Pathology

Downregulated lysyl oxidase in plasma extracellular vesicles: a biomarker linked to brain metastasis risk in lung adenocarcinoma.

BACKGROUND: Brain metastasis (BrM) is a leading cause of mortality in patients with lung adenocarcinoma (LUAD). Extracellular vesicles (EVs), which carry bioactive molecules, play a critical role in tumor microenvironment remodeling and exhibit metastatic organotropism, holding promise as liquid biopsy biomarkers. This study aims to identify plasma EV-derived proteins associated with LUAD-BrM. MET...

Machine learning-driven molecular engineering of nucleic acids.

Molecular engineering has played a pivotal role in biomedical fields, driving significant advancements in gene therapy, disease diagnosis, and biosensing. However, nucleic acid molecular engineering faces various challenges including vast design spaces, complex structure-function relationships, lengthy application validation cycles, and inefficient optimization processes. Machine learning (ML), wi...

Label-Free, AI-Driven Evanescent Microscopy Decodes Single-Cell Membrane Protein Binding Kinetics and Adhesion Biomechanics.

Quantifying ligand interactions with membrane proteins in their native cellular environment is crucial for understanding cellular processes and drug s...

Artificial intelligence for diagnosis and triage in oral cancer: a clinician‑centered narrative review.

BACKGROUND: Early diagnosis of oral squamous cell carcinoma (OSCC) remains challenging, with survival largely stage-dependent at presentation. Artific...

Molecular and immunological heterogeneity of eosinophilic esophagitis: Insights and subtyping.

BACKGROUND: Eosinophilic esophagitis (EoE) and its related subtypes-such as EoE-like esophagitis, lymphocytic esophagitis, and nonspecific esophagitis...

Prediction of facial profiles following orthodontic treatment in adult Class III patients using deep neural networks with feature fusion.

OBJECTIVE: This study proposed a cascaded framework based on deep neural networks that integrate cephalogram and landmark data to predict soft tissue ...

PCa-Mamba: Spatiotemporal state space models for prostate cancer detection in multi-parametric MRI.

Multiparametric Magnetic Resonance Imaging (mpMRI), including T2-weighted imaging (T2), diffusion-weighted imaging (DWI), and dynamic contrast-enhance...

Deep learning on histopathological images to predict breast cancer recurrence risk and chemotherapy benefit: a multicentre, model development and validation study.

BACKGROUND: Genomic assays such as Oncotype DX have transformed adjuvant treatment selection for hormone receptor-positive, HER2-negative, early breas...

SMC-LUD:Large-Scale B-Mode Liver Ultrasound Dataset for Hepatocellular Carcinoma and Hemangioma Classification.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality globally, and accurate classification of liver lesions using ultrasound ...

[Application of artificial intelligence in pathological diagnosis of ocular tumors].

Ocular tumors encompass ocular surface tumors, orbital tumors, and intraocular tumors, characterized by high heterogeneity and complex classifications...

Diagnosing orthopaedic infection by identifying neutrophils in whole histology slide images with machine learning trained on publicly available datasets.

AIMS: This study examines the ability of YOLO (You Only Look Once) 11x, a widely used and state of the art object detection model, trained on publicly...

Color standardization in whole slide imaging: a method to reduce color variability.

Color standardization in digital pathology is essential for ensuring consistency across Whole Slide Imaging (WSI) scanners. This study utilizes color ...

Computer-aided diagnosis of papillary thyroid carcinoma based on deep learning technology.

This article examines global thyroid cancer（TC） incidence trends, with emphasis on epidemiological patterns in China, where papillary thyroid carcinom...

A metabolic-immune subtype of breast cancer defined by G6PD and SHMT2: From single‑cell dissection to dual-targeted therapy.

Breast cancer heterogeneity limits the precision of current prognostic and therapeutic strategies, underscoring the need for molecular frameworks that...

PIBAdb: a public cohort of multimodal colonoscopy videos and images including polyps with histological information.

BACKGROUND AND OBJECTIVE: Colorectal cancer is the third most common cancer worldwide and presents a high mortality rate. Colonoscopy is the gold stan...

Experimentally paired high- and low-resolution confocal fluorescence microscopy dataset for deep-learning super-resolution imaging of tooth dentin porosity.

The proposed dataset provides experimentally acquired high- and low-resolution confocal laser scanning microscopy images of dentin porosity, split int...

Synthetic data-driven deep learning for label-free autonomous atomic force microscopy.

Atomic force microscopy (AFM) is a widely used tool for nanoscale characterization across materials science, energy research, and biology. However, it...

A foundation model for multi-task cross-distribution restoration of fluorescence microscopy images.

Deep learning has demonstrated remarkable abilities in restoring fluorescence microscopy images degraded by noise, blur, or undersampling. However, mo...

Adherence to guidelines, pitfalls, and emerging technologies in endoscopic practice for celiac disease: a nationwide SIGENP survey.

UNLABELLED: Upper gastrointestinal endoscopy (UGIE) with duodenal biopsies remains the gold standard for diagnosing celiac disease (CD) in children an...

An interpretable machine learning model for predicting prognosis of medulloblastoma integrating genetic and clinical features.

BACKGROUND: Medulloblastoma (MB), the most common malignant pediatric brain tumor, lacks prognostic tools integrating clinical, molecular, and treatme...