Routine CSF parameters as predictors of disease course in multiple sclerosis: an MSBase cohort study

Research Report: Predictive Role of Cerebrospinal Fluid Routine Parameters in the Disease Process of Multiple Sclerosis Background Multiple Sclerosis (MS) is characterized by a highly variable and unpredictable disease course. In the diagnosis of MS, cerebrospinal fluid (CSF) analysis is often a standard procedure. However, there has been ongoing d...

Extent of Resection Thresholds in Molecular Subgroups of Newly Diagnosed Isocitrate Dehydrogenase–Wildtype Glioblastoma

Extent of Resection Thresholds in Molecular Subgroups of Newly Diagnosed Isocitrate Dehydrogenase–Wildtype Glioblastoma

Study on the Extent of Resection Threshold in Different Molecular Subtypes of Newly Diagnosed IDH-wildtype Glioblastoma Introduction Glioblastoma (GBM) is the most common malignant brain tumor in adults. Although surgical resection, radiotherapy, and chemotherapy are the current standard treatment regimens, the prognosis of GBM remains poor, with a...

Scalp nerve block alleviates headaches associated with sonication during transcranial magnetic resonance–guided focused ultrasound

In this academic paper, the authors attempt to address the common headache complication during magnetic resonance-guided focused ultrasound (mrgFUS) treatment. Headache is a common complication, and in severe cases, it may even cause patients to be unable to tolerate ultrasound radiation and terminate the treatment. There is currently no establishe...

Targeting PRMT9-mediated arginine methylation suppresses cancer stem cell maintenance and elicits CGAS-mediated anticancer immunity

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...

A 5' UTR Language Model for Decoding Untranslated Regions of mRNA and Function Predictions

A 5' UTR Language Model for Decoding Untranslated Regions of mRNA and Function Predictions

The 5’ untranslated region (5’UTR) is a regulatory region at the start of messenger RNA (mRNA) molecules, playing a crucial role in regulating the translation process and affecting protein expression levels. Language models have demonstrated effectiveness in decoding protein and genomic sequence functions. In this study, the authors introduce a lan...

Sarcoma microenvironment cell states and ecosystems are associated with prognosis and predict response to immunotherapy

Sarcoma microenvironment cell states and ecosystems are associated with prognosis and predict response to immunotherapy

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...

Targeting TGFβ-activated kinase-1 activation in microglia reduces CAR T immune effector cell-associated neurotoxicity syndrome

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...

Targeted Activation of Ferroptosis in Colorectal Cancer via LGR4 Targeting Overcomes Acquired Drug Resistance

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...

Identification of a clinically efficacious CAR T cell subset in diffuse large B cell lymphoma by dynamic multidimensional single-cell profiling

Identification of a clinically efficacious CAR T cell subset in diffuse large B cell lymphoma by dynamic multidimensional single-cell profiling

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...

Hyperbolic secant representation of the logistic function: Application to probabilistic multiple instance learning for CT intracranial hemorrhage detection

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...