bims-ciryme 2023-09-10 papers

Issue of 2023‒09‒10
two papers selected by
Gabriela Da Silva Xavier, University of Birmingham

Cell Rep Methods. 2023 08 28. 3(8): 100545

Uncovering personalized glucose responses and circadian rhythms from multiple wearable biosensors with Bayesian dynamical modeling.

Nicholas E Phillips, Tinh-Hai Collet, Felix Naef.

Wearable biosensors and smartphone applications can measure physiological variables over multiple days in free-living conditions. We measure food and drink ingestion, glucose dynamics, physical activity, heart rate (HR), and heart rate variability (HRV) in 25 healthy participants over 14 days. We develop a Bayesian inference framework to learn personal parameters that quantify circadian rhythms and physiological responses to external stressors. Modeling the effects of ingestion events on glucose levels reveals that slower glucose decay kinetics elicit larger postprandial glucose spikes, and we uncover a circadian baseline rhythm for glucose with high amplitudes in some individuals. Physical activity and circadian rhythms explain as much as 40%-65% of the HR variance, whereas the variance explained for HRV is more heterogeneous across individuals. A more complex model incorporating activity, HR, and HRV explains up to 15% of additional glucose variability, highlighting the relevance of integrating multiple biosensors to better predict glucose dynamics.

Keywords: Bayesian inference; Kalman filter; biosensors; circadian rhythms; continuous glucose monitor (CGM); wearables

DOI: https://doi.org/10.1016/j.crmeth.2023.100545

Sci Rep. 2023 09 02. 13(1): 14423

Reversible suppression of circadian-driven locomotor rhythms in mice using a gradual fragmentation of the day-night cycle.

Melissa E S Richardson, Chérie-Akilah Browne, Citlali I Huerta Mazariegos.

Circadian rhythms are regulated by molecular clockwork and drive 24-h behaviors such as locomotor activity, which can be rendered non-functional through genetic knockouts of clock genes. Circadian rhythms are robust in constant darkness (DD) but are modulated to become exactly 24 h by the external day-night cycle. Whether ill-timed light and dark exposure can render circadian behaviors non-functional to the extent of genetic knockouts is less clear. In this study, we discovered an environmental approach that led to a reduction or lack in rhythmic 24-h-circadian wheel-running locomotor behavior in mice (referred to as arrhythmicity). We first observed behavioral circadian arrhythmicity when mice were gradually exposed to a previously published disruptive environment called the fragmented day-night cycle (FDN-G), while maintaining activity alignment with the four dispersed fragments of darkness. Remarkably, upon exposure to constant darkness (DD) or constant light (LL), FDN-G mice lost any resemblance to the FDN-G-only phenotype and instead, exhibited sporadic activity bursts. Circadian rhythms are maintained in control mice with sudden FDN exposure (FDN-S) and fully restored in FDN-G mice either spontaneously in DD or after 12 h:12 h light-dark exposure. This is the first study to generate a light-dark environment that induces reversible suppression of circadian locomotor rhythms in mice.

DOI: https://doi.org/10.1038/s41598-023-41029-0