Biology subjects

Peruzzi, N.

Publications and source records attributed to Peruzzi, N..

3 recordsLinked to original sources

bioRxiv2026

Quantitative MRI-based assessment of the ultrastructural compactness of myelin lamellae

Efficient neuronal communication relying on rapid saltatory conduction depends not only on the amount of myelin wrapping axons but also on myelin compact organisation. Yet, current quantitative MRI myelin imaging methods, such as Myelin Water Imaging (MWI) and quantitative Magnetization Transfer (qMT), are designed to estimate myelin content and are often treated as interchangeable, overlooking myelin organisation. We introduce Structural Myelin Integrity (SMI), a quantitative MRI metric designed to distinguish myelin compact organisation from content. SMI combines the distinct biophysical sensitivities of MWI and qMT to separate the water confined between myelin layers from the total myelin membrane mass. We evaluated SMI in two rodent models of myelin decompaction and one remyelination model, validating our findings with synchrotron small-angle X-ray scattering and electron microscopy. SMI detected myelin layers decompaction despite largely preserved myelin membranes, revealing structural abnormalities that were not explained by myelin content alone. During remyelination, SMI returned closer to healthy values at early timepoints than myelin-content metrics, consistent with the formation of thin-but-compact sheaths. These findings indicate that myelin content and organisation can dissociate and establish SMI as a non-invasive marker of myelin organisation, compatible with existing clinical MRI approaches for studying white matter changes not detected today.

neuroscience↗

bioRxiv2026

Efficient murine cardiac phenotyping by combining synchrotron-based phase-contrast micro-CT, histology, immunofluorescence and spatial transcriptomics

1.Congenital heart disease is commonly studied using genetically modified mouse models, but characterization of complex three-dimensional (3D) cardiac anomalies remains technically challenging. Histology of fixed paraffin-embedded samples, typically used for structural and molecular analysis, is limited to two dimensions (2D). Synchrotron radiation-based phase-contrast micro-computed tomography (SRPC-{micro}CT) enables rapid, high-resolution, 3D imaging but had yet to be fully integrated with molecular tissue analysis. Importantly, SRPC-{micro}CT is nondestructive and compatible with paraffin-embedded tissue, potentially allowing integration with downstream molecular analyses such as multiplexed spatial transcriptomic profiling on tissue sections. Here, we present a pipeline combining SRPC-{micro}CT with complementary molecular approaches for rapid and accurate phenotyping of mouse hearts and for investigating disease mechanisms. We demonstrate the successful integration of high-resolution 3D imaging with spatial transcriptomics, fluorescent stainings, and histochemistry. Notably, all 2D modalities were applied sequentially to a single tissue section and registered within the 3D volume. This multimodal framework provides a powerful approach for linking structural and molecular information that is broadly applicable across biomedical research.

developmental biology↗

bioRxiv2025

Histology-guided 3D virtual staining of microCT-imaged lung tissue via deep learning

Histologically stained tissue sections are considered the gold standard for studying microscopic anatomy and diagnosing disease in clinical practice. However, the processes of sectioning and staining are laborious, and the overall method relies on two-dimensional (2D) analysis. In contrast, X-ray-based virtual histology offers the advantage of virtual sectioning while retaining the full three-dimensional (3D) volumetric representation of the tissue. Nevertheless, its grayscale nature has prevented it to be readily utilized by pathologists who are accustomed to conventional histological stains. In this work, we present a histology-guided enhancement platform that can integrate the 3D information provided by synchrotron radiation phase-contrast microCT with the rich visual features characteristic of histological stains. We introduce a multi-stage microCT-histology co-registration method combined with a virtual staining deep neural network and demonstrate successful virtual histological staining of microCT human and mouse lung tissue that closely resembles standard histology. We evaluate our strategy on multiple histological stains and apply it to identify 3D collagen-based remodeling of pulmonary arteries in patients with pulmonary hypertension. Overall, this innovative enhancement pipeline has the potential to aid in the incorporation of microCT into clinical practice, and advance non-destructive 3D pathology for improved diagnostic efficiency and accuracy.

pathology↗