Oxymatrine, also known as ammothamnine or oxysophoridine, is a natural compound isolated from Sophora flavescens (in Chinese, Kushen), and many previous researchers have characterized its anti-inflammatory, anti-fibrotic and anti-tumor properties. However, the underlying anti-tumor immunological mechanism of oxymatrine remains elusive. In this study, we carried out experiments both in vitro and in vivo and investigated the anti-tumor effect of oxymatrine to inhibit the proliferation and migration of melanoma B16 cells, while promoting apoptosis. Oxymatrine upregulated CD4⁺ T, CD8⁺ T and NKT cells, downregulated Treg cells, promoted TNF-α secretion, and successfully modulated the immune microenvironment and ultimately suppressed melanoma development in subcutaneous tumor models established in mice. Evidence from network pharmacology and RNAseq suggested that possible targets of oxymatrine for melanoma treatment included PD-L1 and MYC. We observed oxymatrine inhibited PD-L1 and MYC expression in melanoma cells via qRT-PCR and western blotting analysis, and found MYC potentially regulated PD-L1 to mediate anti-tumor effects. These findings provide insight into the mechanism by which oxymatrine inhibits melanoma and enhances the anti-tumor immune effect. In summary, our study proposes a novel approach to suppress melanoma by targeting the MYC/PD-L1 pathway using oxymatrine, which may develop into a less toxic and more efficient anti-tumor agent for melanoma treatment.

This paper proposes a physically unclonable function (PUF) design method based on a magnetic sensor array, leveraging inherent process variations in sensor manufacturing as an entropy source to generate unique cryptographic keys without requiring additional hardware support. This approach reduces system complexity while enhancing security. A balancing algorithm and reconfigurable strategy are employed to optimize PUF responses and improve stability. Furthermore, a lightweight bidirectional authentication protocol based on the magnetic sensor array PUF is introduced, with formal analysis demonstrating its effectiveness in resisting common security threats, including man-in-the-middle attacks, replay attacks, and brute-force attacks. Experimental results show that the proposed PUF exhibits excellent uniqueness, randomness, and reliability, achieving a randomness of 98% and a reliability of 97.8%. Compared to conventional silicon-based PUFs, this approach offers advantages such as low cost, low power consumption, and high environmental adaptability, providing an efficient and secure identity authentication and data protection solution for resource-constrained IoT devices.