Dendritic-cell-targeting Virus-like Particles as Potent mRNA Vaccine Carriers Introduction In vaccine development, especially mRNA vaccines, significant achievements have been made in recent years. The mRNA vaccines developed by Moderna and Pfizer/BioNTech against COVID-19 have set a successful precedent, greatly advancing the development of mRNA v...

Bilingual Speech Neuroprosthesis Driven by Cortical Speech Representations Background In the development of neuroprostheses, research on decoding language from brain activity has primarily focused on decoding a single language. Thus, the extent to which bilingual speech production relies on unique or shared cortical activity between different langu...

The Application of Antibodies Displaying Extracellular Vesicles in Targeted Cancer Therapy Extracellular Vesicles (EVs) have been extensively researched as natural delivery carriers and mediators of biological signals in various tissues. In this study, researchers utilized these characteristics of EVs to demonstrate a modular delivery system for ca...

Academic News Report: New MRI Technology Achieves Biological Fluorescence Imaging by Detecting Local Hemodynamics of Photosensitive Blood Vessels Academic Background Introduction Bioluminescent probes are widely used for monitoring biomedical processes and cellular targets in living animals. However, the absorption and scattering of visible light b...

Spatial Multi-omics High Throughput In Situ Pairwise Sequencing at Subcellular Resolution Research Background and Objectives With the continuous advancement in biomedical research, the application of multi-omics technologies in understanding cell functions and disease mechanisms has gained increasing attention. However, many current in situ sequenc...

StrokeClassifier: An AI Tool for Etiological Classification of Ischemic Stroke Based on Electronic Health Records Project Background and Motivation Identifying the etiology of strokes, particularly acute ischemic stroke (AIS), is crucial for secondary prevention, but it is often very challenging. In the United States, there are nearly 676,000 new c...

Insights into the Association Between Sleep and Mortality Revealed by Self-supervised Learning of Wrist-worn Accelerometer Data In modern society, sleep is an essential basic activity for life, and its importance is self-evident. Accurately measuring and classifying sleep/wake states and different sleep stages is crucial for diagnosing sleep disord...

Development and Validation of Large-Scale Machine Learning Algorithms for Cardiovascular Diagnosis Based on Electrocardiograms Introduction Cardiovascular diseases (CV) have long been a major source of global disease burden. Early diagnosis and intervention are crucial for reducing complications, healthcare utilization, and associated costs. Tradit...

Impact of Deep Learning Sepsis Prediction Model on Nursing Quality and Patient Survival Research Background Sepsis is a systemic inflammatory response caused by infection, affecting approximately 48 million people globally each year, with around 11 million deaths. Due to the heterogeneity of sepsis, early identification often faces significant chal...

Using Large Language Models to Identify Social Determinants of Health from Electronic Health Records Background and Research Motivation Social Determinants of Health (SDOH) have a significant impact on patient health outcomes. However, these factors are often incompletely recorded or missing in the structured data of Electronic Health Records (EHR)...