Pathology

3D chromatin architecture-related genes orchestrate LUAD evolution and therapy resistance: insights from integrative machine learning and spatial single-cell mapping.

BACKGROUND: Lung adenocarcinoma (LUAD) is a prevalent and lethal malignancy. The three-dimensional (3D) chromatin architecture significantly influences tumor progression, yet the contribution of 3D chromatin structure-related genes (3DCRGs) in LUAD remains unclear. This study was designed to explore the role of 3DCRGs in postoperative recurrence of early-stage LUAD, response to Sorafenib therapy i...

Smartphone-Based Proactive Self-Screening for Ocular Surface Malignancies: A Nonrandomized Clinical Trial.

IMPORTANCE: Ocular surface malignancies pose risks to vision and survival yet are frequently misdiagnosed as benign lesions because of their subtle presentation and the lack of widely accessible screening tools, potentially resulting in treatment delays and the need for extensive surgical intervention. OBJECTIVE: To develop and validate a smartphone-based, media-facilitated artificial intelligence...

Integrating morphology and molecular biology: AI-driven molecular prediction in Pathology with a focus on Cytology.

BACKGROUND: Recent computational pathology research proposes using artificial intelligence to infer molecular features from routine hematoxylin-eosin ...

Histopathological Assessment of Myocardial Ischemia-Reperfusion Injury Using Transformer-Based Artificial Intelligence: Model Comparison Study.

BACKGROUND: Myocardial ischemia-reperfusion injury (MIRI) poses diagnostic challenges due to complex histopathological changes. OBJECTIVE: This study ...

DEHP-induced male reproductive toxicity: Evidence from population studies, animal experiments, and multi-omics profiling.

OBJECTIVE: To evaluate the association between di(2-ethylhexyl) phthalate (DEHP) exposure and testosterone deficiency in adult men, and to explore mol...

Image-based consensus molecular subtypes and colon cancer recurrence: Understanding the impact of lifestyle factors across subtypes of colon cancer.

AIM: We investigated associations between consensus molecular subtype (CMS) and colon cancer recurrence, and explored how the inflammatory potential o...

Deep learning of functional perturbations from condensate morphology.

Biomolecular condensates compartmentalize the interior of cells to organize complex functions, yet linking molecular interactions within condensates t...

Diagnostic yield and cost of three-level H&E sectioning in prostate biopsies.

AIM: The traditional three-level H&E sectioning protocol for prostate biopsies was developed for ultrasound-guided systematic sampling and predates le...

Weakly-supervised deep learning on pathological whole-slide images for cutaneous vasculitis and its mimickers: a high-performance diagnostic support tool.

Cutaneous vasculitis represents a heterogeneous group of disorders characterized by inflammation and necrosis of blood vessels within the skin, with o...

Tissueformer: extending single-cell foundation models to predict population-level phenotypes.

BACKGROUND: Single-cell RNA sequencing technologies have enabled unprecedented insights into gene expression and opened new pathways for diagnostics a...

Essential Data Elements for Laboratory Test Interoperability: An Expert Consensus-Based Framework.

The increasing digitalization of healthcare necessitates laboratory data interoperability to ensure reliable clinical decision-making, efficient data ...

CT-based deep learning radiogenomics for predicting key glioma genotypes (IDH, ATRX, EGFR, TP53).

PURPOSE: Molecular subtyping guides diagnosis and targeted therapy for gliomas. Although MRI-the current imaging standard-can be time-consuming and is...

A comparative analysis of deep learning models for disease classification in multi-organ histopathological images.

Histopathological whole slide images (WSIs) provide critical information for disease diagnosis, yet their interpretation remains a time-consuming and ...

Beyond attention heatmaps: How to get better explanations for multiple instance learning models in histopathology.

Multiple instance learning (MIL) has enabled substantial progress in computational histopathology, where a large amount of patches from gigapixel whol...

Multi-omic biomarkers of neoadjuvant treatment response in rectal cancer: A narrative review.

BACKGROUND: Neoadjuvant treatment response in rectal cancer is highly heterogeneous, complicating patient selection for organ-preservation strategies....

Fluorescence spectroscopy and machine learning methods for detection of Alzheimer's disease from circulating white blood cells.

BackgroundAlzheimer's disease (AD) is the most common cause of dementia whose prevalence is projected to increase significantly in the coming decades....

Epigenetic reprogramming of tissue-resident memory T cells in chronic inflammatory disorders and implications for targeted therapies.

BACKGROUND: Tissue-resident memory T (TRM) cells play a role in causing long-term tissue injury in chronic inflammatory diseases via pathological epig...

Extracellular Vesicles in Exhaled Breath Condensate as Emerging Biomarkers in Lung Cancer.

Exhaled breath condensate (EBC) has emerged as a noninvasive liquid biopsy medium that captures aerosolized material from the respiratory tract and ma...

Comparison of volume- and surface-based magnetic resonance imaging morphometry algorithms in the detection of focal cortical dysplasia.

OBJECTIVE: Detection of focal cortical dysplasia (FCD) remains a major challenge in presurgical epilepsy diagnostics. Magnetic resonance imaging (MRI)...

An artificial intelligence solution for evaluation of prostate needle core biopsy specimens: impact in a non-specialist setting.

The diagnosis of prostate cancer rests on the histopathological evaluation of prostate needle core biopsy specimens (NCBS) supplemented by immunohisto...