The determination of the dose of inhaled aerosol particles in animal subjects is not a trivial exercise. In its simplest form, the dose is the amount (particle number, mass or other relevant metric) that deposits in the respiratory tract. The amount deposited will depend on the aerosol particle sizes (e.g. the aerodynamic diameter size distribution), the duration of exposure, the exposure system's delivery efficiency, the subject's ventilation rate, the species and strain, and other factors. Similarly, species differences in the clearance rates of deposited particles will influence the time integrated particle doses. In practice, particle doses are estimated using mathematical models, previous experimental dosimetry data, tracers of the inhaled particles and biomarkers of exposure. With care, desired aerosol doses can be achieved and documented.

The availability of molecular and genetic tools has made the mouse the most common animal model for a variety of human diseases in toxicology studies. However, little is known about the factors that will influence the dose delivery to murine lungs during an inhalation study. Among these factors are the respiratory tract anatomy, lung physiology, and clearance characteristics. Therefore, the objective of this paper is to briefly review the current knowledge on the aforementioned factors in mice and their implications to the dose delivered to mouse models during inhalation studies. Representative scientific publications were chosen from searches using the NCBI PubMed and ISI Web of Knowledge databases. Relevant respiratory physiological differences have been widely reported for different mouse strains and sexes. The limited data on anatomical morphometry that is available for the murine respiratory tract indicates significant differences between mouse strains. These differences have implications to the dose delivered and the biological outcomes of inhalation studies.

The availability of molecular and genetic tools has made the mouse the most common animal model for a variety of human diseases in toxicology studies. However, little is known about the factors that will influence the dose delivery to murine lungs during an inhalation study. Among these factors are the respiratory tract anatomy, lung physiology, and clearance characteristics. Therefore, the objective of this paper is to briefly review the current knowledge on the aforementioned factors in mice and their implications to the dose delivered to mouse models during inhalation studies. Representative scientific publications were chosen from searches using the NCBI PubMed and ISI Web of Knowledge databases. Relevant respiratory physiological differences have been widely reported for different mouse strains and sexes. The limited data on anatomical morphometry that is available for the murine respiratory tract indicates significant differences between mouse strains. These differences have implications to the dose delivered and the biological outcomes of inhalation studies.

Dosimetry provides information linking environmental exposures to sites of deposition, removal from these sites, and translocation of deposited materials. Dosimetry also aids in extrapolating laboratory animal and in vitro data to humans. Recent progress has shed light on: properties of particles in relation to their fates in the body; influence of age, gender, body size, and lung diseases on inhaled particle doses; particle movement to the brain via the olfactory nerves; and particle deposition hot spots in the respiratory tract. Ultrafine size has emerged as an important dosimetric characteristic. Particle count, composition, and surface properties are recognized as potentially important toxicology-related considerations. Differences in body size influence airway sizes, inhaled particle deposition, specific ventilation, and specific doses (e.g. per unit body mass). Related to body size, age, gender, species, and strain are also dosimetric considerations. Diseases, such as chronic obstructive pulmonary disease (COPD) and bronchitis, produce uneven doses within the respiratory tract. Traditional concepts of the translocation and clearance of deposited particles have been challenged. Ultrafine particles can translocate to the brain via olfactory nerves, and from the lung to other organs. The clearance rates of particles from tracheobronchial airways are slowed by respiratory tract infections, but newer evidence implies that slow particle clearance from this region also exists in healthy lungs. Finally, hot spots of particle deposition are seen in hollow models, lung tissue, and dosimetric simulations. Local doses to groups of epithelial cells can be much greater than those to surrounding cells. The new insights challenge dosimetry scientists.

Several methods are available for exposing laboratory animal models to aerosols, each having its advantages and disadvantages (Table 2.1). Whole-body exposure systems (chambers) have a long history in inhalation toxicology, mainly due to their animal loading capacity and adaptability to several species. Chambers are often unsuitable for use with radioactive, infectious, and other potentially hazardous exposure materials, due to the need for large amounts of exposure material, inefficient delivery of aerosols to animals, multiple routes of exposure (e.g., oral, skin, and eyes), and the external contamination of exposed subjects. Also, chambers are costly, require considerable laboratory space, require expensive air supplies, and are difficult to decontaminate.

Over the past 20 years, the explosion of genomic data collection and the cloud computing revolution have made computational and data science research accessible to anyone with a web browser and an internet connection. However, students at institutions with limited resources have received relatively little exposure to curricula or professional development opportunities that lead to careers in genomic data science. To broaden participation in genomics research, the scientific community needs to support these programs in local education and research at underserved institutions (UIs). These include community colleges, historically Black colleges and universities, Hispanic-serving institutions, and tribal colleges and universities that support ethnically, racially, and socioeconomically underrepresented students in the United States. We have formed the Genomic Data Science Community Network to support students, faculty, and their networks to identify opportunities and broaden access to genomic data science. These opportunities include expanding access to infrastructure and data, providing UI faculty development opportunities, strengthening collaborations among faculty, recognizing UI teaching and research excellence, fostering student awareness, developing modular and open-source resources, expanding course-based undergraduate research experiences (CUREs), building curriculum, supporting student professional development and research, and removing financial barriers through funding programs and collaborator support.