AI-powered research to advance understanding of radiation exposure risks

Principal investigator Animesh Ray, professor of systems biology and genomics who has been with KGI since 2001, leads a team using artificial intelligence to study the effects of low-dose radiation on humans. The ultimate goal is that this work might help create and establish a policy standard for what is considered a safe limit of low-level radiation exposure.

For example, Ray and his team are interested in the effects of low-dose radiation on cancer treatment.

"Research shows that if you expose a single cell to radiation, its effect travels outside the cell. The irradiated cells can influence normal cells not exposed to radiation, and sometimes these unirradiated cells even respond as if the cell was directly hit by the radiation," Ray says. "The DNA gets modified and damaged from this. Although sometimes it can be repaired properly, other times it can die or mutate to potentially cause cancer. Then, while trying to remove the cancer with radiation, it could make new cancer. We call this the bystander effect, where unirradiated cells getting information from irradiated cells may produce these negative effects. This is what we want to study."

A team of scientists led by Dr. Kumkum Ganguly at Los Alamos National Laboratory, KGI's partner on the project, will produce the irradiated cells to be studied by KGI's research team using single-cell RNA sequence analysis.

The KGI team, composed of current students and postdoctoral researchers, will analyze the data using novel artificial intelligence techniques.

"The grant is not for solving a problem but for understanding a problem," Animesh says. "The standard for the amount of radiation people can be exposed to came from studies done decades ago, but the work to figure out how low dose radiation produces biological effects has been difficult and long overdue since the human genome revolution began."

Source:

Keck Graduate Institute