Antibody-based methods for the measurement of α-synuclein concentration in human cerebrospinal fluid - method comparison and round robin study.

α-Synuclein is the major component of Lewy bodies and a candidate biomarker for neurodegenerative diseases in which Lewy bodies are common, including Parkinson's disease and dementia with Lewy bodies. A large body of literature suggests that these disorders are characterized by reduced concentrations of α-synuclein in cerebrospinal fluid (CSF), with overlapping concentrations compared to healthy controls and variability across studies. Several reasons can account for this variability, including technical ones, such as inter-assay and inter-laboratory variation (reproducibility). We compared four immunochemical methods for the quantification of α-synuclein concentration in 50 unique CSF samples. All methods were designed to capture most of the existing α-synuclein forms in CSF ('total' α-synuclein). Each of the four methods showed high analytical precision, excellent correlation between laboratories (R2 0.83-0.99), and good correlation with each other (R2 0.64-0.93), although the slopes of the regression lines were different between the four immunoassays. The use of common reference CSF samples decreased the differences in α-synuclein concentration between detection methods and technologies. Pilot data on an immunoprecipitation mass spectrometry (IP-MS) method is also presented. Our results suggest that the four immunochemical methods and the IP-MS method measure similar forms of α-synuclein and that a common reference material would allow harmonization of results between immunoassays.

Individual Differences in the Competence for Physical-Activity-Related Affect Regulation Moderate the Activity-Affect Association in Real-Life Situations.

Physical activity (PA) is positively associated with affective well-being in adults. This study investigated the moderating role of the competence for PA-related affect regulation in the PA-affect association in real-life situations. A total of 37 women and 27 men completed an ecological momentary assessment study in which the authors used accelerometers to record PA and e-diaries to collect data on affective well-being on 4 study days. They applied multilevel analyses to estimate the within-person effects of PA on affective well-being and cross-level interactions between PA (within person) and PA-related affect regulation (between persons). Results revealed cross-level interaction effects between within-person PA variations and competence for PA-related affect regulation on the affect dimensions of calmness (p < .01) and valence (p = .04). Thus, the competence for PA-related affect regulation moderates the PA-affect association in real-life situations. Therefore, individual-based PA promotion should consider these individual differences to develop tailored interventions.

The culturome of the human nose habitats reveals individual bacterial fingerprint patterns.

The complex anatomy of the human nose might offer distinct microbial niches. Microbiota composition may affect nose inflammatory diseases and Staphylococcus aureus carriage. Considering different nasal cavity locations, microbial colonization was analysed across individuals exhibiting chronic nasal inflammatory diseases (n = 18) and those without local inflammation signs (n = 16). Samples were collected systematically during surgery and examined by an extensive culture-based approach and, for a subset, by 16S rRNA gene community profiling. Cultivation yielded 141 taxa with members of Staphylococcus, Corynebacterium and Propionibacterium as most common isolates comprising the nasal core culturome together with Finegoldia magna. Staphylococcus aureus was most frequently found in association with Staphylococcus epidermidis and Propionibacterium acnes, and the posterior vestibules were redefined as S. aureus' principle habitat. Culturome analysis revealed host-specific bacterial 'fingerprints' irrespective of host-driven factors or intranasal sites. Comparisons between cultivable and molecular fingerprints demonstrated that only a small fraction of phylotypes (6.2%) was correlated. While the total number of different phylotypes was higher in the molecular dataset, the total number of identifications down to the species level was higher in the culturomic approach. To determine host-specific microbiomes, the advantages of molecular approaches should be combined with the resolution and reliability of species identification by culturomic analyses.

Unveiling peripheral neuropathy and cognitive dysfunction in diabetes: an observational and proof-of-concept study with video games and sensor-equipped insoles.

Background: Proactive screening for cognitive dysfunction (CD) and peripheral neuropathy (PNP) in elderly patients with diabetes mellitus is essential for early intervention, yet clinical examination is time-consuming and prone to bias. Objective: We aimed to investigate PNP and CD in a diabetes cohort and explore the possibility of identifying key features linked with the respective conditions by machine learning algorithms applied to data sets obtained in playful games controlled by sensor-equipped insoles. Methods: In a cohort of patients diagnosed with diabetes (n=261) aged over 50 years PNP and CD were diagnosed based on complete physical examination (neuropathy symptom and disability scores, and Montreal Cognitive Assessment). In an observational and proof-of-concept study patients performed a 15 min lasting gaming session encompassing tutorials and four video games with 5,244 predefined features. The steering of video games was solely achieved by modulating plantar pressure values, which were measured by sensor-equipped insoles in real-time. Data sets were used to identify key features indicating game performance with correlation regarding CD and PNP findings. Thereby, machine learning models (e.g. gradient boosting and lasso and elastic-net regularized generalized linear models) were set up to distinguish patients in the different groups. Results: PNP was diagnosed in 59% (n=153), CD in 34% (n=89) of participants, and 23% (n=61) suffered from both conditions. Multivariable regression analyses suggested that PNP was positively associated with CD in patients with diabetes (adjusted odds ratio = 1.95; 95% confidence interval: 1.03-3.76; P=0.04). Predictive game features were identified that significantly correlated with CD (n=59), PNP (n=40), or both (n=59). These features allowed to set up classification models that were enriched by individual risk profiles (i.e. gender, age, weight, BMI, diabetes type, and diabetes duration). The obtained models yielded good predictive performance with the area under the receiver-operating-characteristic curves reaching 0.95 for CD without PNP, 0.83 for PNP without CD, and 0.84 for CD and PNP combined. Conclusions: The video game-based assessment was able to categorize patients with CD and/or PNP with high accuracy. Future studies with larger cohorts are needed to validate these results and potentially enhance the discriminative power of video games.

The iReAct study - A biopsychosocial analysis of the individual response to physical activity.

BACKGROUND: Physical activity is a substantial promoter for health and well-being. Yet, while an increasing number of studies shows that the responsiveness to physical activity is highly individual, most studies focus this issue from only one perspective and neglect other contributing aspects. In reference to a biopsychosocial framework, the goal of our study is to examine how physically inactive individuals respond to two distinct standardized endurance trainings on various levels. Based on an assessment of activity- and health-related biographical experiences across the life course, our mixed-method study analyzes the responsiveness to physical activity in the form of a transdisciplinary approach, considering physiological, epigenetic, motivational, affective, and body image-related aspects. METHODS: Participants are randomly assigned to two different training programs (High Intensity Interval Training vs. Moderate Intensity Continuous Training) for six weeks. After this first training period, participants switch training modes according to a two-period sequential-training-intervention (STI) design and train for another six weeks. In order to analyse baseline characteristics as well as acute and adaptive biopsychosocial responses, three extensive mixed-methods diagnostic blocks take place at the beginning (t0) of the study and after the first (t1) and the second (t2) training period resulting in a net follow-up time of 15 weeks. The study is divided into five modules in order to cover a wide array of perspectives. DISCUSSION: The study's transdisciplinary mixed-method design allows to interlace a multitude of subjective and objective data and therefore to draw an integrated picture of the biopsychosocial efficacy of two distinct physical activity programs. The results of our study can be expected to contribute to the development and design of individualised training programs for the promotion of physical activity. TRIAL REGISTRATION: The study was retrospectively registered in the German Clinical Trials Register on 12 June 2019 (DRKS00017446).

Biochemical markers of ongoing joint damage in rheumatoid arthritis--current and future applications, limitations and opportunities.

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease associated with potentially debilitating joint inflammation, as well as altered skeletal bone metabolism and co-morbid conditions. Early diagnosis and aggressive treatment to control disease activity offers the highest likelihood of preserving function and preventing disability. Joint inflammation is characterized by synovitis, osteitis, and/or peri-articular osteopenia, often accompanied by development of subchondral bone erosions, as well as progressive joint space narrowing. Biochemical markers of joint cartilage and bone degradation may enable timely detection and assessment of ongoing joint damage, and their use in facilitating treatment strategies is under investigation. Early detection of joint damage may be assisted by the characterization of biochemical markers that identify patients whose joint damage is progressing rapidly and who are thus most in need of aggressive treatment, and that, alone or in combination, identify those individuals who are likely to respond best to a potential treatment, both in terms of limiting joint damage and relieving symptoms. The aims of this review are to describe currently available biochemical markers of joint metabolism in relation to the pathobiology of joint damage and systemic bone loss in RA; to assess the limitations of, and need for additional, novel biochemical markers in RA and other rheumatic diseases, and the strategies used for assay development; and to examine the feasibility of advancement of personalized health care using biochemical markers to select therapeutic agents to which a patient is most likely to respond.