IntroductionOvarian cancer (OvCa) has the highest mortality rate of all gynecologic tumors and is the fifth leading cause of cancer death among US women (1). It is predominantly confined within the abdominal cavity and, unlike breast, colon, or lung cancer, rarely metastasizes hematogenously. Once an ovarian epithelial cell undergoes neoplastic transformation, it freely disseminates throughout the peritoneal cavity, carried by peritoneal fluid that facilitates attachment to peritoneum and omentum. The omentum is a large fat pad (approximately 12 × 12 cm) located inferior to the stomach and draped over the small bowel. It is the most common metastatic site (80%) for OvCa cells (2) followed by implants on the abdominal peritoneum. Identification of cofactors regulating OvCa cell attachment to omentum and/or peritoneum would have tremendous clinical utility, by enabling identification of cellular or molecular targets that could be pursued therapeutically and thus, enabling blockade of a critical step necessary for OvCa metastasis within the peritoneal cavity.A role for MMPs in OvCa development has been postulated based upon the observation that several members of the MMP family are upregulated during OvCa neoplastic progression (3). When MMPs were first characterized (4), it was hypothesized that their major contribution to cancer development was merely to

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Short-term human exposure concentrations to PM2.5, ultrafine particle counts (particle range: 0.02-1 microm), and carbon monoxide (CO) were investigated at and around a street canyon intersection in Central London, UK. During a four week field campaign, groups of four volunteers collected samples at three timings (morning, lunch, and afternoon), along two different routes (a heavily trafficked route and a backstreet route) via five modes of transport (walking, cycling, bus, car, and taxi). This was followed by an investigation into the determinants of exposure using a regression technique which incorporated the site-specific traffic counts, meteorological variables (wind speed and temperature) and the mode of transport used. The analyses explained 9, 62, and 43% of the variability observed in the exposure concentrations to PM2.5, ultrafine particle counts, and CO in this study, respectively. The mode of transport was a statistically significant determinant of personal exposure to PM2.5, ultrafine particle counts, and CO, and for PM2.5 and ultrafine particle counts it was the most important determinant. Traffic count explained little of the variability in the PM2.5 concentrations, but it had a greater influence on ultrafine particle count and CO concentrations. The analyses showed that temperature had a statistically significant impact on ultrafine particle count and CO concentrations. Wind speed also had a statistically significant effect but smaller. The small proportion in variability explained in PM2.5 by the model compared to the largest proportion in ultrafine particle counts and CO may be due to the effect of long-range transboundary sources, whereas for ultrafine particle counts and CO, local traffic is the main source.