Functional impairment in patients with myotonic dystrophy type 1 can be assessed by an ataxia rating scale (SARA)

Myotonic dystrophy type 1 (DM1) is not characterised by ataxia per se; however, DM1 and ataxia patients show similar disturbances in movement coordination often experiencing walking and balance difficulties, although caused by different underlying pathologies. This study aims to investigate the use of a scale previously described for the assessment and rating of ataxia (SARA) with the hypothesis that it could have utility in DM1 patients as a measure of disease severity and risk of falling. Data from 54 DM1 patients were pulled from the PHENO-DM1 natural history study for analysis. Mean SARA score in the DM1 population was 5.45 relative to the maximum score of eight. A flooring effect (score 0) was observed in mild cases within the sample. Inter-rater and test–retest reliability was high with intraclass coefficients (ICC) of 0.983 and 1.00, respectively. Internal consistency was acceptable as indicated by a Cronbach’s alpha of 0.761. Component analysis revealed two principle components. SARA correlated with: (1) all measures of muscle function tested, including quantitative muscle testing of ankle dorsiflexion (r = −0.584*), the 6 min walk test (r = −0.739*), 10 m walk test (r = 0.741*), and the nine hole peg test (r = 0.602*) and (2) measures of disease severity/burden, such as MIRS (r = 0.718*), MDHI (r = 0.483*), and DM1-Activ (r = −0.749*) (*p < 0.001). The SARA score was predicted by an interaction between modal CTG repeat length and age at sampling (r = 0.678, p = 0.003). A score of eight or above predicted the use of a walking aid with a sensitivity of 100% and a specificity of 85.7%. We suggest that further research is warranted to ascertain whether SARA or components of SARA are useful outcome measures for clinical trials in DM1. As a tool, it can be used for gathering information about disease severity/burden and helping to identify patients in need of a walking aid, and can potentially be applied in both research and healthcare settings

Charged-current inclusive neutrino cross sections in the SuperScaling model including quasielastic, pion production and meson-exchange contributions

Charged current inclusive neutrino-nucleus cross sections are evaluated using the superscaling model for quasielastic scattering and its extension to the pion production region. The contribution of two-particle-two-hole vector meson-exchange current excitations is also considered within a fully relativistic model tested against electron scattering data. The results are compared with the inclusive neutrino-nucleus data from the T2K and SciBooNE experiments. For experiments where $\langle E_\nu \rangle \sim 0.8$ GeV, the three mechanisms considered in this work provide good agreement with the data. However, when the neutrino energy is larger, effects from beyond the $\Delta$ also appear to be playing a role. The results show that processes induced by two-body currents play a minor role at the kinematics considered.Comment: 10 pages, 7 figure

Robotic navigation algorithm with machine vision

In the field of robotics, it is essential to know the work area in which the agent is going to develop, for that reason, different methods of mapping and spatial location have been developed for different applications. In this article, a machine vision algorithm is proposed, which is responsible for identifying objects of interest within a work area and determining the polar coordinates to which they are related to the observer, applicable either with a fixed camera or in a mobile agent such as the one presented in this document. The developed algorithm was evaluated in two situations, determining the position of six objects in total around the mobile agent. These results were compared with the real position of each of the objects, reaching a high level of accuracy with an average error of 1.3271% in the distance and 2.8998% in the angle

Abnormal gait detection by means of LSTM

This article presents a system focused on the detection of three types of abnormal walk patterns caused by neurological diseases, specifically Parkinsonian gait, Hemiplegic gait, and Spastic Diplegic gait. A Kinect sensor is used to extract the Skeleton from a person during its walk, to then calculate four types of bases that generate different sequences from the 25 points of articulations that the Skeleton gives. For each type of calculated base, a recurrent neural network (RNN) is trained, specifically a Long short-term memory (LSTM). In addition, there is a graphical user interface that allows the acquisition, training, and testing of trained networks. Of the four trained networks, 98.1% accuracy is obtained with the database that was calculated with the distance of each point provided by the Skeleton to the Hip-Center point

Real-time moving object segmentation in H.264 compressed domain based on approximate reasoning

AbstractThis paper presents a real-time segmentation algorithm to obtain moving objects from the H.264 compressed domain. The proposed segmentation works with very little information and is based on two features of the H.264 compressed video: motion vectors associated to the macroblocks and decision modes. The algorithm uses fuzzy logic and allows to describe position, velocity and size of the detected regions in a comprehensive way, so the proposed approach works with low level information but manages highly comprehensive linguistic concepts. The performance of the algorithm is improved using dynamic design of fuzzy sets that avoids merge and split problems. Experimental results for several traffic scenes demonstrate the real-time performance and the encouraging results in diverse situations

Meson-exchange currents and quasielastic predictions for charged-current neutrino-12C scattering in the superscaling approach

We evaluate and discuss the impact of meson-exchange currents (MECs) on charged-current quasielastic neutrino cross sections. We consider the nuclear transverse response arising from two-particle two-hole states excited by the action of electromagnetic, purely isovector meson-exchange currents in a fully relativistic framework based on the work by the Torino Collaboration [A. D. Pace, M. Nardi, W. M. Alberico, T. W. Donnelly, and A. Molinari, Nucl. Phys. A726, 303 (2003)]. An accurate parametrization of this MEC response as a function of the momentum and energy transfers involved is presented. Results of neutrino-nucleus cross sections using this MEC parametrization together with a recent scaling approach for the one-particle one-hole contributions (named SuSAv2) are compared with experimental data (MiniBooNE, MINERvA, NOMAD and T2K Collaborations).Comment: 16 pages, 19 figure

Lesson from the habitat suitability models to evaluate the environmental of Pinus nigra Arnold and Pinus sylvesris L. in the Iberian Peninsula

PREDICT POTENTIAL DISTRIBUTION. Spatial and temporal evolution of the species under different climate scenarios. Generation of habitat suitability models (HSM) high degree of uncertainty and limitations. The importance of their validation has been stressed. In this work we discuss the present potential distribution of P. sylvestris and P. nigra in the Iberian Peninsula by using MaxEnt, and evaluate the influence of the different environmental variables. Our intention is to select a set of environmental variables that explains better their current distribution, to achieve the most accurate and reliable models. Then we project them to the past climatic conditions (21 to 0 kyrs BP), to evaluate the outputs with existing palaeo-ecological data

Disease burden of myotonic dystrophy type 1

Objective: The objective of this cross-sectional, observational study was to investigate the disease burden of myotonic dystrophy type 1 (DM1), a disabling muscle disorder. Methods: Adults with DM1 were recruited as part of the PhenoDM1 study from Newcastle University (Newcastle upon Tyne, UK). Disease burden data were recorded through the Individualized Neuromuscular Quality of Life (INQoL) questionnaire. Results were examined by sex and clinical variables [e.g. the six-minute walk test (6MWT), the Mini Mental State Examination, and estimated progenitor and modal allele CTG repeat length]. Results: Our sample consisted of 60 patients with DM1 (mean age: 45 years; 45% female). Muscle weakness and fatigue constituted the two most common disease manifestations, reported by 93% and 90% of patients, respectively, followed by muscle locking (73%). Most patients (> 55%) reported feeling anxious/worried, depressed, frustrated, and/or having low confidence/self-esteem, 23% and 33% indicated substantial impairment of daily and leisure activities, respectively, and 47% did not work as a consequence of the disease. Estimated progenitor CTG length corrected by age correlated surprisingly well with INQoL scores. Differences by sex were generally minor. Conclusion: We show that DM1 is associated with a substantial disease burden resulting in impairment across many different domains of patients’ lives, emphasizing the need for a holistic approach to medical management. Our results also show that the INQoL records relevant information about patients with DM1, but that further investigation of the psychometric properties of the scale is needed for meaningful interpretation of instrument scores

Sliding window multi-curve resolution: application to gas chromatography - ion mobility spectrometry

Blind source separation (BSS) techniques aim to extract a set of source signals from a measured mixture in an unsupervised manner. In the chemical instrumentation domain source signals typically refer to time-varying analyte concentrations, while the measured mixture is the set of observed spectra. Several techniques exist to perform BSS on ion mobility spectrometry, being simple-to-use interactive self-modelling mixture analysis (SIMPLISMA) and multivariate curve resolution (MCR) the most commonly used. The addition of a multi-capillary gas chromatography column using the ion mobility spectrometer as detector has been proposed in the past to increase chemical resolution. Short chromatography times lead to high levels of co-elution, and ion mobility spectra are key to resolve them. For the first time, BSS techniques are used to deconvolve samples of the gas chromatography-ion mobility spectrometry tandem. We propose a method to extract spectra and concentration profiles based on the application of MCR in a sliding window. Our results provide clear concentration profiles and pure spectra, resolving peaks that were not detected by the conventional use of MCR. The proposed technique could also be applied to other hyphenated instruments with similar strong co-elutions

The UK myotonic dystrophy patient registry: facilitating and accelerating clinical research

Myotonic dystrophy type 1 (DM1) is the most frequent muscular dystrophy worldwide with complex, multi-systemic, and progressively worsening symptoms. There is currently no treatment for this inherited disorder and research can be challenging due to the rarity and variability of the disease. The UK Myotonic Dystrophy Patient Registry is a patient self-enrolling online database collecting clinical and genetic information. For this cross-sectional “snapshot” analysis, 556 patients with a confirmed diagnosis of DM1 registered between May 2012 and July 2016 were included. An almost even distribution was seen between genders and a broad range of ages was present from 8 months to 78 years, with the largest proportion between 30 and 59 years. The two most frequent symptoms were fatigue and myotonia, reported by 79 and 78% of patients, respectively. The severity of myotonia correlated with the severity of fatigue as well as mobility impairment, and dysphagia occurred mostly in patients also reporting myotonia. Men reported significantly more frequent severe myotonia, whereas severe fatigue was more frequently reported by women. Cardiac abnormalities were diagnosed in 48% of patients and more than one-third of them needed a cardiac implant. Fifteen percent of patients used a non-invasive ventilation and cataracts were removed in 26% of patients, 65% of which before the age of 50 years. The registry’s primary aim was to facilitate and accelerate clinical research. However, these data also allow us to formulate questions for hypothesis-driven research that may lead to improvements in care and treatment