Search

Nicola Modugno,1 Angelo Antonini,2 Alessandro Tessitore,3 Pietro Marano,4 Francesco Ernesto Pontieri,5,6 Nicola Tambasco,7 Margherita Canesi,8,9 Giovanni Fabbrini,10,11 Mariachiara Sensi,12 Rocco Quatrale,13 Paolo Solla,14 Giovanni Defazio,14 Gabriella Melzi,15 Giuliana Gualberti,15 Leonardo Lopiano16 1Neurology Unit, IRCCS Neuromed, Pozzilli, Italy; 2Parkinson and Movement Disorder Unit, Department of Neuroscience, University of Padua, Padua, Italy; 3Department of Medical and Surgery Sciences, University of Campania, “Luigi Vanvitelli”, Naples, Italy; 4Casa di Cura Madonna del Rosario, Raggruppamento di Riabilitazione, Catania, Italy; 5Department NESMOS, “Sapienza” University, Sant’Andrea Hospital, Roma, Italy; 6IRCCS Fondazione Santa Lucia, Roma, Italy; 7Department of Neurology, Perugia General Hospital and University of Perugia, Perugia, Italy; 8Dipartimento di Riabilitazione Malattia di Parkinson e Disordini del Movimento, Gravi Cerebrolesioni Acquisite, Italia Hospital - Ospedale “Moriggia-Pelascini”, Gravedona ed Uniti, Como, Italy; 9Centro Parkinson e Disordini del Movimento, CTO, G Pini, Milano, Italy; 10Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy; 11IRCCS Neuromed, Pozzilli, Isernia, Italy; 12Neurology Unit, Hospital Sant’Anna, Ferrara, Italy; 13Neurology Unit, Hospital dell’Angelo, Mestre, VE, Italy; 14Neurology Unit, Policlinico Universitario Monserrato, Cagliari, Italy; 15Medical Department, AbbVie Srl, Roma, Italy; 16Department of Neuroscience “Rita Levi Montalcini” University of Torino, Azienda Ospedaliero-Universitaria Città Della Salute e Della Scienza di Torino, Torino, ItalyCorrespondence: Gabriella MelziAbbVie Srl, Viale dell’Arte 25, Roma 00144, ItalyTel +39 06928924346Email gabriella.melzi@abbvie.comPurpose: The aim of this study was to assess the burden and the quality of life (QoL) perceived by caregivers assisting advanced Parkinson’s disease (PD) patients.Patients and Methods: Consecutive advanced PD patients treated with levodopa/carbidopa intestinal gel (LCIG) or continuous subcutaneous apomorphine infusion (CSAI) or care as usual (CU) and their care partners were recruited during routine visits according to a cross-sectional design. Caregiver’s distress was assessed by Zarit Burden Interview (ZBI) and a QoL survey to evaluate and understand the burden experienced by care partners during family and working activities.Results: A total of 126 patients (53 LCIG, 19 CSAI and 54 CU) and their care partners were enrolled. The ZBI score boxplot showed that LCIG and CU populations have a similar distribution (ZBI inter-quartile range [IQR] values respectively 18– 42 for LCIG and 19– 43 for CU group), while the CSAI group has a wider score range (IQR 16– 52). Caregivers assisting patients in treatment with LCIG have more time to perform family or household duties (p=0.0022), or to engage in leisure activities (p=0.0073) compared to CU, while no difference was found when compared to CSAI group. Approximately 50% of the care partners showed mood changes in the last 6 months and LCIG and CSAI had less impact on caregiver’s mood compared to CU. Patients treated with LCIG were more independent in taking a bath or shower without assistance and were more able to move and walk without assistance.Conclusion: Care partners of advanced PD patients treated with device-aided therapies have more time for their own life and a better perception of their QoL with a tendency to an improvement of mood compared with those of patients treated with CU.Keywords: advanced Parkinson’s disease, levodopa/carbidopa, intestinal infusion, caregiver burden, quality of life; QoL

Abstract The microbial ecology of Mycobacterium avium subspecies paratuberculosis infections (MAP) within the context of Multiple Sclerosis (MS) is largely an unexplored topic in the literature. Thus, we have characterized the compositional and predicted functional differences of the gut microbiome between MS patients with MAP (MAP+) and without (MAP−) infection. This was done in the context of exposome differences (through self-reported filled questionnaires), principally in anthropometric and sociodemographic patterns to gain an understanding of the gut microbiome dynamics. 16S rRNA microbiome profiling of faecal samples (n = 69) was performed for four groups, which differed by disease and MAP infection: healthy cohort (HC) MAP−; HC MAP+ ; MS MAP−; and MS MAP+ . Using a dynamic strategy, with MAP infection and time of sampling as occupancy models, we have recovered the core microbiome for both HC and MS individuals. Additional application of neutral modeling suggests key genera that are under selection pressure by the hosts. These include members of the phyla Actinobacteriota, Bacteroidota, and Firmicutes. As several subjects provided multiple samples, a Quasi Conditional Association Test that incorporates paired-nature of samples found major differences in Archaea. To consolidate treatment groups, confounders, microbiome, and the disease outcome parameters, a mediation analysis is performed for MS cohort. This highlighted certain genera i.e., Sutterella, Akkermansia, Bacteriodes, Gastranaerophilales, Alistipes, Balutia, Faecalibacterium, Lachnospiraceae, Anaerostipes, Ruminococcaceae, Eggerthellaceae and Clostridia-UCG-014 having mediatory effect using disease duration as an outcome and MAP infection as a treatment group. Our analyses indicate that the gut microbiome may be an important target for dietary and lifestyle intervention in MS patients with and without MAP infection.

Abstract Aims Drug‐refractory electrical storm (ES) is a life‐threatening medical emergency. We describe the use of venoarterial extracorporeal membrane oxygenation (VA‐ECMO) in drug‐refractory ES without a reversible trigger, for which specific guideline recommendations are still lacking. Methods and results Retrospective observational study in four Iberian centres on the indications, treatment, complications, and outcome of drug‐refractory ES not associated with acute coronary syndromes, decompensated heart failure, drug toxicity, electrolyte disturbances, endocrine emergencies, concomitant acute illness with fever, or poor compliance with anti‐arrhythmic drugs, requiring VA‐ECMO for circulatory support. Thirty‐four (6%) out of 552 patients with VA‐ECMO for cardiogenic shock were included [71% men; 57 (44–62) years], 65% underwent cardiopulmonary resuscitation before VA‐ECMO implantation, and 26% during cannulation. Left ventricular unloading during VA‐ECMO was used in 8 (24%) patients: 3 (9%) with intraaortic balloon pump, 3 (9%) with LV vent, and 2 (6%) with Impella. Thirty (88%) had structural heart disease and 8 (24%) had an implantable cardioverter‐defibrillator. The drug‐refractory ES was mostly due to monomorphic ventricular tachycardia (VT) and ventricular fibrillation (VF) (59%), isolated monomorphic VT (26%), polymorphic VT (9%), or VF (6%). Thirty‐one (91%) required deep sedation, 44% overdrive pacing, 36% catheter ablation, and 26% acute autonomic modulation. The main complications were nosocomial infection (47%), bleeding (24%), and limb ischaemia (21%). Eighteen (53%) were weaned from VA‐ECMO, and 29% had heart transplantation. Twenty‐seven (79%) survived to hospital discharge (48 (33–82) days). Non‐survivors were older [62 (58–67) vs. 54 (43–58); P

Abstract Background In gut ecosystems, there is a complex interplay of biotic and abiotic interactions that decide the overall fitness of an individual. Divulging the microbe-microbe and microbe-host interactions may lead to better strategies in disease management, as microbes rarely act in isolation. Network inference for microbial communities is often a challenging task limited by both analytical assumptions as well as experimental approaches. Even after the network topologies are obtained, identification of important nodes within the context of underlying disease aetiology remains a convoluted task. We therefore present a network perspective on complex interactions in gut microbial profiles of individuals who have multiple sclerosis with and without Mycobacterium avium subspecies paratuberculosis (MAP) infection. Our exposé is guided by recent advancements in network-wide statistical measures that identify the keystone nodes. We have utilised several centrality measures, including a recently published metric, Integrated View of Influence (IVI), that is robust against biases. Results The ecological networks were generated on microbial abundance data (n = 69 samples) utilising 16 S rRNA amplification. Using SPIEC-EASI, a sparse inverse covariance estimation approach, we have obtained networks separately for MAP positive (+), MAP negative (-) and healthy controls (as a baseline). Using IVI metric, we identified top 20 keystone nodes and regressed them against covariates of interest using a generalised linear latent variable model. Our analyses suggest Eisenbergiella to be of pivotal importance in MS irrespective of MAP infection. For MAP + cohort, Pyarmidobacter, and Peptoclostridium were predominately the most influential genera, also hinting at an infection model similar to those observed in Inflammatory Bowel Diseases (IBDs). In MAP- cohort, on the other hand, Coprostanoligenes group was the most influential genera that reduces cholesterol and supports the intestinal barrier. Conclusions The identification of keystone nodes, their co-occurrences, and associations with the exposome (meta data) advances our understanding of biological interactions through which MAP infection shapes the microbiome in MS individuals, suggesting the link to the inflammatory process of IBDs. The associations presented in this study may lead to development of improved diagnostics and effective vaccines for the management of the disease.

Transportation infrastructure serves as the backbone of societal functionality. As aging road networks present increasing challenges, effective monitoring and maintenance become imperative. In this context, this article explores the integration of non-destructive techniques for monitoring and assessing damaged road sections. The work emphasizes the importance of leveraging the complementarity between non-destructive techniques to gain a holistic understanding of damaged road sections' structural integrity. Through the combination of these techniques, structural issues and underlying causes can be identified, as well as to develop maintenance and rehabilitation strategies.A case study of a critical section of the national road N-541 in Pontevedra, Spain, illustrates the application of this integration. First, Interferometry Synthetic Aperture Radar (InSAR) technology revealed points of interest. Four different cases, with two different methods: Scatterer Interferometry (PSI) and Quasi-PS (QPS) were used, to minimize uncertainty. Then, Global Positioning System (GPS) data, together with Laser Imaging Detection and Ranging (LiDAR), were used to create Digital Elevation Models (DEM). Finally, Ground Penetrating Radar (GPR) was useful to create a data cloud of possible subsurface damages. Machine learning technique (clustering) was applied to the GPR data to assist in defect depth analysis, further improving understanding and knowledge. The integration of complementary non-destructive methods offers a comprehensive framework for advancements in road infrastructure analysis and maintenance strategies, thus contributing to decision-makers to enhance transportation infrastructures' resilience and longevity.

Sponge cities are renowned for their efficacy against extreme weather events, reducing surface runoff, managing stormwater, and mitigating flood risks. Moreover, they present multifaceted advantages by integrating blue-green infrastructure, enhancing urban sustainability, and improving water quality. The trend of their expansion beyond China marks a significant development in climate-resilient urban planning. This study pioneers the use of open data to locate suitable sites for sponge Low Impact Development (LID) solutions, showcasing Vigo (Spain) as a viable case for mid-sized cities. Input data is obtained from administrative cartography (DTM, hydrogeology, land cover, river courses, and demographic census) and satellite imagery (impervious coverage, vegetation, and surface temperature) from Landsat 8 and MODIS calculating three spectral indices (NISI, NDVI, NDIH). A robust Geographical Information System (GIS) method is proposed weighting the multi-criteria with AHP matrix. Three main potential sites are identified for deploying specific sponge LID strategies, as green roofs, green parking, or rain gardens. Nevertheless, while the method swiftly identifies intervention sites on a municipal scale, conclusive decisions necessitate terrain insights, public sentiments, urban regulations, and funding considerations.

This work presents a preliminary case study on assessing reinforced concrete pedestrian bridge conditions in A Coruña (Galicia, Spain), employing a novel integration of non-destructive testing (NDT) technologies. The research aims to refine the health monitoring process of pedestrian bridges by adopting a top-down approach, leveraging the data-fusion concept to enhance the analysis of structural defects. A data-fusion methodology that integrates interferometric synthetic aperture radar (InSAR), ground penetrating radar (GPR), and light detection and range (LiDAR) technologies is introduced. Then, the data are visualized within a 3D Geographical Information System (GIS) environment. The MT-InSAR technique is used at the network level to identify bridges requiring detailed inspections. Subsequently, selected bridges undergo thorough examinations using GPR and LiDAR technologies from fieldwork between 2021 and 2023. A comparative analysis of three different LiDAR devices and two GPR setups is conducted to evaluate their effectiveness in capturing detailed structural data. The study also explores the integration challenges and solutions for combining diverse data formats and the possibility of using advanced digital technologies, such as Building Information Modelling (BIM), to facilitate a seamless transition from traditional NDT approaches to a digitized, model-based inspection framework. The findings highlight the advantages of each NDT method, address specific data acquisition challenges, and propose strategies for overcoming issues related to data integration, visualization, and the accuracy of spatial localization. Integrating these NDT technologies within a georeferenced 3D GIS environment facilitates a detailed understanding of the bridge's condition and enhances decision-making processes for maintenance and rehabilitation efforts.

Urban transportation is pivotal in facilitating citizen mobility, and within this sphere, the thermal comfort experienced at bus stops significantly impacts pedestrians' well-being. This research delves into the analysis of direct sun glare at bus stops utilizing Mobile Laser Scanning (MLS) point clouds. Solar angles are calculated to evaluate sun rays, focusing particularly on the summer solstice, and considering the integration of trees to alleviate direct sun glare. The methodological approach comprises four stages: 1) Semantic segmentation of the bus stop environment, 2) Sun glare analysis, 3) Sun glare analysis integrating trees, and 4) Subsoil investigation with Ground-Penetrating Radar (GPR). Various algorithms, including DBSCAN and filters for height, width, and intensity, are employed to classify different elements contained in the bus stop. Sun rays are then derived based on sun angles, identifying intersections with street elements and vertical structures like bus stops or facades. Subsequently, these intersections are recalculated, incorporating trees in the bus stop vicinity. Finally, GPR is utilized to assess the viability of adding trees. Three bus stops in Vigo, Spain, serve as the focal points of analysis. The study delineates specific time intervals when sun rays either encounter new vegetation obstacles or remain unobstructed. While both small and large trees show potential in reducing sun glare, larger trees notably exhibit greater effectiveness in blocking sun glare for extended periods.

IntroductionCoronavirus disease 2019 (COVID-19) affects the population unequally, with a greater impact on older and immunosuppressed people.MethodsHence, we performed a prospective experimental cohort study to characterise the effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination in immune-compromised patients (older adults and oncohaematologic patients), compared with healthy counterparts, based on deep characterisation of the circulating immune cell subsets.Results and discussionWhile acquired humoral and cellular memory did not predict subsequent infection 18 months after full vaccination, spectral and computational cytometry revealed several subsets within the CD8+ T-cells, B-cells, natural killer (NK) cells, monocytes and TEMRA Tγδ cells that were differentially expressed in individuals who were subsequently infected and not infected not just following immunisation, but also prior to vaccination. Of note, we found up to seven clusters within the TEMRA Tγδ cell population, with some of them being expanded and others decreased in subsequently infected individuals. Moreover, some of these cellular clusters were also related to COVID-19-induced hospitalisation in oncohaematologic patients. Therefore, we have identified a cellular signature that even before vaccination is related to COVID-19 vulnerability as opposed to the acquisition of cellular and/or humoral memory following vaccination with SARS-CoV-2 messenger RNA (mRNA) vaccines.

Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We propose that to accelerate progress in AI, we must invest in fundamental research in NeuroAI. A core component of this is the embodied Turing test, which challenges AI animal models to interact with the sensorimotor world at skill levels akin to their living counterparts. The embodied Turing test shifts the focus from those capabilities like game playing and language that are especially well-developed or uniquely human to those capabilities - inherited from over 500 million years of evolution - that are shared with all animals. Building models that can pass the embodied Turing test will provide a roadmap for the next generation of AI.

Floods pose recurrent threats to numerous countries, carrying substantial social, economic and at times, catastrophic implications, especially in extreme scenarios. In addition, coastal areas are strongly threatened by extreme weather events and climate change impacts. Given these pressing challenges, it becomes imperative to conduct thorough assessments of future flood impacts, particularly in areas of significant environmental and socio-economic importance. This study addresses this need by focusing on the potential consequences of flooding in the Loira River, situated in the municipality of Marín, Pontevedra, Northwestern Spain. For this purpose, the free software IBER has been used, these is a free software that solves the 2D depth-averaged shallow water equations (SWEs) by using a finite volume scheme, with the domain being discretized with both structured and unstructured triangular or quadrilateral elements. The hydrological model has been established from the maximum flow for different return periods (T10, T100 and T500). Field observations, including channel widths, bridge configurations, and various parameters, further inform our analysis. Our findings reveal critical insights, including a maximum height differential of 0.48 m, particularly significant at the upstream bridge, exacerbating flooding risks in adjacent plains. Moreover, velocities along riverbanks reach hazardous levels, notably during the 500-year return period, necessitating urgent protective measures for local residents. The hydrological model also indicates that small-scale forestation has no significant effect on flood prevention. This research underscores the utility of advanced hydrological modelling in informing risk management strategies and underscores the necessity of pre-emptive hydrological analyses to mitigate future flood risks effectively.

Introduction Research quality within the neurosurgical field remains suboptimal. Therefore, many studies published in the neurosurgical literature lack enough statistical power to establish the presence or absence of clinically important differences between treatment arms. The field of neurotrauma deals with additional challenges, with fewer financial incentives and restricted resources in low-income and middle-income countries with the highest burden of neurotrauma diseases. In this systematic review, we aim to estimate the prevalence of false claims of equivalence in the neurosurgical trauma literature and identify its predictive factors.Methods and analysis The Preferred Reporting Items for Systematic Review and Meta-Analyses recommendations were followed. Randomised clinical trials that enrolled only traumatic brain injury patients and investigated any type of intervention (surgical or non-surgical) will be eligible for inclusion. The MEDLINE/PubMed database will be searched for articles in English published from January 1960 to July 2020 in 15 top-ranked journals. A false claim of equivalence will be identified by insufficient power to detect a clinically meaningful effect: for categorical outcomes, a difference of at least 25% and 50%, and for continuous outcomes, a Cohen’s d of at least 0.5 and 0.8. Using the number of patients in each treatment arm and the minimum effect sizes to be detected, the power of each study will be calculated with the assumption of a two-tailed alpha that equals 0.05. Standardised differences between the groups with and without a false claim of equivalence will be calculated, and the variables with a standardised difference equal or above 0.2 and 0.5 will be considered weakly and strongly associated with false claims of equivalence, respectively. The data analysis will be blinded to the authors and institutions of the studies.Ethics and dissemination This study will not involve primary data collection. Therefore, formal ethical approval will not be required. The final systematic review will be published in a peer-reviewed journal and presented at appropriate conferences.

IntroductionDisease-modifying therapies (DMTs) have been shown to improve disease outcomes in multiple sclerosis (MS) patients. They may also impair the immune response to vaccines, including the SARS-CoV-2 vaccine. However, available data on both the intrinsic immune effects of DMTs and their influence on cellular response to the SARS-CoV-2 vaccine are still incomplete.MethodsHere, we evaluated the immune cell effects of 3 DMTs on the response to mRNA SARS-CoV-2 vaccination by comparing MS patients treated with one specific therapy (fingolimod, dimethyl fumarate, or natalizumab) with both healthy controls and untreated patients. We profiled 23 B-cell traits, 57 T-cell traits, and 10 cytokines, both at basal level and after stimulation with a pool of SARS-CoV-2 spike peptides, in 79 MS patients, treated with DMTs or untreated, and 32 healthy controls. Measurements were made before vaccination and at three time points after immunization.Results and DiscussionMS patients treated with fingolimod showed the strongest immune cell dysregulation characterized by a reduction in all measured lymphocyte cell classes; the patients also had increased immune cell activation at baseline, accompanied by reduced specific immune cell response to the SARS-CoV-2 vaccine. Also, anti-spike specific B cells progressively increased over the three time points after vaccination, even when antibodies measured from the same samples instead showed a decline. Our findings demonstrate that repeated booster vaccinations in MS patients are crucial to overcoming the immune cell impairment caused by DMTs and achieving an immune response to the SARS-CoV-2 vaccine comparable to that of healthy controls.

El modelo tradicional del turismo fue pensado durante muchos años desde una dimensión económica. Sin embargo, recientemente y debido a los impactos generados por la actividad turística, nuevas modalidades de turismo han sido pensadas, poniendo el foco de la experiencia no solo en lo económico, también en otros aspectos capaces de generar desarrollo. Este artículo, es el resultado de una investigación sobre la importancia de la formación de los profesionales del turismo, para garantizar la realización de actividades equilibradas, que respeten y preserven el medio ambiente en los destinos turísticos. Desde la perspectiva profesional, las personas que actúan en el turismo también son responsables por la continuidad de esta actividad. El objetivo fue comprender cómo afecta el proceso de formación de los profesionales del turismo, al desarrollo de un turismo consciente; de esta manera, crea relación entre los conceptos que le conforman. El estudio cualitativo, permitió traducir los conceptos y esbozar la participación de los profesionales del turismo, en la preservación del medio ambiente y de la actividad misma.

Olfactory dysfunction is a prevalent non-motor symptom in Parkinson’s disease (PD), affecting approximately 65–90% of subjects. PD patients may also report odor perception in the absence of any external source, often referred to as olfactory hallucinations (OHs) or phantosmia. This study aims to explore the current understanding of OHs in PD and offer a comprehensive overview of their prevalence and characteristics. We conducted a systematic search of the literature published on PubMed from inception to July 2023 regarding OHs in PD, following PRISMA guidelines. From the 2875 studies identified through database searching, 29 studies fulfilled the necessary criteria and underwent data extraction. The frequency of OHs in PD patients varies widely, ranging from 0.5% to 18.2%, with female prevalence ranging from 36% to 75% of the patients. Olfactory experiences may vary widely, ranging from pleasant scents to unpleasant odors. Several studies have indicated the concurrent presence of other types of hallucinations alongside phantosmia, especially visual and auditory hallucinations. OHs in PD are a type of hallucination that has been largely overlooked. To gain a deeper understanding of OHs in PD patients, the next crucial step should involve the development and validation of a dedicated questionnaire.

Objectives: This study aimed to assess the real use of cefazolin for methicillin-susceptible Staphylococcus aureus (MSSA) infective endocarditis (IE) in the Spanish National Endocarditis Database (GAMES) and to compare it with antistaphylococcal penicillin (ASP). Methods: Prospective cohort study with retrospective analysis of a cohort of MSSA IE treated with cloxacillin and/or cefazolin. Outcomes assessed were relapse; intra-hospital, overall, and endocarditis-related mortality; and adverse events. Risk of renal toxicity with each treatment was evaluated separately. Results: We included 631 IE episodes caused by MSSA treated with cloxacillin and/or cefazolin. Antibiotic treatment was cloxacillin, cefazolin, or both in 537 (85%), 57 (9%), and 37 (6%) episodes, respectively. Patients treated with cefazolin had significantly higher rates of comorbidities (median Charlson Index 7, P

This paper presents an approach to identifying political fake news in Spanish using Transformer architectures. Current methodologies often overlook political news due to the lack of quality datasets, especially in Spanish. To address this, we created a synthetic dataset of 57,231 Spanish political news articles, gathered via automated web scraping and enhanced with generative large language models. This dataset is used for fine-tuning and benchmarking Transformer models like BERT and RoBERTa for fake news detection. Our fine-tuned models showed outstanding performance on this dataset, with accuracy ranging from 97.4% to 98.6%. However, testing with a smaller, independent hand-curated dataset, including statements from political leaders during Spain’s July 2023 electoral debates, revealed a performance drop to 71%. Although this suggests that the model needs additional refinements to handle the complexity and variability of real-world political discourse, achieving over 70% accuracy seems a promising result in the under-explored domain of Spanish political fake news detection.

Background: Social Communication Disorder (SCD), introduced in the DSM-5, is distinguished from Autism Spectrum Disorder (ASD) by the absence of restricted and repetitive behaviors or interests (RRBIs). Aim: To compare the adaptive, sensory, communication, and cognitive profiles of children with ASD and SCD. Methods: The assessments of nine children with SCD and ten with ASD were compared with either Fisher’s Exact Test or the Mann–Whitney Test. Assessments included the Vineland Adaptive Behavior Scales, the Autism Diagnostic Observation Schedule (ADOS), the Short Sensory Profile, Bishop’s Children’s Communication Checklist, a pragmatics evaluation, and the Wechsler Intelligence Scale for Children IV. Results: The total ADOS score and the second subtotal “Restricted and Repetitive Behaviors” were significantly higher (p = 0.022) in the ASD group than in the SCD group. The Vineland standard score for the “Socialization” domain was significantly lower (p = 0.037) in the ASD group (mean: 51 +/− 19) than in the SCD group (mean: 80 +/− 28). The working memory index score was also significantly lower (p = 0.013) in the ASD group compared to the SCD group. Conclusions: While ASD and SCD share similarities in communication and pragmatic difficulties, some distinctions have been identified, e.g. in executive functioning and the impact on socialization, which may be linked to the absence of RRBIs in SCD. These findings highlight the challenges posed by this nosographic separation during diagnostic evaluations due to the scarcity of discriminative tools.

Multiple sclerosis (MS) is a demyelinating autoimmune disease characterized by early onset, for which the interaction of genetic and environmental factors is crucial. Dysregulation of the immune system as well as myelinization-de-myelinization has been shown to correlate with changes in RNA, including non-coding RNAs. Recently, circular RNAs (circRNAs) have emerged as a key player in the complex network of gene dysregulation associated with MS. Despite several efforts, the mechanisms driving circRNA regulation and dysregulation in MS still need to be properly elucidated. Here, we explore the panorama of circRNA expression in PBMCs purified from five newly diagnosed MS patients and five healthy controls (HCs) using the Arraystar Human circRNAs microarray. Experimental validation was then carried out in a validation cohort, and a possible correlation with disease severity was tested. We identified 64 differentially expressed circRNAs, 53 of which were downregulated in PBMCs purified from MS compared to the HCs. The discovery dataset was subsequently validated using qRT-PCR with an independent cohort of 20 RRMS patients and 20 HCs. We validated seven circRNAs differentially expressed in the RRMS group versus the HC group. hsa_circ_0000518, hsa_circ_0000517, hsa_circ_0000514, and hsa_circ_0000511 were significantly upregulated in the MS group, while hsa_circ_0018905, hsa_circ_0048764, and hsa_circ_0003445 were significantly downregulated; Among them, the expression level of hsa_circ_0018905 was significantly decreased in patients showing a higher level of disability and in progressive forms of MS. We described the circRNAs expression profile of PBMCs in newly diagnosed MS patients and proposed hsa_circ_0018905 as potential MS biomarker.

Fieldwork is a meaningful and authentic learning experience that is rarely included in undergraduate chemistry courses. In this laboratory, we visited a hot spot of perfluoroalkyl acid (PFAA) contamination identified in 2012, in Binbrook, Ontario, Canada, a 1 h drive from the University of Toronto. The persistence and unique environmental partitioning properties of PFAAs at these levels provide an excellent opportunity for students to apply a variety of practical environmental sampling techniques in a real-world scenario. We have taken our cross-listed senior undergraduate and graduate class, CHM410-1410 Analytical Environmental Chemistry, to the site and a nearby background site to collect water, sediment, invertebrates, and fish every October since 2016. Students use matrix-specific extractions and analysis by liquid chromatography--tandem mass spectrometry to quantify seven PFAAs. A major goal of this experiment is to guide students through the process of effective data visualization for the identification and communication of trends and relationships between analytes and their prevalence across environmental samples. This process is facilitated by a report outline where students receive significant feedback prior to writing their final lab report. This laboratory is an authentic learning experience that involves students in all aspects of the investigation from sample collection to extraction, data analysis, interpretation, and communication of results. The field component is also a powerful cohort-building exercise with tangible effects on subsequent peer-to-peer interactions. Given the ubiquitous contamination of PFAAs in the environment, this field-based laboratory experiment could be applied at other institutions.

Background The epidemiology of traumatic brain injury (TBI) is unclear – it is estimated to affect 27–69 million individuals yearly with the bulk of the TBI burden in low-to-middle income countries (LMICs). Research has highlighted significant between-hospital variability in TBI outcomes following emergency surgery, but the overall incidence and epidemiology of TBI remains unclear. To address this need, we established the Global Epidemiology and Outcomes following Traumatic Brain Injury (GEO-TBI) registry, enabling recording of all TBI cases requiring admission irrespective of surgical treatment. Objective The GEO-TBI: Incidence study aims to describe TBI epidemiology and outcomes according to development indices, and to highlight best practices to facilitate further comparative research. Design Multi-centre, international, registry-based, prospective cohort study. Subjects Any unit managing TBI and participating in the GEO-TBI registry will be eligible to join the study. Each unit will select a 90-day study period. All TBI patients meeting the registry inclusion criteria (neurosurgical/ICU admission or neurosurgical operation) during the selected study period will be included in the GEO-TBI: Incidence. Methods All units will form a study team, that will gain local approval, identify eligible patients and input data. Data will be collected via the secure registry platform and validated after collection. Identifiers may be collected if required for local utility in accordance with the GEO-TBI protocol. Data Data related to initial presentation, interventions and short-term outcomes will be collected in line with the GEO-TBI core dataset, developed following consensus from an iterative survey and feedback process. Patient demographics, injury details, timing and nature of interventions and post-injury care will be collected alongside associated complications. The primary outcome measures for the study will be the Glasgow Outcome at Discharge Scale (GODS) and 14-day mortality. Secondary outcome measures will be mortality and extended Glasgow Outcome Scale (GOSE) at the most recent follow-up timepoint.

Background: Different previous studies indicated olfactory function as a predictor of several types of cognitive impairment, in particular related to neurodegenerative disease. However, scanty data are available on the role of odor threshold (OT), odor discrimination (OD), and odor identification (OI) as a predictor of cognitive impairment. The aim of this study was to evaluate potential correlations between each factor of the olfactory function versus each specific cognitive domain of the Montreal Cognitive Assessment (MoCA) test on healthy subjects in relation to gender and age. Methods: Sniffin’ Sticks and MoCA tests were used to determine olfactory function and cognitive abilities, respectively. Results: In men, significant correlations were found in OT versus language index score and OI versus language and executive index score, while in women, OD and OI were correlated to visuospatial index score. Conclusions: Our data suggested that olfactory function (OT, OD, and OI) may be considered a predictor for cognitive impairment in relation to gender and age.