Lung Cancer

Radiolysis in drug discovery: molecular modification, repurposing, and mechanistic insights.

INTRODUCTION: In drug discovery, exploring novel chemical space and elucidating precise molecular mechanisms are essential for successful lead identification. Radiation chemistry offers a highly versatile approach that spans both structural modification and mechanistic analysis. AREAS COVERED: This review examines gamma radiolysis as a robust engine for diversity-oriented molecular modification an...

Large language models enable prognostic stratification of cancer patients using real-world clinical notes.

In medical documentation, vast amounts of unstructured text are generated that are still underutilized in current prognostic models. We investigate the potential of self-hosted large language models (LLM) to extract clinically meaningful, patient-specific information from routine clinical notes for personalized risk stratification in cancer care. We collected real-world medical notes from 2,708 no...

Prediction of PD-L1 expression in nonsmall cell lung cancer using artificial intelligence models based on radiomics: a systematic review and meta-analysis.

BACKGROUND: Since 1992, the incidence of lung cancer has shown an overall downward trend, with survival rates significantly improving in recent years ...

Association of C-reactive protein to albumin ratio with progression of CKD and all-cause mortality in diabetic CKD.

INTRODUCTION: The C-reactive protein to albumin ratio (CAR), an integrative biomarker of inflammation and malnutrition, has shown prognostic value in ...

HyCANet: a hybrid convolutional-attention network with cross-attention fusion for lung cancer histopathological classification.

Histopathology interpretation of lung cancer involves careful examination of tissue morphology, especially differentiating benign lung tissue, adenoca...

Comparative outcomes of proton and photon therapy in the management of malignant peripheral nerve sheath tumors.

BACKGROUND: Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are aggressive sarcomas often arising in the spine, characterized by high metastatic pot...

ALDH18A1 silencing inhibits lung adenocarcinoma progression through mitochondrial dysfunction and PPAR signaling pathway activation.

BACKGROUND: Lung adenocarcinoma (LUAD) remains a prevalent malignant tumor characterized by a dismal prognosis. This study aimed to reveal potential m...

LKCAU-Net: A Large Kernel Coordinated Attention U-Net for Breast Tumors Segmentation in Ultrasound Images.

Breast cancer remains a significant health concern for women worldwide. Ultrasound imaging is widely adopted for screening due to its non-invasive and...

Image sharpening improves the visibility of reference points on low-dose lateral cephalometric radiographs: a phantom study.

This phantom study aimed to determine whether a novel non-artificial intelligence image-sharpening approach improves the visibility of reference point...

Expression characteristics analysis, establishment of prognostic model and screening of key regulators based on selenium protein-related genes in rectal adenocarcinoma.

BACKGROUND: Selenium is an essential trace element in the human body and plays a significant role in multiple cancers. This study aims to comprehensiv...

Targeting galactose metabolic reprogramming overcomes immunotherapy resistance in KRAS-mutant lung adenocarcinoma: Integrative multi-omics and machine learning approaches.

BACKGROUND: KRAS-mutant lung adenocarcinoma (LUAD) is associated with aggressive phenotypes and therapy resistance, which highlights an urgent need to...

Evaluating the Accuracy of ChatGPT-4o in Addressing Complex Clinical Questions Based on NCCN Guidelines for Rectal Adenocarcinoma.

INTRODUCTION: The management of rectal adenocarcinoma requires navigation of complex, branching guideline pathways encompassing neoadjuvant sequencing...

Advances in CT and MRI for Yttrium-90 Radioembolization of Hepatocellular Carcinoma.

RATIONALE AND OBJECTIVES: Transarterial radioembolization (TARE) is increasingly used for patients with hepatocellular carcinoma (HCC) across Barcelon...

Machine learning-driven development of a novel unfolded protein response-related gene signature for predicting lung adenocarcinoma patient prognosis.

Lung adenocarcinoma (LUAD) is the most common lung cancer histological subtype. Although the unfolded protein response (UPR) has been linked to variou...

MCD biomarkers Egfr, Hmox1, Lgmn identified in NAFLD.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is associated with metabolic cell death (MCD), and this study aimed to dig deeper into the bioma...

Comprehensive identification of three key genes and three key DNA methylation CpG sites associated with prognosis and prediction in colon adenocarcinoma.

Colon adenocarcinoma (COAD) is a common cancer with high incidence and mortality rates worldwide. DNA methylation has a significant impact on the occu...

Systematic AI-assisted screening of the cadhesome to map epithelial monolayer mechanics.

Cadherin-mediated adhesions serve as key mechanical and signaling hubs in epithelial tissues, linking the actin cytoskeleton of adjacent cells. Their ...

Improving pancreatic adenocarcinoma prognosis models through ligand receptor interactions and histopathological integration.

BACKGROUND: Pancreatic adenocarcinoma (PAAD) has an extremely poor prognosis, and existing prognostic markers fail to fully capture the complex hetero...

Comment on "MRI and PET-Based Machine Learning Radiomics for Metastasis Prediction in Pancreatic Ductal Adenocarcinoma: A Systematic Review".

Single-cell and machine learning-based neural regulation signature for prognosis prediction and immunotherapy response in lung adenocarcinoma.

OBJECTIVE: Lung adenocarcinoma (LUAD) molecular heterogeneity limits traditional prognostic models. Given the emerging role of neural regulation (NR) ...