Biomarkers.

Background: Parkinson's disease (PD) is a debilitating condition that affects millions of people worldwide, yet there are currently no reliable biomarkers for its diagnosis. Alpha-synuclein aggregation is a well-known hallmark of PD pathology, but the behavior and kinetics of these aggregates are poorly understood. To address this gap in knowledge, this study utilized several approaches to evaluate the potential of alpha-synuclein aggregates as potential biomarker for PD.

β-Glucan reprograms neutrophils to promote disease tolerance against influenza A virus.

Disease tolerance is an evolutionarily conserved host defense strategy that preserves tissue integrity and physiology without affecting pathogen load. Unlike host resistance, the mechanisms underlying disease tolerance remain poorly understood. In the present study, we investigated whether an adjuvant (β-glucan) can reprogram innate immunity to provide protection against influenza A virus (IAV) infection.

African Swine Fever in Saxony-Disease Dynamics.

African swine fever (ASF) emerged in Germany in 2020. A few weeks after the initial occurrence, infected wild boar were detected in Saxony. In this study, data from wild boar surveillance in Saxony were analyzed.

Exploration of Novel Biomarkers for Neurodegenerative Diseases Using Proteomic Analysis and Ligand-Binding Assays.

Background/objectives: Neurodegenerative diseases are a major cause of morbidity and mortality worldwide, and their public health burden continues to increase. There is an urgent need to develop reliable and sensitive biomarkers to aid the timely diagnosis, disease progression monitoring, and therapeutic development for neurodegenerative disorders. Proteomic screening strategies, including antibody microarrays, are a powerful tool for biomarker discovery, but their findings should be confirmed using quantitative assays.

Judged by your neighbors: Brain structural normativity profiles for large and heterogeneous samples.

The detection of norm deviations is fundamental to clinical decision making and impacts our ability to diagnose and treat diseases effectively. Current normative modeling approaches rely on generic comparisons and quantify deviations in relation to the population average. However, generic models interpolate subtle nuances and risk the loss of critical information, thereby compromising effective personalization of health care strategies.