Biology subjects

Ghezzi, S.

Publications and source records attributed to Ghezzi, S..

6 recordsLinked to original sources

bioRxiv2025

Supervised white matter bundle segmentation in glioma patients with transfer learning

In clinical settings, the virtual dissection of white matter tracts represents an informative source of information for monitoring neurological conditions or to support the planning of a treatment. The automation of this task using data-driven approaches, and in particular deep learning models, provides promising evidence of good accuracy when carried out on healthy individuals. However, the lack of large clinical datasets and the profound differences between healthy and clinical populations hinder the translation of these results to patients. Here, we investigated for the first time the effectiveness of transfer learning in adapting a deep learning architecture trained on a healthy population to glioma patients. Importantly, we provided the first thorough characterization of domain shift and its complexity, distinguishing systematic (i.e. measurement and pre-processing related) from tumor specific components. Our results suggest that (i) models trained on a large normative healthy population have a significant performance drop when the inference is carried out on patients; (ii) transfer learning can be an effective strategy to overcome the shortage of clinical data and to manage the systematic shift; (iii) fine tuning of the learning model cannot accommodate large white matter deformations induced by the tumor. The results were coherent across the five white matter bundles and three different input modalities tested, highlighting their robustness and generalizability. Our work provides valuable insights for advancing automated white matter segmentation in clinical populations and enhancing clinical transfer learning applications. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/659452v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@1c2bbbcorg.highwire.dtl.DTLVardef@1b3555eorg.highwire.dtl.DTLVardef@a9bb4dorg.highwire.dtl.DTLVardef@147dc5e_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIWhite matter bundle segmentation is essential for planning glioma tumor resection. C_LIO_LIWe trained a deep learning model on a healthy dataset to segment white matter bundles. C_LIO_LIWe observed a sub-optimal performance on glioma patients due to domain shift. C_LIO_LITransfer learning mitigated domain shift between healthy and clinical populations. C_LIO_LIWe highlighted domain shift domains solved/not solved by transfer learning. C_LI

neuroscience↗

bioRxiv2023

Supervised White Matter Bundle Segmentation in Glioma Patients with Transfer Learning

In clinical neuroscience, the segmentation of the main white matter bundles is propaedeutic for many tasks such as preoperative neurosurgical planning and monitoring of neuro-related diseases. Automating bundle segmentation with data-driven approaches and deep learning models has shown promising accuracy in the context of healthy individuals. The lack of large clinical datasets is preventing the translation of these results to patients. Inference on patients data with models trained on healthy population is not effective because of domain shift. This study aims to carry out an empirical analysis to investigate how transfer learning might be beneficial to overcome these limitations. For our analysis, we consider a public dataset with hundreds of individuals and a clinical dataset of glioma patients. We focus our preliminary investigation on the corticospinal tract. The results show that transfer learning might be effective in partially overcoming the domain shift.

neuroscience↗

bioRxiv2022

RAGE engagement by SARS-CoV-2 enables monocyte infection and underlies COVID-19 severity

The spread of SARS-CoV-2 has fueled the COVID-19 pandemic with its enduring medical and socioeconomic challenges due to subsequent waves and long-term consequences of great concern. Here we charted the molecular basis of COVID-19 pathogenesis, by analysing patients immune response at single-cell resolution across disease course and severity. This approach uncovered cell subpopulation-specific dysregulation in COVID-19 across disease course and severity and identified a severity-associated activation of the receptor for advanced glycation endproduct (RAGE) pathway in monocytes. In vitro experiments confirmed that monocytes bind the SARS-CoV-2 S1-RBD via RAGE and that RAGE-Spike interactions drive monocyte infection. Our results demonstrate that RAGE is a novel functional receptor of SARS-CoV-2 contributing to COVID-19 severity. One-Sentence SummaryMonocyte SARS-CoV-2 infection via the receptor for advanced glycation endproduct triggers severe COVID-19.

immunology↗

bioRxiv2021

Heparin protects human neural progenitor cells from Zika Virus-induced cell death and preserves their differentiation into mature neural-glia cells

Zika virus (ZIKV) is an arbovirus member of the Flaviviridae family that causes severe congenital brain anomalies in infected fetuses. Human neural progenitor cells (hNPCs) are highly permissive to ZIKV infection, causing inhibition of cell proliferation concomitant with an induction of cell death. We previously demonstrated that pharmaceutical-grade heparin inhibited virus-induced cell death with minor effects on in vitro virus replication in ZIKV-infected hNPCs. Here we show that heparin prevented ZIKV-induced intracellular vacuoles, a signature characteristic of paraptosis, but also inhibited necrosis and apoptosis of hNPCs when grown as neurospheres (NS). Furthermore, heparin preserved the differentiation of both ZIKV-infected human-induced pluripotent stem cells (hiPSC) derived-NPCs and fetus-derived NPCs into neural-glial cells. Collectively, these results highlight the potential neuroprotective effect of heparin that could be re-purposed and exploited to drive the development of novel agents for preventing ZIKV damage.

microbiology↗

bioRxiv2020

Rapid Inactivation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) by Tungsten Trioxide-Based (WO3) Photocatalysis

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the etiological agent of coronavirus disease 2019 (COVID-19), is transmitted person-to-person via respiratory droplets and, likely, via smaller droplet nuclei light enough to remain suspended in the air for hours and contaminate surfaces particularly in indoor conditions. Thus, effective measures are needed to prevent SARS-CoV-2 transmission in indoor environments. In this regard, we have investigated whether a system based on a filter combining Tungsten Trioxide-Based (WO3) photocatalysis and an antiviral fabric treated-copper nanocluster could inactivate SARS-CoV-2. To this purpose, an infectious SARS-CoV-2 suspension was introduced in the upper opening of a closed cylinder containing a WO3 filter and a lightbased system that activates WO3 and the antiviral fabric. From the bottom exit, aliquots of fluid were collected every 10 min (up to 60 min) and tested for their infectivity by means of a viral plaque assay in Vero cells whereas, in parallel, the viral RNA content was measured by quantitative PCR (qPCR). As we have previously shown for SARS-CoV, a 1:1,000 ratio of plaque forming units (PFU) vs. viral RNA copies was observed also for SARS-CoV-2. After 10 min, the infectious viral content was already decreased by 98.2% reaching 100% inactivation after 30 min whereas the SARS-CoV-2 RNA load was decreased of 1.5 log10 after 30 min. Thus, in spite of only a partial decrease of viral RNA, SARS-CoV-2 infectivity was completely abolished by the WO3 photocatalysis system by 30 min. These results support the hypothesis that this system could be exploited to achieve SARS-CoV-2 inactivation in indoor environments.

microbiology↗

bioRxiv2020

Vinegar and Its Active Component Acetic Acid Inhibit SARS-CoV-2 Infection In Vitro and Ex Vivo

Effective and economical measures are needed to either prevent or inhibit the replication of SARS-CoV-2, the causative agent of COVID-19, in the upper respiratory tract. As fumigation of vinegar at low concentration (0.34%) ameliorated the symptoms of mild SARS-CoV-2 infection, we tested in vitro the potential antiviral activity of vinegar and of its active component, acetic acid. We here demonstrate that both vinegar and acetic acid indeed strongly inactivate SARS-CoV-2 infectivity in Vero cells. Furthermore, vinegar treatment caused a 90% inhibition of the infectious titer when directly applied to a nasopharyngeal swab transfer medium of a COVID-19 patient. These effects were potentiated if conduced at a temperature of 45 {degrees}C vs. 37 {degrees}C, a condition that is transiently generated in the upper respiratory tract during fumigation. Our findings are consistent and extend the results of studies performed in the early and mid-20th century on the disinfectant capacity of organic acids and can provide an affordable home-made aid to prevent or contain SARS-CoV-2 infection of the upper respiratory tract.

microbiology↗