White matter changes in corticobasal degeneration syndrome and correlation with limb apraxia

BACKGROUND: Data on white matter changes in corticobasal degeneration syndrome (CBDS) are not yet available, whereas cortical gray matter loss is a feature of this condition. The structural abnormalities related to a key feature of CBDS (limb apraxia) are unknown. OBJECTIVES: To measure selective structural changes in early CBDS using diffusion tensor imaging and voxel-based morphometry and to evaluate the structural correlates of limb apraxia. DESIGN: Patient and control group comparison. SETTING: Referral center for dementia and movement disorders. PARTICIPANTS: Twenty patients with CBDS and 21 matched control subjects. INTERVENTIONS: Clinical and standardized neuropsychological evaluations, including assessment of limb apraxia. MAIN OUTCOME MEASURES: Gray and white matter changes in early CBDS. RESULTS: Diffusion tensor imaging revealed decreases in fractional anisotropy in the long frontoparietal connecting tracts, the intraparietal associative fibers, and the corpus callosum. Fractional anisotropy was also reduced in the sensorimotor projections of the cortical hand areas. Voxel-based morphometry showed a prevalent gray matter reduction in the left hemisphere (in the inferior frontal and premotor cortices, parietal operculum, superotemporal gyrus, and hippocampus). The pulvinar, bilaterally, and the right cerebellar cortex also showed atrophy. Limb apraxia correlated with parietal atrophy and with fractional anisotropy reductions in the parietofrontal associative fibers (P < .01). The limb-kinetic component of apraxia correlated with reduction of hand sensorimotor connecting fibers. CONCLUSIONS: The present integrative approach to in vivo structural anatomy combines hodologic imaging, describing patterns of white matter connections between cortical areas, with neuropsychological data. This provides new evidence of gray matter and fiber tract abnormalities in early-phase disease and contributes to clarifying the neural basis of apraxia in CBDS

Indoxyl Sulfate Induces Renal Fibroblast Activation through a Targetable Heat Shock Protein 90-Dependent Pathway

Indoxyl sulfate (IS) accumulation occurs early during chronic kidney disease (CKD) progression and contributes to renal dysfunction by inducing fibrosis, inflammation, oxidative stress, and tissue remodeling. Renal toxicity of high IS concentrations (250\u2009\u3bcM) has been widely explored, particularly in resident tubular and glomerular cells, while the effect of a moderate IS increase on kidneys is still mostly unknown. To define the effects of IS accumulation on renal fibroblasts, we first analyzed kidneys of C57BL/6 mice receiving IS (0.1%) in drinking water for 12 weeks. As a next step, we treated renal fibroblasts (NRK-49F) with IS (20\u2009\u3bcM) with or without the HSP90 inhibitor 17-AAG (1\u2009\u3bcM). In mouse kidneys, IS increased the collagen deposition and HSP90 and \u3b1-SMA expression (immunohistochemistry) in interstitial fibroblasts and caused tubular necrosis (histological H&amp;E and picrosirius red staining). In NRK-49F cells, IS induced MCP1, TGF-\u3b2, collagen I, \u3b1-SMA, and HSP90 gene/protein expression and Smad2/3 pathway activation. IS had no effects on fibroblast proliferation and ROS production. 17-AAG counteracted IS-induced MCP1, TGF-\u3b2, collagen I, and \u3b1-SMA expression and Smad2/3 phosphorylation. Our study demonstrates that the IS increase promotes renal fibroblast activation by a HSP90-dependent pathway and indicates HSP90 inhibition as a potential strategy to restrain IS-induced kidney inflammation and fibrosis in CKD

The control of muscle protein turnover in patients on peritoneal dialys

Wasting is observed in a large percentage of patients receiving peritoneal dialysis (PD) and it is associated with functional impairment and worse outcome. In this article, we review the current state of our knowledge regarding the effects of PD on protein metabolism and their possible interactions with the uremia-induced and comorbidity-induced alterations in protein metabolism. Available evidence shows that glucose-based PD induces a new state in muscle protein dynamics, which is characterized by decreased turnover rates and a reduced efficiency of protein turnover, a condition which may be harmful in stress conditions, when nutrient intake is diminished or during superimposed catabolic illnesses. The effects of PD on protein turnover may overlap with the effects of aging and comorbidities to promote net catabolism. There is a need to develop more effective treatments to enhance the nutritional and functional status of PD patients. New approaches include the use of icodextrins to maintain extracellular volume, amino acids/keto acids-containing supplements combined with physical exercise, vitamin D, myostatin antagonism, and ghrelin agonism for malnourished patients refractory to standard nutritional therapy

Early Detection of External Neurological Symptoms through a Wearable Smart-Glasses Prototype

The Internet of Things (IoT) framework is moving the research community to provide smart systems and solutions aimed at revolutionizing medical sciences and healthcare. Given the extreme diffusion of Alzheimer’s disease (AD) and Parkinson’s disease (PD), the demand for a solution to early detect neurological symptoms of such diseases strongly arose. According to the medical literature, such early detection can be obtained through the correlation between PD and AD and some external symptoms: the Essential Tremor (ET) and the number of Eye Blinks (EBs). In this paper, which can be considered as an extended version of [1], we present a prototype of wearable smart glasses able to detect the presence of ET of the head and to count the number of EBs at the same time, in a transparent way with respect to the final user. Numerical results demonstrate the reliability of the proposed approach: the proposed algorithms are able to i) correctly recognize the ET with an overall accuracy above 97% and ii) count the number of EBs with an overall error around 9%

The Organ Handling of Soluble Klotho in Humans

Chronic kidney disease (CKD) reduces both Klotho expression and its shedding into circulation, an effect that accelerates progression and cardiovascular complications. However, the mechanisms that regulate Klotho release by the human kidney are still unknown. Methods: We measured plasma Klotho across the kidney, splanchnic organs and lung in 22 patients (71 \ub1 2 years, estimated glomerular filtration rate [eGFR] 60 \ub1 5.4 mL/min 1.73 m2) during elective diagnostic cardiac catheterizations. Results: Although the Klotho average renal vein concentrations were remarkably higher (by ~9%) than arterial values, the kidney removed Klotho (or was at zero balance) in 7 subjects, indicating that the kidney contribution to systemic Klotho is not constant. Klotho fractional enrichment across the kidney was inversely related to plasma sodium (r = 0.43, p = 0.045) and acid uric acid levels (r = 0.38, p = 0.084) and directly, to renal oxygen extraction (r = 0.56, p = 0.006). In multivariate analysis, renal oxygen extraction was the only predictor of the enrichment of Klotho across the kidney, suggesting the dependence of renal Klotho release on tubular hypoxia or oxidative metabolism. Klotho balance was neutral across the lung. In patients with eGFR &lt;60 mL/min, Klotho was also removed by splanchnic organs (single pass fractional extraction ~11%). Conclusions: The present study identifies kidney oxygen uptake as a predictor of Klotho release, and splanchnic organs as a site for Klotho removal. This study provides new understanding of kidney Klotho release and suggests that modulating kidney oxygen metabolism could increase Klotho delivery, as an option to slow disease progression and blunt organ damage

Peripheral artery disease and blood pressure profile abnormalities in hemodialysis patients

Patients undergoing chronic hemodialysis (HD) are at increased risk for peripheral artery disease (PAD). Both ankle-brachial index (ABI) and ambulatory blood pressure monitoring (ABPM) in the interdialytic period have been shown to be strong predictors of all-cause mortality

Validation of an optimized SPM procedure for FDG-PET in dementia diagnosis in a clinical setting

Diagnostic accuracy in FDG-PET imaging highly depends on the operating procedures. In this clinical study on dementia, we compared the diagnostic accuracy at a single-subject level of a) Clinical Scenarios, b) Standard FDG Images and c) Statistical Parametrical (SPM) Maps generated via a new optimized SPM procedure. We evaluated the added value of FDG-PET, either Standard FDG Images or SPM Maps, to Clinical Scenarios. In 88 patients with neurodegenerative diseases (Alzheimer's Disease—AD, Frontotemporal Lobar Degeneration—FTLD, Dementia with Lewy bodies—DLB and Mild Cognitive Impairment—MCI), 9 neuroimaging experts made a forced diagnostic decision on the basis of the evaluation of the three types of information. There was also the possibility of a decision of normality on the FDG-PET images. The clinical diagnosis confirmed at a long-term follow-up was used as the gold standard. SPM Maps showed higher sensitivity and specificity (96% and 84%), and better diagnostic positive (6.8) and negative (0.05) likelihood ratios compared to Clinical Scenarios and Standard FDG Images. SPM Maps increased diagnostic accuracy for differential diagnosis (AD vs. FTD; beta 1.414, p = 0.019). The AUC of the ROC curve was 0.67 for SPM Maps, 0.57 for Clinical Scenarios and 0.50 for Standard FDG Images. In the MCI group, SPM Maps showed the highest predictive prognostic value (mean LOC = 2.46), by identifying either normal brain metabolism (exclusionary role) or hypometabolic patterns typical of different neurodegenerative conditions

When eHealth Meets IoT: A Smart Wireless System for Post-Stroke Home Rehabilitation

In recent years, the emerging framework of the Internet of Things has been leading the technological landscape in a number of different fields and applications, from autonomous and connected vehicles to wearable devices. The healthcare system is benefiting from this continuously evolving environment since it leverages the opportunities offered by the ubiquitous and pervasive presence of connected objects and smart services. This attitude has given rise to the concept of eHealth, thus enabling new approaches and solutions for healthcare. In this framework we propose SmartPants, an IoT-based wireless system specifically designed for the remote rehabilitation of lower limbs in poststroke patients. The platform consists of multiple nodes used to monitor physical therapy and a software platform that provides real-time feedback on the execution by recognizing the type of exercise currently being performed by the patient. Our experimental results, evaluated through appropriate metrics, show that the proposed movement recognition algorithm provides very good results in terms of classification performance, independent of the considered classifier, with an average true positive rate of about 91 percent and an overall accuracy of around 96.5 percent

Speaker Recognition Exploiting D2D Communications Paradigm: Performance Evaluation of Multiple Observations Approaches

The diffusion of Device-to-Device (D2D) communications opens the door to exploit the contributions of multiple Mobile Devices (MDs) to accomplish collaborative tasks. In this paper a speaker recognition algorithm for MDs based on a multiple-observations approach is presented. We propose various fusion and clustering algorithms aimed at efficiently exploiting data coming from MDs. Numerical results show that in many cases our multiple-observation approach is able to significantly improve the accuracy of the considered speaker recognition algorithm