History podcast Continued from Page 5
Grev worked backward from his arrival in Milwaukee to track his movements and the spread of the Flu. She stumbled onto a treasure trove of information in the Naval Base’s old bulletins, archived online. In those papers, she found the first report of an outbreak at the station. “The first couple of patients with the Flu (recorded in Milwaukee) came from that base,” she added.
A doctoral student in applied mathematics has developed an algorithm that will allow heart cell researchers to get their results in minutes, rather than hours. John Jurkiewicz is involved in a partnership between UWM’s Department of Mathematical Sciences and the Advocate Aurora Research Institute. His algorithm can isolate valuable experiment data in a fraction of the time that scientists previously needed to do the work manually.
Christopher Cantwell
Grev and Bischof also pulled in medical historian Micaela Sullivan-Fowler at UW-Madison for a Zoom interview to get her expertise. “She was the glue that put all of our stories together,” Grev recalled. In fact, Cantwell said, one side effect of the class’ virtual environment was that students were eager Christina Grev to interview experts that they might never have thought to contact otherwise. “They interviewed an author (on the west coast) who wrote an article about Milwaukee bars during the pandemic. They said, hey, can we call you and interview you? The virtual format allowed us to expand the scope of who to talk to, because everybody is a Zoom call away right now,” he said. Grev is proud of the finished product, and grateful to both learn about podcasting and about public health in the city. “We’re reliving history in a way,” she said, echoing Cantwell. “Things have changed, but not that much. I loved this class. I think my classmates did a fantastic job.” And with the podcast available in so many places, she added, “It’s like having a piece of history in your pocket.” By Sarah Vickery, College of Letters & Science 6 • IN FOCUS • April, 2021
An algorithm for the heart
The Advocate Aurora lab studies heart cells, using them to measure cardiac cell function, aid in developmental studies and, eventually, help conduct drug testing. Their work involves giving the cells an electric shock and recording what happens. But that’s when things get tricky. It’s difficult to separate the electrical signal of activity across some tissue John Jurkiewicz (called field potential, or FP) from the activity of each individual cell (called action potential, or AP). The frequencies connected to action potential are the valuable ones – a heart cell’s AP can say quite a bit about its activity and health. Before Jurkiewicz created his algorithm, Advocate Aurora lab members had to weed out those valuable signals by hand. It would take an afternoon to parse out one day’s experiment, and they were faced with 1 terabyte of data. “They came to us and said, ‘Can you help?’” says Jurkiewicz, whose faculty advisor is mathematics professor Peter Hinow. “So we came up with an algorithm that can segment this data stream automatically. “It turns out the AP versus FP classification is ‘easy’ for mathematicians to do,” says Jurkiewicz, whose paper on the work was accepted fo the Journal of Electrocardiology. And he made a point to run the algorithm on his consumer-grade laptop so researchers wouldn’t need a supercomputer to use the tool. He also wrote the program in the open source language Python. “We would like to make this as accessible as possible,” Hinow says. By Becky Lang, University Relations
