Correlation between Task Complexity and Accuracy of Cortical Language Mapping Introduction This study aimed to investigate whether task complexity affects the accuracy of mapping language functions during direct cortical stimulation mapping (DCS). The researchers hypothesized that due to the reduced computational ability of neurons in the cortex in...
This study revolves around the protein arginine methyltransferase PRMT9, revealing its important role in acute myeloid leukemia (AML) and its potential as an anticancer target. Researchers found that PRMT9 expression levels were significantly elevated in AML stem cells and leukemic cells. Through gene editing and chemical probes, they discovered th...
This study utilized a machine learning framework to explore the underlying cell states and cellular ecosystems constituting soft tissue sarcomas, and associated them with patient prognosis and response to immunotherapy. Research Background: Soft tissue sarcomas are rare and highly heterogeneous malignancies of connective tissues, with limited syste...
Major Breakthrough in Neuroscience Research: Deep Learning Technique Achieves Decoding of Natural Speech from Brain Signals A cross-disciplinary research team at New York University recently achieved a major breakthrough in the fields of neuroscience and artificial intelligence. They developed a novel deep learning-based framework that can directly...
From early drug discovery researchers face a daunting challenge – to find drug-like candidate molecules among approximately 10^60 possible molecular structures. One successful solution is to start from smaller “fragment” molecules, a strategy known as fragment-based drug design (FBDD). In the FBDD process, the first step is to computationally scree...
In this study, researchers explored the role of the TAK1 activation pathway in CAR T cell therapy-associated immune effector cell-associated neurotoxicity syndrome (ICANS). They established a mouse ICANS model and found that following the transfer of CAR19 T cells, cerebellar cells were activated, underwent morphological changes, and expressed more...
Overcoming Acquired Resistance in Colorectal Cancer by Targeting LGR4 Research Background: Acquired drug resistance is a major obstacle in cancer treatment and a leading cause of cancer-related deaths. However, the mechanisms of resistance are diverse, and how to specifically target resistant cancer cells remains a significant clinical challenge. A...
Utilizing Dynamic Single-Cell Analysis to Discover a Clinically Effective Chimeric Antigen Receptor T-Cell Subset for Treating Diffuse Large B-Cell Lymphoma Research Background Chimeric antigen receptor (CAR) T-cell therapy has been proven to be an effective treatment for B-cell malignancies. However, it remains challenging to predict individual cl...
This is a long-term outcome study on survivors of pediatric glioma. The main purpose of the study was to evaluate the impact of changes in treatment approaches for pediatric glioma over the past few decades on long-term mortality, chronic health conditions, and subsequent tumor risk among survivors. Background: In the past, treatment for pediatric ...
There has long been a problem of “weak supervision” in the field of artificial intelligence, where only part of the labels are observable in the training data, while the remaining labels are unknown. Multiple Instance Learning (MIL) is a paradigm to address this issue. In MIL, the training data is divided into multiple “bags”, each containing multi...