Machine Learning Guided Discovery of Superoxide Dismutase Nanozymes for Androgenetic Alopecia
October 2022
in “
Nano Letters
”
superoxide dismutase nanozymes androgenetic alopecia SEM TEM EDS imaging ζ-potential free radical scavenging redox potential cellular antioxidant effects in vitro in vivo biocompatibility MnPS3 SOD scanning electron microscopy transmission electron microscopy energy-dispersive X-ray spectroscopy zeta potential antioxidant effects lab tests live tests
TLDR Machine learning identified promising nanozymes for treating hair loss.
The study titled "Machine Learning Guided Discovery of Superoxide Dismutase Nanozymes for Androgenetic Alopecia" explores the use of machine learning to identify nanozymes with superoxide dismutase (SOD)-like activity for treating androgenetic alopecia. The research includes extensive experimental analysis, such as SEM, TEM, and EDS imaging, ζ-potential measurements, and comparisons of free radical scavenging performance. The study also examines the redox potential, cellular antioxidant effects, and both in vitro and in vivo biocompatibility of the identified nanozymes. Results indicate that the scaly MnPS3 nanozymes exhibit promising SOD-like activity and biocompatibility, suggesting potential for therapeutic application in androgenetic alopecia.
