Glioma represents a dominant primary intracranial malignancy in the central nervous
system. Artificial intelligence that mainly includes machine learning, and deep learning …

In recent years, the development of advanced magnetic resonance imaging (MRI)
technology and machine learning (ML) have created new tools for evaluating treatment …

Developing dynamic and highly sensitive methods for imaging M2‐type tumor‐associated
macrophages (TAMs) is vital for monitoring the tumor progression and assessing the …

The glioma tumor microenvironment (TME), composed of several noncancerous cells and
biomolecules is known for its complexity of cancer-immune system interaction. Given that …

Glioma is a highly malignant brain tumor with a poor survival rate. The involvement of fatty
acid metabolism in glioma was examined to find viable treatment options. The information …

Background JMJD8 has recently been identified as a cancer-related gene, but current
studies provide limited information. We aimed to clarify its roles and the potential …

Although the role of N6‐Methyladenosine (m6A) methylation factors has been established in
multiple cancer types, its involvement in glioblastoma multiforme (GBM) remains limited …

Background: Cluster of differentiation 74 (CD74) is found to be highly involved in the
development of various types of cancers and could affect the activities of infiltrated cells in …

Gliomas are a type of malignant central nervous system tumor with poor prognosis.
Molecular biomarkers of gliomas can predict glioma patient's clinical outcome, but their …

Purpose Glioblastoma (GBM) is the most common and deadly brain tumor. We aimed to
reveal potential prognostic GBM marker genes, elaborate their functions, and build an …