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Abstract Motor fatigue in Multiple Sclerosis (MS) is due to reduced motor cortex (M1) output and altered sensorimotor network (SMN) modulation. Natalizumab, a disease-modifying therapy, reduces neuroinflammation and improves fatigue. However, some patients treated with natalizumab experience fatigue recurrence (‘wearing-off’) before subsequent infusions. Wearing-off provides a valuable window into MS-related motor fatigue mechanisms in a controlled, clinically stable, setting. This study investigates whether wearing-off is associated with worsening motor fatigue and its neurophysiological mechanisms and assesses natalizumab’s effect on MS-related fatigue. Forty-five relapsing–remitting MS patients with wearing-off symptoms were evaluated pre- and post-natalizumab infusion. Assessments included evaluating disability levels, depressive symptoms, and the impact of fatigue symptoms on cognitive, physical, and psychosocial functioning. The motor fatigue index was computed through the number of blocks completed during a fatiguing task and peripheral, central, and supraspinal fatigue (M1 output) were evaluated by measuring the superimposed twitches evoked by peripheral nerve and transcranial magnetic stimulation of M1. Transcranial magnetic stimulation-electroencephalography assessed M1 effective connectivity by measuring TMS-evoked potentials (TEPs) within the SMN before- and after the task. We found that wearing-off was associated with increased motor fatigue index, increased central and supraspinal fatigue, and diminished task-related modulation of TEPs compared to post-natalizumab infusion. Wearing-off was also associated with worsened fatigue impact and depression symptom scores. We conclude that the wearing-off phenomenon is associated with worsening motor fatigue due to altered M1 output and modulation of the SMN. Motor fatigue in MS may reflect reversible, inflammation-related changes in the SMN that natalizumab can modulate. Our findings apply primarily to MS patients receiving natalizumab, emphasizing the need for further research on other treatments with wearing-off.

Abstract Urinary tract infections (UTIs) are the most common bacterial infections and uropathogenic Escherichia coli (UPEC) is the main etiological agent of UTIs. UPEC can persist in bladder cells protected by immunological defenses and antibiotics and intracellular behavior leads to difficulty in eradicating the infection. The aim of this paper is to design, prepare and characterize surfactant-based nanocarriers (niosomes) able to entrap antimicrobial drug and potentially to delivery and release antibiotics into UPEC-infected cells. In order to validate the proposed drug delivery system, gentamicin, was chosen as “active model drug” due to its poor cellular penetration. The niosomes physical–chemical characterization was performed combining different techniques: Dynamic Light Scattering Fluorescence Spectroscopy, Transmission Electron Microscopy. Empty and loaded niosomes were characterized in terms of size, ζ-potential, bilayer features and stability. Moreover, Gentamicin entrapped amount was evaluated, and the release study was also carried out. In addition, the effect of empty and loaded niosomes was studied on the invasion ability of UPEC strains in T24 bladder cell monolayers by Gentamicin Protection Assay and Confocal Microscopy. The observed decrease in UPEC invasion rate leads us to hypothesize a release of antibiotic from niosomes inside the cells. The optimization of the proposed drug delivery system could represent a promising strategy to significatively enhance the internalization of antimicrobial drugs.

Abstract Cranial reconstructions are essential for restoring both function and aesthetics in patients with craniofacial deformities or traumatic injuries. Titanium prostheses have gained popularity due to their biocompatibility, strength, and corrosion resistance. The use of Superplastic Forming (SPF) and Single Point Incremental Forming (SPIF) techniques to create titanium prostheses, specifically designed for cranial reconstructions was investigated in an ovine model through microtomographic and histomorphometric analyses. The results obtained from the explanted specimens revealed significant variations in bone volume, trabecular thickness, spacing, and number across different regions of interest (VOIs or ROIs). Those regions next to the center of the cranial defect exhibited the most immature bone, characterized by higher porosity, decreased trabecular thickness, and wider trabecular spacing. Dynamic histomorphometry demonstrated differences in the mineralizing surface to bone surface ratio (MS/BS) and mineral apposition rate (MAR) depending on the timing of fluorochrome administration. A layer of connective tissue separated the prosthesis and the bone tissue. Overall, the study provided validation for the use of cranial prostheses made using SPF and SPIF techniques, offering insights into the processes of bone formation and remodeling in the implanted ovine model.

Abstract Despite intense and costly treatments, developmental dyslexia (DD) often persists into adulthood. Several brain skills unrelated to speech sound processing (i.e., phonology), including the spatial distribution of visual attention, are abnormal in DD and may represent possible treatment targets. This study explores the efficacy in DD of rightward prismatic adaptation (rPA), a visuomotor adaptation technique that enables visuo-attentive recalibration through shifts in the visual field induced by prismatic goggles. A digital intervention of rPA plus cognitive training was delivered weekly over 10 weeks to adolescents with DD (aged 13–17) assigned either to treatment (N = 35) or waitlist (N = 35) group. Efficacy was evaluated by repeated measures MANOVA assessing changes in working memory index (WMI), processing speed index (PSI), text reading speed, and words/pseudowords reading accuracy. rPA treatment was significantly more effective than waitlist (p ≤ 0.001; ηp2 = 0.815). WMI, PSI, and reading speed increased in the intervention group only (p ≤ 0.001, ηp2 = 0.67; p ≤ 0.001, ηp2 = 0.58; p ≤ 0.001, ηp2 = 0.29, respectively). Although modest change was detected for words and pseudowords accuracy in the waitlist group only (words: p ≤ 0.001, d = 0.17, pseudowords: p = 0.028; d = 0.27), between-group differences were non-significant. rPA-coupled cognitive training enhances cognitive and reading abilities in adolescents with DD. This innovative approach could have implications for early remedial treatment.

Abstract Prolonged febrile seizures (FS) in children are linked to the development of temporal lobe epilepsy (MTLE). The association between these two pathologies may be ascribed to the long-term effects that FS exert on neural stem cells, negatively affecting the generation of new neurons. Among the insults associated with FS, oxidative stress is noteworthy. Here, we investigated the consequences of exposure to hydrogen peroxide (H2O2) in an induced pluripotent stem cell-derived neural stem cells (iNSCs) model of a patient affected by FS and MTLE. In our study, we compare the findings from the MTLE patient with those derived from iNSCs of a sibling exhibiting a milder phenotype defined only by FS, as well as a healthy individual. In response to H2O2 treatment, iNSCs derived from MTLE patients demonstrated an elevated production of reactive oxygen species and increased apoptosis, despite the higher expression levels of antioxidant genes and proteins compared to other cell lines analysed. Among the potential causative mechanisms of enhanced vulnerability of MTLE patient iNSCs to oxidative stress, we found that these cells express low levels of the heat shock protein HSPB1 and of the autophagy adaptor SQSTM1/p62. Pre-treatment of diseased iNSCs with the antioxidant molecule ascorbic acid restored HSBP1 and p62 expression and simultaneously reduced the levels of ROS and apoptosis. Our findings suggest the potential for rescuing the impaired oxidative stress response in diseased iNSCs through antioxidant treatment, offering a promising mechanism to prevent FS degeneration in MTLE.

Abstract Nature-based solutions inherently require a multifaceted perspective that encompasses diverse fields. The aim of this project is to develop more effective nature-based solutions, climate action and environmental awareness by breaking down boundaries between disciplines and fostering a co-creative process. Concepts of ecology and urban forestry were combined with the research on political ecology, environmental humanities, land art, regenerative art, performing art, participatory art, and more-than-human art. This process resulted in the creation of Aula Verde Aniene. It is located in an urban park in Rome and consists of a stand of trees arranged in circles with a specific design to give the perception of being in an outdoor vegetated room. The project activities involved community participation through art performances and citizen science initiatives. Regulating and cultural ecosystem services of Aula Verde were assessed using i-Tree Eco software and citizens’ surveys. Beyond numerical descriptions of ecosystem services, the manuscript introduces shinrin-yoku as a practice to raise awareness of nature. The distinctive approach here described contributed to convey a sense of belonging to the ecosystem to citizens. The project framework and study findings have been developed to formulate policy recommendations and disseminate a format that can be adapted to diverse locations.

Abstract This study aimed to obtain optimized mixture with three essential oils (EOs) for maximum antioxidant activity through the augmented simplex-centroid mixture design and evaluate the effect of this optimized blend on total aerobic psychrotrophic count (TAPC), lipid and protein oxidation, instrumental color parameters and texture profile in rainbow trout fillets at refrigerated storage for nine days. Considering the DPPH and FRAP assays, the ideal EO blend was 66% lemongrass and 34% oregano. During refrigerated storage, this blend at 2000 ppm was equally effective as BHT (100 ppm) (p > 0.05), mitigating the discoloration (a* and b*), lipid, and protein oxidation in 38.83%, 12.95%, 76.13%, and 35.13%, respectively, besides shows greater effectiveness for preserving texture changes (p

Abstract Obesity is the main risk factor for many non-communicable diseases. In clinical practice, unspecific markers are used for the determination of metabolic alterations and inflammation, without allowing the characterization of subjects at higher risk of complications. Circulating microRNAs represent an attractive approach for early screening to identify subjects affected by obesity more at risk of developing connected pathologies. The aim of this study was the identification of circulating free and extracellular vesicles (EVs)-embedded microRNAs able to identify obese patients at higher risk of type 2 diabetes (DM2). The expression data of circulating microRNAs derived from obese patients (OB), with DM2 (OBDM) and healthy donors were combined with clinical data, through network-based methodology implemented by weighted gene co-expression network analysis. The six circulating microRNAs overexpressed in OBDM patients were evaluated in a second group of patients, confirming the overexpression of miR-155-5p in OBDM patients. Interestingly, the combination of miR-155-5p with serum levels of IL-8, Leptin and RAGE was useful to identify OB patients most at risk of developing DM2. These results suggest that miR-155-5p is a potential circulating biomarker for DM2 and that the combination of this microRNA with other inflammatory markers in OB patients can predict the risk of developing DM2.

Abstract Intermittent (or bolus) feeding regimens in critically ill patients have been of increasing interest to clinicians and scientists. Changes in amino acid, fat and carbohydrate metabolites over time might yet deliver other benefits (e.g. modulation of the circadian rhythm and sleep, and impacts on ghrelin secretion, insulin resistance and autophagy). We set out to characterise these changes in metabolite concentration. The Intermittent versus Continuous Feeding in Critically Ill paitents study (NCT02358512) was an eight-centre single-blinded randomised controlled trial. Patients were randomised to received a continuous (control arm) or intermittent (6x/day, intervention arm) enteral feeding regimen. Blood samples were taken on trial days 1, 7 and 10 immediately before and 30 min after intermittent feeds, and at equivalent timepoints in the control arm. A pre-planned targeted metabolomic analysis was performend using Nuclear Resonance Spectroscopy. Five hundred and ninety four samples were analysed from 75 patients. A total of 24 amino acid-, 19 lipid based-, and 44 small molecule metabolite features. Across the main two axes of variation (40–60% and 6–8% of variance), no broad patterns distinguished between intermittent or continuous feeding arms, across intra-day sampling times or over the 10 days from initial ICU admission. Logfold decreases in abundance were seen in metabolites related to amino acids (Glutamine − 0.682; Alanine − 0.594), ketone body metabolism (Acetone − 0.64; 3-Hydroxybutyric Acid − 0.632; Acetonacetic Acid − 0.586), fatty acid (carnitine − 0.509) and carbohydrate metabolism ( Maltose − 0.510; Citric Acid − 0.485). 2–3 Butanediol, a by-product of sugar-fermenting microbial metabolism also decreased (− 0.489). No correlation was seen with change in quadriceps muscle mass for any of the 20 metabolites varying with time (all p > 0.05). Increasing severity of organ failure was related to increasing ketone body metabolism (3 Hydroxybutyric Acid-1 and − 3; p = 0.056 and p = 0.014), carnitine deficiency (p = 0.002) and alanine abundancy (p − 0.005). A 6-times a day intermittent feeding regimen did not alter metabolite patterns across time compared to continuous feeding in critically ill patients, either within a 24 h period or across 10 days of intervention. Future research on intermittent feeding regimens should focus on clinical process benefits, or extended gut rest and fasting.

Abstract Recent experimental evidence indicates a role for the intermediate filament vimentin in regulating cellular mechanical homeostasis, but its precise contribution remains to be discovered. Mechanical homeostasis requires a balanced bi-directional interplay between the cell’s microenvironment and the cellular morphological and mechanical state—this balance being regulated via processes of mechanotransduction and mechanoresponse, commonly referred to as mechanoreciprocity. Here, we systematically analyze vimentin-expressing and vimentin-depleted cells in a swatch of in vitro cellular microenvironments varying in stiffness and/or ECM density. We find that vimentin-expressing cells maintain mechanical homeostasis by adapting cellular morphology and mechanics to micromechanical changes in the microenvironment. However, vimentin-depleted cells lose this mechanoresponse ability on short timescales, only to reacquire it on longer time scales. Indeed, we find that the morphology and mechanics of vimentin-depleted cell in stiffened microenvironmental conditions can get restored to the homeostatic levels of vimentin-expressing cells. Additionally, we observed vimentin-depleted cells increasing collagen matrix synthesis and its crosslinking, a phenomenon which is known to increase matrix stiffness, and which we now hypothesize to be a cellular compensation mechanism for the loss of vimentin. Taken together, our findings provide further insight in the regulating role of intermediate filament vimentin in mediating mechanoreciprocity and mechanical homeostasis.

Abstract Exosomes are well established effectors of cell–cell communication. Their role on maturation of embryonic cells located in hippocampus, seat of memory, is unknown. Here we show that ceramide facilitates release of exosomes from HN9.10e cells extending information for cell differentiation to neighboring cells. We found only 38 miRNAs differentially expressed in exosomes derived from ceramide-treated cells in comparison with control cells (including 10 up-regulated and 28 down-regulated). Some overexpressed miRNAs (mmu-let-7f-1-3p, mmu-let-7a-1-3p, mmu-let-7b-3p, mmu-let-7b-5p, mmu-miR-330-3p) regulate genes encoding for protein involved in biological, homeostatic, biosynthetic and small molecule metabolic processes, embryo development and cell differentiation, all phenomena relevant for HN9.10e cell differentiation. Notably, the overexpressed mmu-let-7b-5p miRNA appears to be important for our study based on its ability to regulate thirty-five gene targets involved in many processes including sphingolipid metabolism, sphingolipid-related stimulation of cellular functions and neuronal development. Furthermore, we showed that by incubating embryonic cells with exosomes released under ceramide treatment, some cells acquired an astrocytic phenotype and others a neuronal phenotype. We anticipate our study to be a start point for innovative therapeutic strategies to regulate the release of exosomes useful to stimulate delayed brain development in the newborn and to improve the cognitive decline in neurodegenerative disorders.

Patient-specific phenotyping of coronary atherosclerosis would facilitate personalized risk assessment and preventive treatment. We explored whether unsupervised cluster analysis can categorize patients with coronary atherosclerosis according to their plaque composition, and determined how these differing plaque composition profiles impact plaque progression. Patients with coronary atherosclerotic plaque (n = 947; median age, 62 years; 59% male) were enrolled from a prospective multi-national registry of consecutive patients who underwent serial coronary computed tomography angiography (median inter-scan duration, 3.3 years). K-means clustering applied to the percent volume of each plaque component and identified 4 clusters of patients with distinct plaque composition. Cluster 1 (n = 52), which comprised mainly fibro-fatty plaque with a significant necrotic core (median, 55.7% and 16.0% of the total plaque volume, respectively), showed the least total plaque volume (PV) progression (+ 23.3 mm3), with necrotic core and fibro-fatty PV regression (- 5.7 mm3 and - 5.6 mm3, respectively). Cluster 2 (n = 219), which contained largely fibro-fatty (39.2%) and fibrous plaque (46.8%), showed fibro-fatty PV regression (- 2.4 mm3). Cluster 3 (n = 376), which comprised mostly fibrous (62.7%) and calcified plaque (23.6%), showed increasingly prominent calcified PV progression (+ 21.4 mm3). Cluster 4 (n = 300), which comprised mostly calcified plaque (58.7%), demonstrated the greatest total PV increase (+ 50.7mm3), predominantly increasing in calcified PV (+ 35.9 mm3). Multivariable analysis showed higher risk for plaque progression in Clusters 3 and 4, and higher risk for adverse cardiac events in Clusters 2, 3, and 4 compared to that in Cluster 1. Unsupervised clustering algorithms may uniquely characterize patient phenotypes with varied atherosclerotic plaque profiles, yielding distinct patterns of progressive disease and outcome.

Abstract Many devices and objects, from microelectronics to microfluidics, consist of parts made from dissimilar materials, such as different polymers, metals or semiconductors. Techniques for joining such hybrid micro-devices, generally, are based on gluing or thermal processes, which all present some drawbacks. For example, these methods are unable to control the size and shape of the bonded area, and present risks of deterioration and contamination of the substrates. Ultrashort laser bonding is a non-contact and flexible technique to precisely join similar and dissimilar materials, used both for joining polymers, and polymers to metallic substrates, but not yet for joining polymers to silicon. We report on direct transmission femtosecond laser bonding of poly(methyl methacrylate) (PMMA) and silicon. The laser process was performed by focusing ultrashort laser pulses at high repetition rate at the interface between the two materials through the PMMA upper layer. The PMMA-Si bond strength was evaluated as a function of different laser processing parameters. A simple, analytical, model was set up and used to determine the temperature of the PMMA during the bonding process. As a proof of concept, the femtosecond-laser bonding of a simple hybrid PMMA-Si microfluidic device has been successfully demonstrated through dynamic leakage tests.

Abstract Back pain is the leading cause of disability worldwide. Its emergence relates not only to the musculoskeletal degeneration biological substrate but also to psychosocial factors; emotional components play a pivotal role. In modern society, people are significantly informed by the Internet; in turn, they contribute social validation to a “successful” digital information subset in a dynamic interplay. The Affective component of medical pages has not been previously investigated, a significant gap in knowledge since they represent a critical biopsychosocial feature. We tested the hypothesis that successful pages related to spine pathology embed a consistent emotional pattern, allowing discrimination from a control group. The pool of web pages related to spine or hip/knee pathology was automatically selected by relevance and popularity and submitted to automated sentiment analysis to generate emotional patterns. Machine Learning (ML) algorithms were trained to predict page original topics from patterns with binary classification. ML showed high discrimination accuracy; disgust emerged as a discriminating emotion. The findings suggest that the digital affective “successful content” (collective consciousness) integrates patients’ biopsychosocial ecosystem, with potential implications for the emergence of chronic pain, and the endorsement of health-relevant specific behaviors. Awareness of such effects raises practical and ethical issues for health information providers.

Abstract Animal conservation relies on assessing the distribution and habitat use of species, but for endangered/elusive animals this can prove difficult. The Monk Seal, Monachus monachus, is one of the world's most endangered species of pinniped, and the only one endemic to the Mediterranean Sea. During recent decades, direct observations have been few and scattered, making it difficult to determine its distribution away from the Aegean Sea (core distribution area of the post-decline relict population). This study relies on environmental DNA (eDNA) analysis to detect the presence of the Monk Seal in 135 samples collected in 120 locations of the central/western Mediterranean Sea, spanning about 1500 km longitudinally and 1000 km latitudinally. A recently described species-specific qPCR assay was used on marine-water samples, mostly collected during 2021 by a Citizen Science (CS) project. Positive detections occurred throughout the longitudinal range, including the westernmost surveyed area (Balearic archipelago). The distribution of the positive detections indicated six “hotspots”, mostly overlapping with historical Monk Seal sites, suggesting that habitat-specific characteristics play a fundamental role. We applied single-season occupancy models to correct for detection probability and to assess the importance of site-specific characteristics. The distance from small islets and protected (or access-restricted) areas was correlated negatively with the detection probability. This novel molecular approach, applied here for the first time in an extensive CS study, proved its potential as a tool for monitoring the distribution of this endangered/elusive species.

Abstract Medulloblastoma (MB) is the most common malignant brain tumour in children. High-risk MB patients harbouring MYC amplification or overexpression exhibit a very poor prognosis. Aberrant activation of MYC markedly reprograms cell metabolism to sustain tumorigenesis, yet how metabolism is dysregulated in MYC-driven MB is not well understood. Growing evidence unveiled the potential of BET-bromodomain inhibitors (BETis) as next generation agents for treating MYC-driven MB, but whether and how BETis may affect tumour cell metabolism to exert their anticancer activities remains unknown. In this study, we explore the metabolic features characterising MYC-driven MB and examine how these are altered by BET-bromodomain inhibition. To this end, we employed an NMR-based metabolomics approach applied to the MYC-driven MB D283 and D458 cell lines before and after the treatment with the BETi OTX-015. We found that OTX-015 triggers a metabolic shift in both cell lines resulting in increased levels of myo-inositol, glycerophosphocholine, UDP-N-acetylglucosamine, glycine, serine, pantothenate and phosphocholine. Moreover, we show that OTX-015 alters ascorbate and aldarate metabolism, inositol phosphate metabolism, phosphatidylinositol signalling system, glycerophospholipid metabolism, ether lipid metabolism, aminoacyl-tRNA biosynthesis, and glycine, serine and threonine metabolism pathways in both cell lines. These insights provide a metabolic characterisation of MYC-driven childhood MB cell lines, which could pave the way for the discovery of novel druggable pathways. Importantly, these findings will also contribute to understand the downstream effects of BETis on MYC-driven MB, potentially aiding the development of new therapeutic strategies to combat medulloblastoma.

Abstract Fibromyalgia (FM) is a chronic and systemic condition that causes widespread chronic pain, asthenia, and muscle stiffness, as well as in some cases depression, anxiety, and disorders of the autonomic system. The exact causes that lead to the development of FM are still unknown today. In a percentage of individuals, the symptoms of FM are often triggered and/or exacerbated by proximity to electrical and electromagnetic devices. Plasma metabolomic profile of 54 patients with fibromyalgia and self-reported electromagnetic sensitivity (IEI-EMF) were compared to 23 healthy subjects using gas chromatography-mass spectrometry (GC–MS) coupled with multivariate statistical analysis techniques. Before the GC–MS analysis the plasma samples were extracted with a modified Folch method and then derivatized with methoxamine hydrochloride in pyridine solution and N-trimethylsilyltrifuoroacetamide. The combined analysis allowed to identify a metabolomic profile able of distinguishing IEI-EMF patients and healthy subjects. IEI-EMF patients were therefore characterized by the alteration of 19 metabolites involved in different metabolic pathways such as energy metabolism, muscle, and pathways related to oxidative stress defense and chronic pain. The results obtained in this study complete the metabolomic "picture" previously investigated on the same cohort of IEI-EMF patients with 1H-NMR spectroscopy, placing a further piece for better understanding the pathophysiological mechanisms in patients with IEI-EMF.

Abstract Aiming to fill a gap in the literature, we aimed to identify the most promising EOs blocking in vitro cellular entry of SARS-CoV-2 delta variant without conferring human cytotoxicity and provide insights into the influence of their composition on these activities. Twelve EOs were characterized by gas chromatography coupled to mass spectrometry. The antiviral and cytotoxicity activities were determined using the cell-based pseudoviral entry with SARS-CoV-2 delta pseudovirus and the XTT assay in HeLa cells expressing human angiotensin-converting enzyme 2 (HeLa ACE-2), respectively. Syzygium aromaticum, Cymbopogon citratus, Citrus limon, Pelargonium graveolens, Origanum vulgare, “Illicium verum”, and Matricaria recutita showed EC50 lowered or close to 1 µg/mL but also the lowest CC50 (0.20–1.70 µg/mL), except “I. verum” (30.00 µg/mL). Among these, “I. verum”, C. limon, P. graveolens and S. aromaticum proved to be promising alternatives for SARS-CoV-2 delta variant inhibition (therapeutic index above 4), which possibly was related to the compounds (E)-anetole, limonene and beta-pinene, citronellol, and eugenol, respectively.

Abstract Alzheimer’s disease (AD) is the most common neurodegenerative disease that currently lacks available effective therapy. Thus, identifying novel molecular biomarkers for diagnosis and treatment of AD is urgently demanded. In this study, we exploited tools and concepts of the emerging research area of Network Medicine to unveil a novel putative disease gene signature associated with AD. We proposed a new pipeline, which combines the strengths of two consolidated algorithms of the Network Medicine: DIseAse MOdule Detection (DIAMOnD), designed to predict new disease-associated genes within the human interactome network; and SWItch Miner (SWIM), designed to predict important (switch) genes within the co-expression network. Our integrated computational analysis allowed us to enlarge the set of the known disease genes associated to AD with additional 14 genes that may be proposed as new potential diagnostic biomarkers and therapeutic targets for AD phenotype.

Abstract Islet transplantation is a unique paradigm in organ transplantation, since multiple donors are required to achieve complete insulin-independence. Preformed or de novo Donor Specific Antibodies (DSA) may target one or several donor islets, which adds complexity to the analysis of their impact. Adult patients with type 1 diabetes transplanted with pancreatic islets between 2005 and 2018 were included in a single-center observational study. Thirty-two recipients with available sera tested by solid-phase assays for anti-HLA antibodies during their whole follow-up were analyzed. Twenty-five recipients were islet-transplantation-alone recipients, and 7 islet-after-kidney recipients. Seven recipients presented with DSA at any time during follow-up (two with preformed DSA only, one with preformed and de novo DSA, 4 with de novo DSA only). Only islet-transplantation-alone recipients presented with de novo DSA. Three clinical trajectories were identified according to: 1/the presence of preformed DSA, 2/early de novo DSA or 3/late de novo DSA. Only late de novo DSA were associated with unfavorable outcomes, depicted by a decrease of the β-score. Islet transplantation with preformed DSA, even with high MFI values, is associated with favorable outcomes in our experience. On the contrary, de novo DSA, and especially late de novo DSA, may be associated with allograft loss.

Abstract In the present study a single screen-printed carbon electrode (SPCE) and chemometric techniques were utilized for forensic differentiation of Brazilian American lager beers. To differentiate Brazilian beers at the manufacturer and brand level, the classification techniques: soft independent modeling of class analogy (SIMCA), partial least squares regression discriminant analysis (PLS-DA), and support vector machines discriminant analysis (SVM-DA) were tested. PLS-DA model presented an inconclusive assignment ratio of 20%. On the other hand, SIMCA models had a 0 inconclusive rate but an sensitivity close to 85%. While the non-linear technique (SVM-DA) showed an accuracy of 98%, with 95% sensitivity and 98% specificity. The SPCE-SVM-DA technique was then used to distinguish at brand level two highly frauded beers. The SPCE coupled with SVM-DA performed with an accuracy of 97% for the classification of both brands. Therefore, the proposed electrochemicalsensor configuration has been deemed an appropriate tool for discrimination of American lager beers according to their producer and brands.

Strain-coupled multiferroic heterostructures provide a path to energy-efficient, voltage-controlled magnetic nanoscale devices, a region where current-based methods of magnetic control suffer from Ohmic dissipation. Growing interest in highly magnetoelastic materials, such as Terfenol-D, prompts a more accurate understanding of their magnetization behavior. To address this need, we simulate the strain-induced magnetization change with two modeling methods: the commonly used unidirectional model and the recently developed bidirectional model. Unidirectional models account for magnetoelastic effects only, while bidirectional models account for both magnetoelastic and magnetostrictive effects. We found unidirectional models are on par with bidirectional models when describing the magnetic behavior in weakly magnetoelastic materials (e.g., Nickel), but the two models deviate when highly magnetoelastic materials (e.g., Terfenol-D) are introduced. These results suggest that magnetostrictive feedback is critical for modeling highly magnetoelastic materials, as opposed to weaker magnetoelastic materials, where we observe only minor differences between the two methods' outputs. To our best knowledge, this work represents the first comparison of unidirectional and bidirectional modeling in composite multiferroic systems, demonstrating that back-coupling of magnetization to strain can inhibit formation and rotation of magnetic states, highlighting the need to revisit the assumption that unidirectional modeling always captures the necessary physics in strain-mediated multiferroics.

Abstract Reach&grasp requires highly coordinated activation of different brain areas. We investigated whether reach&grasp kinematics is associated to EEG-based networks changes. We enrolled 10 healthy subjects. We analyzed the reach&grasp kinematics of 15 reach&grasp movements performed with each upper limb. Simultaneously, we obtained a 64-channel EEG, synchronized with the reach&grasp movement time points. We elaborated EEG signals with EEGLAB 12 in order to obtain event related synchronization/desynchronization (ERS/ERD) and lagged linear coherence between Brodmann areas. Finally, we evaluated network topology via sLORETA software, measuring network local and global efficiency (clustering and path length) and the overall balance (small-worldness). We observed a widespread ERD in α and β bands during reach&grasp, especially in the centro-parietal regions of the hemisphere contralateral to the movement. Regarding functional connectivity, we observed an α lagged linear coherence reduction among Brodmann areas contralateral to the arm involved in the reach&grasp movement. Interestingly, left arm movement determined widespread changes of α lagged linear coherence, specifically among right occipital regions, insular cortex and somatosensory cortex, while the right arm movement exerted a restricted contralateral sensory-motor cortex modulation. Finally, no change between rest and movement was found for clustering, path length and small-worldness. Through a synchronized acquisition, we explored the cortical correlates of the reach&grasp movement. Despite EEG perturbations, suggesting that the non-dominant reach&grasp network has a complex architecture probably linked to the necessity of a higher visual control, the pivotal topological measures of network local and global efficiency remained unaffected.

Abstract Emotions are powerful drivers of human behavior that may make people aware of the urgency to act to mitigate climate change and provide a motivational basis to engage in sustainable action. However, attempts to leverage emotions via climate communications have yielded unsatisfactory results, with many interventions failing to produce the desired behaviors. It is important to understand the underlying affective mechanisms when designing communications, rather than treating emotions as simple behavioral levers that directly impact behavior. Across two field experiments, we show that individual predispositions to experience positive emotions in an environmental context (trait affect) predict pro-environmental actions and corresponding shifts in affective states (towards personal as well as witnessed pro-environmental actions). Moreover, trait affect predicts the individual behavioral impact of positively valenced emotion-based intervention strategies from environmental messages. These findings have important implications for the targeted design of affect-based interventions aiming to promote sustainable behavior and may be of interest within other domains that utilize similar intervention strategies (e.g., within the health domain).

Abstract Ground-glass opacities (GGOs) are a non-specific high-resolution computed tomography (HRCT) finding tipically observed in early Coronavirus disesase 19 (COVID-19) pneumonia. However, GGOs are also seen in other acute lung diseases, thus making challenging the differential diagnosis. To this aim, we investigated the performance of a radiomics-based machine learning method to discriminate GGOs due to COVID-19 from those due to other acute lung diseases. Two sets of patients were included: a first set of 28 patients (COVID) diagnosed with COVID-19 infection confirmed by real-time polymerase chain reaction (RT-PCR) between March and April 2020 having (a) baseline HRCT at hospital admission and (b) predominant GGOs pattern on HRCT; a second set of 30 patients (nCOVID) showing (a) predominant GGOs pattern on HRCT performed between August 2019 and April 2020 and (b) availability of final diagnosis. Two readers independently segmented GGOs on HRCTs using a semi-automated approach, and radiomics features were extracted using a standard open source software (PyRadiomics). Partial least square (PLS) regression was used as the multivariate machine-learning algorithm. A leave-one-out nested cross-validation was implemented. PLS β-weights of radiomics features, including the 5% features with the largest β-weights in magnitude (top 5%), were obtained. The diagnostic performance of the radiomics model was assessed through receiver operating characteristic (ROC) analysis. The Youden’s test assessed sensitivity and specificity of the classification. A null hypothesis probability threshold of 5% was chosen (p

Abstract The SARS-CoV-2 pandemic prompts evaluation of recombination in human coronavirus (hCoV) evolution. We undertook recombination analyses of 158,118 public seasonal hCoV, SARS-CoV-1, SARS-CoV-2 and MERS-CoV genome sequences using the RDP4 software. We found moderate evidence for 8 SARS-CoV-2 recombination events, two of which involved the spike gene, and low evidence for one SARS-CoV-1 recombination event. Within MERS-CoV, 229E, OC43, NL63 and HKU1 datasets, we noted 7, 1, 9, 14, and 1 high-confidence recombination events, respectively. There was propensity for recombination breakpoints in the non-ORF1 region of the genome containing structural genes, and recombination severely skewed the temporal structure of these data, especially for NL63 and OC43. Bayesian time-scaled analyses on recombinant-free data indicated the sampled diversity of seasonal CoVs emerged in the last 70 years, with 229E displaying continuous lineage replacements. These findings emphasize the importance of genomic based surveillance to detect recombination in SARS-CoV-2, particularly if recombination may lead to immune evasion.

Abstract Patient-specific phenotyping of coronary atherosclerosis would facilitate personalized risk assessment and preventive treatment. We explored whether unsupervised cluster analysis can categorize patients with coronary atherosclerosis according to their plaque composition, and determined how these differing plaque composition profiles impact plaque progression. Patients with coronary atherosclerotic plaque (n = 947; median age, 62 years; 59% male) were enrolled from a prospective multi-national registry of consecutive patients who underwent serial coronary computed tomography angiography (median inter-scan duration, 3.3 years). K-means clustering applied to the percent volume of each plaque component and identified 4 clusters of patients with distinct plaque composition. Cluster 1 (n = 52), which comprised mainly fibro-fatty plaque with a significant necrotic core (median, 55.7% and 16.0% of the total plaque volume, respectively), showed the least total plaque volume (PV) progression (+ 23.3 mm3), with necrotic core and fibro-fatty PV regression (− 5.7 mm3 and − 5.6 mm3, respectively). Cluster 2 (n = 219), which contained largely fibro-fatty (39.2%) and fibrous plaque (46.8%), showed fibro-fatty PV regression (− 2.4 mm3). Cluster 3 (n = 376), which comprised mostly fibrous (62.7%) and calcified plaque (23.6%), showed increasingly prominent calcified PV progression (+ 21.4 mm3). Cluster 4 (n = 300), which comprised mostly calcified plaque (58.7%), demonstrated the greatest total PV increase (+ 50.7mm3), predominantly increasing in calcified PV (+ 35.9 mm3). Multivariable analysis showed higher risk for plaque progression in Clusters 3 and 4, and higher risk for adverse cardiac events in Clusters 2, 3, and 4 compared to that in Cluster 1. Unsupervised clustering algorithms may uniquely characterize patient phenotypes with varied atherosclerotic plaque profiles, yielding distinct patterns of progressive disease and outcome.

Abstract Cancer stem-like cells (CSCs) have self-renewal abilities responsible for cancer progression, therapy resistance, and metastatic growth. The glioblastoma stem-like cells are the most studied among CSC populations. A recent study identified four transcription factors (SOX2, SALL2, OLIG2, and POU3F2) as the minimal core sufficient to reprogram differentiated glioblastoma (GBM) cells into stem-like cells. Transcriptomic data of GBM tissues and cell lines from two different datasets were then analyzed by the SWItch Miner (SWIM), a network-based software, and FOSL1 was identified as a putative regulator of the previously identified minimal core. Herein, we selected NTERA-2 and HEK293T cells to perform an in vitro study to investigate the role of FOSL1 in the reprogramming mechanisms. We transfected the two cell lines with a constitutive FOSL1 cDNA plasmid. We demonstrated that FOSL1 directly regulates the four transcription factors binding their promoter regions, is involved in the deregulation of several stemness markers, and reduces the cells’ ability to generate aggregates increasing the extracellular matrix component FN1. Although further experiments are necessary, our data suggest that FOSL1 reprograms the stemness by regulating the core of the four transcription factors.

Abstract With a growing number of parasites and pathogens experiencing large-scale range expansions, monitoring diversity in immune genes of host populations has never been so important because it can inform on the adaptive potential to resist the invaders. Population surveys of immune genes are becoming common in many organisms, yet they are missing in the honey bee (Apis mellifera L.), a key managed pollinator species that has been severely affected by biological invasions. To fill the gap, here we identified single nucleotide polymorphisms (SNPs) in a wide range of honey bee immune genes and developed a medium-density assay targeting a subset of these genes. Using a discovery panel of 123 whole-genomes, representing seven A. mellifera subspecies and three evolutionary lineages, 180 immune genes were scanned for SNPs in exons, introns (