Retaining natural vegetation to safeguard biodiversity and humanity.

Global efforts to deliver internationally agreed goals to reduce carbon emissions, halt biodiversity loss, and retain essential ecosystem services have been poorly integrated. These goals rely in part on preserving natural (e.g., native, largely unmodified) and seminatural (e.g., low intensity or sustainable human use) forests, woodlands, and grasslands. To show how to unify these goals, we empirically derived spatially explicit, quantitative, area-based targets for the retention of natural and seminatural (e.g., native) terrestrial vegetation worldwide. We used a 250-m-resolution map of natural and seminatural vegetation cover and, from this, selected areas identified under different international agreements as being important for achieving global biodiversity, carbon, soil, and water targets. At least 67 million km2 of Earth's terrestrial vegetation (∼79% of the area of vegetation remaining) required retention to contribute to biodiversity, climate, soil, and freshwater conservation objectives under 4 United Nations' resolutions. This equates to retaining natural and seminatural vegetation across at least 50% of the total terrestrial (excluding Antarctica) surface of Earth. Retention efforts could contribute to multiple goals simultaneously, especially where natural and seminatural vegetation can be managed to achieve cobenefits for biodiversity, carbon storage, and ecosystem service provision. Such management can and should co-occur and be driven by people who live in and rely on places where natural and sustainably managed vegetation remains in situ and must be complemented by restoration and appropriate management of more human-modified environments if global goals are to be realized.

Retención de la vegetación natural para salvaguardar la biodiversidad y la humanidad Resumen Hoy en día hay muy poca integración de los esfuerzos mundiales para alcanzar los objetivos internacionales de reducción de las emisiones de carbono, impedimento de la pérdida de biodiversidad y conservación de los servicios ambientales esenciales. Estos objetivos dependen parcialmente de la conservación de los bosques, selvas y praderas naturales (por ejemplo, nativos y en su mayoría sin alteraciones) y seminaturales (por ejemplo, de uso humano sostenible o de baja intensidad). Obtuvimos de manera empírica objetivos espacialmente explícitos, cuantitativos y basados en áreas para la conservación de la vegetación terrestre natural y seminatural (por ejemplo, nativa) en todo el mundo para mostrar cómo unificar los objetivos internacionales. Usamos un mapa de 250 m de resolución de la cubierta vegetal natural y seminatural y, a partir de él, seleccionamos las áreas identificadas como importantes en diferentes acuerdos internacionales para alcanzar los objetivos globales de biodiversidad, carbono, suelo y agua. Al menos 67 millones de km2 de la vegetación terrestre de la Tierra (∼79% de la superficie de vegetación restante) requieren ser conservados para contribuir a los objetivos de conservación de la biodiversidad, el clima, el suelo y el agua dulce en virtud de cuatro de las resoluciones de las Naciones Unidas. Esto equivale a conservar la vegetación natural y seminatural en al menos el 50% de la superficie terrestre total de la Tierra (sin contar a la Antártida). Los esfuerzos de retención podrían contribuir a alcanzar múltiples objetivos simultáneamente, especialmente en donde la vegetación natural y seminatural puede gestionarse para lograr beneficios colaterales para la biodiversidad, el almacenamiento de carbono y la provisión de servicios ambientales. Esta gestión puede y debe ser impulsada y llevada a cabo por las personas que viven en y dependen de los lugares donde la vegetación natural y gestionada de forma sostenible permanece in situ y debe complementarse con la restauración y la gestión adecuada de entornos modificados por el hombre si se quieren alcanzar los objetivos globales.

Predicting nonlinear relationships between external and internal concentrations with physiologically based pharmacokinetic modeling.

Although external concentrations are more readily quantified and often used as the metric for regulating and mitigating exposures to environmental chemicals, the toxicological response to an environmental chemical is more directly related to its internal concentrations than the external concentration. The processes of absorption, distribution, metabolism, and excretion (ADME) determine the quantitative relationship between the external and internal concentrations, and these processes are often susceptible to saturation at high concentrations, which can lead to nonlinear changes in internal concentrations that deviate from proportionality. Using generic physiologically-based pharmacokinetic (PBPK) models, we explored how saturable absorption or clearance influence the shape of the internal to external concentration (IEC) relationship. We used the models for hypothetical chemicals to show how differences in kinetic parameters can impact the shape of an IEC relationship; and models for styrene and caffeine to explore how exposure route, frequency, and duration impact the IEC relationships in rat and human exposures. We also analyzed available plasma concentration data for 2,4-dichlorophenoxyacetic acid to demonstrate how a PBPK modeling approach can be an alternative to common statistical methods for analyzing dose proportionality. A PBPK modeling approach can be a valuable tool used in the early stages of a chemical safety assessment program to optimize the design of longer-term animal toxicity studies or to interpret study results.

Epidemiology and variability in management of acute mastoiditis in children.

BACKGROUND: To evaluate the epidemiology, management and outcome of acute mastoiditis (AM) in children and to improve strategies for antimicrobial stewardship. METHODS: We conducted a retrospective observational study of children aged >6 months to ≤18 years of age admitted to a tertiary care hospital with AM over an 8-year period (2011-2019). Electronic medical records were reviewed to collect data. RESULTS: A total of 129 patients met inclusion criteria for AM during this time period. Eighty-one (63 %) were males with 110 (81 %) White and 67 (52 %) non-Hispanic. The median age at presentation was 6.4 years (3-10.1 years). Ear protrusion was associated with reduced odds of having AM with intracranial extension (ICE) (OR 0.307, 95 % CI = 0.107-0.883) whereas presence of headaches and/or neck pain increased the odds of having AM with ICE (OR = 3.96, 95%CI 1.29-12.1). The most common etiologies were Streptococcus pyogenes (n = 23, 19.2 %), Pseudomonas aeruginosa (n = 20, 17 %), and Streptococcus pneumoniae (n = 15, 12.5 %). Empiric antibiotic selection and duration of therapy was highly variable. The most common empiric antibiotic used was intravenous vancomycin with a third generation cephalosporin (n = 45, 34.8 %). Majority completed course (n = 92; 73 %) with an oral antibiotic. Shorter (≤10 and ≤14 days) versus longer courses (>10 and >14 days) did not affect readmission rates for AM without ICE. CONCLUSION: There is high variability of treatment of AM in children. Broad spectrum antibiotics, especially vancomycin were used most frequently despite low rates of Methicillin Resistant Staphylococcus aureus. The use of antibiotic stewardship is essential for judicious antibiotic use.

Guiding principles for rewilding.

There has been much recent interest in the concept of rewilding as a tool for nature conservation, but also confusion over the idea, which has limited its utility. We developed a unifying definition and 10 guiding principles for rewilding through a survey of 59 rewilding experts, a summary of key organizations' rewilding visions, and workshops involving over 100 participants from around the world. The guiding principles convey that rewilding exits on a continuum of scale, connectivity, and level of human influence and aims to restore ecosystem structure and functions to achieve a self-sustaining autonomous nature. These principles clarify the concept of rewilding and improve its effectiveness as a tool to achieve global conservation targets, including those of the UN Decade on Ecosystem Restoration and post-2020 Global Biodiversity Framework. Finally, we suggest differences in rewilding perspectives lie largely in the extent to which it is seen as achievable and in specific interventions. An understanding of the context of rewilding projects is the key to success, and careful site-specific interpretations will help achieve the aims of rewilding.

Recientemente ha habido mucho interés por el concepto de retorno a la vida silvestre como herramienta para la conservación de la naturaleza, pero también ha habido confusión por la idea que ha limitado su utilidad. Desarrollamos una definición unificadora y diez principios básicos para el retorno a la vida silvestre por medio de encuestas a 59 expertos en retorno a la vida silvestre, un resumen de las visiones de las organizaciones más importantes para el retorno a la vida silvestre y talleres que involucraron a más de 100 participantes de todo el mundo. Los principios básicos transmiten que el retorno a la vida silvestre existe en un continuo de escala, conectividad y nivel de influencia humana y que su objetivo es restaurar la estructura y las funciones del ecosistema para lograr una naturaleza autónoma autosustentable. Estos principios aclaran el concepto del retorno a la vida silvestre e incrementan su efectividad como herramienta para lograr los objetivos mundiales de conservación, incluyendo aquellos de la Década de la ONU para la Restauración de Ecosistemas y el Marco de Trabajo de la Biodiversidad Global post 2020. Finalmente, sugerimos que las diferencias en las perspectivas del retorno a la vida silvestre yacen principalmente en el grado al que es visto como factible y en intervenciones específicas. Un entendimiento del contexto de los proyectos de retorno a la vida silvestre es importante para el éxito, y las interpretaciones específicas de sitio ayudarán a lograr las metas del retorno a la vida silvestre. Principios Básicos para el Retorno a la Vida Silvestre.

In Silico Guidance for In Vitro Androgen and Glucocorticoid Receptor ToxCast Assays.

Molecular initiating events (MIEs) are key events in adverse outcome pathways that link molecular chemistry to target biology. As they are based on chemistry, these interactions are excellent targets for computational chemistry approaches to in silico modeling. In this work, we aim to link ligand chemical structures to MIEs for androgen receptor (AR) and glucocorticoid receptor (GR) binding using ToxCast data. This has been done using an automated computational algorithm to perform maximal common substructure searches on chemical binders for each target from the ToxCast dataset. The models developed show a high level of accuracy, correctly assigning 87.20% of AR binders and 96.81% of GR binders in a 25% test set using holdout cross-validation. The 2D structural alerts developed can be used as in silico models to predict these MIEs and as guidance for in vitro ToxCast assays to confirm hits. These models can target such experimental work, reducing the number of assays to be performed to gain required toxicological insight. Development of these models has also allowed some structural alerts to be identified as predictors for agonist or antagonist behavior at the receptor target. This work represents a first step in using computational methods to guide and target experimental approaches.

Comparative studies of glial fibrillary acidic protein and brain-derived neurotrophic factor expression in two transgenic mouse models of Alzheimer's disease.

In Alzheimer's disease (AD) glial fibrillary acidic protein (GFAP) is expressed by reactive astrocytes surrounding ß-amyloid (Aß) plaques, whereas brain-derived neurotrophic factor (BDNF) levels are typically reduced. We compared the expression of GFAP, BDNF, and its precursor proBDNF in the dorsal hippocampus of two transgenic AD mouse models. APPSwe YAC mice expressing the APPSwe transgene on a yeast artificial chromosome (YAC) were assessed at age 4 and 21 months, and APPSwe/PS1dE9 mice co-expressing mutant amyloid precursor protein (APPSwe) and presenilin-1 (PS1dE9) were assessed at age 4 and 9 months. Significantly increased (1.4-fold) GFAP expression was observed in APPSwe YAC c.f. wild-type (Wt) mice aged 21 months, when Aß deposition was first evident in these mice. In APPSwe/PS1dE9 mice aged 4 and 9 months, GFAP expression was significantly increased (1.6- and 3.1-fold, respectively) c.f. Wt mice, and was associated with robust Aß deposition at 9 months. BDNF expression was significantly lower in 4- and 21-month old APPSwe YAC mice (0.8- and 0.6-fold, respectively) c.f. age-matched Wt mice, whereas proBDNF expression was significantly higher (10-fold) in the APPSwe YAC c.f. Wt mice aged 21 months. In APPSwe/PS1dE9 mice aged 4 months, BDNF expression was significantly lower (0.4-fold) c.f. age-matched Wt mice and was equivalent to that in 9-month old mice of both genotypes; proBDNF expression mirrored that of BDNF in this strain. These findings support a role for reactive astrocytes and neuroinflammation, rather than BDNF, in the spatial memory deficits previously reported for APPSwe YAC and APPSwe/PS1dE9 mice.

Identification of differentially expressed genes and networks related to hepatic lipid dysfunction.

A range of chemical exposures that resulted in the specific pathology of hepatic lipid dysfunction in rats were selected from DrugMatrix, a publicly available toxicogenomic database. Raw microarray data collected from these exposures were further analyzed using bioinformatic tools to generate a differentially expressed genes (DEGs) dataset associated with hepatic lipid dysfunction. Further analysis of the DEGs dataset resulted in 324 upregulated genes, and 275 genes that were down regulated. Meanwhile, 36 genes were either up regulated or down regulated in different chemical treatments. All identified genes were uploaded in the web application for Database for Annotation, Visualization and Integrated Discovery (DAVID) for gene ontology enrichments and to identify Kyoto Encyclopedia of Genes and Genome (KEGG) pathways. Some of the identified pathways included glycolysis/gluconeogenesis, steroid hormone biosynthesis, retinol metabolism, and metabolism of xenobiotics by cytochrome P450. The same DEGs dataset was also analyzed using Ingenuity Pathway Analysis (IPA) software. IPA identified several pathways including PXR/RXR activation, Aryl hydrocarbon receptor signaling, and xenobiotic metabolism signaling. Furthermore, the generated DEGs lists were uploaded into NCATS BioPlanet platform. Some of the identified pathways were related to fatty acid omega oxidation, lipid and lipoprotein metabolism, and adipogenesis. The enrichment and clarification of the pathways and biological networks obtained from the DEGs dataset provide prior knowledge on the underlying biological key events and molecular mechanisms for the computational development of putative adverse outcome pathways (AOPs) for hepatic lipid dysfunction as a precursor to hepatic steatosis.

Progress in data interoperability to support computational toxicology and chemical safety evaluation.

New approach methodologies (NAMs) in chemical safety evaluation are being explored to address the current public health implications of human environmental exposures to chemicals with limited or no data for assessment. For over a decade since a push toward "Toxicity Testing in the 21st Century," the field has focused on massive data generation efforts to inform computational approaches for preliminary hazard identification, adverse outcome pathways that link molecular initiating events and key events to apical outcomes, and high-throughput approaches to risk-based ratios of bioactivity and exposure to inform relative priority and safety assessment. Projects like the interagency Tox21 program and the US EPA ToxCast program have generated dose-response information on thousands of chemicals, identified and aggregated information from legacy systems, and created tools for access and analysis. The resulting information has been used to develop computational models as viable options for regulatory applications. This progress has introduced challenges in data management that are new, but not unique, to toxicology. Some of the key questions require critical thinking and solutions to promote semantic interoperability, including: (1) identification of bioactivity information from NAMs that might be related to a biological process; (2) identification of legacy hazard information that might be related to a key event or apical outcomes of interest; and, (3) integration of these NAM and traditional data for computational modeling and prediction of complex apical outcomes such as carcinogenesis. This work reviews a number of toxicology-related efforts specifically related to bioactivity and toxicological data interoperability based on the goals established by Findable, Accessible, Interoperable, and Reusable (FAIR) Data Principles. These efforts are essential to enable better integration of NAM and traditional toxicology information to support data-driven toxicology applications.

Mode of presentation rather than the 'weekend effect' is a major determinant of in-hospital mortality.

BACKGROUND: The influence of patient demographics and mode of admission on the 'weekend effect' remains unclear. This study examins the relationship between day of admission, patient demographics, mode of presentation and survival. METHODS: Hospital admissions over a three-year period were studied. Patients with an inpatient stay less than 24 h and those who were discharged from the emergency department were excluded. In-hospital mortality was correlated with day of admission, age, gender and mode of presentation in a binary logistical regression analysis. RESULTS: There were 448,827 admissions, of which 350,648 (85.7%) occurred during a weekday. 256,777 (62.7%) were emergency presentations, which was closely related to a weekend admission (92.3% vs 57.8%, p < 0.001). There were 8099 deaths of which 6336 (78.2%) related to a weekday admission and 1736 (21.4%) related a weekend admission. Mortality for elective admissions was 78 (0.05%) compared to 8021 (3.12%), p < 0.001 in emergency admissions. Univariable regression analysis revealed a weekend admission (Odds Ratio (OR) 1.68 (95% confidence interval (CI) 1.60-1.78, p < 0.001) and emergency presentation (OR 63.02 (95%CI 50.42-78.77), p < 0.011) were associated with weekend mortality. On multivariable analysis the OR for weekend admission reduced to 1.07 (95%CI 1.01-1.13), p = 0.013 and the OR for emergency presentation increased to 76.68 (95%CI 61.40-96.00), p < 0.001. CONCLUSION: This study highlights that higher weekend mortality rates are a consequence of a lower proportion of elective admissions. Extending the working week to seven days might reduce weekend mortality without reducing the total number of deaths.

AOP-DB: A database resource for the exploration of Adverse Outcome Pathways through integrated association networks.

The Adverse Outcome Pathway (AOP) framework describes the progression of a toxicity pathway from molecular perturbation to population-level outcome in a series of measurable, mechanistic responses. The controlled, computer-readable vocabulary that defines an AOP has the ability to, automatically and on a large scale, integrate AOP knowledge with publically available sources of biological high-throughput data and its derived associations. To support the discovery and development of putative (existing) and potential AOPs, we introduce the AOP-DB, an exploratory database resource that aggregates association relationships between genes and their related chemicals, diseases, pathways, species orthology information, ontologies, and gene interactions. These associations are mined from publically available annotation databases and are integrated with the AOP information centralized in the AOP-Wiki, allowing for the automatic characterization of both putative and potential AOPs in the context of multiple areas of biological information, referred to here as "biological entities". The AOP-DB acts as a hypothesis-generation tool for the expansion of putative AOPs, as well as the characterization of potential AOPs, through the creation of association networks across these biological entities. Finally, the AOP-DB provides a useful interface between the AOP framework and existing chemical screening and prioritization efforts by the US Environmental Protection Agency.

A Case Study Application of the Aggregate Exposure Pathway (AEP) and Adverse Outcome Pathway (AOP) Frameworks to Facilitate the Integration of Human Health and Ecological End Points for Cumulative Risk Assessment (CRA).

Cumulative risk assessment (CRA) methods promote the use of a conceptual site model (CSM) to apportion exposures and integrate risk from multiple stressors. While CSMs may encompass multiple species, evaluating end points across taxa can be challenging due to data availability and physiological differences among organisms. Adverse outcome pathways (AOPs) describe biological mechanisms leading to adverse outcomes (AOs) by assembling causal pathways with measurable intermediate steps termed key events (KEs), thereby providing a framework for integrating data across species. In this work, we used a case study focused on the perchlorate anion (ClO4-) to highlight the value of the AOP framework for cross-species data integration. Computational models and dose-response data were used to evaluate the effects of ClO4- in 12 species and revealed a dose-response concordance across KEs and taxa. The aggregate exposure pathway (AEP) tracks stressors from sources to the exposures and serves as a complement to the AOP. We discuss how the combined AEP-AOP construct helps to maximize the use of existing data and advances CRA by (1) organizing toxicity and exposure data, (2) providing a mechanistic framework of KEs for integrating data across human health and ecological end points, (3) facilitating cross-species dose-response evaluation, and (4) highlighting data gaps and technical limitations.

Community exposure and vulnerability to water quality and availability: a case study in the mining-affected Pazña Municipality, Lake Poopó Basin, Bolivian Altiplano.

Assessing water sources for drinking and irrigation along with community vulnerability, especially in developing and rural regions, is important for reducing risk posed by poor water quality and limited water availability and accessibility. We present a case study of rural mining-agricultural communities in the Lake Poopó Basin, one of the poorest regions on the Bolivian Altiplano. Here, relatively low rainfall, high evaporation, salinization and unregulated mining activity have contributed to environmental degradation and water issues, which is a situation facing many Altiplano communities. Social data from 72 households and chemical water quality data from 27 surface water and groundwater sites obtained between August 2013 and July 2014 were used to develop locally relevant vulnerability assessment methodologies and ratings with respect to water availability and quality, and Chemical Water Quality Hazard Ratings to assess water quality status. Levels of natural and mining-related contamination in many waters (CWQHR ≥ 6; 78% of assessed sites) mean that effective remediation would be challenging and require substantial investment. Although waters of fair to good chemical quality (CWQHR ≤ 5; 22% of assessed sites) do exist, treatment may still be required depending on use, and access issues remain problematic. There is a need to comply with water quality legislation, improve and maintain basic water supply and storage infrastructure, build and operate water and wastewater treatment plants, and adequately and safely contain and treat mine waste. This study serves as a framework that could be used elsewhere for assessing and mitigating water contamination and availability affecting vulnerable populations.

Adverse Outcome Pathways-Organizing Toxicological Information to Improve Decision Making.

The number of chemicals for which environmental regulatory decisions are required far exceeds the current capacity for toxicity testing. High-throughput screening commonly used for drug discovery has the potential to increase this capacity. The adverse outcome pathway (AOP) concept has emerged as a framework for connecting high-throughput toxicity testing (HTT) and other results to potential impacts on human and wildlife populations. As a result of international efforts, the AOP development process is now well-defined and efforts are underway to broaden the participation through outreach and training. One key principle is that AOPs represent the chemical-agnostic portions of pathways to increase the generalizability of their application from early key events to overt toxicity. The closely related mode of action framework extends the AOP as needed when evaluating the potential risk of a specific chemical. This in turn enables integrated approaches to testing and assessment (IATA), which incorporate results of assays at various levels of biologic organization such as in silico; HTT; chemical-specific aspects including absorption, distribution, metabolism, and excretion (ADME); and an AOP describing the biologic basis of toxicity. Thus, it is envisaged that provision of limited information regarding both the AOP for critical effects and the ADME for any chemical associated with any adverse outcome would allow for the development of IATA and permit more detailed AOP and ADME research, where higher precision is needed based on the decision context.

Evaluating the Impact of Uncertainties in Clearance and Exposure When Prioritizing Chemicals Screened in High-Throughput Assays.

The toxicity-testing paradigm has evolved to include high-throughput (HT) methods for addressing the increasing need to screen hundreds to thousands of chemicals rapidly. Approaches that involve in vitro screening assays, in silico predictions of exposure concentrations, and pharmacokinetic (PK) characteristics provide the foundation for HT risk prioritization. Underlying uncertainties in predicted exposure concentrations or PK behaviors can significantly influence the prioritization of chemicals, though the impact of such influences is unclear. In the current study, a framework was developed to incorporate absorbed doses, PK properties, and in vitro dose-response data into a PK/pharmacodynamic (PD) model to allow for placement of chemicals into discrete priority bins. Literature-reported or predicted values for clearance rates and absorbed doses were used in the PK/PD model to evaluate the impact of their uncertainties on chemical prioritization. Scenarios using predicted absorbed doses resulted in a larger number of bin misassignments than those scenarios using predicted clearance rates, when comparing to bin placement using literature-reported values. Sensitivity of parameters on the model output of toxicological activity was examined across possible ranges for those parameters to provide insight into how uncertainty in their predicted values might impact uncertainty in activity.

Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework.

Driven by major scientific advances in analytical methods, biomonitoring, computation, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the "systems approaches" used in the biological sciences is a necessary step in this evolution. Here we propose the aggregate exposure pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the adverse outcome pathway (AOP) concept in the toxicological sciences. Aggregate exposure pathways offer an intuitive framework to organize exposure data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathways and adverse outcome pathways, completing the source to outcome continuum for more meaningful integration of exposure assessment and hazard identification. Together, the two frameworks form and inform a decision-making framework with the flexibility for risk-based, hazard-based, or exposure-based decision making.

Adverse outcome pathways: From research to regulation scientific workshop report.

An adverse outcome pathway (AOP) helps to organize existing knowledge on chemical mode of action, starting with a molecular initiating event such as receptor binding, continuing through key events, and ending with an adverse outcome such as reproductive impairment. AOPs can help identify knowledge gaps where more research is needed to understand the underlying mechanisms, aid in chemical hazard characterization, and guide the development of new testing approaches that use fewer or no animals. A September 2014 workshop in Bethesda, Maryland considered how the AOP concept could improve regulatory assessments of chemical toxicity. Scientists from 21 countries, representing industry, academia, regulatory agencies, and special interest groups, attended the workshop, titled Adverse Outcome Pathways: From Research to Regulation. Workshop plenary presentations were followed by breakout sessions that considered regulatory acceptance of AOPs and AOP-based tools, criteria for building confidence in an AOP for regulatory use, and requirements to build quantitative AOPs and AOP networks. Discussions during the closing session emphasized a need to increase transparent and inclusive collaboration, especially with disciplines outside of toxicology. Additionally, to increase impact, working groups should be established to systematically prioritize and develop AOPs. Multiple collaborative projects and follow-up activities resulted from the workshop.

Increasing Scientific Confidence in Adverse Outcome Pathways: Application of Tailored Bradford-Hill Considerations for Evaluating Weight of Evidence.

Systematic consideration of scientific support is a critical element in developing and, ultimately, using adverse outcome pathways (AOPs) for various regulatory applications. Though weight of evidence (WoE) analysis has been proposed as a basis for assessment of the maturity and level of confidence in an AOP, methodologies and tools are still being formalized. The Organization for Economic Co-operation and Development (OECD) Users' Handbook Supplement to the Guidance Document for Developing and Assessing AOPs (OECD 2014a; hereafter referred to as the OECD AOP Handbook) provides tailored Bradford-Hill (BH) considerations for systematic assessment of confidence in a given AOP. These considerations include (1) biological plausibility and (2) empirical support (dose-response, temporality, and incidence) for Key Event Relationships (KERs), and (3) essentiality of key events (KEs). Here, we test the application of these tailored BH considerations and the guidance outlined in the OECD AOP Handbook using a number of case examples to increase experience in more transparently documenting rationales for assigned levels of confidence to KEs and KERs, and to promote consistency in evaluation within and across AOPs. The major lessons learned from experience are documented, and taken together with the case examples, should contribute to better common understanding of the nature and form of documentation required to increase confidence in the application of AOPs for specific uses. Based on the tailored BH considerations and defining questions, a prototype quantitative model for assessing the WoE of an AOP using tools of multi-criteria decision analysis (MCDA) is described. The applicability of the approach is also demonstrated using the case example aromatase inhibition leading to reproductive dysfunction in fish. Following the acquisition of additional experience in the development and assessment of AOPs, further refinement of parameterization of the model through expert elicitation is recommended. Overall, the application of quantitative WoE approaches hold promise to enhance the rigor, transparency and reproducibility for AOP WoE determinations and may play an important role in delineating areas where research would have the greatest impact on improving the overall confidence in the AOP.

Systems Biology and Biomarkers of Early Effects for Occupational Exposure Limit Setting.

In a recent National Research Council document, new strategies for risk assessment were described to enable more accurate and quicker assessments. This report suggested that evaluating individual responses through increased use of bio-monitoring could improve dose-response estimations. Identification of specific biomarkers may be useful for diagnostics or risk prediction as they have the potential to improve exposure assessments. This paper discusses systems biology, biomarkers of effect, and computational toxicology approaches and their relevance to the occupational exposure limit setting process. The systems biology approach evaluates the integration of biological processes and how disruption of these processes by chemicals or other hazards affects disease outcomes. This type of approach could provide information used in delineating the mode of action of the response or toxicity, and may be useful to define the low adverse and no adverse effect levels. Biomarkers of effect are changes measured in biological systems and are considered to be preclinical in nature. Advances in computational methods and experimental -omics methods that allow the simultaneous measurement of families of macromolecules such as DNA, RNA, and proteins in a single analysis have made these systems approaches feasible for broad application. The utility of the information for risk assessments from -omics approaches has shown promise and can provide information on mode of action and dose-response relationships. As these techniques evolve, estimation of internal dose and response biomarkers will be a critical test of these new technologies for application in risk assessment strategies. While proof of concept studies have been conducted that provide evidence of their value, challenges with standardization and harmonization still need to be overcome before these methods are used routinely.

Variations in DNA elucidate molecular networks that cause disease.

Identifying variations in DNA that increase susceptibility to disease is one of the primary aims of genetic studies using a forward genetics approach. However, identification of disease-susceptibility genes by means of such studies provides limited functional information on how genes lead to disease. In fact, in most cases there is an absence of functional information altogether, preventing a definitive identification of the susceptibility gene or genes. Here we develop an alternative to the classic forward genetics approach for dissecting complex disease traits where, instead of identifying susceptibility genes directly affected by variations in DNA, we identify gene networks that are perturbed by susceptibility loci and that in turn lead to disease. Application of this method to liver and adipose gene expression data generated from a segregating mouse population results in the identification of a macrophage-enriched network supported as having a causal relationship with disease traits associated with metabolic syndrome. Three genes in this network, lipoprotein lipase (Lpl), lactamase beta (Lactb) and protein phosphatase 1-like (Ppm1l), are validated as previously unknown obesity genes, strengthening the association between this network and metabolic disease traits. Our analysis provides direct experimental support that complex traits such as obesity are emergent properties of molecular networks that are modulated by complex genetic loci and environmental factors.

Comparative studies using the Morris water maze to assess spatial memory deficits in two transgenic mouse models of Alzheimer's disease.

Evaluation of the efficacy of novel therapeutics for potential treatment of Alzheimer's disease (AD) requires an animal model that develops age-related cognitive deficits reproducibly between independent groups of investigators. Herein we assessed comparative temporal changes in spatial memory function in two commercially available transgenic mouse models of AD using the Morris water maze (MWM), incorporating both visible and hidden platform training. Individual cohorts of cDNA-based 'line 85'-derived double-transgenic mice coexpressing the 'Swedish' mutation of amyloid precursor protein (APPSwe) and the presenillin 1 (PS1) 'dE9' mutation were assessed in the MWM at mean ages of 3.6, 9.3 and 14.8 months. We found significant deficits in spatial memory retention in APPSwe/PS1dE9 mice aged 3.6 months and robust deficits in spatial memory acquisition and retention in APPSwe/PS1dE9 mice aged 9.3 months, with a further significant decline by age 14.8 months. ß-Amyloid deposits were present in brain sections by 7.25 months of age. In contrast, MWM studies with individual cohorts (aged 4-21 months) of single-transgenic genomic-based APPSwe mice expressing APPSwe on a yeast artificial chromosomal (YAC) construct showed no significant deficits in spatial memory acquisition until 21 months of age. There were no significant deficits in spatial memory retention up to 21 months of age and ß-amyloid deposits were not present in brain sections up to 24 months of age. These data, generated using comprehensive study designs, show that APPSwe/PS1dE9 but not APPSwe YAC mice appear to provide a suitably robust model of AD for efficacy assessment of novel AD treatments in development.