ObjectivesGlioma is the most common tumor of the central nervous system. In this review, we outline the immunobiological factors that interact with glioma cells and tumor microenvironment (TME), providing more potential targets for clinical inhibition of glioma development and more directions for glioma treatment.ContentRecent studies have shown that glioma cells secrete a variety of immune regulatory factors and interact with immune cells such as microglial cells, peripheral macrophages, myeloid-derived suppressor cells (MDSCs), and T lymphocytes in the TME. In particular, microglia plays a key role in promoting glioma growth. Infiltrating immune cells induce local production of cytokines, chemokines and growth factors. Further leads to immune escape of malignant gliomas.Summary and OutlookThe complex interaction of tumor cells with the TME has largely contributed to tumor heterogeneity and poor prognosis. We review the immunobiological factors, immune cells and current immunotherapy of gliomas, provide experimental evidence for future research and treatment of gliomas.

This study aimed to explore whether microRNA (miR) 223 affects microglial autophagy by targeting autophagy-related 16-like 1 (ATG16L1) in the kainic acid (KA) model of temporal lobe epilepsy (TLE). The miRNA and mRNA expression levels were quantified using quantitative real-time polymerase chain reaction (qRT-PCR), and the protein expression was investigated using western blotting. A dual-luciferase reporter assay was used to test the direct interaction between miR 223 and ATG16L1. In situ hybridization was performed to measure the hippocampal expression of miR 223. We used immunofluorescence staining to assess the expression of ATG16L1 and microtubule-associated protein light chain 3 (LC3) in the murine hippocampal microglia. Inhibitor of miR 223 was utilized to investigate the role of miR 223 in TLE, and the epileptic activity was assessed using electroencephalography (EEG). The autophagosomes were observed by transmission electron microscopy. In patients with TLE, the murine KA model of TLE, and the KA-stimulated BV2 cells, miR 223, and sequestosome 1 (SQSTM1/P62) expressions were remarkably increased, whereas ATG16L1 and LC3 levels were significantly decreased. Using a dual-luciferase reporter assay, ATG16L1 was determined as a direct target of miR 223. Treatment with antagomir 223 alleviated epilepsy, prevented abnormalities in EEG recordings and increased the ATG16L1 and LC3 levels in KA-treated mice. Inhibition of miR 223 induced increased autophagy in BV2 cells upon Rapamycin stimulation. These findings show that miR 223 affects microglial autophagy via ATG16L1 in the KA model of TLE. The miR 223/ATG16L1 pathway may offer a new treatment option for TLE.

Objective. Epilepsy is one of the most common severe brain disorders. Ultrasound deep brain stimulation (UDBS) has shown a potential capability to suppress seizures. However, because seizures occur sporadically, it is necessary to develop a closed-loop system to suppress them. Therefore, we developed a closed-loop wearable UDBS system that delivers ultrasound to the hippocampus to suppress epileptic seizures. Approach. Mice were intraperitoneally injected with 10 mg kg−1 kainic acid and divided into sham and UDBS groups. Epileptic seizures were detected by applying both long short-term memory (LSTM) and bidirectional LSTM (BILSTM) networks according to EEG signal characteristics. When epileptic seizures were detected, the closed-loop UDBS system automatically activated a trigger switch to stimulate the hippocampus for 10 min and continuously record EEG signals until 20 min after ultrasonic stimulation. EEG signals were analyzed using the MATLAB software. After EEG recording, we observed the survival rate of the experimental mice for 72 h. Main results. The BiLSTM network was found to have preferable classification performance over the LSTM network. The closed-loop UDBS system with BiLSTM could automatically detect epileptic seizures using EEG signals and effectively reduce epileptic EEG power spectral density and seizure duration by 10.73%, eventually improving the survival rate of early epileptic mice from 67.57% in the sham group to 88.89% in the UDBS group. Significance. The closed-loop UDBS system developed in this study could be an effective clinical tool for the control of epilepsy.