Brain network topology and personality traits: A source level magnetoencephalographic study

Personality neuroscience is focusing on the correlation between individual differences and the efficiency of large-scale networks from the perspective of the brain as an interconnected network. A suitable technique to explore this relationship is the magnetoencephalography (MEG), but not many MEG studies are aimed at investigating topological properties correlated to personality traits. By using MEG, the present study aims to evaluate how individual differences described in Cloninger's psychobiological model are correlated with specific cerebral structures. Fifty healthy individuals (20 males, 30 females, mean age: 27.4 ± 4.8 years) underwent Temperament and Character Inventory examination and MEG recording during a resting state condition. High harm avoidance scores were associated with a reduced centrality of the left caudate nucleus and this negative correlation was maintained in females when we analyzed gender differences. Our data suggest that the caudate nucleus plays a key role in adaptive behavior and could be a critical node in insular salience network. The clear difference between males and females allows us to suggest that topological organization correlated to personality is highly dependent on gender. Our findings provide new insights to evaluate the mutual influences of topological and functional connectivity in neural communication efficiency and disruption as biomarkers of psychopathological traits

The Italian TREETALKER NETWORK (ITT-Net): continuous large scale monitoring of tree functional traits and vulnerabilities to climate change

20openItalian coauthor/editorThe Italian TREETALKER NETWORK (ITT-Net) aims to respond to one of the grand societal challenges: the impact of climate changes on forests ecosystem services and forest dieback. The comprehension of the link between these phenomena requires to complement the most classical approaches with a new monitoring paradigm based on large scale, single tree, high frequency and long-term monitoring tree physiology, which, at present, is limited by the still elevated costs of multi-sensor devices, their energy demand and maintenance not always suitable for monitoring in remote areas. The ITT-Net network will be a unique and unprecedented worldwide example of real time, large scale, high frequency and long-term monitoring of tree physiological parameters. By spring 2020, as part of a national funded project (PRIN) the network will have set 37 sites from the north-east Alps to Sicily where a new low cost, multisensor technology “the TreeTalker®” equipped to measure tree radial growth, sap flow, transmitted light spectral components related to foliage dieback and physiology and plant stability (developed by Nature 4.0), will monitor over 600 individual trees. A radio LoRa protocol for data transmission and access to cloud services will allow to transmit in real time high frequency data on the WEB cloud with a unique IoT identifier to a common database where big data analysis will be performed to explore the causal dependency of climate events and environmental disturbances with tree functionality and resilience. With this new network, we aim to create a new knowledge, introducing a massive data observation and analysis, about the frequency, intensity and dynamical patterns of climate anomalies perturbation on plant physiological response dynamics in order to: 1) characterize the space of “normal or safe tree operation mode” during average climatic conditions; 2) identify the non-linear tree responses beyond the safe operation mode, induced by extreme events, and the tipping points; 3) test the possibility to use a high frequency continuous monitoring system to identify early warning signals of tree stress which might allow to follow tree dynamics under climate change in real time at a resolution and accuracy that cannot always be provided through forest inventories or remote sensing technologies.openCastaldi, S.; Antonucci, S.; Asgharina, S.; Battipaglia, G.; Belelli Marchesini, L.; Cavagna, M.; Chini, I.; Cocozza, C.; Gianelle, D.; La Mantia, T.; Motisi, A.; Niccoli, F.; Pacheco Solana, A.; Sala, G.; Santopuoli, G.; Tonon, G.; Tognetti, R.; Zampedri, R.; Zorzi, I.; Valentini, R.Castaldi, S.; Antonucci, S.; Asgharina, S.; Battipaglia, G.; Belelli Marchesini, L.; Cavagna, M.; Chini, I.; Cocozza, C.; Gianelle, D.; La Mantia, T.; Motisi, A.; Niccoli, F.; Pacheco Solana, A.; Sala, G.; Santopuoli, G.; Tonon, G.; Tognetti, R.; Zampedri, R.; Zorzi, I.; Valentini, R

AB012. Transcriptional and chromatin profiling reveals the molecular architecture and druggable vulnerabilities of thymic epithelial tumors (TETs)

Thymic epithelial tumors (TETs) have been profiled to the present moment mainly through several analyses of FFPE samples. Despite the leap forward brought by the TCGA, several questions remain still unsolved. Among these, TETs are characterized by a strong component of immune infiltrate which makes the transcriptomic analyses conducted so far scarcely interpretable to profile stromal subpopulations constitutive of the tumor. Furthermore, rarely correspondent healthy tissue is available due to the lipomatous atrophy of aged thymi. Therefore, the recent report of (I) isolation, (II) propagation (III) and characterization of human thymic epithelial cells (TECs) and their capacity to reconstitute the functional organ ex vivo and in vivo, represents a novel approach to study the biology of both healthy and neoplastic thymi. Human thymic biopsies (both healthy and neoplastic) were digested and plated on a lethally irradiated murine feeder layer. Both RNA-Seq and CUTANDTAG were performed on cultivated TECs at different passages. Cultured TECs were injected with human thymic interstitial cells into rat decellularized scaffolds and cultivated for 10–12 days. sc-RNA Seq is currently being performed on both healthy and neoplastic thymic mini-organs and their correspondent primary tissues. Here show that we successfully cultivated a cohort of 21 clonogenic TECs in vitro including adult neoplastic TECs, their non-tumoral counterpart and pediatric TECs. We show that at the transcriptome level each class of TECs clusters independently and that neoplastic TECs belong to the same cloud independently from thymoma histotype. Around 1,400 differentially expressed genes (DEGs) can be found when comparing adult neoplastic and non-neoplastic counterpart, among which around 70 are transcription factors. Importantly, we prove for the first time that clonogenic TECs derived from TETs can repopulate a decellularized rat scaffold and recreate a 3D architecture mimicking the primary tumor. This work demonstrates that this culture system allows the expansion of clonogenic TECs from both tumor samples and their non-tumoral counterpart. Those cells, when transplanted into decellularized thymi, reproduce the architecture of the primary tissue, showing that TETs contain progenitor/stem epithelial cells. We are currently characterizing TECs at the transcriptomic and epigenomic level with aim of identifying new druggable targets prior to clinical trials

Using biochar for environmental recovery and boosting the yield of valuable non-food crops: the case of hemp in a soil contaminated by potentially toxic elements (PTEs)

Hemp (Cannabis sativa L.) is known to tolerate high concentrations of soil contaminants which however can limit its biomass yield. On the other hand, organic-based amendments such as biochar can immobilize soil contaminants and assist hemp growth in soils contaminated by potentially toxic elements (PTEs), allowing for environmental recovery and income generation, e.g. due to green energy production from plant biomass. The aim of this study was therefore to evaluate the suitability of a softwood-derived biochar to enhance hemp growth and promote the assisted phytoremediation of a PTE-contaminated soil (i.e., Sb 2175 mg kg-1; Zn 3149 mg kg-1; Pb 403 mg kg-1; and Cd 12 mg kg-1). Adding 3% (w/w) biochar to soil favoured the reduction of soluble and exchangeable PTEs, decreased soil dehydrogenase activity (by ~2.08-fold), and increased alkaline phosphomonoesterase and urease activities, basal respiration and soil microbial carbon (by ~1.18-, 1.22-, 1.22-, and 1.66-fold, respectively). Biochar increased the abundance of selected soil culturable microorganisms, while amplicon sequencing analysis showed a positive biochar impact on α-diversity and the induction of structural changes on soil bacterial community structure. Biochar did not affect root growth of hemp but significantly increased its aboveground biomass by ~1.67-fold for shoots, and by ~2-fold for both seed number and weight. Biochar increased the PTEs phytostabilisation potential of hemp with respect to Cd, Pb and Zn, and also stimulated hemp phytoextracting capacity with respect to Sb. Overall, the results showed that biochar can boost hemp yield and its phytoremediation effectiveness in soils contaminated by PTEs providing valuable biomass that can generate profit in economic, environmental and sustainability terms

Management of Asymptomatic Sporadic Nonfunctioning Pancreatic Neuroendocrine Neoplasms (ASPEN) <= 2 cm: Study Protocol for a Prospective Observational Study

Introduction: The optimal treatment for small, asymptomatic, nonfunctioning pancreatic neuroendocrine neoplasms (NF-PanNEN) is still controversial. European Neuroendocrine Tumor Society (ENETS) guidelines recommend a watchful strategy for asymptomatic NF-PanNEN <2 cm of diameter. Several retrospective series demonstrated that a non-operative management is safe and feasible, but no prospective studies are available. Aim of the ASPEN study is to evaluate the optimal management of asymptomatic NF-PanNEN ≤2 cm comparing active surveillance and surgery. Methods: ASPEN is a prospective international observational multicentric cohort study supported by ENETS. The study is registered in ClinicalTrials.gov with the identification code NCT03084770. Based on the incidence of NF-PanNEN the number of expected patients to be enrolled in the ASPEN study is 1,000 during the study period (2017–2022). Primary endpoint is disease/progression-free survival, defined as the time from study enrolment to the first evidence of progression (active surveillance group) or recurrence of disease (surgery group) or death from disease. Inclusion criteria are: age >18 years, the presence of asymptomatic sporadic NF-PanNEN ≤2 cm proven by a positive fine-needle aspiration (FNA) or by the presence of a measurable nodule on high-quality imaging techniques that is positive at 68Gallium DOTATOC-PET scan. Conclusion: The ASPEN study is designed to investigate if an active surveillance of asymptomatic NF-PanNEN ≤2 cm is safe as compared to surgical approach

Comparison of Epithelial Differentiation and Immune Regulatory Properties of Mesenchymal Stromal Cells Derived from Human Lung and Bone Marrow

Mesenchymal stromal cells (MSCs) reside in many organs including lung, as shown by their isolation from fetal lung tissues, bronchial stromal compartment, bronchial-alveolar lavage and transplanted lung tissues. It is still controversial whether lung MSCs can undergo mesenchymal-to-epithelial-transition (MET) and possess immune regulatory properties. To this aim, we isolated, expanded and characterized MSCs from normal adult human lung (lung-hMSCs) and compared with human bone marrow-derived MSCs (BM-hMSCs). Our results show that lung-MSCs reside at the perivascular level and do not significantly differ from BM-hMSCs in terms of immunophenotype, stemness gene profile, mesodermal differentiation potential and modulation of T, B and NK cells. However, lung-hMSCs express higher basal level of the stemness-related marker nestin and show, following in vitro treatment with retinoic acid, higher epithelial cell polarization, which is anyway partial when compared to a control epithelial bronchial cell line. Although these results question the real capability of acquiring epithelial functions by MSCs and the feasibility of MSC-based therapeutic approaches to regenerate damaged lung tissues, the characterization of this lung-hMSC population may be useful to study the involvement of stromal cell compartment in lung diseases in which MET plays a role, such as in chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis

Architecture and performance of the KM3NeT front-end firmware

The KM3NeT infrastructure consists of two deep-sea neutrino telescopes being deployed in the Mediterranean Sea. The telescopes will detect extraterrestrial and atmospheric neutrinos by means of the incident photons induced by the passage of relativistic charged particles through the seawater as a consequence of a neutrino interaction. The telescopes are configured in a three-dimensional grid of digital optical modules, each hosting 31 photomultipliers. The photomultiplier signals produced by the incident Cherenkov photons are converted into digital information consisting of the integrated pulse duration and the time at which it surpasses a chosen threshold. The digitization is done by means of time to digital converters (TDCs) embedded in the field programmable gate array of the central logic board. Subsequently, a state machine formats the acquired data for its transmission to shore. We present the architecture and performance of the front-end firmware consisting of the TDCs and the state machine

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

The Power Board of the KM3NeT Digital Optical Module: design, upgrade, and production

The KM3NeT Collaboration is building an underwater neutrino observatory at the bottom of the Mediterranean Sea consisting of two neutrino telescopes, both composed of a three-dimensional array of light detectors, known as digital optical modules. Each digital optical module contains a set of 31 three inch photomultiplier tubes distributed over the surface of a 0.44 m diameter pressure-resistant glass sphere. The module includes also calibration instruments and electronics for power, readout and data acquisition. The power board was developed to supply power to all the elements of the digital optical module. The design of the power board began in 2013, and several prototypes were produced and tested. After an exhaustive validation process in various laboratories within the KM3NeT Collaboration, a mass production batch began, resulting in the construction of over 1200 power boards so far. These boards were integrated in the digital optical modules that have already been produced and deployed, 828 until October 2023. In 2017, an upgrade of the power board, to increase reliability and efficiency, was initiated. After the validation of a pre-production series, a production batch of 800 upgraded boards is currently underway. This paper describes the design, architecture, upgrade, validation, and production of the power board, including the reliability studies and tests conducted to ensure the safe operation at the bottom of the Mediterranean Sea throughout the observatory's lifespa