scholarly journals Moderation of the Stressor-Strain Process in Interns by Heart Rate Variability Measured With a Wearable and Smartphone App: Within-Subject Design Using Continuous Monitoring (Preprint)

2021 ◽  
Author(s):  
Herman de Vries ◽  
Wim Kamphuis ◽  
Hilbrand Oldenhuis ◽  
Cees van der Schans ◽  
Robbert Sanderman

BACKGROUND The emergence of smartphones and wearable sensor technologies enables easy and unobtrusive monitoring of physiological and psychological data related to an individual’s resilience. Heart rate variability (HRV) is a promising biomarker for resilience based on between-subject population studies, but observational studies that apply a within-subject design and use wearable sensors in order to observe HRV in a naturalistic real-life context are needed. OBJECTIVE This study aims to explore whether resting HRV and total sleep time (TST) are indicative and predictive of the within-day accumulation of the negative consequences of stress and mental exhaustion. The tested hypotheses are that demands are positively associated with stress and resting HRV buffers against this association, stress is positively associated with mental exhaustion and resting HRV buffers against this association, stress negatively impacts subsequent-night TST, and previous-evening mental exhaustion negatively impacts resting HRV, while previous-night TST buffers against this association. METHODS In total, 26 interns used consumer-available wearables (Fitbit Charge 2 and Polar H7), a consumer-available smartphone app (Elite HRV), and an ecological momentary assessment smartphone app to collect resilience-related data on resting HRV, TST, and perceived demands, stress, and mental exhaustion on a daily basis for 15 weeks. RESULTS Multiple linear regression analysis of within-subject standardized data collected on 2379 unique person-days showed that having a high resting HRV buffered against the positive association between demands and stress (hypothesis 1) and between stress and mental exhaustion (hypothesis 2). Stress did not affect TST (hypothesis 3). Finally, mental exhaustion negatively predicted resting HRV in the subsequent morning but TST did not buffer against this (hypothesis 4). CONCLUSIONS To our knowledge, this study provides first evidence that having a low within-subject resting HRV may be both indicative and predictive of the short-term accumulation of the negative effects of stress and mental exhaustion, potentially forming a negative feedback loop. If these findings can be replicated and expanded upon in future studies, they may contribute to the development of automated resilience interventions that monitor daily resting HRV and aim to provide users with an early warning signal when a negative feedback loop forms, to prevent the negative impact of stress on long-term health outcomes. CLINICALTRIAL

2021 ◽  
Vol 22 (16) ◽  
pp. 8472
Author(s):  
Senem Aykul ◽  
Jordan Maust ◽  
Vijayalakshmi Thamilselvan ◽  
Monique Floer ◽  
Erik Martinez-Hackert

Adipose tissues (AT) expand in response to energy surplus through adipocyte hypertrophy and hyperplasia. The latter, also known as adipogenesis, is a process by which multipotent precursors differentiate to form mature adipocytes. This process is directed by developmental cues that include members of the TGF-β family. Our goal here was to elucidate, using the 3T3-L1 adipogenesis model, how TGF-β family growth factors and inhibitors regulate adipocyte development. We show that ligands of the Activin and TGF-β families, several ligand traps, and the SMAD1/5/8 signaling inhibitor LDN-193189 profoundly suppressed 3T3-L1 adipogenesis. Strikingly, anti-adipogenic traps and ligands engaged the same mechanism of action involving the simultaneous activation of SMAD2/3 and inhibition of SMAD1/5/8 signaling. This effect was rescued by the SMAD2/3 signaling inhibitor SB-431542. By contrast, although LDN-193189 also suppressed SMAD1/5/8 signaling and adipogenesis, its effect could not be rescued by SB-431542. Collectively, these findings reveal the fundamental role of SMAD1/5/8 for 3T3-L1 adipogenesis, and potentially identify a negative feedback loop that links SMAD2/3 activation with SMAD1/5/8 inhibition in adipogenic precursors.


2016 ◽  
Vol 24 (3) ◽  
pp. 421-432 ◽  
Author(s):  
Yanbo Wang ◽  
Hongwei Liang ◽  
Geyu Zhou ◽  
Xiuting Hu ◽  
Zhengya Liu ◽  
...  

2017 ◽  
Vol 27 (15) ◽  
pp. 2260-2270.e5 ◽  
Author(s):  
Junior J. West ◽  
Teresa Zulueta-Coarasa ◽  
Janna A. Maier ◽  
Donghoon M. Lee ◽  
Ashley E.E. Bruce ◽  
...  

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