New Diagnostic Tool Help Detect Radiation Sickness

Sep, 2020 - By SMI

Radiation sickness is the damage to the body that often results in excessive amounts of radiation in a short period.

The research team from Ohio State University has developed a new diagnostic tool that may help reduce the time required to detect radiation sickness by measuring biomarkers through a single drop of blood. According to the researchers, a new diagnostic tool has the potential to quickly detect radiation sickness and could help save lives through early identification. Moreover, technology can help health workers to identify people who need immediate treatment. Radiation sickness is the damage to the body that often results in excessive amounts of radiation in a short period.

The amount of radiation absorbed by the body determines how sick an individual will be. It is also known as radiation poisoning or acute radiation syndrome (ARS). Symptoms of radiation sickness may include hair loss, fever, diarrhea, dehydration, sloughing of skin, open sores on the skin, skin burns, confusion, fainting, fatigue, weakness, and bleeding from the mouth, nose, and gums. It is important to determine the degree of radiation exposure to triage the patient's treatment, although it currently takes around 3 to 4 days to determine the exposure through a dysentery chromosomal assay.

Now, the researchers have found a promising way by focusing on a pair of biomarkers (microRNA). One of these, microRNA-150, was shown to be a reliable biomarker of the degree of bone marrow damage through previous research, a reduction in numbers as a result of radiation exposure. Whereas, microRNA-23a, the second molecule remains unchanged in this process. This allows researchers to quantify the risk to the patient and the radiation absorbed during an event. The new tool can prove to be very valuable in emergency response. Moreover, the team envisions that with further work it can also be used in the treatment of cancer, where patients are often exposed to radiation therapy. The research was published in the Science Translational Medicine journal.