Fibroblast Growth Factor 21 as a Potential Biomarker for Improved Locomotion and Olfaction Detection Ability after Weight Reduction in Obese Mice.

Obesity is one of the most challenging diseases of the 21st century and is accompanied by behavioural disorders. Exercise, dietary adjustments, or time-restricted feeding are the only successful long-term treatments to date. Fibroblast growth factor 21 (FGF21) plays a key role in dietary regulation, but FGF21 resistance is prevalent in obesity. The aim of this study was to investigate in obese mice whether weight reduction leads to improved behaviour and whether these behavioural changes are associated with decreased plasma FGF21 levels. After establishing a model for diet-induced obesity, mice were subjected to three different interventions for weight reduction, namely dietary change, treadmill exercise, or time-restricted feeding. In this study, we demonstrated that only the combination of dietary change and treadmill exercise affected all parameters leading to a reduction in weight, fat, and FGF21, as well as less anxious behaviour, higher overall activity, and improved olfactory detection abilities. To investigate the interrelationship between FGF21 and behavioural parameters, feature selection algorithms were applied designating FGF21 and body weight as one of five highly weighted features. In conclusion, we concluded from the complementary methods that FGF21 can be considered as a potential biomarker for improved behaviour in obese mice after weight reduction.

Workflow Development for the Functional Characterization of ncRNAs.

During the last decade, ncRNAs have been investigated intensively and revealed their regulatory role in various biological processes. Worldwide research efforts have identified numerous ncRNAs and multiple RNA subtypes, which are attributed to diverse functionalities known to interact with different functional layers, from DNA and RNA to proteins. This makes the prediction of functions for newly identified ncRNAs challenging. Current bioinformatics and systems biology approaches show promising results to facilitate an identification of these diverse ncRNA functionalities. Here, we review (a) current experimental protocols, i.e., for Next Generation Sequencing, for a successful identification of ncRNAs; (b) sequencing data analysis workflows as well as available computational environments; and (c) state-of-the-art approaches to functionally characterize ncRNAs, e.g., by means of transcriptome-wide association studies, molecular network analyses, or artificial intelligence guided prediction. In addition, we present a strategy to cover the identification and functional characterization of unknown transcripts by using connective workflows.