One challenge to studying organic molecules is that life is a process. Traditional methods of analyzing cell structures require that scientists isolate cells by freezing them in time, essentially removing them from the context that makes their function uniquely interesting. Klaus Ley, a professor of biomedical engineering at the University of Virginia, is investigating white-bloodcell trafficking in inflammation and atherosclerosis. He and his students once had to mark individual cells by hand. "We burnt too many hours on analyzing data -- hundreds of hours," he said. In addition, students tend to choose cells that "look good" for study, which could provide skewed data about overall cellular function. A camera with image analysis software can track and count white blood cells automatically, saving time and providing more accurate (and less subjective) data than manual analysis. In the mid-1980s, Ley initiated the development of an automated cell-tracking system, but he lacked the technological sophistication to produce a working system. The computers and frame grabbers of that time also could not compute the complicated cross-correlation and coasting-algorithm functions required. He recently found a commercial system that accomplishes these goals: the Cell Motion Tracker from Ed Marcus Laboratories. The automated cell tracker emerged from Marcus' work with Dr. Bill Luscinskas at Brigham & Women's Hospital in Boston. The system digitizes a video signal from a standard microscope camera (in this case a Pulnix TM7 monochrome camera with 4X objective). Computer software completes the motion analysis, recording and analyzing segments in 20-s intervals. "It's more accurate, is less time-consuming and eliminates investigator bias," Ley said. He is working with Marcus to improve the device. One drawback is that it cannot track hidden cells or cells that have moved too close to other cells. Marcus said he has succeeded in splitting clustered cells into separate positions, creating a splitting adjustment that will be standard on next-generation devices. He added that the system could also work in other particle-tracking applications.