Different protocols for analyzing behavior and adaptability in obstacle crossing in Parkinson's disease

Imbalance and tripping over obstacles as a result of altered gait in older adults, especially in patients with Parkinson's disease (PD), are one of the most common causes of falls. During obstacle crossing, patients with PD modify their behavior in order to decrease the mechanical demands and enhance dynamic stability. Various descriptions of dynamic traits of gait that have been collected over longer periods, probably better synthesize the underlying structure and pattern of fluctuations in gait and can be more sensitive markers of aging or early neurological dysfunction and increased risk of falls. This confirmation challenges the clinimetric of different protocols and paradigms used for gait analysis up till now, in particular when analyzing obstacle crossing. The authors here present a critical review of current knowledge concerning the interplay between the cognition and gait in aging and PD, emphasizing the differences in gait behavior and adaptability while walking over different and challenging obstacle paradigms, and the implications of obstacle negotiation as a predictor of falls. Some evidence concerning the effectiveness of future rehabilitation protocols on reviving obstacle crossing behavior by trial and error relearning, taking advantage of dual-task paradigms, physical exercise, and virtual reality have been put forward in this article.Supported by the projects NORTE-01–0145-FEDER-000026 (DeM-Deus Ex Machina) financed by the Regional Operational Program of the North (NORTE2020) PORTUGAL2020 and FEDER, and FP7 Marie Curie ITN Neural Engineering Transformative Technologies (NETT) projectinfo:eu-repo/semantics/publishedVersio

Fabry disease therapy: State-of-the-art and current challenges

Fabry disease (FD) is a lysosomal storage disorder caused by mutations of the GLA gene that lead to a deficiency of the enzymatic activity of α-galactosidase A. Available therapies for FD include enzyme replacement therapy (ERT) (agalsidase alfa and agalsidase beta) and the chaperone migalastat. Despite the large body of literature published about ERT over the years, many issues remain unresolved, such as the optimal dose, the best timing to start therapy, and the clinical impact of anti-drug antibodies. Migalastat was recently approved for FD patients with amenable GLA mutations; however, recent studies have raised concerns that “in vitro” amenability may not always reflect “in vivo” amenability, and some findings on real-life studies have contrasted with the results of the pivotal clinical trials. Moreover, both FD specific therapies present limitations, and the attempt to correct the enzymatic deficiency, either by enzyme exogenous administration or enzyme stabilization with a chaperone, has not shown to be able to fully revert FD pathology and clinical manifestations. Therefore, several new therapies are under research, including new forms of ERT, substrate reduction therapy, mRNA therapy, and gene therapy. In this review, we provide an overview of the state-of-the-art on the currently approved and emerging new therapies for adult patients with FD

Postural stability analysis with inertial measurement units in alzheimer’s disease

BACKGROUND: The cause of frequent falls in patients with Alzheimer's disease (AD) is still not well understood. Nevertheless, balance control and sensory organization are known to be critical for moving safely and adapting to the environment. METHODS: We evaluated postural stability in 20 AD patients (11 fallers and 9 nonfallers) and 16 healthy controls with an inertial measurement unit (triaxial accelerometers and gyroscopes) attached to the center of mass (COM) in different balance conditions (Romberg on flat surface and frontward/backward-inclined surface, with or without visual suppression) in a motor lab. RESULTS: In AD patients, the group of fallers showed a different kinetic pattern of postural stability characterized by higher vulnerability to visual suppression, higher total/maximal displacement and a mediolateral/anteroposterior range of sway, and a consequent need for more corrections of COM pitch and roll angles. CONCLUSION: Further studies are needed to consolidate the normative values of the discriminatory kinetic variables with the potential of inclusion in a multifactorial analysis of the risk of falls. Nevertheless, these results highlight signs of impairment of central postural control in AD, which may require early therapeutic intervention.The Center ALGORITMI was funded by the Neural Engineering Transformative Technologies (NETT) project

Role of 99mTc-Sulesomab Immunoscintigraphy in the Management of Infection following Deep Brain Stimulation Surgery

Infection constitutes a serious adverse event in patients submitted to deep brain stimulation, often leading to removal of the device. We set to evaluate the potential role of immunoscintigraphy with 99mTc-labelled antigranulocyte antibody fragments (99mTc-sulesomab) in the management of infection following DBS. 99mTc-sulesomab immunoscintigraphy seems to correlate well with the presence and extent of infection, thus contributing to differentiate between patients who should remove the hardware entirely at presentation and those who could undergo a more conservative approach. Also, 99mTc-sulesomab immunoscintigraphy has a role in determining the most appropriate timing for reimplantation. Finally, we propose an algorithm for the management of infection following DBS surgery, based on the results of the 99mTc-sulesomab immunoscintigraphy

Discrimination of idiopathic Parkinson's disease and vascular parkinsonism based on gait time series and the levodopa effect

Idiopathic Parkinson's disease (IPD) and vascular parkinsonism (VaP) present highly overlapping phenotypes, making it challenging to distinguish between these two parkinsonian syndromes. Recent evidence suggests that gait assessment and response to levodopa medication may assist in the objective evaluation of clinical differences. In this paper, we propose a new approach for gait pattern differentiation that uses convolutional neural networks (CNNs) based on gait time series with and without the influence of levodopa medication. Wearable sensors positioned on both feet were used to acquire gait data from 14 VaP patients, 15 IPD patients, and 34 healthy subjects. An individual's gait features are affected by physical characteristics, including age, height, weight, sex, and walking speed or stride length. Therefore, to reduce bias due to intersubject variations, a multiple regression normalization approach was used to obtain gait data. Recursive feature elimination using the linear support vector machine, lasso, and random forest were applied to infer the optimal feature subset that led to the best results. CNNs were implemented by means of various hyperparameters and feature subsets. The best CNN classifiers achieved accuracies of 79.33%±6.46, 82.33%±10.62, and 86.00%±7.12 without (off state), with (on state), and with the simultaneous consideration of the effect of levodopa medication (off/on state), respectively. The response to levodopa medication improved classification performance. Based on gait time series and response to medication, the proposed approach differentiates between IPD and VaP gait patterns and reveals a high accuracy rate, which might prove useful when distinguishing other diseases related to movement disorders.This research was partially financed by NORTE2020 and FEDER within the project NORTE-01–0145-FEDER- 000026 (DeM-Deus Ex Machina) and by Portuguese Funds through FCT (Fundação para a Ciência e a Tecnologia) within the Projects UIDB/00013/2020, UIDP/00013/2020 and UIDB/00319/2020

Gait classification of patients with Fabry's disease based on normalized gait features obtained using multiple regression models

Diagnosis of Fabry disease (FD) remains a challenge mostly due to its rare occurrence and phenotipical variability, with considerable delay between onset and clinical diagnosis. It is then of extreme importance to explore biomarkers capable of assisting the earlier diagnosis of FD. There is growing evidence supporting the use of gait assessment in the diagnosis and management of several neurological diseases. In fact, gait abnormalities have previously been observed in FD, justifying further investigation. The aim of this study is to evaluate the effectiveness of different machine learning strategies when distinguishing patients with FD from healthy controls based on normalized gait features. Gait features of an individual are affected by physical characteristics including age, height, weight, and gender, as well as walking speed or stride length. Therefore, in order to reduce bias due to inter-subject variations a multiple regression (MR) normalization approach for gait data was performed. Four different machine learning strategies - Support Vector Machines (SVM), Random Forest (RF), Multiple Layer Perceptrons (MLPs), and Deep Belief Networks (DBNs) - were employed on raw and normalized gait data. Wearable sensors positioned on both feet were used to acquire the gait data from 36 patients with FD and 34 healthy subjects. Gait normalization using MR revealed significant differences in percentage of stance phase spent in foot flat and pushing (p < 0.05), with FD presenting lower percentages in foot flat and higher in pushing. No significant differences were observed before gait normalization. Support Vector Machine was the superior classifier achieving an FD classification accuracy of 78.21% after gait normalization, compared to 71.96% using raw gait data. Gait normalization improved the performance of all classifiers. To the best of our knowledge, this is the first study on gait classification that includes patients with FD, and our results support the use of gait assessment on the clinical assessment of FD.This work was partially supported by the projects NORTE-01-0145- FEDER- 000026 (DeM-Deus Ex Machina) financed by NORTE2020 and FEDER, and the Pluriannual Funding Programs of the research centres CMAT and Algoritm

The effect of levodopa on postural stability evaluated by wearable inertial measurement units for idiopathic and vascular Parkinson’s disease

BACKGROUND: Postural stability analysis has shown that postural control is impaired in untreated idiopathic Parkinson's disease (IPD), even in the early stages of the disease. Vascular Parkinson's disease (VPD) lacks consensus clinical criteria or diagnostic tests. Moreover, the levodopa effect on postural balance remains undefined for IPD and even less so for VPD. OBJECTIVE: To characterize postural stability, using kinematic analysis with wearable inertial measurement units, in IPD and VPD patients without clinical PI, and to subsequently analyze the response to levodopa. METHODS: Ten patients with akinetic-rigid IPD and five patients with VPD were included. Clinical and postural stability kinematic analysis was performed before and after levodopa challenge, on different standing tasks: normal stance (NS), Romberg eyes open (REO) and Romberg eyes closed. RESULTS: In the "off state", VPD patients had higher mean distances and higher maximal distance of postural sway on NS and REO tasks, respectively. VPD patients maintained a higher range of anterior-posterior (AP) postural sway after levodopa. In the absence of PI and non-significant differences in UPDRS-III, a higher mPIGD score in the VPD patients was mainly due to gait disturbance. Gait disturbance, and not UPDRS-III, influenced the degree of postural sway response to levodopa for VPD patients. CONCLUSION: Quantitative postural sway evaluation is useful in the investigation of Parkinsonian syndromes. VPD patients have higher AP postural sway that is correlated with their gait disturbance burden and also not responsive to levodopa. These observations corroborate the interconnection of postural control and locomotor networks

Fabry disease and the heart: a comprehensive review

Fabry disease (FD) is an X-linked lysosomal storage disorder caused by mutations of the GLA gene that result in a deficiency of the enzymatic activity of α-galactosidase A and consequent accumulation of glycosphingolipids in body fluids and lysosomes of the cells throughout the body. GB3 accumulation occurs in virtually all cardiac cells (cardiomyocytes, conduction system cells, fibroblasts, and endothelial and smooth muscle vascular cells), ultimately leading to ventricular hypertrophy and fibrosis, heart failure, valve disease, angina, dysrhythmias, cardiac conduction abnormalities, and sudden death. Despite available therapies and supportive treatment, cardiac involvement carries a major prognostic impact, representing the main cause of death in FD. In the last years, knowledge has substantially evolved on the pathophysiological mechanisms leading to cardiac damage, the natural history of cardiac manifestations, the late-onset phenotypes with predominant cardiac involvement, the early markers of cardiac damage, the role of multimodality cardiac imaging on the diagnosis, management and follow-up of Fabry patients, and the cardiac efficacy of available therapies. Herein, we provide a comprehensive and integrated review on the cardiac involvement of FD, at the pathophysiological, anatomopathological, laboratory, imaging, and clinical levels, as well as on the diagnosis and management of cardiac manifestations, their supportive treatment, and the cardiac efficacy of specific therapies, such as enzyme replacement therapy and migalastat

Parkinson’s Disease and Fabry Disease: Clinical, Biochemical and Neuroimaging Analysis of Three Pedigrees

Background: Sporadic Parkinson's disease (PD) patients have lower α-galactosidase A (α-GAL A) enzymatic activity and Fabry disease (FD) patients potentially carry an increased risk of PD. Objective: Determination of PD prevalence in FD and clinical, biochemical and vascular neuroimaging description of FD pedigrees with concomitant PD. Methods: Clinical screening for PD in 229 FD patients belonging to 31 families, harbouring GLA gene mutation p.F113L, and subsequent pedigree analysis. Gender-stratified comparison of FD+/PD+ patients with their family members with FD but without PD (FD+/PD-) regarding Mainz scores, plasma & leukocytes α-GAL A enzymatic activity, urinary Gb3 and plasma Lyso-Gb3, vascular brain neuroimaging. Results: Prevalence of PD in FD was 1.3% (3/229) (3% in patients aged ≥50 years). Three FD patients, one female (73 years old) (P1) and two males (60 and 65 years old) (P2 and P3), three different pedigrees, presented akinetic-rigid PD, with weak response to levodopa (16% - 36%), and dopaminergic deficiency on 18F-DOPA PET. No pathogenic mutations were found in a PD gene panel. FD+/PD+ patients had worse clinical severity of FD (above upper 75% IQR in Mainz scores), and cortico-subcortical white matter/small vessel lesions. P3 patient was under enzyme therapy, started 1 year before PD diagnosis. P2-P3 patients had higher leucocyte α-GAL A activity (2,2-3 vs.1,0 (median)(nmol/h/mg)). Conclusion: We have shown a high prevalence of PD in a late-onset phenotype of FD, presenting high cerebrovascular burden and weak response to levodopa. Further studies will untangle how much of this PD phenotype is due to Gb3 deposition versus cerebrovascular lesions in the nigro-striatal network.info:eu-repo/semantics/publishedVersio

Azimuthal anisotropy of charged jet production in root s(NN)=2.76 TeV Pb-Pb collisions

We present measurements of the azimuthal dependence of charged jet production in central and semi-central root s(NN) = 2.76 TeV Pb-Pb collisions with respect to the second harmonic event plane, quantified as nu(ch)(2) (jet). Jet finding is performed employing the anti-k(T) algorithm with a resolution parameter R = 0.2 using charged tracks from the ALICE tracking system. The contribution of the azimuthal anisotropy of the underlying event is taken into account event-by-event. The remaining (statistical) region-to-region fluctuations are removed on an ensemble basis by unfolding the jet spectra for different event plane orientations independently. Significant non-zero nu(ch)(2) (jet) is observed in semi-central collisions (30-50% centrality) for 20 <p(T)(ch) (jet) <90 GeV/c. The azimuthal dependence of the charged jet production is similar to the dependence observed for jets comprising both charged and neutral fragments, and compatible with measurements of the nu(2) of single charged particles at high p(T). Good agreement between the data and predictions from JEWEL, an event generator simulating parton shower evolution in the presence of a dense QCD medium, is found in semi-central collisions. (C) 2015 CERN for the benefit of the ALICE Collaboration. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe