Pathology

A deep learning and morphometric hybrid model for automated quantification of kidney interstitial fibrosis in trichrome-stained whole-slide image.

BACKGROUND: Interstitial fibrosis (IF) is the strongest predictor of chronic kidney disease progression. Visual estimation of IF from trichrome (TRI)-stained slides has high interobserver variability and limited reproducibility. METHODS: We developed and validated TRI_IF, a deep learning algorithm that mimics a nephropathologist's workflow to quantify IF from TRI-stained whole-slide images (WSIs) ...

A systematic evaluation of grayscale conversion methods for mitigating color variation in deep learning-based histopathological image analysis.

The clinical adoption of deep learning (DL) for histopathological image analysis is hindered by performance degradation caused by color variations arising from disparate staining protocols and scanning technologies. As morphological features may effectively provide the diagnostic information in hematoxylin and eosin slides, this study investigated grayscale conversion as an approach to standardize...

Computational discovery and prioritization of ribose-5-phosphate isomerase A as a mitochondrial target for reversing senescence in mesenchymal stem cells.

Age-related osteoporosis is increasingly recognized as a disease of stem cell dysfunction, hallmarked by the skewed lineage commitment of mesenchymal ...

An integrative genomic framework to identify remote ischemic preconditioning-responsive genes associated with stroke risk.

BACKGROUND: Remote ischemic preconditioning (RIPC) is a promising, non-invasive strategy for reduction in ischemic injury after stroke, yet its molecu...

Early detection of female-specific cancers using longitudinal healthcare records with a multichannel convolutional neural network.

OBJECTIVES: Female-specific cancers, including breast, ovarian, cervical and uterine malignancies, lack comprehensive early detection approaches, part...

Start4All protocol for a Bayesian cost-effectiveness model of tuberculosis screening and diagnosis in seven high burden low-income and middle-income countries.

INTRODUCTION: High costs of screening and diagnostic tests remain a major barrier to timely tuberculosis (TB) identification in resource-limited setti...

[The Digital Lab: Practical digital workflow and integration of AI for routine in pathology, through the example of prostate cancer].

Digital pathology is a major technological revolution for pathology. It modernizes routine practices and paves the way for the integration of artifici...

Radiomics-based differentiation of benign and malignant breast masses on contrast-enhanced mammography: a reproducible workflow using open-source tools.

PURPOSE: To differentiate benign and malignant breast masses by extracting radiomic features from low-energy and recombined contrast-enhanced mammogra...

Intelligent Stain-Free Histology on Structural Colorimetric Nanocavities.

Optical microscopic imaging and analysis are indispensable in modern pathology for providing conclusive evidence in disease diagnosis. However, the cu...

Advances in extracellular vesicle research: tools and techniques.

Extracellular vesicles (EVs) are lipid bilayer vesicles produced endogenously by all cell types and they contain cytosolic, extracellular, and membran...

Association of Circulating T Cell and Tumor Microenvironment Profiles with Immune Checkpoint Blockade Outcome in Sarcoma.

PURPOSE: Immune checkpoint blockade (ICB) benefits only a subset of sarcoma patients. Biomarkers of response and resistance are needed to help guide p...

Ancestry-Associated Performance Variability of Open-Source AI Models for EGFR Prediction in Lung Cancer.

IMPORTANCE: Artificial intelligence (AI) models are emerging as rapid, low-cost tools for predicting targetable genomic alterations directly from rout...

Volume electron microscopy reveals heterogeneity of the hemostatic response in veins and arteries.

Intravital imaging studies have provided insights into the spatial and temporal variations of platelet activation and thrombin generation that occur d...

[Application of a novel robot-assisted navigation system in CT-guided percutaneous lung biopsy].

Objective: To compare the clinical efficacy and safety of robot-assisted navigation systems with those of the conventional puncture localization metho...

Large-Scale Histological Image Dataset with Metadata for Colorectal Cancer Microenvironment.

The pronounced heterogeneity of the tumor microenvironment (TME) in colorectal cancer (CRC) presents major obstacles in accurately predicting patient ...

Development of a multi-task learning framework with gradnorm for precise wound tissue analysis.

Chronic wounds impose a substantial burden on patients and healthcare systems, necessitating accurate qualification of precise wound analysis for effe...

NTDscope: A multi-contrast portable microscope for disease diagnosis.

Accurate diagnostics are essential for disease control and elimination efforts. However, access to diagnostics for neglected tropical diseases (NTDs) ...

Redefining Pathobiology with Spatial Multi-Omics at the Intersection of Biology, Computation, and Histopathological Assessment.

Spatial profiling technologies are transforming our understanding of tissue organization by enabling high-resolution mapping of molecular features in ...

Multimodal activity-affinity assay of ADAM-10 extracellular vesicles in untreated plasma reveals metastatic stage of colorectal cancer.

Metalloproteinases (MPs) such as a-disintegrin and metalloproteinase-10 (ADAM-10) are key drivers of extracellular matrix remodeling during tumor prog...

Automated segmentation of pterygium lesions using multiscale deep learning networks.

Pterygium is an eye condition that needs to be identified at an early stage so that its progression can be mitigated in order to avoid the possible th...