Pathology

Exploratory multi-cohort, multi-reader study on the clinical utility of a deep learning model for transforming cryosectioned to formalin-fixed, paraffin-embedded (FFPE) images in breast lesion diagnosis.

BACKGROUND: Cryosectioned tissues often exhibit artifacts that compromise pathologists' diagnostic accuracy during intraoperative assessments. These inconsistencies, compounded by variations in frozen section (FS) production across laboratories, highlight the need for improved diagnostic tools. This study aims to develop and validate a deep-learning model that transforms cryosectioned images into ...

Self-Driving and Detachable Lab-Microrobots Tailor Drug Delivery for Closed-Loop Stimulation of the Antitumor Immune Cycle.

Hypoxia arises in most solid tumors with insufficient blood flow, which hinders the delivery and efficacy of therapeutic agents to tumors. In this work, utilizing anaerobic bacteria capable of seeking out hypoxic areas for flourishing, we constructed a liposome-anchored anaerobic bacteria (Lab)-microrobot for self-driving and detachable delivery of immunity activators to tumor sites, thereby orche...

Fast and accurate lung cancer subtype classication and localization based on Intraoperative frozen sections of lung adenocarcinoma.

Current lung cancer diagnostic techniques primarily focus on tissue subtype classification, yet remain inadequate in distinguishing pathological progr...

Multifunctional nanophotonic photoacoustic biosensors: a new era in molecular imaging-guided deep-tissue cancer monitoring.

Monitoring cancer therapy is difficult because of restricted imaging depth, inadequate molecular specificity, and delayed response evaluation. Moreove...

Unsupervised Machine Learning-Based Process Analytical Tools for Near Real-Time Cell Morphology Analysis During CAR-T Cell Manufacturing.

Cell therapies like Chimeric Antigen Receptor (CAR)-T cell therapy deliver living cells to patients as active pharmaceutical ingredients. Manufacturin...

Deep Learning Methodology for Quantification of Normal Pancreas Structures.

Histopathologic evaluation plays a crucial role in assessing morphological tissue alterations in disease models and toxicology studies. Identifying sm...

A robust and scalable framework for hallucination detection in virtual tissue staining and digital pathology.

Histopathological staining of human tissue is essential for disease diagnosis. Recent advances in virtual tissue staining technologies using artificia...

Nanoneedles enable spatiotemporal lipidomics of living tissues.

Spatial biology provides high-content diagnostic information by mapping the molecular composition of tissues. However, traditional spatial biology app...

The melanoma MEGA-study: Integrating proteogenomics, digital pathology, and AI-analytics for precision oncology.

Melanoma remains the most aggressive form of skin cancer, characterized by high metastatic potential, genetic heterogeneity, and resistance to convent...

Application Value of Deep Learning-Based AI Model in the Classification of Breast Nodules.

Breast nodules are highly prevalent among women, and ultrasound is a widely used screening tool. However, single ultrasound examinations often result...

Advances in molecular pathology and therapy of non-small cell lung cancer.

Over the past two decades, non-small cell lung cancer (NSCLC) has witnessed encouraging advancements in basic and clinical research. However, substant...

Epithelial cell shape changes contribute to regulation of ureteric bud branching morphogenesis.

Branching morphogenesis orchestrates organogenesis in many tissues, including the kidney, where ureteric bud (UB) branching determines kidney size and...

Comparing machine learning isoscapes of Sr/Sr ratios of plants on the island of Sardinia: Implications for the use of isoscapes for assessing the provenance of biological specimens.

Strontium isotope analysis is widely used to evaluate the provenance and mobility of biological specimens. Frequently applied in archaeology, palaeont...

Advanced molecular approaches to thalassemia disorder and the selection of molecular-level diagnostic testing in resource-limited settings.

Beta-thalassemia is a genetic disorder that significantly burdens healthcare systems globally. This inherited blood disorder, categorized into beta-th...

3D bioprinting in tissue engineering: current state-of-the-art and challenges towards system standardization and clinical translation.

Over the past decade, 3D bioprinting has made significant progress, transforming into a key innovation in tissue engineering. Despite the early stride...

An artificial intelligence accelerated ab initio molecular dynamics dataset for electrochemical interfaces.

Understanding atomic-scale structures at electrochemical interfaces is essential for advancing research and applications in electrochemistry. While ex...

Identification of bacterial infection types in decomposition stages at various temperatures using pathology images and artificial intelligence algorithms.

Bacterial infections present a significant threat to human health, and accurate identification of infection type is crucial for both clinical and fore...

Classifying Stereotactic Radiosurgery Patients by Primary Diagnosis Using Natural Language Processing of Clinical Notes.

PURPOSE: Accurate identification of the primary tumor diagnosis of patients who have undergone stereotactic radiosurgery (SRS) from electronic health ...

Visualizing nuclear pore complex plasticity with pan-expansion microscopy.

The exploration of cell-type and environmentally responsive nuclear pore complex (NPC) plasticity requires new, accessible tools. Using pan-expansion ...

Multimodal deep learning for enhanced breast cancer diagnosis on sonography.

This study introduces a novel multimodal deep learning model tailored for the differentiation of benign and malignant breast masses using dual-view br...