Biology subjects

Vitali, P.

Publications and source records attributed to Vitali, P..

5 recordsLinked to original sources

bioRxiv2021

White matter microstructure characterisation in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is the most common form of focal epilepsy. Parameters of microstructural abnormalities derived from diffusion tensor imaging(DTI) have been reported to be helpful in differentiating between Left and Right TLE (L-TLE and R-TLE) but few of them compared L-TLE and R-TLE with a voxelwise approach. In this study, a whole brain tract based spatial statistical analysis was performed on DTI, diffusion kurtosis and NODDI derived parameters of 88 subjects to identify specific white matter patterns of alteration in patient affected by L-TLE and R-TLE with respect to healthy controls. Our findings demonstrated the presence of specific patterns of white matter alterations, with L-TLE more widely affected both in cerebral and cerebellar regions. This result supports the need to consider patients separately, according to the side of their pathology.

neuroscience↗

bioRxiv2021

Long non-coding RNA Neat1 is a key translational regulator in hypoxia.

Internal ribosome entry sites (IRESs) drive translation initiation during stress. In response to hypoxia, (lymph)angiogenic factors responsible for tissue revascularization in ischemic diseases are induced by the IRES-dependent mechanism. Here we searched for IRES trans-acting factors (ITAFs) active in early hypoxia in mouse cardiomyocytes. Using knock-down and proteomics approaches, we show a link between a stressed-induced nuclear body, the paraspeckle, and IRES-dependent translation. Furthermore, smiFISH experiments demonstrate the recruitment of IRES-containing mRNA into paraspeckle during hypoxia. Our data reveal that the long non-coding RNA Neat1, an essential paraspeckle component, is a key translational regulator, active on IRESs of (lymph)angiogenic and cardioprotective factor mRNAs. In addition, paraspeckle proteins p54nrb and PSPC1 as well as nucleolin and Rps2, two p54nrb-interacting proteins identified by mass spectrometry, are ITAFs for IRES subgroups. Paraspeckle thus appears as a platform to recruit IRES-containing mRNAs and possibly host IRESome assembly. Polysome PCR array shows that Neat1 isoforms regulate IRES-dependent translation and, more widely, translation of mRNAs involved in stress response. HighlightsO_LIParaspeckle formation correlates with activation of translation via internal ribosome entry sites (IRES) in mouse hypoxic cardiomyocytes as well as in tumoral cells. C_LIO_LIThe long non-coding RNA Neat1, an essential paraspeckle component, is a key translational regulator of (lymph)angiogenic and cardioprotective factor expression in this process. C_LIO_LIIRES-containing mRNA is recruited into paraspeckles during hypoxia. C_LIO_LIParaspeckle proteins p54nrb and PSPC1 as well as two p54nrb-interacting proteins, nucleolin and RPS2, contribute to this process. C_LIO_LIParaspeckle appears as a platform for IRESome formation in the nucleus. C_LIO_LIThe Neat1 isoforms widely regulate the translation of mRNAs containing IRESs and of genes involved in the stress response. C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/430272v2_ufig1.gif" ALT="Figure 1"> View larger version (98K): org.highwire.dtl.DTLVardef@1741648org.highwire.dtl.DTLVardef@62e741org.highwire.dtl.DTLVardef@13c86a8org.highwire.dtl.DTLVardef@acae63_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2020

Automatic segmentation of dentate nuclei for microstructure assessment: example of application to temporal lobe epilepsy patients

Dentate nuclei (DNs) segmentation is helpful for assessing their potential involvement in neurological diseases. Once DNs have been segmented, it becomes possible to investigate whether DNs they are microstructurally affected, through analysis of quantitative MRI parameters, such as the ones derived from diffusion weighted imaging (DWI). This study, therefore, aimed to develop a fully automated segmentation method using the non-DWI (b0) images from a DWI dataset to obtain DN masks inherently registered with parameter maps. Three different automatic methods were applied to healthy subjects in order to segment the DNs: registration to SUIT (a spatially unbiased atlas template of the cerebellum and brainstem), OPAL (Optimized Patch Match for Label fusion) and CNN (Convolutional Neural Network). DNs manual segmentation was considered the gold standard. Results show that the segmentation obtained with SUIT has an average Dice Similarity Coefficient (DSC) of 0.4907{+/-}0.0793 between the automatic SUIT masks and the gold standard. A comparison with manual masks was also performed for OPAL (DSC = 0.7624 {+/-} 0.1786) and CNN (DSC = 0.8658 {+/-} 0.0255), showing a better performance when using CNN. OPAL and CNN were optimised on heathy subjects data with high spatial resolution from the Human Connectome Project. The three methods were further used to segment the DNs of a subset of subjects affected by Temporal Lobe Epilepsy (TLE). This subset was derived from a 3T MRI research study which included DWI data acquired with a coarser resolution. In TLE dataset, SUIT performed similarly to using the HCP dataset, with a DSC = 0.4145 {+/-} 0.1023. Using TLE data, OPAL performed worse than using HCP data: after changing the probability threshold the DSC was 0.4522 {+/-} 0.1178. CNN was able to extract the DNs using the TLE data without need for retraining and with a good DSC = 0.7368 {+/-} 0.0799. Statistical comparison of quantitative parameters derived from DWI analysis, as well as volumes of each DN, revealed altered and lateralised changes in TLE patients compared to healthy controls. The proposed CNN is therefore a viable option for accurate extraction of DNs from b0 images of DWI data with different resolutions and acquired at different sites.

bioengineering↗

bioRxiv2020

Impact of long- and short-range fiber depletion on the cognitive deficits of fronto-temporal dementia

Fronto-temporal dementia (FTD) is a neurodegenerative disease characterized by focal atrophy of the gray matter (GM), especially in the frontal and temporal regions. Recent studies suggest a framework where white matter (WM) atrophy plays an important role in FTD pathophysiology. However, these studies often overlook the fact that WM tracts bridging different brain regions may have different vulnerabilities to the disease and the relative contribution of GM atrophy to this WM model, resulting in a less comprehensive understanding of the relationship between clinical symptoms and pathology. Here, by leveraging the sensitivity of advanced diffusion MRI modelling and metrics to precise white matter microstructural properties, we aim to clarify the relative contributions of WM fibers and GM atrophy to the cognitive symptoms typically found in FTD. A total of 155 participant from the Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI) were analysed, including 68 normal elderly controls (CN), 28 behavioral variants (BV), 26 sematic variants (SV) and 30 progressive non fluent aphasia variants (PNFA) of FTD. Diffusion MRI analysis was performed using two complementary techniques: whole brain fixel-based analysis (FBA) and structural connectivity based on probabilistic tractography. Whole brain GM atrophy was assessed using voxel-based morphometry (VBM). Using a common factor analysis to extract a semantic and an executive factor, we aim to test the relative contribution of WM and GM of specific tracts in predicting cognition. We found that semantic symptoms were mainly dependent on short-range WM fiber disruption, while damage to long-range WM fibers was preferentially associated to executive dysfunction with the GM contribution to cognition being predominant for local processing. Our results support the importance of the disruption of specific WM tracts to the core cognitive symptoms associated with FTD. As large-scale WM tracts, which are particularly vulnerable to vascular disease, were highly associated with executive dysfunction, our findings highlight the importance of controlling for risk factors associated with deep white matter disease, such as vascular risk factors, in patients with FTD in order not to potentiate underlying executive dysfunction.

neuroscience↗

bioRxiv2019

Cervical spinal cord atrophy and Alzheimer’s disease

ObjectiveBrain atrophy is an established biomarker for dementia, yet spinal cord involvement has not been investigated to date. As the spinal cord is relaying sensorimotor control signals from the cortex to the peripheral nervous system and viceversa, it is indeed a very interesting question to assess whether it is affected by atrophy in a disease that is known for its involvement of cognitive domains first and foremost, with motor symptoms being clinically assessed too. We therefore hypothesize that Alzheimer Disease severe atrophy can affect the spinal cord too and that spinal cord atrophy is indeed an important in vivo imaging biomarker contributing to understanding neurodegeneration associated with dementia.\n\nMethods3DT1 images of 31 Alzheimers disease (AD) and 35 healthy control (HC) subjects were processed to calculate volumes of brain structures and cross-sectional area (CSA) and volume (CSV) of the cervical cord (per vertebra as well as the C2-C3 pair (CSA23 and CSV23)). Correlated features ({rho}>0.7) were removed, and best subset identified for patients classification with the Random Forest algorithm. General linear model regression was used to find significant differences between groups (p<=0.05). Linear regression was implemented to assess the explained variance of the Mini Mental State Examination (MMSE) score as dependent variable with best features as predictors.\n\nResultsSpinal cord features were significantly reduced in AD, independently of brain volumes. Patients classification reached 76% accuracy when including CSA23 together with volumes of hippocampi, left amygdala, white and grey matter, with 74% sensitivity and 78% specificity. CSA23 alone explained 13% of MMSE variance.\n\nDiscussionOur findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. Results show that CSA23, calculated form the same 3DT1 scan as all other brain volumes (including right and left hippocampi), has a considerable weight in classification tasks warranting further investigations. Together with recent studies revealing that AD atrophy is spread beyond the temporal lobes, our result adds the spinal cord to a number of unsuspected regions involved in the disease. Interestingly, spinal cord atrophy explains also cognitive scores, which could significantly impact how we model sensorimotor control in degenerative diseases with a primary cognitive domain involvement. Prospective studies should be purposely designed to understand the mechanisms of atrophy and the role of the spinal cord in AD.

neuroscience↗