Pathology

Exploring the toxicological impact of perfluorooctanoic acid and perfluorooctane sulfonate on glioblastoma through network toxicology, machine learning, and multi-dimensional bioinformatics analysis.

Exposure to perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) has been associated with the development of various malignant tumors. However, their roles and molecular mechanisms in glioblastoma (GBM) are still unclear. This study combined network toxicology, machine learning, immune infiltration analysis, single-cell RNA sequencing (scRNA-seq), molecular docking, Mendelian randomi...

MRI-based machine learning model to distinguish hippocampal sclerosis (HS) ILAE type 1 and no HS gliosis only in medial temporal lobe epilepsy.

PURPOSE: Despite recent advances in preoperative work-up of drug resistant medial temporal lobe epilepsy (MTLE), predicting post-surgical seizure and memory outcomes remains challenging. Differentiating between "no hippocampal sclerosis Gliosis Only" [i.e. gliosis only; no pyramidal neuronal loss] and "HS ILAE Type 1" is essential as these two are distinct histopathological entities in MTLE with d...

Crosstalk between immune and programmed cell death and their application in colorectal cancer risk stratification.

Programmed cell death (PCD) and cellular immunity play pivotal roles in colorectal cancer (CRC) progression; understanding their crosstalk and identif...

A comprehensive toolkit for analyzing cell-free DNA genomic sequencing data in liquid biopsy.

Liquid biopsy via plasma cell-free DNA (cfDNA) is transforming precision medicine by enabling non-invasive insights into the genomic and epigenomic la...

Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in chronic spontaneous urticaria and autophagy based on machine learning.

BACKGROUND: The exact molecular mechanisms governing a heightened risk of chronic spontaneous urticaria (CSU) associated with autophagy remain largely...

World Health Organization classification of tumours of the breast 6th edition 2026.

The 6th edition of the WHO Classification of Breast Tumours introduces both major and minor changes based on recent advances in our understanding of b...

Challenges and Barriers in Implementing AI for Clinical Applications in Anatomic Pathology.

The transformation of anatomic pathology from microscope-based practice to digital and computational workflows has created unprecedented opportunities...

Beta cell microRNAs function as molecular hubs of type 1 diabetes pathogenesis and as biomarkers of diabetes risk.

AIMS/HYPOTHESIS: Clinically actionable biomarkers that accurately reflect the health status of the beta cell are needed to improve risk stratification...

Structurally robust quaterphenyl-dicarbonitrile 2D MOF nanopores on Cu(111) for cobalt spin-coordination motifs.

We demonstrate a strategy for fabricating robust ∼2 nm nanopores on copper (Cu) surfaces using a nonmagnetic two-dimensional (2D) metal-organic framew...

Multi-Beholder: Biomarker Prediction for Low-Grade Glioma with Multiple Instance Learning and One-Class Classification.

Biomarker detection is an indispensable part of the diagnosis and treatment of low-grade glioma (LGG). However, current LGG biomarker detection method...

Clinical Model Autophagy: The Risk of Interpretative Drift in Recursive Medical AI.

The rapid integration of large language models into electronic medical record systems introduces a critical theoretical vulnerability. Drawing on foun...

From pixels to pathology: how artificial intelligence mammographic risk scores capture tumor biology through imaging.

OBJECTIVES: To characterize clinical-pathologic tumor features associated with artificial intelligence (AI)-generated risk scores from prior-year scre...

A multi-modal dataset for insect biodiversity with imagery and DNA at the trap and individual level.

Insects comprise millions of species, many experiencing severe population declines under environmental and habitat changes. High-throughput approaches...

Automated detection of basement-membrane breaches in oral squamous cell carcinoma : A comparative study of convolutional neural network architectures.

BACKGROUND: Oral squamous cell carcinoma (OSCC) remains a leading cause of cancer-related morbidity and mortality worldwide. The ability to detect ear...

Next-Generation Disease Profiling by Integrating Histopathology with Spatial Multi-Omics Data.

The field of pathology has experienced several transformative changes in recent years with the advent of digital pathology and spatial multi-omics. Th...

Amino acid metabolism in retinal diseases: Mechanisms, diagnostics, and therapeutic opportunities.

Amino acid metabolism serves as a central hub linking retinal energy supply, neurotransmission, and cell signaling, which is critical for maintaining ...

Clinical utility of BOLD-MRI in accurate diagnosis and prognostic evaluation of diabetic nephropathy: a prospective renal biopsy-based cohort study.

OBJECTIVES: To validate blood oxygen level-dependent MRI (BOLD-MRI) for non-invasive discrimination of diabetic nephropathy (DN) vs non-diabetic renal...

Learning Where to Look: Differentiable Slice Selection and Efficient Channel Attention for FCD-II MRI Classification.

Focal Cortical Dysplasia (FCD) is a major cause of drug-resistant epilepsy both in children and adults. In most such cases, surgery is the most effect...

Hybrid supervised deep learning for lung adenocarcinoma diagnosis to optimize surgical strategies.

Intraoperative frozen section pathological diagnosis of lung adenocarcinoma serves as the gold standard for determining the extent of surgical resecti...

Low-latency HRV analysis from ultra-short ECG windows using a modular deep-learning framework.

We present a universal modular deep-learning framework and demonstrate its application to low-latency, streaming-compatible heart rate variability (HR...