Objective assessment of walking impairments in myotonic dystrophy by means of a wearable technology and a novel severity index

Myotonic dystrophy type 1 (DM1) is a genetic inherited autosomal dominant disease characterized by multisystem involvement, including muscle, heart, brain, eye, and endocrine system. Although several methods are available to evaluate muscle strength, endurance, and dexterity, there are no validated outcome measures aimed at objectively evaluating qualitative and quantitative gait alterations. Advantageously, wearable sensing technology has been successfully adopted in objectifying the assessment of motor disabilities in different medical occurrences, so that here we consider the adoption of such technology specifically for DM1. In particular, we measured motor tasks through inertial measurement units on a cohort of 13 DM1 patients and 11 healthy control counterparts. The motor tasks consisted of 16 meters of walking both at a comfortable speed and fast pace. Measured data consisted of plantar-flexion and dorsi-flexion angles assumed by both ankles, so to objectively evidence the footdrop behavior of the DM1 disease, and to define a novel severity index, termed SI-Norm2, to rate the grade of walking impairments. According to the obtained results, our approach could be useful for a more precise stratification of DM1 patients, providing a new tool for a personalized rehabilitation approach

Microwave driven synthesis of narrow bandgap alpha-tin nanoparticles on silicon

This work proposes a microwave-based synthetic route for the preparation of tin nanospheres with a diamond-like a-phase structure on silicon. The main characteristics of the synthesized material are an extraordinarily narrow (around 50 meV) direct bandgap and an improved thermal stability (up to 200° C). Structural and compositional characterizations showed a core–shell structure comprised of an outer amorphous oxide shell and inner core containing a-phase tin domains. Microwaves turned out to be instrumental in achieving the specific nanostructures reported, due to their peculiar heating characteristics. Low pressure, low temperature and compatibility with integrated circuits manufacturing represent the most innovative features of the present synthetic process

Klebsiella pneumoniae is able to trigger epithelial-mesenchymal transition process in cultured airway epithelial cells

The ability of some bacterial pathogens to activate Epithelial-Mesenchymal Transition normally is a consequence of the persistence of a local chronic inflammatory response or depends on a direct interaction of the pathogens with the host epithelial cells. In this study we monitored the abilities of the K. pneumoniae to activate the expression of genes related to EMT-like processes and the occurrence of phenotypic changes in airway epithelial cells during the early steps of cell infection. We describe changes in the production of intracellular reactive oxygen species and increased HIF-1α mRNA expression in cells exposed to K. pneumoniae infection. We also describe the upregulation of a set of transcription factors implicated in the EMT processes, such as Twist, Snail and ZEB, indicating that the morphological changes of epithelial cells already appreciable after few hours from the K. pneumoniae infection are tightly regulated by the activation of transcriptional pathways, driving epithelial cells to EMT. These effects appear to be effectively counteracted by resveratrol, an antioxidant that is able to exert a sustained scavenging of the intracellular ROS. This is the first report indicating that strains of K. pneumoniae may promote EMT-like programs through direct interaction with epithelial cells without the involvement of inflammatory cells

iCollections – Digitising the British and Irish Butterflies in the Natural History Museum, London

This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The attached file is the published version of the article.NHM Repositor

Influence of common source and word line electrodes on program operation in superflash memory

A theoretical study of the influence of word line and common source electrodes on the program operation in shrank SuperFlash memory is proposed. Numerical simulations demonstrate that the literature model defined for previous nodes is not always suitable, due to the continuous cell physical size reduction and to the consequent increment of capacitive coupling between the floating gate and adjacent electrodes. To get a deeper insight, an analytical model of the electric field in the region of source side injection is proposed. This model describes the impact of the cell physical and electrical parameters on the vertical and horizontal field components and highlights the strong dependence of the carrier injection on the technology node. Furthermore, the numerical and analytical models estimate the influence of the word line and common source electrodes on the time‐toprogram, the floating gate potential and the source side injection efficiency, taking into consideration, at the same time, their possible impact on the cell reliability

Toward A Quantitative Evaluation of the Fall Risk Using the Fusion of Inertial Signals and Electromyography with Wearable Sensors

Freezing of Gait (FOG) is an unpredictable gait disorder typical of Parkinson's Disease (PD). The main goals of this work are detecting FOG episodes, classifying FOG subtypes and analyzing the leg muscles activity toward a deeper insight into the disorder pathophysiology and in the associated risk of fall. Fusion of inertial and electromyographic signals in our wearable system allows distinguishing correctly 98.4% of FOG episodes and monitoring in free-living conditions the activity type and intensity of leg antagonist muscles involved in FOG. This is an advancement in the state-of-art knowledge of PD pathophysiology, possibly allowing the implementation of current therapeutic strategies

Prediction of freezing of gait in parkinson’s disease using wearables and machine learning

Freezing of gait (FOG) is one of the most troublesome symptoms of Parkinson’s disease, affecting more than 50% of patients in advanced stages of the disease. Wearable technology has been widely used for its automatic detection, and some papers have been recently published in the direction of its prediction. Such predictions may be used for the administration of cues, in order to prevent the occurrence of gait freezing. The aim of the present study was to propose a wearable system able to catch the typical degradation of the walking pattern preceding FOG episodes, to achieve reliable FOG prediction using machine learning algorithms and verify whether dopaminergic therapy affects the ability of our system to detect and predict FOG. Methods: A cohort of 11 Parkinson’s disease patients receiving (on) and not receiving (off) dopaminergic therapy was equipped with two inertial sensors placed on each shin, and asked to perform a timed up and go test. We performed a step-to-step segmentation of the angular velocity signals and subsequent feature extraction from both time and frequency domains. We employed a wrapper approach for feature selection and optimized different machine learning classifiers in order to catch FOG and pre-FOG episodes. Results: The implemented FOG detection algorithm achieved excellent performance in a leave-one-subject-out validation, in patients both on and off therapy. As for pre-FOG detection, the implemented classification algorithm achieved 84.1% (85.5%) sensitivity, 85.9% (86.3%) specificity and 85.5% (86.1%) accuracy in leave-onesubject- out validation, in patients on (off) therapy. When the classification model was trained with data from patients on (off) and tested on patients off (on), we found 84.0% (56.6%) sensitivity, 88.3% (92.5%) specificity and 87.4% (86.3%) accuracy. Conclusions: Machine learning models are capable of predicting FOG before its actual occurrence with adequate accuracy. The dopaminergic therapy affects pre-FOG gait patterns, thereby influencing the algorithm’s effectiveness

Predicting Axial Impairment in Parkinson’s Disease through a Single Inertial Sensor

Background: Current telemedicine approaches lack standardised procedures for the remote assessment of axial impairment in Parkinson’s disease (PD). Unobtrusive wearable sensors may be a feasible tool to provide clinicians with practical medical indices reflecting axial dysfunction in PD. This study aims to predict the postural instability/gait difficulty (PIGD) score in PD patients by monitoring gait through a single inertial measurement unit (IMU) and machine-learning algorithms. Methods: Thirty-one PD patients underwent a 7-m timed-up-and-go test while monitored through an IMU placed on the thigh, both under (ON) and not under (OFF) dopaminergic therapy. After pre-processing procedures and feature selection, a support vector regression model was implemented to predict PIGD scores and to investigate the impact of L-Dopa and freezing of gait (FOG) on regression models. Results: Specific time-and frequency-domain features correlated with PIGD scores. After optimizing the dimensionality reduction methods and the model parameters, regression algorithms demonstrated different performance in the PIGD prediction in patients OFF and ON therapy (r = 0.79 and 0.75 and RMSE = 0.19 and 0.20, respectively). Similarly, regression models showed different performances in the PIGD prediction, in patients with FOG, ON and OFF therapy (r = 0.71 and RMSE = 0.27; r = 0.83 and RMSE = 0.22, respectively) and in those without FOG, ON and OFF therapy (r = 0.85 and RMSE = 0.19; r = 0.79 and RMSE = 0.21, respectively). Conclusions: Optimized support vector regression models have high feasibility in predicting PIGD scores in PD. L-Dopa and FOG affect regression model performances. Overall, a single inertial sensor may help to remotely assess axial motor impairment in PD patients

Large-scale CMOS-compatible process for silicon nanowires growth and BC8 phase formation

A novel, low temperature process for the formation of Si-BC8 phase is obtained while growing Silicon nanowires. The nanowires growth is performed in a CVD reactor under exposure of the substrate to microwaves, employing Sn nanospheres as catalyst and a flux of SiH4 as precursor, respectively. Microwaves allow for selective heating of the metal catalyst while keeping the substrate at low temperature. At the end of the process, silicon nanowires with the metal sphere on top are obtained, together with the (unexpected) transition of a portion of silicon substrate from the diamond to the Si-BC8 crystallographic phase. Silicon atoms in Si-BC8 phase are arranged in body-centered-cubic unit cells resulting into a different energy-wavevector diagram compared to the silicon diamond cubic phase. Indeed, Si-BC8 possesses a direct band gap as low as 30 meV at room temperature. These features may be employed in a large variety of applications, requiring CMOS-compatible manufacturing. Systematic structural analysis and a phenomenological model for Si-BC8 phase formation are discussed

Large-scale CMOS-compatible process for silicon nanowires growth and BC8 phase formation

A novel, low temperature process for the formation of Si-BC8 phase is obtained while growing Silicon nanowires. The nanowires growth is performed in a CVD reactor under exposure of the substrate to microwaves, employing Sn nanospheres as catalyst and a flux of SiH4 as precursor, respectively. Microwaves allow for selective heating of the metal catalyst while keeping the substrate at low temperature. At the end of the process, silicon nanowires with the metal sphere on top are obtained, together with the (unexpected) transition of a portion of silicon substrate from the diamond to the Si-BC8 crystallographic phase. Silicon atoms in Si-BC8 phase are arranged in body-centered-cubic unit cells resulting into a different energy-wavevector diagram compared to the silicon diamond cubic phase. Indeed, Si-BC8 possesses a direct band gap as low as 30 meV at room temperature. These features may be employed in a large variety of applications, requiring CMOS-compatible manufacturing. Systematic structural analysis and a phenomenological model for Si-BC8 phase formation are discussed