Conditionally induced RAGE expression by proximal airway epithelial cells in transgenic mice causes lung inflammation.

BACKGROUND: Receptors for advanced glycation end-products (RAGE) are multiligand cell-surface receptors expressed abundantly by distal pulmonary epithelium. Our lab has discovered RAGE-mediated effects in the orchestration of lung inflammation induced by tobacco smoke and environmental pollutants; however, the specific contribution of RAGE to the progression of proximal airway inflammation is still inadequately characterized. METHODS AND RESULTS: We generated a Tet-inducible transgenic mouse that conditionally overexpressed RAGE using the club cell (Clara) secretory protein (CCSP) promoter expressed by club (Clara) cells localized to the proximal airway. RAGE was induced for 40 days from weaning (20 days of age) until sacrifice date at 60 days. Immunohistochemistry, immunoblotting, and qPCR revealed significant RAGE up-regulation when compared to non-transgenic controls; however, H&E staining revealed no detectible morphological abnormalities and apoptosis was not enhanced during the 40 days of augmentation. Freshly procured bronchoalveolar lavage fluid (BALF) from CCSP-RAGE TG mice had significantly more total leukocytes and PMNs compared to age-matched control littermates. Furthermore, CCSP-RAGE TG mice expressed significantly more tumor necrosis factor alpha (TNF-α), interleukin 7 (IL-7), and interleukin 14 (IL-14) in whole lung homogenates compared to controls. CONCLUSIONS: These data support the concept that RAGE up-regulation specifically in lung airways may function in the progression of proximal airway inflammation.

Does image quality matter? Impact of resolution and noise on mammographic task performance.

The purpose of this study was to examine the effects of different resolution and noise levels on task performance in digital mammography. This study created an image set with images at three different resolution levels, corresponding to three digital display devices, and three different noise levels, with noise magnitudes similar to full clinical dose, half clinical dose, and quarter clinical dose. The images were read by five experienced breast imaging radiologists. The data were then analyzed to compute two accuracy statistics (overall classification accuracy and lesion detection accuracy) and performance at four diagnostic tasks (detection of microcalcifications, benign masses, malignant masses, and discrimination of benign and malignant masses). Human observer results showed decreasing display resolution had little effect on overall classification accuracy and individual diagnostic task performance, but increasing noise caused overall classification accuracy to decrease by a statistically significant 21% as the breast dose went to one quarter of its normal clinical value. The noise effects were most prominent for the tasks of microcalcification detection and mass discrimination. When the noise changed from full clinical dose to quarter clinical dose, the microcalcification detection performance fell from 89% to 67% and the mass discrimination performance decreased from 93% to 79%, while malignant mass detection performance remained relatively constant with values of 88% and 84%, respectively. As a secondary aim, the image set was also analyzed by two observer models to examine whether their performance was similar to humans. Observer models differed from human observers and each other in their sensitivity to resolution degradation and noise. The primary conclusions of this study suggest that quantum noise appears to be the dominant image quality factor in digital mammography, affecting radiologist performance much more profoundly than display resolution.