Lowerymcpherson3742

78 ± 0.23 vs. 0.92 ± 0.09 vs. 0.90 ± 0.17,

 ≤ 0.005), but no different between ET and controls. this website AT phasic and "any" RSWA was similar between the 3 groups. ET and control RSWA was similar in all measures. Two ET patients (8.7%) had SM RSWA similar to PD patients.

Elevated SM RSWA distinguished PD from ET in patients without dream-enactment symptoms and occurs frequently in PD patients, and in isolated tremor suggests underlying synucleinopathy. Prospective studies will further validate these findings.

Elevated SM RSWA distinguished PD from ET in patients without dream-enactment symptoms and occurs frequently in PD patients, and in isolated tremor suggests underlying synucleinopathy. Prospective studies will further validate these findings.

Impulse control disorders (ICDs) have an increased frequency in patients with Parkinson's disease (PD), mainly because of treatment with dopamine agonists (DA). Factors related with the country of origin (culture, economy, healthcare politics) may impact phenomenology.

To explore phenomenology of ICDs depending on the country.

A systematic review following PRISMA guidelines was performed using Pubmed database. Articles published up to 2018 in which the prevalence of ICDs was analyzed were selected.

Thirty-two studies from 22 countries worldwide were included. The highest prevalence of ICDs in each continent was found in UK (59%), USA (39.1%) and India (31.6%). Frequency of ICDs was higher in those studies with lower mean age, higher proportion of males, whenever a screening instrument was used and whenever prescription of DAs was more common. Prevalence of ICDs was higher in Western countries compared to Asian countries (20.8% vs. 12.8%,

 < 0.001) as it was the proportion of patients treated with DAs (66% vs. 48.2%,

 < 0.001). Hypersexuality was the most common ICD overall (up to 23.8%). The highest frequencies of compulsive buying and eating were found in Western countries. Gambling was less commonly diagnosed, but prevalence was relevant Japan (14%).

We observed a tendency towards a different ICD profile in different geographical areas, which may be attributable to socio-economical, cultural or political influences in the phenomenology of these disorders. Acknowledging these differences could help their early detection, which is critical for prognosis.

We observed a tendency towards a different ICD profile in different geographical areas, which may be attributable to socio-economical, cultural or political influences in the phenomenology of these disorders. Acknowledging these differences could help their early detection, which is critical for prognosis.

A myriad of disorders combine myoclonus and ataxia. Most causes are genetic and an increasing number of genes are being associated with myoclonus-ataxia syndromes (MAS), due to recent advances in genetic techniques. A proper etiologic diagnosis of MAS is clinically relevant, given the consequences for genetic counseling, treatment, and prognosis.

To review the causes of MAS and to propose a diagnostic algorithm.

A comprehensive and structured literature search following PRISMA criteria was conducted to identify those disorders that may combine myoclonus with ataxia.

A total of 135 causes of combined myoclonus and ataxia were identified, of which 30 were charted as the main causes of MAS. These include four acquired entities opsoclonus-myoclonus-ataxia syndrome, celiac disease, multiple system atrophy, and sporadic prion diseases. The distinction between progressive myoclonus epilepsy and progressive myoclonus ataxia poses one of the main diagnostic dilemmas.

Diagnostic algorithms for pediatric and adult patients, based on clinical manifestations including epilepsy, are proposed to guide the differential diagnosis and corresponding work-up of the most important and frequent causes of MAS. A list of genes associated with MAS to guide genetic testing strategies is provided. Priority should be given to diagnose or exclude acquired or treatable disorders.

Diagnostic algorithms for pediatric and adult patients, based on clinical manifestations including epilepsy, are proposed to guide the differential diagnosis and corresponding work-up of the most important and frequent causes of MAS. A list of genes associated with MAS to guide genetic testing strategies is provided. Priority should be given to diagnose or exclude acquired or treatable disorders.Purpose Automatic instance segmentation of glomeruli within kidney whole slide imaging (WSI) is essential for clinical research in renal pathology. In computer vision, the end-to-end instance segmentation methods (e.g., Mask-RCNN) have shown their advantages relative to detect-then-segment approaches by performing complementary detection and segmentation tasks simultaneously. As a result, the end-to-end Mask-RCNN approach has been the de facto standard method in recent glomerular segmentation studies, where downsampling and patch-based techniques are used to properly evaluate the high-resolution images from WSI (e.g., > 10,000 × 10,000    pixels on 40 × ). However, in high-resolution WSI, a single glomerulus itself can be more than 1000 × 1000    pixels in original resolution which yields significant information loss when the corresponding features maps are downsampled to the 28 × 28 resolution via the end-to-end Mask-RCNN pipeline. Approach We assess if the end-to-end instance segmentation framework is optim study provides an extensive quantitative reference for other researchers to select the optimized and most accurate segmentation approach for glomeruli, or other biological objects of similar character, on high-resolution WSI.Purpose Deep learning has achieved major breakthroughs during the past decade in almost every field. There are plenty of publicly available algorithms, each designed to address a different task of computer vision in general. However, most of these algorithms cannot be directly applied to images in the medical domain. Herein, we are focused on the required preprocessing steps that should be applied to medical images prior to deep neural networks. Approach To be able to employ the publicly available algorithms for clinical purposes, we must make a meaningful pixel/voxel representation from medical images which facilitates the learning process. Based on the ultimate goal expected from an algorithm (classification, detection, or segmentation), one may infer the required pre-processing steps that can ideally improve the performance of that algorithm. Required pre-processing steps for computed tomography (CT) and magnetic resonance (MR) images in their correct order are discussed in detail. We further supported our discussion by relevant experiments to investigate the efficiency of the listed preprocessing steps.