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BMEF (BME Frontiers)


Deep learning-enabled virtual multiplexed immunostaining of label-free tissue for vascular invasion assessment

Researchers created a novel approach for simultaneous ERG, PanCK, and H&E image generation from label-free tissue sections, enhancing vascular invasion assessment accuracy and efficiency. The virtual multiplexed immunostaining method overcomes traditional IHC limitations, such as section-to-section variability and tissue loss.

SourceBMEF (BME Frontiers)·TypeExperimental study·DateMar 6, 2026

Dual-scale imaging platform captures metabolic and vascular adaptations in vivo, offering new insights for cancer treatment strategies

A multidisciplinary team developed a dual-scale Capillary-Cell microscope to visualize tumor metabolism and vasculature dynamics. The platform revealed complex relationships between tumor vascular network and metabolic behavior, highlighting distinct adaptations based on local conditions.

SourceBMEF (BME Frontiers)·JournalBME Frontiers·TypeExperimental study·DateJan 21, 2026

Machine learning approach to investigating macrophage polarization on various titanium surface characteristics

Researchers utilized machine learning models to identify key surface attributes modulating immune response, paving the way for improved implant materials. The study revealed pivotal factors regulating cytokine secretion and offered insights into designing alloys with optimized immunoregulatory functions.

SourceBMEF (BME Frontiers)·JournalBME Frontiers·TypeData/statistical analysis·DateApr 9, 2025

Deep learning-based virtual staining of tissue facilitates rapid assessment of breast cancer biomarker

A recent study published in BME Frontiers developed an AI-based approach that rapidly transforms autofluorescence images into virtual histological images for accurate HER2 assessment. This computational staining process takes only a few minutes per sample and does not require expensive facilities or toxic chemicals.

SourceBMEF (BME Frontiers)·JournalBME Frontiers·TypeExperimental study·DateOct 26, 2022