The Role of SDCBP in Immunotherapy of Colorectal Cancer

Role of Syndecan Binding Protein (SDCBP) in Regulating Tumor Microenvironment, Tumor Progression, and Anti-PD1 Efficacy in Colorectal Cancer Background In recent years, immunotherapy has brought revolutionary advancements in cancer treatment. However, for colorectal cancer (CRC), anti-programmed cell death 1 (APD1) therapy shows relatively limited ...

Romidepsin Exhibits Anti-Esophageal Squamous Cell Carcinoma Activity Through the DDIT4-mTORC1 Pathway

Romidepsin Exhibits Anti-Esophageal Squamous Cell Carcinoma Activity through DDIT4-mTORC1 Pathway Esophageal squamous cell carcinoma (ESCC) is one of the most common human malignancies globally, with high incidence and mortality rates. Given the limited current treatment options, there is an urgent need to develop new effective therapeutic drugs. I...

Identification of Lineage-Specific Epigenetic Regulators FOXA1 and GRHL2 through Chromatin Accessibility Profiling in Breast Cancer Cell Lines

Identification of Lineage-Specific Epigenetic Regulators FOXA1 and GRHL2 through Chromatin Accessibility Analysis of Breast Cancer Cell Lines Background Breast cancer is a highly heterogeneous disease currently classified clinically based on gene expression patterns, intrinsic molecular subtypes, and the expression of hormone receptors/human epider...

Adeno-Associated Virus-Mediated Trastuzumab Delivery to the Central Nervous System for Human Epidermal Growth Factor Receptor 2+ Brain Metastasis

AAV-Mediated Trastuzumab Delivery to the Central Nervous System for EGFR2-Positive Brain Metastases Introduction In the treatment of breast cancer, tumors that are human epidermal growth factor receptor 2 (HER2) positive exhibit more aggressive characteristics, posing significant challenges for clinical treatment. Since the approval of trastuzumab ...

A Wearable Fluorescence Imaging Device for Intraoperative Identification of Human Brain Tumors

Malignant Glioma (MG) Report Malignant Glioma (MG) is the most common type of primary malignant brain tumor. Surgical resection of MG remains the cornerstone of treatment, and the extent of resection is highly correlated with patient survival. However, it is difficult to distinguish tumor tissue from normal tissue during surgery, which greatly limi...

An Explicit Estimated Baseline Model for Robust Estimation of Fluorophores Using Multiple-Wavelength Excitation Fluorescence Spectroscopy

Research Background Fluorescence spectroscopy is a widely used method for identifying and quantifying fluorescent substances (fluorophores). However, quantifying the fluorophores of interest becomes challenging when the material contains other fluorophores (baseline fluorophores), especially when the emission spectrum of the baseline is not well-de...

Multi-view Spatial-Temporal Graph Convolutional Networks with Domain Generalization for Sleep Stage Classification

Sleep stage classification is crucial for sleep quality assessment and disease diagnosis. However, existing classification methods still face numerous challenges in handling the spatial and temporal features of time-varying multi-channel brain signals, coping with individual differences in biological signals, and model interpretability. Traditional...

A Temporal Dependency Learning CNN with Attention Mechanism for MI-EEG Decoding

MI-EEG Decoding Using a Temporal Dependency Learning Convolutional Neural Network (CNN) Based on Attention Mechanism Research Background and Problem Description Brain-Computer Interface (BCI) systems provide a new way of communicating with computers by real-time translation of brain signals. In recent years, BCI technology has played an important r...

Physics-Informed Deep Learning for Musculoskeletal Modeling: Predicting Muscle Forces and Joint Kinematics from Surface EMG

Musculoskeletal models have been widely used in biomechanical analysis because they can estimate motion variables that are difficult to measure directly in living organisms, such as muscle forces and joint moments. Traditional physics-driven computational musculoskeletal models can explain the dynamic interactions between neural inputs to muscles, ...

Deep Learning-Based Assessment Model for Real-Time Identification of Visual Learners Using Raw EEG

In the current educational environment, understanding students’ learning styles is crucial for improving their learning efficiency. Specifically, the identification of visual learning styles can help teachers and students adopt more effective strategies in the teaching and learning process. Currently, automatic identification of visual learning sty...