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Antimicrobial peptides (AMPs) with dual intrinsic antibacterial and antioxidative functions have emerged as promising choice to cure infected wound. However, the most widely applied approach to endow AMPs with antioxidative function is to combine with antioxidative moieties, which may affect the spatial structure and physiological stability of AMPs. Herein, a new type of AMPs with inherent desired stability, antibacterial activity, and reactive oxygen species (ROS) scavenging is developed to effectively heal the infected wound. This formulation is in situ formed at wound site by tyrosinase‐triggered oxidation and self‐assembly of lyophilized antimicrobial peptide Trp‐Arg‐Trp‐Arg‐Trp‐Tyr, providing enhanced stability and a fourfold and sevenfold increasement in antibacterial efficiency against E. coli and S. aureus compared to peptide monomers. The antimicrobial peptide is first oxidized and then assembled into nanoparticles. The melanin‐like structure has been demonstrated with efficient antioxidant properties, and the experimental data show that peptide nanoparticles to scavenge superoxide radicals, hydroxyl radicals, and H2O2. In vivo experiments confirmed that peptide nanoparticles effectively heal infected wounds and obviously reduce ROS. Overall, the research provides a new approach to formulating antimicrobial peptides to treat wound with high healing efficiency.

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Although predicting temperature variation is important for designing treatment plans for thermal therapies, research in this area is yet to investigate the applicability of prevalent thermal conduction models, such as the Pennes equation, the thermal wave model of bio-heat transfer, and the dual phase lag (DPL) model. To address this shortcoming, we heated a tissue phantom and ex vivo bovine liver tissues with focused ultrasound (FU), measured the temperature response, and compared the results with those predicted by these models. The findings show that, for a homogeneous-tissue phantom, the initial temperature increase is accurately predicted by the Pennes equation at the onset of FU irradiation, although the prediction deviates from the measured temperature with increasing FU irradiation time. For heterogeneous liver tissues, the predicted response is closer to the measured temperature for the non-Fourier models, especially the DPL model. Furthermore, the DPL model accurately predicts the temperature response in biological tissues because it increases the phase lag, which characterizes microstructural thermal interactions. These findings should help to establish more precise clinical treatment plans for thermal therapies.

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