Pathology

Identification of aging-related signature genes in temporomandibular joint degeneration based on bioinformatics.

BACKGROUND: Degenerative temporomandibular joint diseases (TMJ-DJD) are increasingly affecting elderly populations, with aging being a significant risk factor driving the TMJ degenerative changes. This study aims to explore the shared characteristics between aging and TMJ degenerative diseases at the tissue level, and to identify aging-related signature genes in TMJ degenerations using bioinformat...

Multi-omics reveals fibroblast subtypes with distinct roles in inflammatory bowel disease.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract involving complex interactions among epithelial, immune, and stromal components. Fibroblasts are key regulators of intestinal inflammation and fibrosis, but their heterogeneity, distribution, and therapeutic potential remain unclear. METHODS: We systematically identified and characterized ...

Artificial intelligence in inflammatory bowel disease: From current evidence, clinical translation, and the road to precision medicine.

Artificial intelligence (AI) is rapidly transforming healthcare, supporting disease management and enabling outcome prediction across multiple clinica...

Development of a Computed Tomography Enterography Based Radiomics Model to Characterize Inflammation, Fibrosis and Smooth Muscle Thickening in Stricturing Crohn's Disease.

BACKGROUND AIMS: Computed tomography enterography (CTE) is a non-invasive cross-sectional imaging modality routinely used for diagnosis of Crohn's dis...

Breast Cancer Diagnosis and HER2+ Versus Triple Negative Discrimination by Infrared Spectral Histopathology.

Breast cancer is a heterogeneous disease comprising distinct molecular subtypes that require accurate diagnosis for effective treatment. Conventional ...

Accurately Deciphering Tissue Heterogeneity From Spatial Multi-Modal and Multi-Omics With STransformer.

Advances in spatially resolved technologies enable the simultaneous acquisition of diverse data modalities within a tissue slice while preserving crit...

Development and interpretability of a machine learning-derived model for the identification of latent prostate cancer in patients initially diagnosed with benign prostatic hyperplasia: a retrospective cohort study.

BACKGROUND: Prostate cancer (PCa) is characterized by pronounced intratumoral heterogeneity and multifocality, presenting ongoing challenges for early...

Quantitative RNA spatial profiling using single-molecule RNA FISH on plant tissue cryosections.

Single-molecule fluorescence in situ hybridization (smFISH) has emerged as a powerful tool to study gene expression dynamics with unparalleled precisi...

Multiclass convolutional neural network vs. 96 dermatologists in skin lesion diagnosis, an international study.

BACKGROUND AND OBJECTIVES: Artificial intelligence was shown to improve diagnostic accuracy for skin cancer detection. While most clinically approved ...

Molecular Encoding during Amplification Enables Multiplex Nanopore Profiling of Small Noncoding RNAs.

Many cancers are characterized by the coordinated dysregulation of multiple small noncoding RNAs (sncRNAs), yet fluorescence-based assays such as quan...

Integrating Molecular Pathology, Tumor Microenvironment, and Novel Therapies to Overcome Resistance in Glioblastoma.

Glioblastoma multiforme (GBM) represents the most aggressive primary brain tumor in adults, characterized by significant heterogeneity, rapid progress...

Noninvasive prediction of severe histopathology in drug-induced liver injury using a dual elastography-based machine learning model.

OBJECTIVES: To develop and validate a machine learning (ML) model integrating dual elastography, clinical features, and serum biomarkers for noninvasi...

Integrating weighted gene co-expression network analysis and machine learning reveal that NDUFA4L2 alleviates KA-induced HT22 cell neurotoxicity, apoptosis, oxidative stress, and mitochondrial dysfunction.

Temporal lobe epilepsy (TLE) is one of the most common types of epilepsy, with frequent seizures often leading to cognitive, emotional, and psychiatri...

Deep Learning-Based Restoration of Distorted Transmission Raman Spectra through Biological Tissue.

Retrieving optical information from photons traversing scattering media is essential in fields relating to detection and imaging. Raman spectroscopy o...

Deep Learning Predicts Mutations and Outcomes in Gastrointestinal Stromal Tumors from Whole-Slide Images.

Gastrointestinal stromal tumor (GIST) is the most common gastrointestinal mesenchymal tumor, driven by tyrosine-protein kinase (KIT) and platelet-deri...

Targeting the IKKα/NF-κB Axis with SGEC-Derived Exosomal miR-23b-3p Rebalances Treg/Th17 Immunity in Sjögren's Syndrome.

BACKGROUND: Sjögren's syndrome (SS) is a systemic autoimmune disorder characterized by chronic inflammation, oxidative stress, and progressive salivar...

A temporal-spectral dual-stream anti-noise bearing fault diagnosis model based on adaptive mode decomposition.

In recent years, deep learning-based bearing fault diagnosis models have achieved remarkable performance under ideal experimental conditions. However,...

[Role and limitations of genome-wide DNA methylation profiling in the diagnosis of brain tumors].

Genome-wide DNA methylation profiling, a high-throughput epigenomic technology, systematically examines the methylation status of CpG sites across the...

Machine learning models for non-invasive endometriosis triage using a laparoscopically and histologically verified cohort.

OBJECTIVE: To develop and internally validate machine-learning models for non-invasive triage of women at risk for endometriosis using structured clin...

First-trimester multi-modal cell-free DNA analysis for prediction of preterm and term preeclampsia.

BACKGROUND: Preeclampsia, which is a leading cause of maternal and perinatal mortality and morbidity, represents a biologically heterogeneous syndrome...