Pathology

Integrating network toxicology, machine learning, and single-cell sequencing to reveal the FASN-mediated role of phenolic endocrine disruptors in water in promoting prostate cancer.

BACKGROUND: Phenolic endocrine-disrupting chemicals (EDCs) like nonylphenol (NP) and octylphenol (OP) are widespread water pollutants. Their estrogen-like properties are suspected contributors to prostate cancer, but their precise molecular mechanisms remain unclear. METHODS: We employed a multidimensional framework to investigate this link. Potential NP/OP targets were predicted using SwissTarget...

Continuum damage modeling of fatigue failure in whole bone under combined compression-torsional loading: A hybrid approach with machine learning integration.

Repetitive loading of bone is associated with microdamage accumulation and material property degradation that may ultimately result in fatigue fracture. Our previous work used continuum damage mechanics (CDM)-based finite element (FE) modeling to predict stiffness loss and fatigue failure in whole bone; however, this model did not account for inter-specimen variability in fatigue behaviour and com...

Deep learning-driven decoding of ubiquitination: from regulatory mechanisms to targeted protein degradation.

BACKGROUND: Ubiquitination is a highly dynamic post-translational modification that plays central roles in protein homeostasis, signal transduction, i...

Development and validation of a machine learning model for predicting distant metastasis in patients with renal cell carcinoma: a population-based study.

BACKGROUND: Distant metastasis is the leading cause of death in renal cell carcinoma (RCC), yet accurate prediction tools remain lacking. We aimed to ...

Integration of Raman Spectroscopy and Metabolomics for Early Breast Cancer Detection and Classification.

Breast cancer, now the fourth leading cause of cancer-related mortality worldwide, necessitates early detection for improved clinical outcomes. Conven...

Machine learning in tissue engineering: a comprehensive review of applications, challenges, and prospects.

Tissue engineering, rooted in cell biology and materials science, focuses on repairing or replacing injured tissues and organs, offering groundbreakin...

Artificial Intelligence for the Diagnosis of Pancreatic Diseases Using Endoscopic Ultrasonography.

Artificial intelligence (AI) is rapidly being applied to medical imaging; however, the evidence base for endoscopic ultrasonography-based AI (EUS-AI) ...

AI-based Histologic Heterogeneity of Microvascular Obstruction at Cardiac MRI for Predicting MACEs: A Multicenter Study.

Background Microvascular obstruction (MVO) is strongly associated with adverse outcomes after ST-segment elevation myocardial infarction (STEMI). Howe...

The role of infrared thermography in thyroid nodule detection and classification: a scoping review.

PURPOSE: To conduct a scoping review to assess the extent and type of evidence on the use of IRT as a diagnostic tool for thyroid nodule detection and...

Identification of Pathological Secretions in Bronchoscopic Images Based on Edge Features and Multi-Scale Attention Mechanism.

The accumulation of pathological bronchial secretions compromises ventilation and oxygenation in critically ill patients and may lead to atelectasis o...

Artificial intelligence-assisted urine cytology based on the Paris System for Reporting Urothelial Carcinoma.

BACKGROUND: Urine cytology is a noninvasive and valuable tool for detecting urothelial carcinoma but suffers from variable sensitivity and observer de...

AI-Based Quantitative Nasal Cytology for Predicting Eosinophilic Chronic Rhinosinusitis With Nasal Polyps: A Pilot Study.

Physical Parameter-Guided Deep Learning Ultrasound Localization Microscopy Framework Based on Diffusion Model.

OBJECTIVE: Deep learning based-imaging methods have demonstrated significant potential for achieving high spatiotemporal resolution in Ultrasound Loca...

Liver Nodule Anomaly Detection Using Ultra-sound Radiofrequency Signals and Variational Autoencoders.

OBJECTIVE: Detection of liver nodules in ultrasound (US) is challenging due to the low visibility in the presence of steatotic and cirrhotic livers. A...

Universal and transferable attacks on pathology foundation models using microscopic perturbations.

The advent of foundation models initiated a paradigm shift in pathology and optical microscopy. However, these powerful systems also introduce vulnera...

Conditional survival patterns and individualized prognostic prediction in malignant peritoneal mesothelioma.

Malignant peritoneal mesothelioma (MPM) is a rare, aggressive cancer with limited treatment options and extremely poor survival outcomes. Due to the d...

A Cost-Efficient Multi-Angle Fusion Deep Learning for Ultrasound Localization Microscopy.

Ultrasound localization microscopy (ULM) enables super-resolution imaging of microvascular structures by localizing microbubbles from clutter-filtered...

Dual Adaptive Disentangled Representation Learning With Multimodal Data for Disease Diagnosis.

The use of imaging and genetic data for biomarker detection and disease diagnosis can deepen the understanding of disease pathogenesis and assist in c...

Molecular Pathology of Soft-tissue Neoplasms.

Soft-tissue tumors are rare mesenchymal neoplasms characterized by extensive morphologic and genetic heterogeneity. Advances in molecular pathology ha...

From Theory to Practice: Which Biomarkers Are Ready for Predicting Response in Advanced HCC?

Systemic therapies for advanced hepatocellular carcinoma (HCC) have expanded considerably with the advent of tyrosine kinase inhibitors, immune checkp...