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a b s t r a c tInhaled aerosol dose models play critical roles in medicine, the regulation of air pollutants and basic research. The models fall into several categories: traditional, computational fluid dynamical (CFD), physiologically based pharmacokinetic (PBPK), empirical, semi-empirical, and "reference". Each type of model has its strengths and weaknesses, so multiple models are commonly used for practical applications. Aerosol dose models combine information on aerosol behavior and the anatomy and physiology of exposed human and laboratory animal subjects. Similar models are used for in-vitro studies. Several notable advances have been made in aerosol dose modeling in the past 80 years. The pioneers include Walter Findeisen, who in 1935 published the first traditional model and established the structure of modern models. His model combined aerosol behavior with simplified respiratory tract structures. Ewald Weibel established morphometric techniques for the lung in 1963 that are still used to develop data for modeling today. Advances in scanning techniques have similarly contributed to the knowledge of respiratory tract structure and its use in aerosol dose modeling. Several scientists and research groups have developed and advanced traditional, CFD, and PBPK models. Current issues under study include understanding individual and species differences; examining localized particle deposition; modeling non-ideal aerosols and nanoparticle behavior; linking the regions of the respiratory tract airways from nasal-oral to alveolar; and developing sophisticated supporting software. Although a complete history of inhaled aerosol dose modeling is far too extensive to cover here, selected highlights are described in this paper.

Diabetic cardiomyopathy is related directly to hyperglycemia. Cell death such as apoptosis plays a critical role in cardiac pathogenesis. Whether hyperglycemia induces myocardial apoptosis, leading to diabetic cardiomyopathy, remains unclear. We tested the hypothesis that apoptotic cell death occurs in the diabetic myocardium through mitochondrial cytochrome c-mediated caspase-3 activation pathway. Diabetic mice produced by streptozotocin and H9c2 cardiac myoblast cells exposed to high levels of glucose were used. In the hearts of diabetic mice, apoptotic cell death occurred as detected by terminal deoxynucleotidyl transferasemediated dUTP nick-end labeling (TUNEL) assay. Correspondingly, caspase-3 activation as determined by enzymatic assay and mitochondrial cytochrome c release detected by Western blotting analysis were observed. Supplementation of insulin inhibited diabetesinduced myocardial apoptosis as well as suppressed hyperglycemia. To explore whether apoptosis in diabetic hearts is related directly to hyperglycemia, we exposed cardiac myoblast H9c2 cells to high levels of glucose (22 and 33 mmol/l) in cultures. Apoptotic cell death was detected by TUNEL assay and DAPI nuclear staining. Caspase-3 activation with a concomitant mitochondrial cytochrome c release was also observed. Apoptosis or activation of caspase-3 was not observed in the cultures exposed to the same concentrations of mannitol. Inhibition of caspase-3 with a specific inhibitor, Ac-DEVD-cmk, suppressed apoptosis induced by high levels of glucose. In addition, reactive oxygen species (ROS) generation was detected in the cells exposed to high levels of glucose. These results suggest that hyperglycemia directly induces apoptotic cell death in the myocardium in vivo. Hyperglycemiainduced myocardial apoptosis is mediated, at least in part, by activation of the cytochrome c-activated caspase-3 pathway, which may be triggered by ROS derived from high levels of glucose.

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Interaction detection methods have led to the discovery of thousands of interactions between proteins, and discerning relevance within large-scale data sets is important to present-day biology. Here, a spectral method derived from graph theory was introduced to uncover hidden topological structures (i.e. quasi-cliques and quasi-bipartites) of complicated protein-protein interaction networks. Our analyses suggest that these hidden topological structures consist of biologically relevant functional groups. This result motivates a new method to predict the function of uncharacterized proteins based on the classification of known proteins within topological structures. Using this spectral analysis method, 48 quasi-cliques and six quasi-bipartites were isolated from a network involving 11,855 interactions among 2617 proteins in budding yeast, and 76 uncharacterized proteins were assigned functions.