Nanoparticle-based X-ray radiosensitization strategies have garnered significant attention in recent years. However, the underlying mechanisms of radiosensitization remain incompletely understood. In this work, we explore the influence of the K-edge effect in the X-ray absorption of nanomaterials on sensitization. Due to the alignment of the K-edge of thulium (Tm) with the Bremsstrahlung peak in the energy spectrum of medical X-ray accelerators, the following four different rare-earth nanomaterials with varying Tm percentages were designed: NaTmF₄, NaTm_0.6Lu_0.4F₄, NaTm_0.4Lu_0.6F₄, and NaLuF₄. We evaluated the X-ray absorption and the ability to generate secondary electrons and reactive oxygen species (ROS) of these nanoparticles. The radiosensitizing effect was evaluated through clonogenic assays. Our results showed that the K-edge effect affected secondary electron generation but did not significantly change ROS production. Nonetheless, NaTmF₄ induced marginally more DNA damage in the U87 cells than the other cell types. NaTmF₄ also exhibited superior radiosensitization efficacy against the U87 tumor cells. This shows that secondary electrons and ROS play pivotal roles in radiosensitization, which might be crucial to improving cancer treatment efficacy through enhanced radiation therapy outcomes.

In recent years, teaching staff has increased the frequency of application of multimedia teaching equipment in subject teaching. The scientific application of the teaching staff to the database can gain efficiency of teaching for English. According to situation, we describe the role of English teaching. This article uses big data, takes college English teaching as the research object, applies data mining technology, analyses from the teaching environment, faculty, teaching process and students' learning methods, learning motivation, learning time and other factors, statistics of college English learning behaviour data. Combined with questionnaire survey and interview, the validity of the model in learning activities, knowledge acquisition and other aspects are verified. Results show the English teaching model can improve teaching effect under the big data environment.