A robotic model to investigate human motor control

n/

Physical Activity in Patients with Neuromuscular Disease Three Years after COVID-19, a Longitudinal Survey: The After-Effects of the Quarantine and the Benefits of a Return to a Healthier Life-Style

Background: Quarantine was one of the strategies adopted by governments against the spread of COVID-19. This restriction has caused an increase in sedentary behaviors and a decrease in the practice of physical activity (PA), with a consequent negative impact on lifestyle both in healthy people and in those who need constant practice of PA to combat diseases, such as patients suffering from neuromuscular diseases (NMDs). Hence, this study aimed to compare PA levels among patients with NMD during and after quarantine. Methods: An adapted version of the International Physical Activity Questionnaire Short-Form and the Short-Form Health Survey were administered during COVID-19 quarantine (T0) and after 3 years (T1) to 91 Italian patients with NMDs. Results: We found a significant increase in the total PA level at T1, with no significant changes in vigorous-intensity PA. Moreover, a significant decrease in the PA level was found among the patients with different NMDs. No significant changes in physical component scores and mental component scores were detected. Conclusions: Our results suggest that it would be necessary to provide alternative indoor exercise settings to prevent the adoption of sedentary behaviors

1H-NMR-Based Metabolomics in Autism Spectrum Disorder and Pediatric Acute-Onset Neuropsychiatric Syndrome

We recently described a unique plasma metabolite profile in subjects with pediatric acute-onset neuropsychiatric syndrome (PANS), suggesting pathogenic models involving specific patterns of neurotransmission, neuroinflammation, and oxidative stress. Here, we extend the analysis to a group of patients with autism spectrum disorder (ASD), as a consensus has recently emerged around its immune-mediated pathophysiology with a widespread involvement of brain networks. This observational case-control study enrolled patients referred for PANS and ASD from June 2019 to May 2020, as well as neurotypical age and gender-matched control subjects. Thirty-four PANS outpatients, fifteen ASD outpatients, and twenty-five neurotypical subjects underwent physical and neuropsychiatric evaluations, alongside serum metabolomic analysis with 1H-NMR. In supervised models, the metabolomic profile of ASD was significantly different from controls (p = 0.0001), with skewed concentrations of asparagine, aspartate, betaine, glycine, lactate, glucose, and pyruvate. Metabolomic separation was also observed between PANS and ASD subjects (p = 0.02), with differences in the concentrations of arginine, aspartate, betaine, choline, creatine phosphate, glycine, pyruvate, and tryptophan. We confirmed a unique serum metabolomic profile of PANS compared with both ASD and neurotypical subjects, distinguishing PANS as a pathophysiological entity per se. Tryptophan and glycine appear as neuroinflammatory fingerprints of PANS and ASD, respectively. In particular, a reduction in glycine would primarily affect NMDA-R excitatory tone, overall impairing downstream glutamatergic, dopaminergic, and GABAergic transmissions. Nonetheless, we found metabolomic similarities between PANS and ASD that suggest a putative role of N-methyl-D-aspartate receptor (NMDA-R) dysfunction in both disorders. Metabolomics-based approaches could contribute to the identification of novel ASD and PANS biomarkers

Telecoaching: a potential new training model for Charcot-Marie-Tooth patients: a systematic review

IntroductionCharcot–Marie–Tooth disease (CMT) is an inherited neuropathy that affects the sensory and motor nerves. It can be considered the most common neuromuscular disease, with a prevalence of 1/2500.MethodsConsidering the absence of a specific medical treatment and the benefits shown by physical activity in this population, a systematic review was completed using several search engines (Scopus, PubMed, and Web of Science) to analyze the use, effectiveness, and safety of a training program performed in telecoaching (TC). TC is a new training mode that uses mobile devices and digital technology to ensure remote access to training.ResultsOf the 382 studies identified, only 7 met the inclusion criteria. The effects of a TC training program included improvements in strength, cardiovascular ability, and functional abilities, as well as gait and fatigue. However, the quality of the studies was moderate, the size of the participants in each study was small, and the outcome measured was partial.DiscussionAlthough many studies have identified statistically significant changes following the administration of the TC training protocol, further studies are needed, with appropriate study power, better quality, and a higher sample size

Sistema per l’identificazione di difetti su una superficie di almeno una porzione di una scocca e relativo metodo

La presente invenzione riguarda un sistema e un metodo per l’identificazione, la classificazione e la successiva rimozione di difetti di fabbricazione presenti sui componenti di veicoli

UAVIMALS: Unmanned Aerial Vehicle Integrated with Micro Airborne Laser Scanner

Il progetto consiste in un piccolo drone, leggero e trasportabile, utile come strumento di rilievo della morfologia della superficie del terreno. La sua ingegnerizzazione è stata il frutto di un finanziamento National Geographic Society che ha consentito l’integrazione tra un mezzo personalizzato e un sensore laser a stato solido. Il sistema ha ottenuto ottimi risultati nel context test, la città medievale di Cencelle (VT), rivelando i profili di due grandi ambienti urbani, posti a ridosso delle mura urbiche, non ancora intercettati dalle indagini di scavo

“Intelligent” Drones: novel tools for Remote Sensing applications

In this paper, following an introduction to the use of drones in Remote Sensing applications, we intend to describe our research efforts in the field of autonomous drones and how they can bring innovations to the sector with the aim of enhancing system performance and usability for operators. The focal point revolves around the real-time integration and processing of flight data from on-board sensors with data acquired from Remote Sensing sensors using artificial intelligence algorithms processed directly on-board. This is done to provide operators with high-level information that enables them to make decisions more easily and quickly