Pathology

Limits of Artificial Intelligence Models for Skin Cancer Diagnosis in Realistic Settings.

IMPORTANCE: Artificial intelligence (AI) systems for skin cancer detection perform well in controlled settings but frequently underperform in everyday clinical practice, raising critical questions about their readiness for deployment. OBJECTIVE: To compare the diagnostic accuracy of AI algorithms vs human evaluators across varying expertise levels for skin lesion diagnosis, including rare and atyp...

Biomarker-driven and AI-assisted nanomedicine for breast cancer: advancing precision drug delivery from bench to bedside.

INTRODUCTION: Breast cancer remains the most prevalent malignancy among women worldwide, with its pronounced molecular heterogeneity demanding therapeutic strategies that transcend conventional systemic chemotherapy toward tumor-selective, molecularly precise interventions. The convergence of biomarker science, engineered nanomedicine, and artificial intelligence (AI) offers a transformative frame...

Bubble nucleation as a non-equilibrium phase transition in CO2/CH4 Hydrates.

Gas hydrate dissociation is a complex non-equilibrium process involving coupled lattice destabilization, gas release, and bubble nucleation, which pla...

An integrated machine learning and mendelian randomization approach identifies SERPING1 as a prognostic biomarker associated with CD8 + T-cell infiltration in DLBCL.

BACKGROUND: SERPING1, which encodes the C1 inhibitor (C1-INH) of the complement system, and plays a key regulator in regulating inflammatory responses...

O-SNAP uncovers nanoscale chromatin remodeling in dedifferentiation and stress responses.

The multi-scale organization of chromatin underlies gene regulation and cell identity, yet how nuclear architecture remodels during cell state transit...

Profiling of extracellular vesicles from primary hepatocytes, organoids, and mash patients identifies cell injury-specific signatures.

Metabolic Dysfunction-Associated Steatohepatitis (MASH) is a severe form of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), traditio...

An explainable meta-learned hybrid CNN-transformer model with dual attention for leukemia diagnosis from peripheral blood smears.

Acute Lymphoblastic Leukemia (ALL) is one of the most aggressive hematological malignancies, and its early diagnosis remains challenging due to non-sp...

privateST: a feasible framework for privacy-preserving spatial transcriptomics prediction from histopathology images.

Predicting spatial transcriptomics from histology images offers cost-effective insights but faces privacy barriers preventing cross-institutional data...

Learning continuous activation fields from microscopic SEM images of lycoperdioid fungi via CNN-guided neural operator modeling.

Accurate interpretation of microscopic morphological features is critical for resolving taxonomic boundaries in morphologically similar fungal taxa, y...

Integration of single-cell and bulk RNA sequencing reveals programmed cell death-associated transcriptional programs in sepsis-induced acute lung injury.

BACKGROUND: Sepsis-induced acute lung injury (ALI) is a frequent and life-threatening complication of sepsis, yet clinically actionable transcriptomic...

ViGNet: A clinical data-supported deep learning approach for NSCLC immunotherapy response prediction in digital pathology.

Histopathology is the cornerstone of oncology diagnosis, while whole-slide images (WSIs) enable the transition to digital, quantitative pathology. Lev...

Insights into middle-aged men (40-70) who died by suicide: a nationwide mixed methods study in the Netherlands.

BACKGROUND: Globally, middle-aged men dominate suicide statistics in many regions. To understand their heightened vulnerability, we examine the interp...

Prospective germline exome and machine learning-based risk score identify predictive and prognostic biomarkers of immunotherapy outcomes in advanced non-small cell lung cancer.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). However, a su...

Synaptic dysfunction-related gene expression spatially correlates with widespread cortical network atrophy in temporal lobe epilepsy.

Temporal lobe epilepsy (TLE) exhibits marked lateralized gray matter alterations, yet whole-brain network vulnerability patterns, particularly those i...

[Artificial intelligence in molecular pathology : Introduction and overview].

Over the past approximately 15 years, pathology has undergone a significant transformation, accompanied by increasing mechanization, technological adv...

Large Language Models for Cholesteatoma Diagnosis: A Pathology-Validated Study.

OBJECTIVES: To evaluate the diagnostic performance of the large language model (LLM) Gemini 2.5 for cholesteatoma detection using histopathology as th...

Spatial omics of immunity: Mapping cellular landscapes in tissue microenvironments.

The tumor microenvironment (TME) is composed of diverse heterogeneous components and plays a crucial role in immune cell infiltration, immune evasion,...

Multimodal Ultrasound Integration Pathways and Paradigm Innovations in Precision Diagnosis and Treatment of Thyroid Cancer.

RATIONALE AND OBJECTIVES: Thyroid cancer, the fastest-growing endocrine malignancy, is shifting from morphological evaluation to molecular-functional ...

Compilation of Creep Property Data for Nuclear Structural Materials.

As advanced nuclear reactor designs move towards higher operating temperatures, rapid nuclear material creep research has become increasingly importan...

Deep learning prediction of pathological complete response in breast cancer using Mamba architecture.

Deep learning is capable of efficiently predicting the therapeutic efficacy of neoadjuvant chemotherapy (NAC) in breast cancer. However, current metho...