Proteomic Stratification of Prognosis and Treatment Options for Small Cell Lung Cancer

Proteomic Subtyping of Small Cell Lung Cancer: Analysis of Prognosis and Treatment Strategies Research Background Small Cell Lung Cancer (SCLC) is a highly malignant and heterogeneous cancer characterized by rapid growth, early metastasis, and drug resistance, which limits treatment options and challenges prognostic prediction models. Current genom...

Association of NID2 SNPs with Glioma Risk and Prognosis in the Chinese Population

Association of NID2 SNPs with Glioma Risk and Prognosis in the Chinese Population

Association of NID2 gene single nucleotide polymorphisms with glioma risk and prognosis in Chinese Han population Academic Background Glioma is the most common primary intracranial tumor, characterized by high mortality and poor prognosis. Despite some progress in diagnostic and treatment strategies, conventional therapies have limited improvement ...

Clinically Unfavorable Transcriptome Subtypes of Non-WNT/Non-SHH Medulloblastomas are Associated with a Predominance in Proliferating and Progenitor-Like Cell Subpopulations

Association of Adverse Transcriptomic Subtypes of Non-WNT/Non-SHH Medulloblastoma with the Dominance of Proliferative and Progenitor-like Subpopulations Research Background Medulloblastoma (MB) is one of the most common malignant tumors of the central nervous system in children. Based on molecular characteristics, the medical community typically cl...

Retrospective Study of Claudin 18 Isoform 2 Prevalence and Prognostic Association in Gastric and Gastroesophageal Junction Adenocarcinoma

Research Report on Claudin 18.2 in Gastric Cancer and Gastroesophageal Junction Adenocarcinoma Background Introduction Gastric cancer and gastroesophageal junction (G/GEJ) adenocarcinoma are major global health burdens. It is estimated that in 2020 alone, there were approximately 1.7 million new cases of gastric and esophageal cancers worldwide, wi...

Disease Staging of Alzheimer's Disease Using a CSF-Based Biomarker Model

Research Background and Objectives With over 50 million people worldwide affected by cognitive impairment disorders, this number is expected to double by 2050. Alzheimer’s disease (AD) is the most common form of dementia, characterized by extracellular amyloid-beta (Aβ) plaques and intracellular tau protein aggregates in the brain. Over the past tw...

Genomic Profiling of Small Bowel Adenocarcinoma: A Pooled Analysis from 3 Databases

Overview of Genomics in Small Bowel Adenocarcinoma: A Data Integration Analysis Based on Three Major Databases Background and Significance of the Study Small Bowel Adenocarcinoma (SBA) is a rare tumor, but its incidence has increased in recent years, especially in duodenal adenocarcinoma. Approximately 20% of SBA patients have certain susceptibilit...

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 [...

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...

Glioma Survival Analysis Empowered with Data Engineering—A Survey

Survival Analysis of Glioblastoma Patients: An Overview Empowered by Data Engineering Introduction Glioblastoma is a type of tumor that occurs in glial cells and accounts for 26.7% of all primary brain and central nervous system tumors. Survival analysis of glioblastoma patients is a key task in clinical management due to the heterogeneity of the t...

Analysis of Cerebral CT Based on Supervised Machine Learning as a Predictor of Outcome After Out-of-Hospital Cardiac Arrest

Brain CT Analysis as a Tool for Outcome Prediction after Out-of-Hospital Cardiac Arrest: A Supervised Machine Learning Analysis Research Background Out-of-Hospital Cardiac Arrest (OHCA) is one of the leading causes of death in the Western world, with extremely low survival rates, ranging from 3% to 16%. The neurological and overall outcomes after O...