Pathology

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 framework (MOF), without the need for additional 3d metal atom deposition, that serves as a platform for constructing single-atom transition-metal coordination sites. Scanning tunneling microscopy and spectroscopy (STM/STS) conducted at 78 K under ultrahig...

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 screening mammograms. MATERIALS AND METHODS: This retrospective study included women who underwent breast biopsy following a screening mammogram in 2021 across four U.S. states. AI risk scores were obtained from prior-year screening mammograms using an F...

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...

Diagnosis of Leukemia from Bone Marrow Flow Cytometry Data Using Deep Learning and Explainable Artificial Intelligence.

Leukemia is a life-threatening blood cancer requiring rapid and accurate diagnosis to improve patient survival. Although flow cytometry offers powerfu...

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...

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...

Interpretable predictions from whole-body FDG-PET/CT using parameters associated with clinical outcome.

BACKGROUND: Accurate prediction of clinical outcomes is challenging yet important for patient care. The aim of the study was to evaluate a deep learni...

Prospective biopsy-controlled validation of an AI model for predicting glioblastoma infiltration: Results from the SupraGlio trial.

BACKGROUND: Glioblastoma recurrence is driven by diffuse microscopic infiltration beyond the contrast-enhancing tumour margin. GlioMap is an open-acce...

A Transformer-ResNet-Integrated Deep Learning Model for Digital Pathology-Based Grading and Risk Stratification of MASLD-Related Liver Fibrosis.

INTRODUCTION: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects up to 30% of the global population and drives progression to fi...

Deciphering the molecular network of Trichostatin A in regulating Alzheimer's disease screening of core genes and mechanistic investigation based on multidimensional bioinformatics and molecular simulation.

BACKGROUND: Histone deacetylases (HDACs) regulate neuroprotection; however, Trichostatin A (TSA), an HDAC inhibitor, lacks clear molecular mechanisms ...

Cuproptosis-related circulating non-coding RNAs as diagnostic and prognostic biomarkers in oncology.

Cuproptosis is a recently described copper-dependent form of regulated cell death linked to mitochondrial metabolic stress and is emerging as a biolog...

SOHO State of the Art Updates and Next Questions | Management of Primary Central Nervous System Lymphoma.

Primary Central Nervous System Lymphoma (PCNSL) is a rare and aggressive form of extranodal non-Hodgkin lymphoma. Recent insights into the molecular c...

GUIDE-US: grade-informed unpaired distillation of encoder knowledge from histopathology to micro-ultrasound.

PURPOSE: Non-invasive grading of prostate cancer (PCa) from micro-ultrasound (micro-US) could expedite triage and guide biopsies toward the most aggre...

plasmaCHORD: A Machine Learning Approach to Distinguish Clonal Hematopoiesis-Derived Variants in Liquid Biopsies from Patients with Solid Tumors.

PURPOSE: Targeted next-generation sequencing (NGS) of cell-free DNA (cfDNA) enables comprehensive molecular profiling and can guide the selection of g...

Deep learning for fluorescence confocal microscopy image interpretation in radical prostatectomy.

OBJECTIVE: To develop and validate a deep learning model for interpretation of fluorescence confocal microscopy (FCM) images for intraoperative surgic...

Clinical Machine Learning Model for Predicting Pathological Complete Response in Patients with Esophageal and Gastroesophageal Junction Adenocarcinoma After Trimodality Therapy.

BACKGROUND: Accurate prediction of pathological complete response (pCR) after preoperative chemoradiation therapy, followed by surgery (trimodality th...