Biology subjects

Muratori, F.

Publications and source records attributed to Muratori, F..

4 recordsLinked to original sources

bioRxiv2026

Real-time mass-resolved label-free single-molecule immunoassay

Protein-protein interactions govern the biomolecular logic of immunity, signalling, and disease. Elementary rates of association, dissociation, and inhibition underpin our understanding of life processes and remain a limiting factor at the frontier of therapeutic discovery. Yet existing assays infer these processes indirectly through ensemble-averaged signals or molecular labels that obscure native dynamics. Here, we introduce a label-free, real-time, mass-resolved single-molecule immunoassay based on interferometric scattering microscopy (iSCAT) that directly observes individual protein-protein binding events in complex biological samples. By detecting light scattered from single proteins as they bind to an antibody-functionalized surface, we resolve discrete antibody-antigen interactions with single-molecule sensitivity and molecular-weight discrimination. Using IgM as a model system, we demonstrate real-time detection of individual binding events, with measured association rates that scale linearly with concentration over three orders of magnitude. Direct counts of IgM binding events in human serum yield quantitative concentrations that agree with bulk measurements obtained by enzyme-linked immunosorbent assay (ELISA). This bioaffinity iSCAT platform unifies molecular specificity, label-free detection, real-time kinetics, and mass-resolved single-molecule sensitivity, enabling direct access to protein-protein recognition processes and establishing a general framework for quantitative, single-molecule immunoassays.

biophysics↗

bioRxiv2021

Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium

Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls. Although these alterations affect multiple and widespread cortical regional asymmetries, the extent to which specific structural networks might be affected remains unknown. Inter-regional morphological covariance analysis can capture network connectivity relations between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1,455 individuals with ASD and 1,560 controls, across 43 independent datasets of the ENIGMA consortiums ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered asymmetry of hemispheric networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, driven by shifts toward higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve working memory, executive functions, language, reading, and sensorimotor processes. Taken together, these findings provide new insights into how altered brain left-right asymmetry in ASD affects specific structural and functional brain networks. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.

neuroscience↗

bioRxiv2019

Altered structural brain asymmetry in autism spectrum disorder: large-scale analysis via the ENIGMA Consortium

BackgroundLeft-right asymmetry is an important organizing feature of the healthy brain. Various studies have reported altered structural brain asymmetry in autism spectrum disorder (ASD). However, findings have been inconsistent, likely due to limited sample sizes and low statistical power.\n\nMethodsWe investigated 1,774 subjects with ASD and 1,809 controls, from 54 datasets, for differences in the asymmetry of thickness and surface area of 34 cerebral cortical regions. We also examined global hemispheric measures of cortical thickness and area asymmetry, and volumetric asymmetries of subcortical structures. Data were obtained via the ASD Working Group of the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. T1-weighted MRI data were processed with a single protocol using FreeSurfer and the Desikan-Killiany atlas.\n\nResultsASD was significantly associated with reduced leftward asymmetry of total hemispheric average cortical thickness, compared to controls. Eight regional thickness asymmetries, distributed over the cortex, also showed significant associations with diagnosis after correction for multiple comparisons, for which asymmetry was again generally lower in ASD versus controls. In addition, the medial orbitofrontal surface area was less rightward asymmetric in ASD than controls, and the putamen volume was more leftward asymmetric in ASD than controls. The largest effect size had Cohens d = 0.15. Most effects did not depend on age, sex, IQ, or disorder severity.\n\nConclusionAltered lateralized neurodevelopment is suggested in ASD, affecting widespread cortical regions with diverse functions. Large-scale analysis was necessary to reliably detect, and accurately describe, subtle alterations of structural brain asymmetry in this disorder.

neuroscience↗

bioRxiv2019

Visual processing and attention rather than face and emotion processing play a distinct role in ASD: an EEG study

Autism Spectrum Disorder results in deficit in social interaction, non-verbal communication and social reciprocity. Cognitive tasks pertaining to emotion processing are often preferred to distinguish the ASD children from the typically developing ones. We analysed the role of face and emotion processing in ASD and explored the feasibility of using EEG as a neural marker for detecting ASD. Subjects performed a visual perceptual task with face and nonface stimuli. Successful ASD detection was possible as early as 50 ms. post stimulus onset. Alpha and Beta oscillations seem to best identify autistic individuals. Multivariate pattern analysis and source localization studies points to the role of early visual processing and attention rather than emotion and face processing in detecting autism.

animal behavior and cognition↗