High-performance speech neuroprosthesis

Prof. Francis R. Willett from the Department of Neurobiology, Stanford University School of Medicine, reported their newly developed BCI device/method for speech neuroprosthesis. They focused on addressing the communication challenges faced by individuals with paralysis, particularly those who can no longer speak due to conditions such as amyotrophic lateral sclerosis (ALS). People with neurological disorders often experience severe speech and motor impairments, including the complete loss of speech (locked-in syndrome). While there have been advancements in brain-computer interfaces (BCIs) that enable individuals to communicate through hand movement activities, speech BCIs have not yet achieved high accuracies for unconstrained communication with large vocabularies.

TIM-3 blockade in diffuse intrinsic pontine glioma models promotes tumor regression and antitumor immune memory

TIM-3 blockade in diffuse intrinsic pontine glioma models promotes tumor regression and antitumor immune memory The scientist Marta M. Alonso from Spain recently reported their finding on the potential of TIM-3 (HAVCR2) in targeting Diffuse Intrinsic Pontine Glioma (DIPG). TIM-3 is highly expressed in DIPGs In this study, researchers investigate the potential of targeting TIM-3, an immune checkpoint molecule, as a therapeutic strategy for Diffuse Intrinsic Pontine Glioma (DIPG), an aggressive brain stem tumor with a high mortality rate.

Combining DINO with Grounded Pre-Training can improve performances in Open-Set Object Detection

Combining DINO with Grounded Pre-Training can improve performances in Open-Set Object Detection Chinese researchers report that combining DINO with Grounded Pre-Training can improve performances in Open-Set Object Detection Grounding DINO, an open-set object detector that utilizes language to detect arbitrary objects with human inputs such as category names or referring expressions. The model builds upon DINO, a transformer-based detector that incorporates multi-level text information through grounded pre-training. The authors introduce a tight fusion solution, which includes a feature enhancer, language-guided query selection, and a cross-modality decoder for effective cross-modality fusion.