Workshop to identify critical windows of exposure for children's health: immune and respiratory systems work group summary.

Fetuses, infants, and juveniles (preadults) should not be considered simply "small adults" when it comes to toxicological risk. We present specific examples of developmental toxicants that are more toxic to children than to adults, focusing on effects on the immune and respiratory systems. We describe differences in both the pharmacokinetics of the developing immune and respiratory systems as well as changes in target organ sensitivities to toxicants. Differential windows of vulnerability during development are identified in the context of available animal models. We provide specific approaches to directly investigate differential windows of vulnerability. These approaches are based on fundamental developmental biology and the existence of discrete developmental processes within the immune and respiratory systems. The processes are likely to influence differential developmental susceptibility to toxicants, resulting in lifelong toxicological changes. We also provide a template for comparative research. Finally, we discuss the application of these data to risk assessment

Xenbase: a Xenopus biology and genomics resource

Xenbase (www.xenbase.org) is a model organism database integrating a diverse array of biological and genomic data on the frogs, Xenopus laevis and Xenopus (Silurana) tropicalis. Data is collected from other databases, high-throughput screens and the scientific literature and integrated into a number of database modules covering subjects such as community, literature, gene and genomic analysis. Gene pages are automatically assembled from data piped from the Entrez Gene, Gurdon Institute, JGI, Metazome, MGI, OMIM, PubMed, Unigene, Zfin, commercial suppliers and others. These data are then supplemented with in-house annotation. Xenbase has implemented the Gbrowse genome browser and also provides a BLAST service that allows users to specifically search either laevis or tropicalis DNA or protein targets. A table of Xenopus gene synonyms has been implemented and allows the genome, genes, publications and high-throughput gene expression data to be seamlessly integrated with other Xenopus data and to external database resources, making the wealth of developmental and functional data from the frog available to the broader research community

Cold Inactivation of l-Threonine Deaminase from Rhodospirillum rubrum

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66171/1/j.1432-1033.1971.tb01491.x.pd

Pathway-based predictive approaches for non-animal assessment of acute inhalation toxicity

New approaches are needed to assess the effects of inhaled substances on human health. These approaches will be based on mechanisms of toxicity, an understanding of dosimetry, and the use of in silico modeling and in vitro test methods. In order to accelerate wider implementation of such approaches, development of adverse outcome pathways (AOPs) can help identify and address gaps in our understanding of relevant parameters for model input and mechanisms, and optimize non-animal approaches that can be used to investigate key events of toxicity. This paper describes the AOPs and the toolbox of in vitro and in silico models that can be used to assess the key events leading to toxicity following inhalation exposure. Because the optimal testing strategy will vary depending on the substance of interest, here we present a decision tree approach to identify an appropriate non-animal integrated testing strategy that incorporates consideration of a substance's physicochemical properties, relevant mechanisms of toxicity, and available in silico models and in vitro test methods. This decision tree can facilitate standardization of the testing approaches. Case study examples are presented to provide a basis for proof-of-concept testing to illustrate the utility of non-animal approaches to inform hazard identification and risk assessment of humans exposed to inhaled substances

Gene expression profiling and therapeutic interventions in neurodegenerative diseases: a comprehensive study on potentiality and limits

Neurodegenerative diseases are incurable debilitating disorders of the nervous system that affect approximately 30 million people worldwide. Despite profuse efforts attempting to define the molecular mechanisms underlying neurodegeneration, many aspects of these pathologies remain elusive. The novelty of their mechanisms represents a challenge to biology, to their related biomarkers identification and drug discovery. Because of their multifactorial aspects and complexity, gene expression analysis plat- forms have been extensively used to investigate altered pathways during degeneration and to identify potential biomarkers and drug targets

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

Xenbase: gene expression and improved integration

Article deposited according to publisher policy posted on SHERPA/RoMEO, 15/09/2010.YesFunding provided by the Open Access Authors Fund