Quantitative cytoarchitectural phenotyping of deparaffinized human brain tissues

Year: 2025

Authors: Di Meo D., Sorelli M., Ramazzotti J., Cheli F., Bradley S., Perego L., Lorenzon B., Mazzamuto G., Emmi A., Porzionato A., De Caro R., Garbelli R., Biancheri D., Pelorosso C., Conti V., Guerrini R., Pavone F.S., Costantini I.

Autors Affiliation: Univ Florence, European Lab Nonlinear Spect LENS, Sesto Fiorentino, Italy; Univ Florence, Dept Biol, Sesto Fiorentino, Italy; Univ Florence, Dept Informat Engn, Florence, Italy; Univ Florence, Dept Phys & Astron, Sesto Fiorentino, Italy; CNR, Natl Inst Opt INO, Natl Res Council, Sesto Fiorentino, Italy; Univ Padua, Inst Human Anat, Dept Neurosci, Padua, Italy; Fdn IRCCS Ist Neurol Carlo Besta, Epilepsy Unit, Milan, Italy; Meyer Childrens Hosp IRCCS, Dept Neurosci & Med Genet, Florence, Italy; Univ Florence, Dept Neurosci Psychol Drug Res & Child Hlth, Florence, Italy.

Abstract: Advanced 3D imaging techniques and image segmentation and classification methods can transform biomedical research by offering insights into the human brain cytoarchitecture under pathological conditions. We propose a comprehensive pipeline for 3D imaging and automated quantitative cellular phenotyping on Formalin-Fixed Paraffin-Embedded human brain specimens. We exploit the versatility of our method by applying it to different human specimens from both adult and pediatric, normal and abnormal brain regions. Quantitative data on neuronal morphology, local density, and spatial clustering level are obtained from a machine-learning-based analysis of the 3D cytoarchitectural organization of cells identified by different molecular markers in two subjects with malformations of cortical development. This approach grants access to a wide range of clinical specimens, allowing for volumetric imaging and quantitative analysis of human brain samples at cellular resolution. Possible genotype-phenotype correlations can be unveiled, providing insights into the pathogenesis of various brain diseases and enlarging treatment opportunities.

Journal/Review: COMMUNICATIONS BIOLOGY

Volume: 8 (1)      Pages from: 1527-1  to: 1527-13

More Information: We thank Dr. Giuseppe de Vito (from University of Florence, National Research Council – National Institute of Optics, and the European Laboratory for Non-Linear Spectroscopy, LENS) for his useful suggestions on the adopted statistical analysis approaches. We express our gratitude to the donors involved in the body and tissue donation programs who made this study possible by generously donating their brains to science. This project was supported by the European Union’s Horizon Europe research and innovation program under grant agreement No. 101147319 (EBRAINS 2.0) and under grant agreement No. 654148 (Laserlab-Europe). From the Italian Ministry for Education in the framework of Euro-Bioimaging Italian Node (ESFRI research infrastructure) and by the European Union – Next Generation EU, Mission 4 Component 1, CUP B53C22001810006, Project IR0000023 SeeLife Strengthening the Italian Infrastructure of Euro-Bioimaging. From the General Hospital Corporation Center of the National Institutes of Health under award number U01 MH117023 and BRAIN CONNECTS (award number U01 NS132181). The content of this work is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health-USA. The work was also supported by grants to RG from the Tuscany Region Call for Health 2018 (project DECODE-EE), Fondazione Cassa di Risparmio di Firenze (project Human Brain Optical Mapping), and the Ministry of University and Research (MUR), National Recovery and Resilience Plan (NRRP), project MNESYS (PE0000006). This work was also supported, in part, by funds from the ’Current Research Annual Funding’ of the Italian Ministry of Health (to R.Gu. and V.C.). The research was also funded by RICTD2025_2026-CUP: B97G24000240005, by LENS and CNR for the technical and scientific support to the Italian National Node FOE 2022 – CUP B53C24004790001. From the University of Florence (D.R. n. 464 del 02/04/2024) with the project Smart hydrogels with enhanced toughness to enable human brain tissue clearing (SMART-brain), CUP: B97G24000240005.
KeyWords: Single-cell Resolution; Light-sheet Microscopy; Whole-body; Neurons; Number; Hippocampus; Volume
DOI: 10.1038/s42003-025-08887-y