Detection of REM Sleep Behaviour Disorder by Automated Polysomnography Analysis

Evidence suggests Rapid-Eye-Movement (REM) Sleep Behaviour Disorder (RBD) is an early predictor of Parkinson's disease. This study proposes a fully-automated framework for RBD detection consisting of automated sleep staging followed by RBD identification. Analysis was assessed using a limited polysomnography montage from 53 participants with RBD and 53 age-matched healthy controls. Sleep stage classification was achieved using a Random Forest (RF) classifier and 156 features extracted from electroencephalogram (EEG), electrooculogram (EOG) and electromyogram (EMG) channels. For RBD detection, a RF classifier was trained combining established techniques to quantify muscle atonia with additional features that incorporate sleep architecture and the EMG fractal exponent. Automated multi-state sleep staging achieved a 0.62 Cohen's Kappa score. RBD detection accuracy improved by 10% to 96% (compared to individual established metrics) when using manually annotated sleep staging. Accuracy remained high (92%) when using automated sleep staging. This study outperforms established metrics and demonstrates that incorporating sleep architecture and sleep stage transitions can benefit RBD detection. This study also achieved automated sleep staging with a level of accuracy comparable to manual annotation. This study validates a tractable, fully-automated, and sensitive pipeline for RBD identification that could be translated to wearable take-home technology.Comment: 20 pages, 3 figure

Parkinson's disease subtypes in the Oxford Parkinson disease centre (OPDC) discovery cohort

Background: Within Parkinson’s there is a spectrum of clinical features at presentation which may represent sub-types of the disease. However there is no widely accepted consensus of how best to group patients. Objective: Use a data-driven approach to unravel any heterogeneity in the Parkinson’s phenotype in a well-characterised, population-based incidence cohort. Methods: 769 consecutive patients, with mean disease duration of 1.3 years, were assessed using a broad range of motor, cognitive and non-motor metrics. Multiple imputation was carried out using the chained equations approach to deal with missing data. We used an exploratory and then a confirmatory factor analysis to determine suitable domains to include within our cluster analysis. K-means cluster analysis of the factor scores and all the variables not loading into a factor was used to determine phenotypic subgroups. Results: Our factor analysis found three important factors that were characterised by: psychological well-being features; non-tremor motor features, such as posture and rigidity; and cognitive features. Our subsequent five cluster model identified groups characterised by (1) mild motor and non-motor disease (25.4%), (2) poor posture and cognition (23.3%), (3) severe tremor (20.8%), (4) poor psychological well-being, RBD and sleep (18.9%), and (5) severe motor and non-motor disease with poor psychological well-being (11.7%). Conclusion: Our approach identified several Parkinson’s phenotypic sub-groups driven by largely dopaminergic-resistant features (RBD, impaired cognition and posture, poor psychological well-being) that, in addition to dopaminergic-responsive motor features may be important for studying the aetiology, progression, and medication response of early Parkinson’s

Finite temperature effects on the collapse of trapped Bose-Fermi mixtures

By using the self-consistent Hartree-Fock-Bogoliubov-Popov theory, we present a detailed study of the mean-field stability of spherically trapped Bose-Fermi mixtures at finite temperature. We find that, by increasing the temperature, the critical particle number of bosons (or fermions) and the critical attractive Bose-Fermi scattering length increase, leading to a significant stabilization of the mixture.Comment: 5 pages, 4 figures; minor changes, proof version, to appear in Phys. Rev. A (Nov. 1, 2003

Alpha-synuclein RT-QuIC in the CSF of patients with alpha-synucleinopathies

We have developed a novel real-time quaking-induced conversion RT-QuICbased assay to detect alpha-synuclein aggregation in brain and cerebrospinal fluid from dementia with Lewy bodies and Parkinson’s disease patients. This assay can detect alpha-synuclein aggregation in Dementia with Lewy bodies and Parkinson’s disease cerebrospinal fluid with sensitivities of 92% and 95%, respectively, and with an overall specificity of 100% when compared to Alzheimer and control cerebrospinal fluid. Patients with neuropathologically confirmed tauopathies (progressive supranuclear palsy; corticobasal degeneration) gave negative results. These results suggest that RT-QuiC analysis of cerebrospinal fluid is potentially useful for the early clinical assessment of patients with alpha-synucleinopathies

Nigrosome 1 imaging in REM sleep behavior disorder and its association with dopaminergic decline

Objectives Rapid eye movement sleep behavior disorder (RBD) patients have a high risk of developing a Parkinsonian disorder, offering an opportunity for neuroprotective intervention. Predicting near‐term conversion, however, remains a challenge. Dopamine transporter imaging, while informative, is expensive and not widely available. Here, we investigate the utility of susceptibility‐weighted MRI (SWI) to detect abnormalities of the substantia nigra in RBD, and explore their association with striatal dopaminergic deficits. Methods SWI of the substantia nigra was performed in 46 RBD patients, 27 Parkinson’s patients, and 32 control subjects. Dorsal nigral hyperintensity (DNH) was scored by two blinded raters, and separately quantified using a semiautomated process. Forty‐two RBD patients were also imaged with 123I‐ioflupane single‐photon emission computed tomography (DaT SPECT/CT). Results Consensus visual DNH classification was possible in 87% of participants. 27.5% of RBD patients had lost DNH, compared with 7.7% of control subjects and 96% of Parkinson’s patients. RBD patients lacking DNH had significantly lower putamen dopaminergic SPECT/CT activity compared to RBD patients with DNH present (specific uptake ratios 1.89 vs. 2.33, P = 0.002). The mean quantified DNH signal intensity declined in a stepwise pattern, with RBD patients having lower intensity than controls (0.837 vs. 0.877, P = 0.01) but higher than PD patients (0.837 vs. 0.765, P < 0.001). Interpretation Over one quarter of RBD patients have abnormal substantia nigra SWI reminiscent of Parkinson’s, which is associated with a greater dopaminergic deficit. This modality may help enrich neuroprotective trials with early converters

LARGE Expression Augments the Glycosylation of Glycoproteins in Addition to α-Dystroglycan Conferring Laminin Binding

Mutations in genes encoding glycosyltransferases (and presumed glycosyltransferases) that affect glycosylation and extracellular matrix binding activity of α-dystroglycan (α-DG) cause congenital muscular dystrophies (CMDs) with central nervous system manifestations. Among the identified genes, LARGE is of particular interest because its overexpression rescues glycosylation defects of α-DG in mutations of not only LARGE but also other CMD-causing genes and restores laminin binding activity of α-DG. It is not known whether LARGE protein glycosylates other proteins in addition to α-DG. In this study, we overexpressed LARGE in DG-deficient cells and analyzed glycosylated proteins by Western blot analysis. Surprisingly, overexpression of LARGE in α-DG-deficient cells led to glycosylation dependent IIH6C4 and VIA4-1 immunoreactivity, despite the prevailing view that these antibodies only recognize glycosylated α-DG. Furthermore, the hyperglycosylated proteins in LARGE-overexpressing cells demonstrated the functional capacity to bind the extracellular matrix molecule laminin and promote laminin assembly at the cell surface, an effect that was blocked by IIH6C4 antibodies. These results indicate that overexpression of LARGE catalyzes the glycosylation of at least one other glycoprotein in addition to α-DG, and that this glycosylation(s) promotes laminin binding activity

The Atacama Cosmology Telescope: A Measurement of the Cosmic Microwave Background Power Spectrum at 148 and 218 GHz from the 2008 Southern Survey

We present measurements of the cosmic microwave background (CMB) power spectrum made by the Atacama Cosmology Telescope at 148 GHz and 218 GHz, as well as the cross-frequency spectrum between the two channels. Our results clearly show the second through the seventh acoustic peaks in the CMB power spectrum. The measurements of these higher-order peaks provide an additional test of the {\Lambda}CDM cosmological model. At l > 3000, we detect power in excess of the primary anisotropy spectrum of the CMB. At lower multipoles 500 < l < 3000, we find evidence for gravitational lensing of the CMB in the power spectrum at the 2.8{\sigma} level. We also detect a low level of Galactic dust in our maps, which demonstrates that we can recover known faint, diffuse signals.Comment: 19 pages, 13 figures. Submitted to ApJ. This paper is a companion to Hajian et al. (2010) and Dunkley et al. (2010

Visual short-term memory deficits associated with GBA mutation and Parkinson's disease.

Individuals with mutation in the lysosomal enzyme glucocerebrosidase (GBA) gene are at significantly high risk of developing Parkinson's disease with cognitive deficit. We examined whether visual short-term memory impairments, long associated with patients with Parkinson's disease, are also present in GBA-positive individuals-both with and without Parkinson's disease. Precision of visual working memory was measured using a serial order task in which participants observed four bars, each of a different colour and orientation, presented sequentially at screen centre. Afterwards, they were asked to adjust a coloured probe bar's orientation to match the orientation of the bar of the same colour in the sequence. An additional attentional 'filtering' condition tested patients' ability to selectively encode one of the four bars while ignoring the others. A sensorimotor task using the same stimuli controlled for perceptual and motor factors. There was a significant deficit in memory precision in GBA-positive individuals-with or without Parkinson's disease-as well as GBA-negative patients with Parkinson's disease, compared to healthy controls. Worst recall was observed in GBA-positive cases with Parkinson's disease. Although all groups were impaired in visual short-term memory, there was a double dissociation between sources of error associated with GBA mutation and Parkinson's disease. The deficit observed in GBA-positive individuals, regardless of whether they had Parkinson's disease, was explained by a systematic increase in interference from features of other items in memory: misbinding errors. In contrast, impairments in patients with Parkinson's disease, regardless of GBA status, was explained by increased random responses. Individuals who were GBA-positive and also had Parkinson's disease suffered from both types of error, demonstrating the worst performance. These findings provide evidence for dissociable signature deficits within the domain of visual short-term memory associated with GBA mutation and with Parkinson's disease. Identification of the specific pattern of cognitive impairment in GBA mutation versus Parkinson's disease is potentially important as it might help to identify individuals at risk of developing Parkinson's disease