A new study unveils a method to non-invasively monitor cell spatiotemporal dynamics involved in cancer progression in a ...

Our findings confirmed that incorporating nuclei segmentation significantly enhances classification performance and model interpretability. The proposed model enhances feature localization by ...

This study addresses the critical challenge of cell nuclei segmentation in histopathological image analysis, which is essential for cancer diagnosis and prognosis. Traditional segmentation methods ...

AbstractTo explore how early cancers can be detected prior to clinical signs or symptoms, we assessed prospectively collected serial plasma samples from the Atherosclerosis Risk in Communities study, ...

Proliferating cell nuclear antigen (PCNA) is a central regulator of numerous cellular processes impacting DNA metabolism and genetic integrity, including DNA damage, cell cycle progression, and ...

A new AI tool, AAnet, has discovered five distinct cell types within tumors, offering a deeper look into cancer's inner diversity. This insight could transform how we treat cancer, enabling ...

Neurons often receive organelles called mitochondria from other cells. It emerges that neurons donate mitochondria that support cancer-cell spread.

Through this, they identified five different cancer cell groups within a tumor, with distinct gene expression profiles that indicated vast differences in cell behavior.

To evaluate the efficacy of patritumab deruxtecan (HER3-DXd) in patients with advanced non–small cell lung cancer without common EGFR -activating mutations. Knowledge Generated HER3-DXd therapy ...

Survival for non-small-cell lung cancer (NSCLC) remains unacceptably low, even in stage IA–IIA. Current guidelines recommend adjuvant treatment for patients considered to be at high risk in stages IB ...

Self-supervised deep learning models can accurately perform 3D segmentation of cell nuclei in complex biological tissues, enabling scalable analysis in settings with limited or no ground truth ...