Pathology

The application of artificial intelligence in adrenal imaging: current state of knowledge, challenges, and future directions.

Adrenal incidentalomas are frequently detected on abdominal imaging and require evaluation for malignancy and hormonal activity. Although most are benign adenomas, distinguishing them from pheochromocytomas, adrenocortical carcinomas, metastases, and functioning tumors remains difficult, especially in indeterminate cases. Artificial intelligence as emerged as a promising tool to improve adrenal le...

Identification and validation of novel diagnostic biomarkers across multiple tissues in osteoarthritis.

BACKGROUND: Osteoarthritis (OA) is a degenerative joint disease characterized by synovial inflammation, cartilage degradation, and subchondral bone remodeling. Currently, no universally accepted or clinically validated biomarkers exist for OA diagnosis and treatment, highlighting the need to identify potential genetic biomarkers to support early detection and therapeutic research. OBJECTIVES: This...

Multidimensional analysis of tumour immune microenvironment in HCC: prognostic significance and implications for immunotherapy.

BACKGROUND: The combination of immune checkpoint inhibitors (ICIs) and anti-angiogenic agents represents the standard first-line therapy for patients ...

Homogeneity of Liver Fat Distribution Serves as a Diagnostic Marker for Metabolic Dysfunction-Associated Steatohepatitis.

RATIONALE AND OBJECTIVES: To characterize liver fat distribution in metabolic dysfunction-associated steatohepatitis (MASH) and propose a magnetic res...

Machine learning ensemble reveals distinct molecular pathways of retinal damage in spaceflown mice.

Spaceflight-associated neuro-ocular syndrome (SANS) poses significant ocular health risks in long-duration missions, yet its molecular mechanisms rema...

Pan-cancer analysis of tissue-plasma genomic concordance reveals enhanced concordance with liver metastasis and plasma clonality as predictor of poorer overall survival.

Circulating tumor DNA (ctDNA) enables noninvasive tumor genotyping, yet its concordance with tissue remains unclear. Using a 437-gene panel in 1111 pa...

Automated identification of clinically important Candida yeast species for microscopic images using self-supervised learning.

Opportunistic fungal infections are an escalating global challenge, impacting over a billion people worldwide, particularly immunocompromised individu...

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...

SpaHNR: a spatial domain identification method via sparse attention-based hierarchical node representation and multi-view contrastive learning.

BACKGROUND: Leveraging deep learning on spatial transcriptomics data enables the identification of distinct spatial domains within tissues, thereby cl...

Preoperative Serum Alkaline Phosphatase Predicts Arteriovenous Fistula Maturation Failure.

INTRODUCTION: Arteriovenous fistula (AVF) maturation failure remains a major obstacle for hemodialysis, yet its underlying molecular drivers are poorl...

Routine biomarkers map response probability in HER2-positive breast cancer treated with neoadjuvant chemotherapy and dual HER2 blockade.

BACKGROUND: Pathologic complete response (pCR) after neoadjuvant chemotherapy and dual HER2 blockade is associated with improved outcomes in HER2-posi...

Radiomics-Based AI for the Diagnosis and Prognosis of Vessels Encapsulating Tumor Clusters in Hepatocellular Carcinoma: Systematic Review and Meta-Analysis.

BACKGROUND: Vessels encapsulating tumor clusters (VETCs), a CD34-positive vascular pattern in hepatocellular carcinoma (HCC), are linked to aggressive...

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

MOTIVATION: Spatial transcriptomics (ST) enables the precise mapping of gene expression within tissue architecture, however its application is often l...

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) ...

Deep Learning for Differentiating Pulmonary Metastasis from Primary Lung Cancer Constructed on Frozen Sections for Intraoperative Diagnosis.

The surgical procedures for primary lung cancer and metastatic lung tumors differ. An intraoperative diagnosis is important for surgical procedure dec...

Multiview Laryngoscopic Image Fusion for Patient-Level Stratification of Vocal Fold Lesions.

Malignant or high-grade vocal fold disease is usually judged across repeated laryngoscopic views at different observation distances and fields of view...

Geometric-structural multi-label learning for non-invasive prediction of breast cancer biomarkers.

Accurate profiling of molecular biomarkers, including ER, PR, HER2, and Ki-67, is pivotal for tailoring therapeutic strategies in breast cancer manage...

Endomyocardial Gremlin-1 is associated with structural remodeling and adverse clinical outcomes in non-ischemic cardiomyopathy.

BACKGROUND: Risk stratification in non-ischemic cardiomyopathies (NICM) remains challenging despite guideline-based phenotypic classification using mu...

Key molecular mechanisms of mitochondrial metabolic pathways in specific cell subpopulations of pancreatic cancer based on scRNA-seq and bulk RNA-seq.

BACKGROUND: Pancreatic cancer (PC) is a highly malignant tumor with increasing incidence, mortality, and a low five-year survival rate. Mitochondrial ...

Dual-mode analysis of ischemic stroke based on urine SERS spectra and carotid B-ultrasound.

Achieving noninvasive high-frequency monitoring of ischemic stroke (IS) remains a major clinical challenge for timely intervention and precise seconda...