期刊
ACS OMEGA
卷 -, 期 -, 页码 -出版社
AMER CHEMICAL SOC
DOI: 10.1021/acsomega.2c07262
关键词
-
资金
- U.S. Department of Energy Office of Science, Office of Basic Energy Sciences [DE-FC02-04ER15533]
This study explores the application of atmospheric pressure plasma jet (APPJ) in medicine and its damage to DNA, and predicts the type and extent of DNA damage under different parameters based on a machine learning model, providing important insights into the potential adverse effects of APPJ on biological samples.
An atmospheric pressure plasma jet (APPJ) is being advanced as an alternative radiation type that offers excellent efficacy in an array of medical applications against specific biological targets such as DNA. This work explores the possibility of implementing DNA and its damage as a probe for specific plasma diagnostics such as reactive plasma species formation and transient local heating. We analyzed both APPJ characteristics based on the detection of plasma induced strand breaks and DNA denaturation. Further, we implemented a machine learning model based on artificial neural networks to predict the type and extent of DNA damage for a given combination of APPJ parameter values. This methodology is an important step toward deciphering and explaining the potential adverse effects of APPJ on biological samples of any prospective interest in medicine.
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