fig9

Figure 9. ML-engineered nanozyme system for synergistic anti-tumor ferroptosis/apoptosis therapy. The upper schematic illustrates the ML-driven synthesis and optimization cycle for Fe-Arg-CDs, showing the iterative interaction between experiments and model-guided predictions. The lower table compares predicted (Pre.) and experimental (Exp.) NO release values under different synthesis conditions, with the final optimal parameters highlighted in red. These figures are quoted with permission from Li et al.^[92], Copyright 2024, Wiley-VCH GmbH. ML: Machine learning; CDs: carbon dots; NO: nitric oxide; TCGPR: sequential backward tree-classifier for Gaussian process regression; GSH: glutathione; GSSG: glutathione disulfide; CAT: catalase; ROS: reactive oxygen species; POD: peroxidase; OXD: oxidase; LPO: lipid peroxidation; UST: ultrasonic time.