Polycyclic aromatic hydrocarbons (PAHs) have toxic impacts on humans and ecosystems. One of the most carcinogenic PAHs, benzo(a)pyrene (BaP), is efficiently bound to and transported with atmospheric particles. Laboratory measurements show that particle-bound BaP degrades in a few hours by heterogeneous reaction with ozone, yet field observations indicate BaP persists much longer in the atmosphere, and some previous chemical transport modeling studies have ignored heterogeneous oxidation of BaP to bring model predictions into better agreement with field observations. We attribute this unexplained discrepancy to the shielding of BaP from oxidation by coatings of viscous organic aerosol (OA). Accounting for this OA viscosity-dependent shielding, which varies with temperature and humidity, in a global climate/chemistry model brings model predictions into much better agreement with BaP measurements, and demonstrates stronger long-range transport, greater deposition fluxes, and substantially elevated lung cancer risk from PAHs. Model results indicate that the OA coating is more effective in shielding BaP in the middle/high latitudes compared with the tropics because of differences in OA properties (semisolid when cool/dry vs. liquid-like when warm/humid). Faster chemical degradation of BaP in the tropics leads to higher concentrations of BaP oxidation products over the tropics compared with higher latitudes. This study has profound implications demonstrating that OA strongly modulates the atmospheric persistence of PAHs and their cancer risks.

The National Heart, Lung, and Blood Institute is funding an effort to create a molecular atlas of the developing lung (LungMAP) to serve as a research resource and public education tool. The lung is a complex organ with lengthy development time driven by interactive gene networks and dynamic cross talk among multiple cell types to control and coordinate lineage specification, cell proliferation, differentiation, migration, morphogenesis, and injury repair. A better understanding of the processes that regulate lung development, particularly alveologenesis, will have a significant impact on survival rates for premature infants born with incomplete lung development and will facilitate lung injury repair and regeneration in adults. A consortium of four research centers, a data coordinating center, and a human tissue repository provides high-quality molecular data of developing human and mouse lungs. LungMAP includes mouse and human data for cross correlation of developmental processes across species. LungMAP is generating foundational data and analysis, creating a web portal for presentation of results and public sharing of data sets, establishing a repository of young human lung tissues obtained through organ donor organizations, and developing a comprehensive lung ontology that incorporates the latest findings of the consortium. The LungMAP website ( www.lungmap.net ) currently contains more than 6,000 high-resolution lung images and transcriptomic, proteomic, and lipidomic human and mouse data and provides scientific information to stimulate interest in research careers for young audiences. This paper presents a brief description of research conducted by the consortium, database, and portal development and upcoming features that will enhance the LungMAP experience for a community of users.

Computational fluid dynamics (CFD) models are useful for predicting site-specific dosimetry of airborne materials in the respiratory tract and elucidating the importance of species differences in anatomy, physiology, and breathing patterns. We improved the imaging and model development methods to the point where CFD models for the rat, monkey, and human now encompass airways from the nose or mouth to the lung. A total of 1272, 2172, and 135 pulmonary airways representing 17±7, 19±9, or 9±2 airway generations were included in the rat, monkey and human models, respectively. A CFD/physiologically based pharmacokinetic model previously developed for acrolein was adapted for these anatomically correct extended airway models. Model parameters were obtained from the literature or measured directly. Airflow and acrolein uptake patterns were determined under steady-state inhalation conditions to provide direct comparisons with prior data and nasal-only simulations. Results confirmed that regional uptake was sensitive to airway geometry, airflow rates, acrolein concentrations, air:tissue partition coefficients, tissue thickness, and the maximum rate of metabolism. Nasal extraction efficiencies were predicted to be greatest in the rat, followed by the monkey, and then the human. For both nasal and oral breathing modes in humans, higher uptake rates were predicted for lower tracheobronchial tissues than either the rat or monkey. These extended airway models provide a unique foundation for comparing material transport and site-specific tissue uptake across a significantly greater range of conducting airways in the rat, monkey, and human than prior CFD models.

A complete mode of action human relevance analysis—as distinct from mode of action (MOA) analysis alone—depends on robust information on the animal MOA, as well as systematic comparison of the animal data with corresponding information from humans. In November 2003, the International Life Sciences Institute's Risk Science Institute (ILSI RSI) published a 2-year study using animal and human MOA information to generate a four-part Human Relevance Framework (HRF) for systematic and transparent analysis of MOA data and information. Based mainly on non-DNA-reactive carcinogens, the HRF features a “concordance” analysis of MOA information from both animal and human sources, with a focus on determining the appropriate role for each MOA data set in human risk assessment. With MOA information increasingly available for risk assessment purposes, this article illustrates the further applicability of the HRF for reproductive, developmental, neurologic, and renal endpoints, as well as cancer. Based on qualitative and quantitative MOA considerations, the MOA/human relevance analysis also contributes to identifying data needs and issues essential for the dose-response and exposure assessment steps in the overall risk assessment.