Rapid detection of brain tumor cells using memristors for biomedical applications
2025
Longhui Fu | Huangtao Chen | Bai Sun | Zelin Cao | Kaikai Gao | Mengna Wang | Wentao Yan | Kun Wang | Teng Wu | Siyuan Zhang | Shouping Gong | Pengyu Ren
Brain tumors often lead to compression or hemorrhage that can seriously threaten patients' life. However, the rapid detection of brain tumor types has always been a bottleneck technology in the field of neuroscience research. Herein, it is firstly developed a rapid detection method of brain tumor cells by using a memristor with Ag/WO3/Ti structure, aiming to provide an innovative diagnostic tool. Four brain tumor cell lines representing varying degrees of malignancy, including LN-18, SHG44, U251, and U87, were selected. Each tumor cell suspension was loaded onto the memristor surface, which can induce a noticeable change I‒V curves of the device being recorded. Thus, the memristor's resistance states impacted by different cell lines could be used to identify the types of brain tumors. Our results demonstrated that the memristor can rapidly and effectively identify different types of brain tumor cells based on the changes in its resistance states, especially distinguishing between highly invasive brain tumor cells (U251 and U87) and low invasive brain tumor cells (LN-18 and SHG44). These results support a rapid detection for brain tumor cell with promising clinical applications, thus paving the way for optimization of treatment protocols as well as guidance of the surgical process during operation.
Afficher plus [+] Moins [-]Informations bibliographiques
Cette notice bibliographique a été fournie par Directory of Open Access Journals
Découvrez la collection de ce fournisseur de données dans AGRIS
