Biology subjects

Meloni, S.

Publications and source records attributed to Meloni, S..

4 recordsLinked to original sources

bioRxiv2026

Cortical plasticity of the tactile mirror system in borderline personality disorder

Individuals with borderline personality disorder (BPD) show alterations in empathic abilities, potentially involving automatic simulation processes supported by mirror-like mechanisms in the somatosensory domain. Within the tactile mirror system (TaMS), observing touch on another persons body activates cortical regions involved in tactile perception, including the primary somatosensory cortex (S1). Although mirror-like alterations have been suggested in BPD, the underlying mechanisms of plasticity remain underexplored. Here, we used a cross-modal paired associative stimulation (cm-PAS) protocol to investigate the plasticity mechanisms of TaMS functioning in BPD. Twenty-four individuals with BPD and 24 healthy controls (HCs) were included. Empathic abilities were assessed using self-report questionnaires. Participants performed tactile acuity and visuo-tactile spatial congruity (VTSC) tasks before and after a cm-PAS protocol. During cm-PAS, images of a hand being touched were paired with transcranial magnetic stimulation over the S1. The effects of cm-PAS were assessed on tactile acuity, as an index of S1 activity, and VTSC performance, as an index of TaMS functioning. Preregistered analyses revealed that patients with BPD tended to have lower cognitive empathy than HCs, with no significant cm-PAS effects on tactile acuity or VTSC performance in HCs, precluding between-group comparisons of plasticity effects. Exploratory analyses were conducted to further investigate potential sources of variability in the effects of cm-PAS, as well as the relationship between cognitive empathy and visuo-tactile processing as measure of TaMS functioning. Preregistered Stage 1 protocol: https://osf.io/sqnwd (date of in-principle acceptance: 25/06/2023).

neuroscience↗

bioRxiv2024

Investigating visuo-tactile mirror properties in Borderline Personality Disorder: a TMS-EEG study

Patients with Borderline Personality Disorder (pw-BPD) are characterized by lower levels of cognitive empathy compared to healthy controls (HCs), indicating difficulties in understanding others perspective. A candidate neural mechanism subtending empathic abilities is represented by the Tactile Mirror System (TaMS), which refers to mirror-like mechanisms in the somatosensory cortices. However, little is known about TaMS alterations in BPD, specifically in terms of brain connectivity within this network. Here, we aimed at providing novel insights on TaMS as neurophysiological candidate for BPD empathic deficits, with a special focus on TaMS connectivity by means of the combined use of transcranial magnetic stimulation and electroencephalography (TMS-EEG). Twenty pw-BPD and 20 HCs underwent a thorough investigation: we collected measures of empathic abilities obtained from self-report questionnaires, behavioral performance in a visuo-tactile spatial congruency task, and TMS-evoked potentials (TEPs) as effective connectivity indexes. In the TMS-EEG session, TMS was delivered over the right primary somatosensory cortex (S1) following the presentation of real touches and visual touches, while 74-channel EEG was continuously recorded. In the visuo-tactile spatial congruency task and the TMS-EEG recording, control conditions with visual touches on objects instead of body parts enabled to disentangle the involvement of TaMS from non-specific effects. The study is the first one employing TMS-EEG in pw-BPD and it has been preregistered before data collection. Consistent with previous findings, results show that pw-BPD reported significantly lower levels of cognitive empathy. Moreover, pw-BPD made significantly more errors than controls in the visuo-tactile spatial congruency task during visual touches on human body parts and not on objects. Finally, pw-BPD displayed a different connectivity pattern from S1-TEPs that was not specific for TaMS: they showed a lower P60 component during touch observation, as well as reduced amplitude of later TEPs responses (after [~]100 ms) during real touches. Overall, the present study shows behavioral evidence of TaMS impairment and a more general alteration in the connectivity pattern of the somatosensory network in pw-BPD.

neuroscience↗

bioRxiv2020

On the accuracy of molecular simulation-based predictions of koff values: a Metadynamics study

Molecular simulations have made great progresses in predicting koff values--the kinetic constant of drug unbinding, a key parameter for modern pharmacology--yet computed values under- or over-estimate experimental data in a system- and/or technique-dependent way. In an effort at gaining insights on this issue, here we used an established method to calculate koff values--frequency-adaptive metadynamics with force field-- and a subsequent QM/MM descriptions of the interactions. First, using force field-based metadynamics, we calculate koff of the Positron Emission Tomography (PET) ligand iperoxo targeting the human muscarinic acetylcholine receptor M2. In line with previously performed in silico studies, the prediction (3.7 {+/-} 0.7 * 10-4 s-1) turned out to differ significantly from the experimentally measured value (1.0 {+/-} 0.2 * 10-2 s-1). Next, we use DFT-based QM/MM simulations to show that this discrepancy arises from erroneous force field energetics at the transition state. It turns out that this discrepancy is partly caused by lack of electronic polarization and/or charge transfer in commonly employed force field. We expect these issues to arise also in other systems where charged portions of the system play a pivotal role, such as protein- or DNA-protein complexes. Graphical TOC Entry O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/015396v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1ee4e1aorg.highwire.dtl.DTLVardef@49ba0forg.highwire.dtl.DTLVardef@565f25org.highwire.dtl.DTLVardef@80940e_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2018

Unsupervised Extraction of Epidemic Syndromes from Participatory Influenza Surveillance Self-reported Symptoms

Seasonal influenza surveillance is usually carried out by sentinel general practitioners who compile weekly reports based on the number of influenza-like illness (ILI) clinical cases observed among visited patients. This practice for surveillance is generally affected by two main issues: i) reports are usually released with a lag of about one week or more, ii) the definition of a case of influenza-like illness based on patients symptoms varies from one surveillance system to the other, i.e. from one country to the other. The availability of novel data streams for disease surveillance can alleviate these issues; in this paper, we employed data from Influenzanet, a participatory web-based surveillance project which collects symptoms directly from the general population in real time. We developed an unsupervised probabilistic framework that combines time series analysis of symptoms counts and performs an algorithmic detection of groups of symptoms, hereafter called syndromes. Symptoms counts were collected through the participatory web-based surveillance platforms of a consortium called Influenzanet which is found to correlate with Influenza-like illness incidence as detected by sentinel doctors. Our aim is to suggest how web-based surveillance data can provide an epidemiological signal capable of detecting influenza-like illness temporal trends without relying on a specific case definition. We evaluated the performance of our framework by showing that the temporal trends of the detected syndromes closely follow the ILI incidence as reported by the traditional surveillance, and consist of combinations of symptoms that are compatible with the ILI definition. The proposed framework was able to predict quite accurately the ILI trend of the forthcoming influenza season based only on the available information of the previous years. Moreover, we assessed the generalisability of the approach by evaluating its potentials for the detection of gastrointestinal syndromes. We evaluated the approach against the traditional surveillance data and despite the limited amount of data, the gastrointestinal trend was successfully detected. The result is a real-time flexible surveillance and prediction tool that is not constrained by any disease case definition.\n\nAuthor summaryThis study suggests how web-based surveillance data can provide an epidemiological signal capable of detecting influenza-like illness temporal trends without relying on a specific case definition. The proposed framework was able to predict quite accurately the ILI trend of the forthcoming influenza season based only on the available information of the previous years. Moreover, we assessed the generalisability of the approach by evaluating its potentials for the detection of gastrointestinal syndromes. We evaluated the approach against the traditional surveillance data and despite the limited amount of data, the gastrointestinal trend was successfully detected. The result is a real-time flexible surveillance and prediction tool that is not constrained by any disease case definition.

epidemiology↗