How future surgery will benefit from SARS-COV-2-related measures: a SPIGC survey conveying the perspective of Italian surgeons

COVID-19 negatively affected surgical activity, but the potential benefits resulting from adopted measures remain unclear. The aim of this study was to evaluate the change in surgical activity and potential benefit from COVID-19 measures in perspective of Italian surgeons on behalf of SPIGC. A nationwide online survey on surgical practice before, during, and after COVID-19 pandemic was conducted in March-April 2022 (NCT:05323851). Effects of COVID-19 hospital-related measures on surgical patients' management and personal professional development across surgical specialties were explored. Data on demographics, pre-operative/peri-operative/post-operative management, and professional development were collected. Outcomes were matched with the corresponding volume. Four hundred and seventy-three respondents were included in final analysis across 14 surgical specialties. Since SARS-CoV-2 pandemic, application of telematic consultations (4.1% vs. 21.6%; p < 0.0001) and diagnostic evaluations (16.4% vs. 42.2%; p < 0.0001) increased. Elective surgical activities significantly reduced and surgeons opted more frequently for conservative management with a possible indication for elective (26.3% vs. 35.7%; p < 0.0001) or urgent (20.4% vs. 38.5%; p < 0.0001) surgery. All new COVID-related measures are perceived to be maintained in the future. Surgeons' personal education online increased from 12.6% (pre-COVID) to 86.6% (post-COVID; p < 0.0001). Online educational activities are considered a beneficial effect from COVID pandemic (56.4%). COVID-19 had a great impact on surgical specialties, with significant reduction of operation volume. However, some forced changes turned out to be benefits. Isolation measures pushed the use of telemedicine and telemetric devices for outpatient practice and favored communication for educational purposes and surgeon-patient/family communication. From the Italian surgeons' perspective, COVID-related measures will continue to influence future surgical clinical practice

Induction of mirror-touch synaesthesia by increasing somatosensory cortical excitability

4Understanding others' tactile sensations is a fundamental component of social behaviour. This complex process is most likely supported by a 'mirror' network for touch, which allows for an automatic and unconscious simulation of others' somatic states [1]. In everyday life, we are typically unaware of this process, because the system is physiologically active below the threshold of perceptual awareness. In a minority of persons with synaesthesia, however, the sight of a touch on another person elicits conscious tactile experiences on their own bodies - mirror-touch synaesthesia [2]. This peculiar crossmodal experience has been attributed to an unusual activation of the mirror mechanisms for touch - a visual stimulus that elicits a tactile sensation [3] - but this hypothesis requires empirical support. Here, we report the existence of a causal brain-behaviour relationship between increased excitability of two key areas of the tactile mirror system and the emergence of synaesthesia-like effects in non-synaesthetes. Furthermore, we show that individual differences in empathic capacity may modulate the ability to resonate with others' somatic feelings.reservedmixedN. Bolognini; C. Miniussi; S. Gallo; G. VallarN., Bolognini; Miniussi, Carlo; S., Gallo; G., Valla

Classifying Autism Spectrum Disorder Using the Temporal Statistics of Resting-State Functional MRI Data With 3D Convolutional Neural Networks

Resting-state functional magnetic resonance imaging (rs-fMRI) data are 4-dimensional volumes (3-space + 1-time) that have been posited to reflect the underlying mechanisms of information exchange between brain regions, thus making it an attractive modality to develop diagnostic biomarkers of brain dysfunction. The enormous success of deep learning in computer vision has sparked recent interest in applying deep learning in neuroimaging. But the dimensionality of rs-fMRI data is too high (~20 M), making it difficult to meaningfully process the data in its raw form for deep learning experiments. It is currently not clear how the data should be engineered to optimally extract the time information, and whether combining different representations of time could provide better results. In this paper, we explored various transformations that retain the full spatial resolution by summarizing the temporal dimension of the rs-fMRI data, therefore making it possible to train a full three-dimensional convolutional neural network (3D-CNN) even on a moderately sized [~2,000 from Autism Brain Imaging Data Exchange (ABIDE)-I and II] data set. These transformations summarize the activity in each voxel of the rs-fMRI or that of the voxel and its neighbors to a single number. For each brain volume, we calculated regional homogeneity, the amplitude of low-frequency fluctuations, the fractional amplitude of low-frequency fluctuations, degree centrality, eigenvector centrality, local functional connectivity density, entropy, voxel-mirrored homotopic connectivity, and auto-correlation lag. We trained the 3D-CNN on a publically available autism dataset to classify the rs-fMRI images as being from individuals with autism spectrum disorder (ASD) or from healthy controls (CON) at an individual level. We attained results competitive on this task for a combined ABIDE-I and II datasets of ~66%. When all summary measures were combined the result was still only as good as that of the best single measure which was regional homogeneity (ReHo). In addition, we also applied the support vector machine (SVM) algorithm on the same dataset and achieved comparable results, suggesting that 3D-CNNs could not learn additional information from these temporal transformations that were more useful to differentiate ASD from CON

Molecular imaging of multiple sclerosis: from the clinical demand to novel radiotracers

Abstract Background Brain PET imaging with different tracers is mainly clinically used in the field of neurodegenerative diseases and brain tumors. In recent years, the potential usefulness of PET has also gained attention in the field of MS. In fact, MS is a complex disease and several processes can be selected as a target for PET imaging. The use of PET with several different tracers has been mainly evaluated in the research setting to investigate disease pathophysiology (i.e. phenotypes, monitoring of progression) or to explore its use a surrogate end-point in clinical trials. Results We have reviewed PET imaging studies in MS in humans and animal models. Tracers have been grouped according to their pathophysiological targets (ie. tracers for myelin kinetic, neuroinflammation, and neurodegeneration). The emerging clinical indication for brain PET imaging in the differential diagnosis of suspected tumefactive demyelinated plaques as well as the clinical potential provided by PET images in view of the recent introduction of PET/MR technology are also addressed. Conclusion While several preclinical and fewer clinical studies have shown results, full-scale clinical development programs are needed to translate molecular imaging technologies into a clinical reality that could ideally fit into current precision medicine perspectives

The causal role of the somatosensory cortex in prosocial behaviour

Witnessing another person's suffering elicits vicarious brain activity in areas active when we ourselves are in pain. Whether this activity influences prosocial behavior remains debated. Here participants witnessed a confederate express pain via a reaction of the swatted hand or via a facial expression and could decide to reduce that pain by donating money. Participants donate more money on trials in which the confederate expressed more pain. EEG shows that activity of the SI hand region explains variance in donation; TMS shows that altering this activity interferes with the pain-donation coupling only when pain is expressed by the hand and HD-tDCS that altering SI activity also interferes with pain perception. These experiments show vicarious somatosensory activations contribute to prosocial decision-making and suggest they do so by helping transform observed reactions of affected body-parts into accurate perceptions of pain that are necessary for decision making

Intracranial Human Recordings Reveal Intensity Coding for the Pain of Others in the Insula

Based on neuroimaging data, the insula is considered important for people to empathize with the pain of others, whether that pain is perceived through facial expressions or the sight of limbs in painful situations. Here we present the first report of intracranial electroencephalographic (iEEG) recordings from the insulae collected while 7 presurgical epilepsy patients rated the intensity of a woman’s painful experiences viewed in movies. In two separate conditions, pain was deduced from seeing facial expressions or a hand being slapped by a belt. We found that broadband activity in the 20-190 Hz range correlated with the trial-by-trial perceived intensity in the insula for both types of stimuli. Using microwires at the tip of a selection of the electrodes, we additionally isolated 8 insular neurons with spiking that correlated with perceived intensity. Within the insula, we found a patchwork of locations with differing preferences within our stimulus set, some representing intensity only for facial expressions, others only for the hand being hit, and others for both. That we found some locations with intensity coding only for faces, and others only for hand across simultaneously recorded locations suggests that insular activity while witnessing the pain of others cannot be entirely reduced to a univariate salience representation. Psychophysics and the temporal properties of our signals indicate that the timing of responses encoding intensity for the sight of the hand being hit are best explained by kinematic information; the timing of those encoding intensity for facial expressions are best explained by shape information. In particular, the furrowing of the eyebrows and the narrowing of the eyes of the protagonist in the movies suffice to predict both the rating of, and the timing of the neuronal response to, the facial expressions. Comparing the broadband activity in the iEEG signal with spiking activity and an fMRI experiment with similar stimuli revealed a consistent spatial organization for the representation of intensity from our hand stimuli, with stronger intensity representation more anteriorly and around neurons with intensity coding. In contrast, for the facial expressions, we found that the activity at the three levels of measurement do not coincide, suggesting a more disorganized representation. Together, our intracranial recordings indicate that the insula encodes, in a partially intermixed layout, both static and dynamic cues from different body parts that reflect the intensity of pain experienced by others

Selective Grafting of Ga(i-Bu)3on the Silanols of Mesoporous H-ZSM-5 by Surface Organometallic Chemistry

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