M. Leonetti

Bone pain in Fibrous dysplasia does not rely on aberrant sensory nerve sprouting or neuroma formation

This study shows that bone pain in Fibrous dysplasia is intrinsic and not caused by abnormal sensory nerve sprouting or neuroma formation.

Correlative imaging of spatio-angular dynamics of molecular assemblies and cells with multimodal instant polarization microscope

The paper introduces a new microscope, miPolScope, that enables label-free imaging of molecular and cellular architecture with high speed and resolution, and demonstrates its application on various biological samples.

mTOR activation induces endolysosomal remodeling and nonclassical secretion of IL-32 via exosomes in inflammatory reactive astrocytes

A technique for resolution assessment in blind-SIM experiments

The paper proposes a protocol to measure resolution enhancement in Scattering Assisted Imaging (SAI), a blind SIM technique, by testing different collection PSF values.

Self-Supervised Deep-Learning Encodes High-Resolution Features of Protein Subcellular Localization

The paper introduces cytoself, a self-supervised deep-learning method for protein localization profiling, achieving higher clustering accuracy than existing approaches.

Spatiotemporal dissection of the cell cycle with single-cell proteogenomics

The paper maps spatiotemporal proteomic heterogeneity during the cell cycle using single-cell proteogenomics and identifies 235 cell cycle-associated proteins.

Mapping the nucleolar proteome reveals a spatiotemporal organization related to intrinsic protein disorder

The paper maps the human nucleolar proteome, identifies a new subcompartment, and shows intrinsic disorder levels are higher in nucleolar and mitotic proteins.

Conserved function of ether lipids and sphingolipids in the early secretory pathway

The paper identifies hypersensitive mutants in lipid biosynthesis and trafficking genes in sphingolipid-depleted cells and shows coordinate regulation of ether and sphingolipids.

Revealing architectural order with quantitative label-free imaging and deep learning

This paper combines label-free imaging with deep learning to analyze biological structures, showing it can predict 3D fluorescent features in tissues.