Microphthalmia-associated transcription (MiT) family translocation related renal cell carcinoma (RCC) is an important type of renal cell carcinoma, which was included in the new classification of renal tumors by the World Health Organization (WHO) as an independent subtype in 2016. This type of renal cell carcinoma mainly includes Xp11.2 translocation /TFE3 gene fusions associated with renal cell carcinoma and T (6; 11)(p21; q12)/TFEB gene fusion-associated renal cell carcinoma, which has similar clinical features, histology, immunohistochemistry, and molecular genetics, but is significantly different from other renal cell carcinomas. In this review, the clinicopathology and genetics of MiT family translocation associated renal cell carcinoma were reviewed in order to provide guidance and help to the clinical and pathologic work.

Brain-computer interfaces (BCIs) have become one of the cutting-edge technologies in the world, and have been mainly applicated in medicine. In this article, we sorted out the development history and important scenarios of BCIs in medical application, analyzed the research progress, technology development, clinical transformation and product market through qualitative and quantitative analysis, and looked forward to the future trends. The results showed that the research hotspots included the processing and interpretation of electroencephalogram (EEG) signals, the development and application of machine learning algorithms, and the detection and treatment of neurological diseases. The technological key points included hardware development such as new electrodes, software development such as algorithms for EEG signal processing, and various medical applications such as rehabilitation and training in stroke patients. Currently, several invasive and non-invasive BCIs are in research. The R&D level of BCIs in China and the United State is leading the world, and have approved a number of non-invasive BCIs. In the future, BCIs will be applied to a wider range of medical fields. Related products will develop shift from a single mode to a combined mode. EEG signal acquisition devices will be miniaturized and wireless. The information flow and interaction between brain and machine will give birth to brain-machine fusion intelligence. Last but not least, the safety and ethical issues of BCIs will be taken seriously, and the relevant regulations and standards will be further improved.
Humans ; Brain-Computer Interfaces ; Medicine ; Algorithms ; Artificial Intelligence ; Brain