Lung Cancer

Single‑cell mapping of neutrophil extracellular trap signatures in lung adenocarcinoma reveals immune landscapes, prognostic potential, and therapeutic targets.

Neutrophil extracellular traps (NETs) have emerged as key modulators in the tumor microenvironment, yet their cellular heterogeneity, molecular mechanisms, and clinical relevance in lung adenocarcinoma (LUAD) remain elusive. Here, we performed an integrative single‑cell and multi‑omics dissection of NETs activity across LUAD tissues. Single‑cell transcriptomics revealed that NETs signatures were p...

Deep learning image reconstruction improves 40 keV virtual monoenergetic image quality in rectal cancer.

BACKGROUND: Accurate preoperative evaluation of rectal cancer is essential for staging and treatment planning. Low-energy virtual monoenergetic imaging (VMI) enhances iodine contrast in dual-energy computed tomography (DECT) but increases image noise. Deep learning image reconstruction (DLIR) may mitigate this issue, but its effectiveness for 40 keV VMI in rectal cancer is underexplored. OBJECTIVE...

Artificial intelligence in diagnostic, prognostic, and predictive genomic biomarkers for prostate cancer: Ready for prime time?

INTRODUCTION: Until recently, the widespread use of genetic markers in prostate cancer (PCa) has been limited by the complexities and cost of genomic ...

Anomaly detection in gamma-ray spectra using autoencoders with small form factor CZT detectors.

The detection of weak radioactive sources in fluctuating background environments is a critical task for nuclear security, environmental monitoring, an...

Unraveling the molecular mechanisms of air pollution-induced lung adenocarcinoma through machine learning, network toxicology, and molecular docking.

OBJECTIVE: Airborne environmental contaminants are established carcinogens. This investigation elucidates the mechanistic contributions to pulmonary a...

Pectin from Phyllanthus emblica L.: Structure elucidation and synergistic in vitro anti-stomach adenocarcinoma effects with 5-fluorouracil.

In recent years, polysaccharides with potential anticancer activity have attracted widespread attention. In this study, a homogeneous polysaccharide f...

Diagnostic accuracy of ¹⁸F-FDG PET/CT radiomics for non-invasive prediction of PD-L1 expression in non-small cell lung cancer: A systematic review and meta-analysis.

To evaluate the diagnostic performance, methodological quality, and clinical feasibility of ¹⁸F-FDG PET/CT-based radiomics machine learning models for...

Causal Inference and Prognostic Modeling in Colorectal Cancer through Integration of Computational Pathology and Mendelian Randomization.

BACKGROUND: While traditional pathology supports the diagnosis and staging of colorectal cancer (CRC), computational pathology provides novel prognost...

Proteomic Profiling of Plasma Extracellular Vesicles Combined with Multivariate Modeling Identified Potential Biomarkers for Distinguishing Benign Pulmonary Nodules from Early-Stage Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer and is difficult to distinguish from benign pulmonary nodules (BPNs), particularl...

Ensemble learning-based radiomics model for predicting radiation-induced temporal lobe injury in nasopharyngeal carcinoma.

PURPOSE: To develop and validate a multimodal ensemble machine learning model integrating multi-sequence magnetic resonance imaging (MRI) radiomics, c...

Computed Tomography-Pathology Deep Learning Model for the Precise Prediction of Recurrence in Pathological Stage IA Lung Adenocarcinoma.

BACKGROUND: The postoperative prognosis of pathological stage IA lung adenocarcinoma (LUAD) exhibits significant heterogeneity. While the tumor node m...

Combining the prognostic values of entropy-based heterogeneity features from 18 F-fluorodeoxyglucose PET and transmission computed tomography using machine learning in patients with lung adenocarcinoma undergoing curative surgery.

OBJECTIVE: The objective of this study is to evaluate the combined prognostic values of 18 F-fluorodeoxyglucose ( 18 F-FDG) PET and computed tomograph...

A multicenter multimodel habitat radiomics model for predicting immunotherapy response in advanced NSCLC.

A robust predictive biomarker is critical for identifying patients with NSCLC who may benefit from immunotherapy. This study developed a CT-based habi...

Automated Lymph Node and Extranodal Extension Assessment Improves Risk Stratification in Oropharyngeal Carcinoma.

PURPOSE: Extranodal extension (ENE) is a biomarker in oropharyngeal carcinoma (OPC) but can only be diagnosed via surgical pathology. We applied an au...

Smooth Muscle Disruptive Feature Defines Molecular Subtyping, Risk Stratification, and Metastatic Potential in Prostate Cancer.

BACKGROUND: Smooth muscle (SM) invasion represents a critical feature of prostate cancer (PCa) progression and metastasis. This study aimed to develop...

Relationship between cardiometabolic index and worsening renal function in T2DM: Insights from machine learning, growth mixture modelling, and development of a web-based risk prediction tool.

AIM: Worsening renal function (WRF) is a common and serious complication of type 2 diabetes mellitus (T2DM), contributing to adverse clinical outcomes...

The actual performance of ML/AI models in predicting radiation-induced toxicity in head and neck cancer: a systematic review and meta-analysis.

An increasing number of Artificial intelligence (AI) and machine learning (ML) models are being developed to predict radiation-induced toxicities (RIT...

Bayesian selection of lipidome dynamics features for a K-nearest neighbors (KNN) classifier model of tumor response in patients with advanced gastrointestinal adenocarcinoma undergoing systemic treatment.

BACKGROUND: Dysregulated lipid metabolism is common in patients with gastrointestinal (GI) cancer. This study investigated the ability of plasma lipid...

Amentoflavone from Ginkgo biloba inhibits EMT-driven lung cancer metastasis by targeting TGFBR2: Integrative network pharmacology, machine learning, and experimental validation.

ETHNOPHARMACOLOGICAL RELEVANCE: In non-small cell lung cancer (NSCLC), fatal outcomes predominantly result from metastatic dissemination, highlighting...

Artificial intelligence takes on the multidisciplinary committee: A single-center study for rectal cancer management.

BACKGROUND: As rectal cancer management evolves, the multidisciplinary committee becomes increasingly important in integrating expertise to optimize p...