Chinese researchers have successfully developed a kind of nanoparticles that can achieve accurate cancer detection and treatment, which can significantly reduce the side effects of excessive drug use in cancer detection and treatment. The relevant research results have recently been published in the internationally renowned academic journal "Advanced Materials". Reporters learned from the Institute of Precision Measurement Science and Technology Innovation of the Chinese Academy of Sciences on the 6th that the researcher team of Zhou Xin of the Academy has developed a nano particle GQDNT that can intelligently identify tumors by taking advantage of the difference between tumor microenvironment and normal tissues. By constantly deforming in the tumor, the nanoparticles extend the residence time of drugs in the particles in the tumor, enhance the penetrability of drugs in the tumor, and achieve long-term magnetic resonance imaging detection and efficient treatment of cancer with extremely low drug doses. According to team experts, drug overdose is the main cause of significant side effects in cancer detection and treatment. This is because the existing drugs have insufficient targeting for the lesion, making it difficult to concentrate in the tumor area, and have a short residence time at the lesion site. Therefore, high-dose injection is required to achieve the expected imaging detection and treatment effect. It is reported that GQDNT is a kind of modular self-assembled nanoparticles, which can use very simple steps to encapsulate drug molecules, promote GQDNT deformation through the tumor microenvironment, and gradually increase the concentration of drugs in the focus. Mouse experiments have found that the contrast agent usage of GQDNT in cancer detection is only 6% to 22% of existing clinical techniques. Within 4 to 36 hours after injection, the contrast agent at the tumor site has a high contrast with normal tissue, with clear boundaries, greatly prolonging the magnetic resonance imaging time. (Outlook New Era Network)