Natural and artificial enzyme oxygen-generating systems for photodynamic therapy (PDT) are developed for tumor treatment, yet they have fallen short of the desired efficacy. Moreover, both the enzymes and photosensitizers usually need carriers for efficient delivery to tumor sites. Here, a self-cascade-enhanced multimodal tumor therapy is developed by ingeniously integrating self-cascade-enhanced PDT with Zn2+-overloading therapy. Manganese-porphyrin (TCPP-Mn) is chosen both as the photosensitizer and catalase (CAT) mimic, which can be encapsulated within glucose oxidase (GOx). Acid-responsive zeolitic imidazolate framework-8 (ZIF-8) is applied as the carrier for TCPP-Mn@GOx (T@G), attaining TCPP-Mn@GOx@ZIF-8 (T@G@Z). T@G@Z demonstrates robust anti-tumor ability as follows: upon the structural degradation of ZIF-8, GOx can mediate the oxidation of glucose and generate hydrogen peroxide (H2O2); TCPP-Mn can catalyze H2O2 into O2 for self-cascade-enhanced PDT; meanwhile, the released Zn2+ can enhance oxidative stress and induce mitochondrial dysfunction by destroying mitochondrial membrane potential; furthermore, immunotherapy can be activated to resist primary tumor and tumor metastasis. The self-cascade-enhanced T@G@Z exhibited its potential application for further tumor management.

Quinoline-based fibroblast activation protein (FAP) inhibitors (FAPIs) have recently emerged as a focal point in global nuclear medicine, underscored by their promising applications in cancer theranostics and the diagnosis of various nononcological conditions. This review offers an in-depth summary of the existing literature on the evolution and use of FAPI tracers in China, tracing their journey from preclinical to clinical research. Moreover, this review also assesses the diagnostic accuracy of FAPI PET for the most common cancers in China, analyzes its impact on oncologic management paradigms, and investigates the potential of FAP-targeted radionuclide therapy in patients with advanced or metastatic cancer. This review also summarizes studies using FAPI PET for nononcologic disorders in China. Thus, this qualitative overview presents a snapshot of China\'s engagement with FAPI tracers, aiming to guide future research endeavors.

Based on the advantages of revealing the functional status and molecular expression of tumor cells, positron emission tomography (PET) imaging has been performed in numerous types of malignant diseases for diagnosis and monitoring. However, insufficient image quality, the lack of a convincing evaluation tool and intra- and interobserver variation in human work are well-known limitations of nuclear medicine imaging and restrict its clinical application. Artificial intelligence (AI) has gained increasing interest in the field of medical imaging due to its powerful information collection and interpretation ability. The combination of AI and PET imaging potentially provides great assistance to physicians managing patients. Radiomics, an important branch of AI applied in medical imaging, can extract hundreds of abstract mathematical features of images for further analysis. In this review, an overview of the applications of AI in PET imaging is provided, focusing on image enhancement, tumor detection, response and prognosis prediction and correlation analyses with pathology or specific gene mutations in several types of tumors. Our aim is to describe recent clinical applications of AI-based PET imaging in malignant diseases and to focus on the description of possible future developments.

In recent years, the incidence of gynecological malignant tumors during pregnancy has increased, mainly due to the increased number of old age pregnancy. The most common gynecological malignant tumors in pregnancy are cervical cancer, accounting for 71.6%, followed by ovarian malignant tumors, accounting for 7.0%. The incidence of cervical cancer in pregnancy is itself not very high, and the symptoms are easily confused with other diseases in pregnancy. During pregnancy, gynecological examination is limited, and therefore, the rate of misdiagnosis is higher. The treatment of cervical cancer during pregnancy is related to many factors, such as tumor size, pathological type, period of gestation, lymph node involvement, and patients\' willingness to maintain pregnancy. As a reason of these factors, it is difficult to determine the optimal treatment. This article reviews the research progress on the diagnosis and treatment principles of cervical cancer in pregnancy, in order to strike a balance between effective treatment of tumors and protection of fetal health, and avoid delays in treatment and preterm delivery.