Proteomic comparison between non-purified cerebrospinal fluid and cerebrospinal fluid-derived extracellular vesicles from patients with Alzheimer's, Parkinson's and Lewy body dementia.

Dementia is a leading cause of death worldwide, with increasing prevalence as global life expectancy increases. The most common neurodegenerative disorders are Alzheimer's disease (AD), dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD). With this study, we took an in-depth look at the proteome of the (non-purified) cerebrospinal fluid (CSF) and the CSF-derived extracellular vesicles (EVs) of AD, PD, PD-MCI (Parkinson's disease with mild cognitive impairment), PDD and DLB patients analysed by label-free mass spectrometry. This has led to the discovery of differentially expressed proteins that may be helpful for differential diagnosis. We observed a greater number of differentially expressed proteins in CSF-derived EV samples (N = 276) compared to non-purified CSF (N = 169), with minimal overlap between both datasets. This finding suggests that CSF-derived EV samples may be more suitable for the discovery phase of a biomarker study, due to the removal of more abundant proteins, resulting in a narrower dynamic range. As disease-specific markers, we selected a total of 39 biomarker candidates identified in non-purified CSF, and 37 biomarker candidates across the different diseases under investigation in the CSF-derived EV data. After further exploration and validation of these proteins, they can be used to further differentiate between the included dementias and may offer new avenues for research into more disease-specific pharmacological therapeutics.

What can we learn from studying plastic debris in the Sea Scheldt estuary?

The Sea Scheldt estuary has been suggested to be a significant pathway for transfer of plastic debris to the North Sea. We have studied 12,801 plastic items that were collected in the Sea Scheldt estuary (Belgium) during 3 sampling campaigns (in spring, summer, and autumn) using a technique called anchor netting. The investigation results indicated that the abundance of plastic debris in the Scheldt River was on average 1.6 × 10-3 items per m3 with an average weight of 0.38 × 10-3 g per m3. Foils were the most abundant form, accounting for >88 % of the samples, followed by fragments for 11 % of the samples and filaments, making up for <1 % of the plastic debris. FTIR spectroscopy of 7 % of the total number of plastic debris items collected in the Sea Scheldt estuary (n = 883) revealed that polypropylene (PP), polyethylene (PE), and polystyrene (PS) originating from disposable packaging materials were the most abundant types of polymers. A limited number of plastic debris items (n = 100) were selected for non-destructive screening of their mineral element composition using micro-X-ray fluorescence spectrometry (µXRF). The corresponding results revealed that S, Ca, Si, P, Al, and Fe were the predominant mineral elements. These elements originate from flame retardants, mineral fillers, and commonly used catalysts for plastic production. Finally, machine learning algorithms were deployed to test a new concept for forensic identification of the different plastic entities based on the most important elements present using a limited subset of PP (n = 36) and PE (n = 35) plastic entities.

Retinal microvascular complexity comparing mono- and multifractal dimensions in relation to cardiometabolic risk factors in a Middle Eastern population.

PURPOSE: Metrics that capture changes in the retinal microvascular structure are relevant in the context of cardiometabolic disease development. The microvascular topology is typically quantified using monofractals, although it obeys more complex multifractal rules. We study mono- and multifractals of the retinal microvasculature in relation to cardiometabolic factors. METHODS: The cross-sectional retrospective study used data from 3000 Middle Eastern participants in the Qatar Biobank. A total of 2333 fundus images (78%) passed quality control and were used for further analysis. The monofractal (Df ) and five multifractal metrics were associated with cardiometabolic factors using multiple linear regression and were studied in clinically relevant subgroups. RESULTS: Df and multifractals are lowered in function of age, and Df is lower in males compared to females. In models corrected for age and sex, Df is significantly associated with BMI, insulin, systolic blood pressure, glycated haemoglobin (HbA1c), albumin, LDL and total cholesterol concentrations. Multifractals are negatively associated with systolic and diastolic blood pressure, glucose and the WHO/ISH cardiovascular risk score. Df was higher, and multifractal curve asymmetry was lower in diabetic patients (HbA1c > 6.5%) compared to healthy individuals (HbA1c < 5.7%). Insulin resistance (insulin ≥ 23 mcU/mL) was associated with significantly lower Df values. CONCLUSION: One or more fractal metrics are in association with sex, age, BMI, systolic and diastolic blood pressure and biochemical blood measurements in a Middle Eastern population study. Follow-up studies aiming at investigating retinal microvascular changes in relation to cardiometabolic risk should analyse both monofractal and multifractal metrics for a more comprehensive microvascular picture.

Visual Circular Analysis of 266 Years of Sunspot Counts.

Sunspots, colder areas that are visible as dark spots on the surface of the Sun, have been observed for centuries. Their number varies with a period of ∼11 years, a phenomenon closely related to the solar activity cycle. Recently, observation records dating back to 1749 have been reassessed, resulting in the release of a time series of sunspot numbers covering 266 years of observations. This series is analyzed using circular analysis to determine the periodicity of the occurrence of solar maxima. The circular analysis is combined with spiral graphs to provide a single visualization, simultaneously showing the periodicity of the series, the degree to which individual cycle lengths deviate from the average period, and differences in levels reached during the different maxima. This type of visualization of cyclic time series with varying cycle lengths in which significant events occur periodically is broadly applicable. It is aimed particularly at science communication, education, and public outreach.

Disentangling mode-specific selection and measurement bias in social surveys.

A large-scale mixed-mode experiment linked to the Dutch Crime Victimization Survey was conducted in 2011. The experiment consisted of two waves; one wave with random assignment to one of the modes web, paper, telephone and face-to-face, and one follow-up wave to the full sample with interviewer modes only. The objective of the experiment is to estimate total mode effects and more specifically the corresponding mode effect components arising from undercoverage, nonresponse and measurement. In this paper, mode-specific selection and measurement bias are defined, and estimators for the bias terms based on the experimental design are introduced and discussed. The proposed estimators are applied to a number of key survey variables from the Labour Force Survey and the Crime Victimization Survey.