Predicting Chronic Stress among Healthy Females Using Daily-Life Physiological and Lifestyle Features from Wearable Sensors

Background Chronic stress is a highly prevalent condition that may stem from different sources and can substantially impact physiology and behavior, potentially leading to impaired mental and physical health. Multiple physiological and behavioral lifestyle features can now be recorded unobtrusively in daily-life using wearable sensors. The aim of the current study was to identify a distinct set of physiological and behavioral lifestyle features that are associated with elevated levels of chronic stress across different stress sources. Methods For that, 140 healthy female participants completed the Trier inventory for chronic stress (TICS) before wearing the Fitbit Charge3 sensor for seven consecutive days while maintaining their daily routine. Physiological and lifestyle features that were extracted from sensor data, alongside demographic features, were used to predict high versus low chronic stress with support vector machine classifiers, applying out-of-sample model testing. Results The model achieved 79% classification accuracy for chronic stress from a social tension source. A mixture of physiological (resting heart-rate, heart-rate circadian characteristics), lifestyle (steps count, sleep onset and sleep regularity) and non-sensor demographic features (smoking status) contributed to this classification. Conclusion As wearable technologies continue to rapidly evolve, integration of daily-life indicators could improve our understanding of chronic stress and its impact of physiology and behavior

MAL/VIP17, a New Player in the Regulation of NKCC2 in the Kidney

In this work, we demonstrate that MAL/VIP17 increases the cell surface retention of NKCC2 at the apical membrane of thick ascending limb cells by attenuating its internalization. This coincides with an increase in cotransporter phosphorylation. Thus, MAL/VIP17 could play an important role in the regulated absorption of Na+ and Cl− in the kidney

Clustering and Lateral Concentration of Raft Lipids by the MAL Protein

MAL, a compact hydrophobic, four-transmembrane-domain apical protein that copurifies with detergent-resistant membranes is obligatory for the machinery that sorts glycophosphatidylinositol (GPI)-anchored proteins and others to the apical membrane in epithelia. The mechanism of MAL function in lipid-raft–mediated apical sorting is unknown. We report that MAL clusters formed by two independent procedures—spontaneous clustering of MAL tagged with the tandem dimer DiHcRED (DiHcRED-MAL) in the plasma membrane of COS7 cells and antibody-mediated cross-linking of FLAG-tagged MAL—laterally concentrate markers of sphingolipid rafts and exclude a fluorescent analogue of phosphatidylethanolamine. Site-directed mutagenesis and bimolecular fluorescence complementation analysis demonstrate that MAL forms oligomers via ϕxxϕ intramembrane protein–protein binding motifs. Furthermore, results from membrane modulation by using exogenously added cholesterol or ceramides support the hypothesis that MAL-mediated association with raft lipids is driven at least in part by positive hydrophobic mismatch between the lengths of the transmembrane helices of MAL and membrane lipids. These data place MAL as a key component in the organization of membrane domains that could potentially serve as membrane sorting platforms