which are related to an immune response in the PS exposed zebrafish larvae. Most notably the complement system was enriched as indicated by upregulation of genes in the alternative complement pathway (e.g. cfhl3, cfhl4, cfb and c9) . The fact that complement pathway is activated indicates that plastic microparticles are integrated in immunological recognition processes. This was supported by fluorescence microscopy results, in which we observed co-localisation of neutrophils and macrophages around the PS particles. Identifying these key events can be a first building block to the development of an adverse outcome pathway (AOP). These data subsequently can be used within ecological and human risk assessment. [ABSTRACT FROM AUTHOR]

Unravelling gene regulatory networks (GRNs) influenced by chemicals is a major challenge in systems toxicology. Because toxicant-induced GRNs evolve over time and dose, the analysis of global gene expression data measured at multiple time points and doses will provide insight in the adverse effects of compounds. Therefore, there is a need for mathematical methods for GRN identification from time-over-dose-dependent data. One of the current approaches for GRN inference is Time Series Network Identification (TSNI). TSNI is based on ordinary differential equations (ODE), describing the time evolution of the expression of each gene, which is assumed to be dependent on the expression of other genes and an external perturbation (i.e. chemical exposure). Here, we present Dose-Time Network Identification (DTNI), a method extending TSNI by including ODE describing how the expression of each gene evolves with dose, which is supposed to depend on the expression of other genes and the exposure time. We also adapted TSNI in order to enable inclusion of time-over-dose-dependent data from multiple compounds. Here, we show that DTNI outperforms TSNI in inferring a toxicant-induced GRN. Moreover, we show that DTNI is a suitable method to infer a GRN dose- and time-dependently induced by a group of compounds influencing a common biological process. Applying DTNI on experimental data from TG-GATEs, we demonstrate that DTNI provides in-depth information on the mode of action of compounds, in particular key events and potential molecular initiating events. Furthermore, DTNI also discloses several unknown interactions which have to be verified experimentally. [ABSTRACT FROM AUTHOR]

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The purpose of this work is to systematically consider the data relating to the mode of action (MOA) for the effects of industrially produced trans fatty acid (iTFA) on plasma low-density lipoprotein (LDL) levels. The hypothesized MOA is composed of two key events: increased LDL production and decreased LDL clearance. A substantial database supports this MOA, although the key events are likely to be interdependent, rather than sequential. Both key events are functions of nonlinear biological processes including rate-limited clearance, receptor-mediated transcription, and both positive and negative feedback regulation. Each key event was evaluated based on weight-of-evidence analysis and for human relevance. We conclude that the data are inadequate for a detailed dose-response analysis in the context of the evolved Bradford Hill considerations; however, the weight of evidence is strong and the overall shape of the dose-response curves for markers of the key events and the key determinants of those relationships is well understood in many cases and is nonlinear. Feedback controls are responsible for maintaining homeostasis of cholesterol and triglyceride levels and underlie both of the key events, resulting in a less-than-linear or thresholded relationship between TFA and LDL-C. The inconsistencies and gaps in the database are discussed. [ABSTRACT FROM AUTHOR]

Chemical risk assessment remains entrenched in chronic toxicity tests that set safety thresholds based on animal pathology or fitness. Chronic tests are resource expensive and lack mechanistic insight. Discovering a chemical’s mode-of-action can in principle provide predictive molecular biomarkers for a toxicity endpoint. Furthermore, since molecular perturbations precede pathology, early-response molecular biomarkers may enable shorter, more resource efficient testing that can predict chronic animal fitness. This study applied untargeted metabolomics to attempt to discover early-response metabolic biomarkers that can predict reproductive fitness of Daphnia magna, an internationally-recognized test species. First, we measured the reproductive toxicities of cadmium, 2,4-dinitrophenol and propranolol to individual Daphnia in 21-day OECD toxicity tests, then measured the metabolic profiles of these animals using mass spectrometry. Multivariate regression successfully discovered putative metabolic biomarkers that strongly predict reproductive impairment by each chemical, and for all chemicals combined. The non-chemical-specific metabolic biomarkers were then applied to metabolite data from Daphnia 24-h acute toxicity tests and correctly predicted that significant decreases in reproductive fitness would occur if these animals were exposed to cadmium, 2,4-dinitrophenol or propranolol for 21 days. While the applicability of these findings is limited to three chemicals, they provide proof-of-principle that early-response metabolic biomarkers of chronic animal fitness can be discovered for regulatory toxicity testing.

Links between gender, activity/travel patterns and the life course have become a significant subject of inquiry in recent years. This paper draws upon a previous study that found that key events in the life course had significant effects on the complexity of trip and activity patterns. Some of these effects differed significantly between men and women. The panel data analysis presented here uses descriptive statistics to illustrate more clearly the patterns of time use before and after key events such as the birth of a child, entry into the labour market, or retirement. Further, regression models of time use changes for employed work, out-of-home leisure, escort, and time spent at home are presented. The data used is the German Mobility Panel (GMP) 1994 to 2014 in which households and their members are asked three times in three successive years to report the trips they made over a week. The results show the gendered effects of various key events on change in time use. Key events in partnership and the family affect women's time use more than men's, while for labour market events it is mostly the other way round. [ABSTRACT FROM AUTHOR]

Since the large majority of households have access to one or more cars in the developed world, encouraging multimodal travel behaviours has become a goal for many cities. Multimodality refers to the use of more than one transport mode within a given period of time. While correlates of multimodality have been identified from cross-sectional data, there is very little known about the circumstances over time in which individuals become more or less multimodal. This paper is the first to fully adopt the mobility biography approach to study changes in multimodality over time at the individual level. Multimodality is measured using four continuous indicators of mode use in a seven-day period: the share in trips made by the most commonly used mode (primary mode), the Herfindahl-Hirschman Index, Shannon’s entropy, and the number of modes used. The paper uses the German Mobility Panel (GMP) for the period 1994–2012. The results demonstrate that some of the life course events studied are significantly associated with changes in multimodality. Specifically, a child moving out of the household increases the multimodality of parents. Leaving the labour market increases multimodality, while entering the labour market conversely reduces multimodality. Changes in car access and driver licence holding have significant effects as well. An improvement to the public transport system in the neighbourhood increases multimodality, and vice versa. Reduced parking space availability also increases multimodality. The latter two findings endorse ‘carrot and stick’ transport policies as means of creating a more balanced use of transport modes. [ABSTRACT FROM AUTHOR]

In transport research, important changes in an individual’s life, so-called key events, are of particular interest because changes in one’s environment and surrounding context weaken routines, and a ‘window of opportunity’ opens up for behavioural change. In the framework of the mobility biographies approach, several studies have been undertaken to improve understanding of travel behaviour change in the last decade. This paper critically and systematically reviews emerging results from mobility biographies research, focusing on key events which potentially induce contextual and travel behaviour changes. The first step was to identify 25 of the most important studies for this approach and their related concepts. Next, notions other than key events in the literature are discussed and a theoretical framework for the longitudinal interaction of four dimensions of key events and other factors for travel behaviour change are identified: (i) life events in private and professional careers, (ii) adaptation of long-term mobility decisions, (iii) exogenous interventions, and (iv) other long-term processes which are not key events (e.g. socialisation). Furthermore, the understanding of key events, methodological challenges and further research gaps are critically discussed in this review. [ABSTRACT FROM AUTHOR]

Non-genotoxic carcinogens act by promoting the clonal expansion of preneoplastic cells by directly or indirectly stimulating cell division or inhibiting cell loss in the target organ. The specific mode-of-action (MoA) by which some non-genotoxic carcinogens ultimately cause cancer is not completely understood. To date, there are several proposed MoAs for non-genotoxic carcinogens, and some of these propose inhibition of apoptosis as one of the key events. In general, inhibition of apoptosis is considered a necessary step for cell survival and in theory can occur in combination or in association with other key promotional events, such as cell proliferation, oxidative stress and inhibition of intercellular communication to promote carcinogenesis. However, the evidence supporting the role of inhibition of apoptosis as a necessary step in promoting specific chemically induced tumors is often debated. To address this evidence, we reviewed studies that utilized prototypical nuclear receptor-mediated hepatocarcinogens. Based on this review, it is proposed that the ability to determine the importance of inhibition of apoptosis as a key event in the MoA for tumor promotion is hampered by the limitations of the methods utilized for its detection. This review provides an assessment of the strengths and limitations of the current methodology used for detection of apoptosis and provides suggestions for improving its detection, thereby strengthening the weight of evidence supporting inhibition of apoptosis as a key event in a MoA for tumor promotion. [ABSTRACT FROM PUBLISHER]

A major problem in developmental neurotoxicity (DNT) risk assessment is the lack of toxicological hazard information for most compounds. Therefore, new approaches are being considered to provide adequate experimental data that allow regulatory decisions. This process requires a matching of regulatory needs on the one hand and the opportunities provided by new test systems and methods on the other hand. Alignment of academically and industrially driven assay development with regulatory needs in the field of DNT is a core mission of the International STakeholder NETwork (ISTNET) in DNT testing. The first meeting of ISTNET was held in Zurich on 23-24 January 2014 in order to explore the concept of adverse outcome pathway (AOP) to practical DNT testing. AOPs were considered promising tools to promote test systems development according to regulatory needs. Moreover, the AOP concept was identified as an important guiding principle to assemble predictive integrated testing strategies (ITSs) for DNT. The recommendations on a road map towards AOP-based DNT testing is considered a stepwise approach, operating initially with incomplete AOPs for compound grouping, and focussing on key events of neurodevelopment. Next steps to be considered in follow-up activities are the use of case studies to further apply the AOP concept in regulatory DNT testing, making use of AOP intersections (common key events) for economic development of screening assays, and addressing the transition from qualitative descriptions to quantitative network modelling. [ABSTRACT FROM AUTHOR]

The HESI RISK21 project formed the Dose-Response/Mode-of-Action Subteam to develop strategies for using all available data ( in vitro, in vivo, and in silico) to advance the next-generation of chemical risk assessments. A goal of the Subteam is to enhance the existing Mode of Action/Human Relevance Framework and Key Events/Dose Response Framework (KEDRF) to make the best use of quantitative dose-response and timing information for Key Events (KEs). The resulting Quantitative Key Events/Dose-Response Framework (Q-KEDRF) provides a structured quantitative approach for systematic examination of the dose-response and timing of KEs resulting from a dose of a bioactive agent that causes a potential adverse outcome. Two concepts are described as aids to increasing the understanding of mode of action-Associative Events and Modulating Factors. These concepts are illustrated in two case studies; 1) cholinesterase inhibition by the pesticide chlorpyrifos, which illustrates the necessity of considering quantitative dose-response information when assessing the effect of a Modulating Factor, that is, enzyme polymorphisms in humans, and 2) estrogen-induced uterotrophic responses in rodents, which demonstrate how quantitative dose-response modeling for KE, the understanding of temporal relationships between KEs and a counterfactual examination of hypothesized KEs can determine whether they are Associative Events or true KEs. [ABSTRACT FROM AUTHOR]

Highlights: [•] Changes in travel mode use after life course and accessibility related key events are studied from a gender perspective. [•] Significant effects were found for some key events, including the birth of a child and entry into the labour market. [•] Changes in spatial context, accessibility and mobility were significant as well. [•] The effects of some key events differed distinctly between men and women. [•] Taken together the effects, as well as their gender differences, are limited. [Copyright &y& Elsevier]

Copyright of Cuadernos de Información y Comunicación is the property of Universidad Complutense de Madrid and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: This paper studies changes in people’s travel mode use from oneyear to the next. It is informed by three distinct discourses: travel behaviour change, the mobility biographies approach, and cohort analysis. The data used is the German Mobility Panel (GMP) 1994–2008 in which households and their members are asked three times in three subsequent years to report the trips they made over a week. The changes reported are regressed to key events over the life course, cohort effects and period effects, while various sociodemographic and spatial attributes are controlled. Due to the non-independent nature of panel observations, a cluster-robust regression approach is used. The findings suggest that behind the aggregate stability in travel mode use over time there is much change ‘under the surface’, induced by life course changes, individual and household sociodemographic, and spatial context. The changes found induced by life course related key events favour the notion of mobility biographies. However, taken over all key events seem to be relatively loosely associated with mode use changes. Nonetheless, various significant effects of baseline variables suggest that mode use may change even in the absence of a key event. [Copyright &y& Elsevier]

Abstract: It is inevitable that in a lifetime humans will be exposed to a diverse array of chemical mixtures through occupational, recreational, and/or domestic activities. These mixtures may be simple, consisting of two or more definable compounds, or may be more complex containing several hundred related congeners and/or unrelated compounds. Due to a paucity of mixtures toxicity data, the estimation of risk of adverse health effects associated with mixtures typically comes from empirical observations of single chemical exposures. Under existing policy, characterizing the relative contribution of each compound depends on identification of the target organ or tissue dose, mode of action, and duration of effect. Currently, there is no consensus on what constitutes a toxic mode or mechanism of action, nor is there a universally accepted framework to determine similarity or independence of mode of action for mixtures risk assessment. This lack of a comprehensive classification paradigm for mode or mechanism of toxic action continues to be a major rate-limiting step in the advancement of mixtures risk assessment. A potential unifying approach to characterizing mode of action involves critical evaluation of data at all levels of biological organization for identification of ‘key events’. Development of a biologically plausible weight of evidence description of the key obligatory steps in mechanistic pathways may facilitate selection of the most appropriate component-based mixtures risk assessment approach. Hypothetical case studies are presented to demonstrate the quantitative impact of the choice of dose addition or response addition to estimate risk. [Copyright &y& Elsevier]