Indoor radon trends with building code change in two Canadian cities.

Radon studies were conducted in two Canadian cities, in Halifax, Nova Scotia, and Winnipeg, Manitoba, to evaluate trends in indoor radon before and after the 2010 National Building Code of Canada was adopted into the legally binding provincial building codes in 2011. Participants were recruited in neighbourhoods characterized by newer housing developments. A postcard campaign in each city offered free radon testing to every house in the target areas, and free testing kits were mailed to study participants.

Bioinformatic Workflows for Deriving Transcriptomic Points of Departure: Current status, Data Gaps, and Research Priorities.

There is a pressing need to increase the efficiency and reliability of toxicological safety assessment for protecting human health and the environment. While conventional toxicology tests rely on measuring apical changes in vertebrate models, there is increasing interest in the use of molecular information from animal and in vitro studies to inform safety assessment. One promising and pragmatic application of molecular information involves the derivation of transcriptomic points of departure (tPODs).

Considerations for application of benchmark dose modeling in radiation research: workshop highlights.

Background: Exposure to different forms of ionizing radiation occurs in diverse occupational, medical, and environmental settings. Improving the accuracy of the estimated health risks associated with exposure is therefore, essential for protecting the public, particularly as it relates to chronic low dose exposures. A key aspect to understanding health risks is precise and accurate modeling of the dose-response relationship.

Benchmark dose modeling of transcriptional data: a systematic approach to identify best practices for study designs used in radiation research.

Purpose: Benchmark dose (BMD) modeling is a method commonly used in chemical toxicology to identify the point of departure (POD) from a dose-response curve linked to a health-related outcome. Recently, its application in the analysis of transcriptional data for quantitative adverse outcome pathway (AOP) development is being explored. As AOPs are informed by diverse data types, it is important to understand the impact of study parameters such as dose selection, the number of replicates and dose range on BMD outputs for radiation-induced genes and pathways.

Challenges in the quantification approach to a radiation relevant adverse outcome pathway for lung cancer.

Purpose: Adverse outcome pathways (AOPs) provide a modular framework for describing sequences of biological key events (KEs) and key event relationships (KERs) across levels of biological organization. Empirical evidence across KERs can support construction of quantified AOPs (qAOPs). Using an example AOP of energy deposition from ionizing radiation onto DNA leading to lung cancer incidence, we investigate the feasibility of quantifying data from KERs supported by all types of stressors.

Meta-analysis of transcriptomic datasets using benchmark dose modeling shows value in supporting radiation risk assessment.

Purpose: Benchmark dose (BMD) modeling is used to determine the dose of a stressor at which a predefined increase in any biological effect above background occurs (e.g. 10% increase from control values).

NASA GeneLab Platform Utilized for Biological Response to Space Radiation in Animal Models.

Ionizing radiation from galactic cosmic rays (GCR) is one of the major risk factors that will impact the health of astronauts on extended missions outside the protective effects of the Earth's magnetic field. The NASA GeneLab project has detailed information on radiation exposure using animal models with curated dosimetry information for spaceflight experiments. We analyzed multiple GeneLab omics datasets associated with both ground-based and spaceflight radiation studies that included and approaches.

A case example of a radiation-relevant adverse outcome pathway to lung cancer.

Background: Adverse outcome pathways (AOPs) describe how a measurable sequence of key events, beginning from a molecular initiator, can lead to an adverse outcome of relevance to risk assessment. An AOP is modular by design, comprised of four main components: (1) a Molecular Initiating Event (MIE), (2) Key Events (KEs), (3) Key Event Relationships (KERs) and (4) an Adverse Outcome (AO).

Purpose: Here, we illustrate the utility of the AOP concept through a case example in the field of ionizing radiation, using the Organisation for Economic Cooperation and Development (OECD) Users' Handbook.