Lorenzo Albertazzi

This paper introduces a 3D bioprinting technique called Mechanoscribed Xolography to create cell-laden hydrogels with controlled mechanical heterogeneity and monitors their evolution over time.

This paper develops a method to analyze cancer biomarkers at the nanoscale using single-molecule imaging on clinical liquid biopsies, revealing patient-specific heterogeneity and enabling cancer cell classification.

The paper introduces a computational package for visualizing, describing, and comparing nanoparticle datasets from super-resolution microscopy to analyze material properties and heterogeneity.

This paper introduces an automated DNA-PAINT workflow for nanoparticle characterization, improving throughput and reproducibility through simulation-guided imaging and analysis.

This study uses single particle tracking to analyze DNA origami interaction dynamics with cancer cells, revealing ligand-specific binding and density-dependent behavior.

This paper introduces Glyco-PAINT-APP, a method to quantify single-molecule glycan-mannose receptor binding kinetics on myeloid cells, revealing subcellular binding heterogeneity.

nanoFeatures is a cross-platform tool for quantitative analysis of super-resolution microscopy images of nanoparticles, extracting features like size, shape, and molecular abundance.

This study investigates how design parameters affect the binding of antibody-functionalized DNA nanostructures to cell surface receptors, finding that nanostructure size and DNA handle location influence receptor binding.