Pathology

Primary tissue metabolic fingerprinting for efficient diagnosis of lymph node metastasis and metabolic reprogramming mechanisms in colorectal cancer.

Accurate detection of lymph node metastasis (LNM) is critical for colorectal cancer (CRC) staging and treatment planning, yet current histopathological assessment based on lymph nodes remains labor-intensive and operator-dependent. Here, we developed a tissue metabolic fingerprinting platform leveraging label-free ferric nanoparticle-enhanced laser desorption/ionization mass spectrometry (FELDI-MS...

A deep learning framework to stratify Nottingham histologic grade 2 breast tumors based on dynamic contrast-enhanced MRI.

OBJECTIVE: The Nottingham Histologic Grade (NHG) informs prognosis and treatment decisions in breast cancer, but NHG2 tumors are biologically heterogeneous, leading to both under- and over-treatment. MATERIALS AND METHODS: Clinical and imaging data from the Duke-Breast-Cancer-MRI (n = 877) and advanced-MRI-breast-lesions (n = 37) datasets were used to develop DeepRadGrade (DRG), a convolutional ne...

Evaluating the Reliability of GPT-4o in Histological Image Interpretation.

Advanced large language models with multimodal capabilities offer potential new applications in medical education. This study evaluated GPT-4o's perfo...

Interobserver variability in histopathologic diagnosis of melanocytic neoplasms.

BACKGROUND: Precise histopathologic diagnosis of melanocytic neoplasms is required to guide appropriate clinical management; however, significant inte...

Mitochondrial energy metabolism-associated Predictive model constriction for coronary artery disease(CAD) of acute myocardial infarction(AMI) patients via integrative bioinformatic analysis.

Coronary artery disease (CAD) is a leading cause of acute myocardial infarction (AMI), a condition characterized by the sudden blockage of blood flow ...

Progress in constitutive modeling of arterial wall tissue mechanics: from theoretical frameworks to clinical application.

Cardiovascular disease (CVD) is a leading cause of mortality worldwide, and the mechanical behavior of arterial wall tissue (AWT) is central to its in...

An interpretable model based on weakly supervised learning for uterine smooth muscle tumor diagnosis: A multi-center study.

Uterine smooth muscle tumors (USMTs) are the most common tumors of the female reproductive system, but remain diagnostically challenging due to morpho...

A filter-level explainability framework for CNNs in histopathology image analysis.

Convolutional neural networks (CNNs) have achieved remarkable accuracy in histopathology image classification, yet their decision logic remains largel...

NLRP1 as a Novel Pyroptosis Biomarker in Irreversible Pulpitis: A Laboratory Investigation and Animal Model Study.

AIM: Irreversible pulpitis poses a significant clinical burden due to progressive inflammatory pulp damage. While inflammatory mechanisms are central ...

Editorial for "Deep Learning for Differentiating Benign From Malignant Bile Duct Dilation on MRCP: Development and Prospective Evaluation of an Xception-Logistic Regression Ensemble Model".

Cellular and molecular determinants of lymph node metastasis in papillary thyroid carcinoma: Integrated multi-omics profiling and machine learning models.

The mechanisms underlying lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) remain elusive. This study integrated single-cell RNA seque...

Machine learning-guided repurposing of FDA-approved quinolones as dual cholinesterase inhibitors: A multi-level docking, molecular dynamics, DFT, and SHAP-based analysis.

Alzheimer's disease (AD) involves progressive cholinergic degeneration, with acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) playing key ...

[Artificial intelligence in diagnostics-a pathology perspective].

The increasing complexity and individualization of oncologic diagnostics and therapy present new challenges for pathology. At the same time, artificia...

CLIP-Guided Generative network for pathology nuclei image augmentation.

Nuclei segmentation and classification play a crucial role in the quantitative analysis of computational pathology (CPath). However, the challenge of ...

Multi-center-validated machine learning model for cervical cancer based on human papillomavirus genotyping results.

OBJECTIVE: Cervical cancer remains a leading cause of gynecologic cancer-related mortality worldwide, with human papillomavirus (HPV) testing being a ...

Use of gadolinium-based contrast agents in head and neck cancer diagnosis, staging, and monitoring: current applications and future perspectives.

Gadolinium-based contrast agents (GBCAs) have been fundamental to head and neck cancer (HNC) imaging, enabling effective detection, characterization, ...

Optimized data augmentation for osteosarcoma detection in deep and lightweight networks.

Osteosarcoma (Ost) is an extremely aggressive primary bone malignancy that mostly occurs among children and young adults. Precise histopathological cl...

Aspartame promotes ovarian cancer progression: A multi-omics study integrating mendelian randomization, network toxicology, and in vitro validation.

The causal relationship between the artificial sweetener aspartame and ovarian cancer (OC), a highly lethal malignancy, remains unclear. This study, t...

Advances in endometrial cancer screening: a comprehensive review of current methods and emerging technologies.

Endometrial cancer represents a major global health concern, with rising incidence particularly in developed countries despite declining mortality rat...

Deep learning discriminates thymic epithelial tumors' histological subtypes using digital pathology.

BACKGROUND: Thymic epithelial tumors (TETs) are rare malignancies that pose significant diagnostic challenges due to their heterogeneous histological ...