Persistence and Enrichment of Dominant T Cell Clonotypes in Expanded Tumor-Infiltrating Lymphocytes of Breast Cancer

Research Report: Dominance and Persistence of T-Cell Clones in Tumor-Infiltrating Lymphocytes during Expansion in Breast Cancer Background Tumor-infiltrating lymphocytes (TILs) are lymphocytes that naturally infiltrate the tumor microenvironment and exhibit reactivity to the tumor. This subject is one of the most actively researched areas in tumor ...

Autoimmune Conditions and Gastric Cancer Risk in a Population-Based Study in the United Kingdom

The Relationship Between Autoimmune Diseases and Gastric Cancer Risk in the British Population Background Introduction Despite the overall incidence of gastric cancer has declined over the past few decades, the incidence of gastric cancer among young people in some Western countries has increased in recent years. This trend may be related to the in...

Comprehensive Genomic and Transcriptomic Characterization of High-Grade Gastro-Entero-Pancreatic Neoplasms

Comprehensive Genomic and Transcriptomic Characterization of High-Grade Gastro-Entero-Pancreatic Neoplasms

Research Report on Comprehensive Genomic and Transcriptomic Characteristics of High-Grade Gastro-Entero-Pancreatic Neuroendocrine Tumors Research Background High-grade gastro-entero-pancreatic neuroendocrine neoplasms (HG GEP-NENs) are a heterogeneous group of malignant tumors characterized by neuroendocrine differentiation. According to WHO 2019 [...

Outdoor Air Pollution and Risk of Incident Adult Haematologic Cancer Subtypes in a Large US Prospective Cohort

A Large Prospective Cohort Study in the United States Reveals Potential Links Between Outdoor Air Pollution and Subtypes of Adult Hematologic Cancers Background and Purpose In recent years, the impact of outdoor air pollution on human health has garnered extensive attention. Since 2013, the International Agency for Research on Cancer (IARC) has cla...

Improving the Segmentation of Pediatric Low-Grade Gliomas through Multitask Learning

Improved Segmentation of Pediatric Low-Grade Gliomas Through Multitask Learning Background Introduction The segmentation of pediatric brain tumors is a critical task in tumor volume analysis and artificial intelligence algorithms. However, this process is time-consuming and requires the expertise of neuroradiologists. Although significant research ...

Prediction of Glioma Grade Using Intratumoral and Peritumoral Radiomic Features from Multiparametric MRI Images

“Prediction of Glioma Grades Based on Radiomic Features Inside and Outside Tumors Using Multiparametric MRI Images” Research Background Glioma is the most common primary brain tumor in the central nervous system, accounting for 80% of adult malignant brain tumors. In clinical practice, treatment decisions often require individualized adjustments ba...

Self-Attention Similarity Guided Graph Convolutional Network for Multi-type Lower-Grade Glioma Classification Research

Self-Attention Similarity Guided Graph Convolutional Network for Multi-type Lower-Grade Glioma Classification Research

Graph Convolutional Network Based on Self-Attention Similarity for Multi-type Low-Grade Glioma Classification 1. Research Background Low-grade glioma is a common malignant brain tumor caused by the cancerous transformation of glial cells in the brain and spinal cord. Gliomas are characterized by high incidence, high recurrence rate, high mortality ...

AI-Powered Radiomics Algorithm Based on Slice Pooling for the Glioma Grading

AI-Powered Radiomics Algorithm Based on Slice Pooling for the Glioma Grading

AI-Assisted Radiomics Algorithm for Glioma Grading Based on Slice Pooling Background Introduction Glioma is the most common and threatening tumor in the central nervous system, characterized by high incidence, high recurrence rates, high mortality, and low cure rates. The World Health Organization (WHO) classifies gliomas into four grades (I, II, I...

Gliomas Disease Prediction: An Optimized Ensemble Machine Learning-Based Approach

Glioma Disease Prediction Based on Optimized Integrated Machine Learning Background and Research Objectives In medical research, gliomas are the most common type of primary brain tumors, encompassing various cancer types with different clinical behaviors and treatment outcomes. Accurate prognosis prediction for glioma patients is crucial for optimi...

Noninvasive Grading of Glioma by Knowledge Distillation Based Lightweight Convolutional Neural Network

Review of Non-Invasive Glioma Grading Research: Lightweight Convolutional Neural Networks Based on Knowledge Distillation Background Gliomas are the main tumors of the central nervous system, and early detection is crucial. The World Health Organization (WHO) classifies gliomas from grade I to IV, with grades I and II being low-grade gliomas (LGG) ...