Adaptation strategies and neurophysiological response in early-stage Parkinson's disease: BioVRSea approach

IntroductionThere is accumulating evidence that many pathological conditions affecting human balance are consequence of postural control (PC) failure or overstimulation such as in motion sickness. Our research shows the potential of using the response to a complex postural control task to assess patients with early-stage Parkinson's Disease (PD).MethodsWe developed a unique measurement model, where the PC task is triggered by a moving platform in a virtual reality environment while simultaneously recording EEG, EMG and CoP signals. This novel paradigm of assessment is called BioVRSea. We studied the interplay between biosignals and their differences in healthy subjects and with early-stage PD.ResultsDespite the limited number of subjects (29 healthy and nine PD) the results of our work show significant differences in several biosignals features, demonstrating that the combined output of posturography, muscle activation and cortical response is capable of distinguishing healthy from pathological.DiscussionThe differences measured following the end of the platform movement are remarkable, as the induced sway is different between the two groups and triggers statistically relevant cortical activities in α and θ bands. This is a first important step to develop a multi-metric signature able to quantify PC and distinguish healthy from pathological response

sEMG Spectral Analysis and Machine Learning Algorithms Are Able to Discriminate Biomechanical Risk Classes Associated with Manual Material Liftings

Funding Information: The authors thank the researchers of the Motion Sickness Laboratory of the Reykjavik University (Iceland) and Engg. Teresa Pirozzi and Federica Cirillo for their technical support. Work by LD and FE in part supported by #NEXTGENERATIONEU (NGEU) and funded by the Ministry of University and Research (MUR), National Recovery and Resilience Plan (NRRP), project MNESYS (PE0000006)—A Multiscale integrated approach to the study of the nervous system in health and disease (DN. 1553 11.10.2022). Publisher Copyright: © 2023 by the authors.Manual material handling and load lifting are activities that can cause work-related musculoskeletal disorders. For this reason, the National Institute for Occupational Safety and Health proposed an equation depending on the following parameters: intensity, duration, frequency, and geometric characteristics associated with the load lifting. In this paper, we explore the feasibility of several Machine Learning (ML) algorithms, fed with frequency-domain features extracted from electromyographic (EMG) signals of back muscles, to discriminate biomechanical risk classes defined by the Revised NIOSH Lifting Equation. The EMG signals of the multifidus and erector spinae muscles were acquired by means of a wearable device for surface EMG and then segmented to extract several frequency-domain features relating to the Total Power Spectrum of the EMG signal. These features were fed to several ML algorithms to assess their prediction power. The ML algorithms produced interesting results in the classification task, with the Support Vector Machine algorithm outperforming the others with accuracy and Area under the Receiver Operating Characteristic Curve values of up to 0.985. Moreover, a correlation between muscular fatigue and risky lifting activities was found. These results showed the feasibility of the proposed methodology—based on wearable sensors and artificial intelligence—to predict the biomechanical risk associated with load lifting. A future investigation on an enriched study population and additional lifting scenarios could confirm the potential of the proposed methodology and its applicability in the field of occupational ergonomics.Peer reviewe

Adaptation strategies and neurophysiological response in early-stage Parkinson's disease : BioVRSea approach

Copyright © 2023 Jacob, Guerrini, Pescaglia, Pierucci, Gelormini, Minutolo, Fratini, Di Lorenzo, Petersen and Gargiulo.INTRODUCTION: There is accumulating evidence that many pathological conditions affecting human balance are consequence of postural control (PC) failure or overstimulation such as in motion sickness. Our research shows the potential of using the response to a complex postural control task to assess patients with early-stage Parkinson's Disease (PD). METHODS: We developed a unique measurement model, where the PC task is triggered by a moving platform in a virtual reality environment while simultaneously recording EEG, EMG and CoP signals. This novel paradigm of assessment is called BioVRSea. We studied the interplay between biosignals and their differences in healthy subjects and with early-stage PD. RESULTS: Despite the limited number of subjects (29 healthy and nine PD) the results of our work show significant differences in several biosignals features, demonstrating that the combined output of posturography, muscle activation and cortical response is capable of distinguishing healthy from pathological. DISCUSSION: The differences measured following the end of the platform movement are remarkable, as the induced sway is different between the two groups and triggers statistically relevant cortical activities in α and θ bands. This is a first important step to develop a multi-metric signature able to quantify PC and distinguish healthy from pathological response.Peer reviewe

Adaptation strategies and neurophysiological response in early-stage Parkinson's disease: BioVRSea approach

Introduction: There is accumulating evidence that many pathological conditions affecting human balance are consequence of postural control (PC) failure or overstimulation such as in motion sickness. Our research shows the potential of using the response to a complex postural control task to assess patients with early-stage Parkinson's Disease (PD). Methods: We developed a unique measurement model, where the PC task is triggered by a moving platform in a virtual reality environment while simultaneously recording EEG, EMG and CoP signals. This novel paradigm of assessment is called BioVRSea. We studied the interplay between biosignals and their differences in healthy subjects and with early-stage PD. Results: Despite the limited number of subjects (29 healthy and nine PD) the results of our work show significant differences in several biosignals features, demonstrating that the combined output of posturography, muscle activation and cortical response is capable of distinguishing healthy from pathological. Discussion: The differences measured following the end of the platform movement are remarkable, as the induced sway is different between the two groups and triggers statistically relevant cortical activities in α and θ bands. This is a first important step to develop a multi-metric signature able to quantify PC and distinguish healthy from pathological response

Toward New Assessment of Knee Cartilage Degeneration

Funding Information: The authors would like to thank the project RESTORE for their contribution to this study, Marco Ghiselli and Kristján Örn Jóhannesson from the National University Hospital of Iceland for the medical image acquisition, Vicenzo Cangiano for his help in medical image segmentation. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study is part of the European project RESTORE ( https://restoreproject.eu/ ), funded by the European Union’s Horizon 2020 research and innovation program (grant agreement ID: 814558). This work has also been funded by Landspitalin Science fund (grant number: 960221). Publisher Copyright: © The Author(s) 2022. Publisher Copyright: © The Author(s) 2022.Objective: Assessment of human joint cartilage is a crucial tool to detect and diagnose pathological conditions. This exploratory study developed a workflow for 3D modeling of cartilage and bone based on multimodal imaging. New evaluation metrics were created and, a unique set of data was gathered from healthy controls and patients with clinically evaluated degeneration or trauma. Design: We present a novel methodology to evaluate knee bone and cartilage based on features extracted from magnetic resonance imaging (MRI) and computed tomography (CT) data. We developed patient specific 3D models of the tibial, femoral, and patellar bones and cartilages. Forty-seven subjects with a history of degenerative disease, traumatic events, or no symptoms or trauma (control group) were recruited in this study. Ninety-six different measurements were extracted from each knee, 78 2D and 18 3D measurements. We compare the sensitivity of different metrics to classify the cartilage condition and evaluate degeneration. Results: Selected features extracted show significant difference between the 3 groups. We created a cumulative index of bone properties that demonstrated the importance of bone condition to assess cartilage quality, obtaining the greatest sensitivity on femur within medial and femoropatellar compartments. We were able to classify degeneration with a maximum recall value of 95.9 where feature importance analysis showed a significant contribution of the 3D parameters. Conclusion: The present work demonstrates the potential for improving sensitivity in cartilage assessment. Indeed, current trends in cartilage research point toward improving treatments and therefore our contribution is a first step toward sensitive and personalized evaluation of cartilage condition.Peer reviewe

Efficacy of ketamine in refractory convulsive status epilepticus in children: A protocol for a sequential design, multicentre, randomised, controlled, open-label, non-profit trial (KETASER01)

Introduction: Status epilepticus (SE) is a lifethreatening neurological emergency. SE lasting longer than 120 min and not responding to first-line and second-line antiepileptic drugs is defined as 'refractory' (RCSE) and requires intensive care unit treatment. There is currently neither evidence nor consensus to guide either the optimal choice of therapy or treatment goals for RCSE, which is generally treated with coma induction using conventional anaesthetics (high dose midazolam, thiopental and/or propofol). Increasing evidence indicates that ketamine (KE), a strong N-methyl-D-aspartate glutamate receptor antagonist, may be effective in treating RCSE. We hypothesised that intravenous KE is more efficacious and safer than conventional anaesthetics in treating RCSE. Methods and analysis: A multicentre, randomised, controlled, open-label, non-profit, sequentially designed study will be conducted to assess the efficacy of KE compared with conventional anaesthetics in the treatment of RCSE in children. 10 Italian centres/ hospitals are involved in enrolling 57 patients aged 1 month to 18 years with RCSE. Primary outcome is the resolution of SE up to 24 hours after withdrawal of therapy and is updated for each patient treated according to the sequential method. Ethics and dissemination: The study received ethical approval from the Tuscan Paediatric Ethics Committee (12/2015). The results of this study will be published in peer-reviewed journals and presented at international conferences

Productos naturales: investigación y perspectivas en Ecuador

Ecuador es un país privilegiado por su riqueza en organismos vivos íntimamente relacionados con su alta biodiversidad. En los últimos 20 años, las universidades públicas y privadas, así como los institutos de investigación, han invertido en la formación de sus docentes-investigadores como en tecnología de última generación relacionada con este tema. Este texto refleja los avances en la producción científica que se han generado en el país. Tres capítulos son revisiones exhaustivas del uso tradicional y el potencial de las plantas medicinales en problemas de salud y aplicaciones puntuales. Un capítulo analiza las plantas medicinales y sus metabolitos en una determinada área biogeográfica del Ecuador. Una revisión se centra en el aceite esencial de una especie nativa de elevado potencial bio-económico como la Psidium guajava. Dos estudios experimentales confirman la riqueza fitoquímica y el potencial medicinal de especies de nuestra biodiversidad como la Persea americana y Chuquiraga jussiuei. Y finalmente, un capítulo analiza la importancia del control en los productos naturales procesados con base en su calidad microbiológica y la relación con las correctas prácticas de manufactura. Este texto confirma que Ecuador tiene mucho que mostrar al mundo de la ciencia

Segmentazione del cammino nel Parkinson con e senza freezing: confronto della performance di 17 algoritmi per l'analisi di misure inerziali

I disturbi motori sono per le persone affette da Parkinson una delle più frequenti cause di disabilità e limitazione nello svolgimento delle attività della vita quotidiana. La loro camminata è caratterizzata da bassa velocità, produzione di shuffling, passi corti e alta cadenza del passo. Questo studio si pone come obiettivo l’analisi cinematica del cammino su persone con Parkinson tramite l’utilizzo di sensori inerziali. 20 soggetti sono stati acquisiti durante 6 minuti di cammino con 5 sensori inerziali applicati su tronco, caviglie e piedi. Sono stati valutati 17 algoritmi proposti in letteratura per l’identificazione degli istanti di interesse: FC (‘Foot Contact’, istante di contatto del piede col suolo) e FO (‘Foot off’, istante in cui le dita del piede si staccano dal suolo). Gli eventi ripresi da una telecamera sono stati assunti come riferimento. Se la percentuale di rilevazione degli eventi del passo da parte di un algoritmo era inferiore all’81% rispetto al Gold standard non poteva essere incluso nelle analisi. Sono stati calcolati gli intervalli temporali che intercorrevano tra le varie fasi. Sulla base dei risultati è stata condotta un’analisi statistica per valutare le prestazioni migliori a seconda di posizionamento dei sensori, variabile analizzata e approccio computazionale. Tutti gli algoritmi sono stati confrontati tra loro. Dai risultati emerge che, nell’identificazione degli eventi del passo, il posizionamento dei sensori posti su piede e caviglia danno performance migliori, rispetto a quando vengono posizionati sul tronco. Per la variabile analizzata, gli algoritmi che sfruttano la velocità angolare sono da preferire a quelli che utilizzano l’accelerazione. In base al diverso approccio implementativo, performance diverse sono state osservate in relazione al posizionamento e al filtraggio utilizzato. Per gli algoritmi che non superavano la soglia minima richiesta sulla sensitività sono state avanzate alcune modifiche nella loro implementazione

Folic Acid-Peptide Conjugates Combine Selective Cancer Cell Internalization with Thymidylate Synthase Dimer Interface Targeting

Drug-target interaction, cellular internalization, and target engagement should be addressed to design a lead with high chances of success in further optimization stages. Accordingly, we have designed conjugates of folic acid with anticancer peptides able to bind human thymidylate synthase (hTS) and enter cancer cells through folate receptor alpha (FRalpha) highly expressed by several cancer cells. Mechanistic analyses and molecular modeling simulations have shown that these conjugates bind the hTS monomer-monomer interface with affinities over 20 times larger than the enzyme active site. When tested on several cancer cell models, these conjugates exhibited FRalpha selectivity at nanomolar concentrations. A similar selectivity was observed when the conjugates were delivered in synergistic or additive combinations with anticancer agents. At variance with 5-fluorouracil and other anticancer drugs that target the hTS catalytic pocket, these conjugates do not induce overexpression of this protein and can thus help combating drug resistance associated with high hTS levels