Immune disruptions and night shift work in hospital healthcare professionals: The intricate effects of social jet-lag and sleep debt

Sleep deprivation detected by voice analysis

Sleep deprivation has an ever-increasing impact on individuals and societies. Yet, to date, there is no quick and objective test for sleep deprivation. Here, we used automated acoustic analyses of the voice to detect sleep deprivation. Building on current machine-learning approaches, we focused on interpretability by introducing two novel ideas: the use of a fully generic auditory representation as input feature space, combined with an interpretation technique based on reverse correlation. The auditory representation consisted of a spectro-temporal modulation analysis derived from neurophysiology. The interpretation method aimed to reveal the regions of the auditory representation that supported the classifiers' decisions. Results showed that generic auditory features could be used to detect sleep deprivation successfully, with an accuracy comparable to state-of-the-art speech features. Furthermore, the interpretation revealed two distinct effects of sleep deprivation on the voice: changes in slow temporal modulations related to prosody and changes in spectral features related to voice quality. Importantly, the relative balance of the two effects varied widely across individuals, even though the amount of sleep deprivation was controlled, thus confirming the need to characterize sleep deprivation at the individual level. Moreover, while the prosody factor correlated with subjective sleepiness reports, the voice quality factor did not, consistent with the presence of both explicit and implicit consequences of sleep deprivation. Overall, the findings show that individual effects of sleep deprivation may be observed in vocal biomarkers. Future investigations correlating such markers with objective physiological measures of sleep deprivation could enable "sleep stethoscopes" for the cost-effective diagnosis of the individual effects of sleep deprivation.

Chronic jet lag alters gut microbiome and mycobiome and promotes the progression of MAFLD in HFHFD-fed mice

Metabolic dysfunction-associated fatty liver disease (MAFLD) is the most common chronic liver disease worldwide. Circadian disruptors, such as chronic jet lag (CJ), may be new risk factors for MAFLD development. However, the roles of CJ on MAFLD are insufficiently understood, with mechanisms remaining elusive. Studies suggest a link between gut microbiome dysbiosis and MAFLD, but most of the studies are mainly focused on gut bacteria, ignoring other components of gut microbes, such as gut fungi (mycobiome), and few studies have addressed the rhythm of the gut fungi. This study explored the effects of CJ on MAFLD and its related microbiotic and mycobiotic mechanisms in mice fed a high fat and high fructose diet (HFHFD). Forty-eight C57BL6J male mice were divided into four groups: mice on a normal diet exposed to a normal circadian cycle (ND-NC), mice on a normal diet subjected to CJ (ND-CJ), mice on a HFHFD exposed to a normal circadian cycle (HFHFD-NC), and mice on a HFHFD subjected to CJ (HFHFD-CJ). After 16 weeks, the composition and rhythm of microbiota and mycobiome in colon contents were compared among groups. The results showed that CJ exacerbated hepatic steatohepatitis in the HFHFD-fed mice. Compared with HFHFD-NC mice, HFHFD-CJ mice had increases in Aspergillus, Blumeria and lower abundances of Akkermansia, Lactococcus, Prevotella, Clostridium, Bifidobacterium, Wickerhamomyces, and Saccharomycopsis genera. The fungi-bacterial interaction network became more complex after HFHFD and/or CJ interventions. The study revealed that CJ altered the composition and structure of the gut bacteria and fungi, disrupted the rhythmic oscillation of the gut microbiota and mycobiome, affected interactions among the gut microbiome, and promoted the progression of MAFLD in HFHFD mice.

Circadian lifestyle determinants of immune checkpoint inhibitor efficacy

Immune Checkpoint Inhibitors (ICI) have revolutionised cancer care in recent years. Despite a global improvement in the efficacy and tolerability of systemic anticancer treatments, a sizeable proportion of patients still do not benefit maximally from ICI. Extensive research has been undertaken to reveal the immune- and cancer-related mechanisms underlying resistance and response to ICI, yet more limited investigations have explored potentially modifiable lifestyle host factors and their impact on ICI efficacy and tolerability. Moreover, multiple trials have reported a marked and coherent effect of time-of-day ICI administration and patients' outcomes. The biological circadian clock indeed temporally controls multiple aspects of the immune system, both directly and through mediation of timing of lifestyle actions, including food intake, physical exercise, exposure to bright light and sleep. These factors potentially modulate the immune response also through the microbiome, emerging as an important mediator of a patient's immune system. Thus, this review will look at critically amalgamating the existing clinical and experimental evidence to postulate how modifiable lifestyle factors could be used to improve the outcomes of cancer patients on immunotherapy through appropriate and individualised entrainment of the circadian timing system and temporal orchestration of the immune system functions.

Relationship between night shift and sleep problems, risk of metabolic abnormalities of nurses: a 2 years follow-up retrospective analysis in the National Nurse Health Study (NNHS)

BACKGROUND AND PURPOSE

Efforts to improve nurses' physical and mental health are critical to ensuring the safety and quality of the healthcare system. Long-term studies targeting the relevancy of nurses' occupation characteristics with health conditions remain insufficient. This study aimed to examine the relationship between nurses' night shift and sleep problems and metabolic abnormalities risk.

METHODS

This study was a part of the National Nurse Health Study, an ambispective cohort study in China, in 2021. Based on an integration physical examination data system, this study carried out a retrospective analysis of 730 nurses from 2018 to 2020 and combined with a questionnaire survey in 2021. The STROBE guidelines were adopted for reporting.

RESULTS

In the 23 (23.0, 24.0) months follow-up, higher night shift load was associated with more sleep problems such as shortened sleep duration, sleep disorders, poor sleep quality, and sleep deprivation. Moreover, night shift load was associated with chronic diseases risk factors, increasing body mass index and body fat, with more night shift density, increasing the occurrence of low levels of high-density lipoprotein cholesterol, high triglyceride, triglyceride/high-density lipoprotein cholesterol ratio, and serum uric acid.

CONCLUSION

The night shift load has become an occupational health concern, contributing to chronic diseases relevant metabolic risk factors and negative influence on sleep health. Focus on the strategies to improve the sleep quality of nurses undergoing night shift work, optimize work scheduling and ongoing monitor the relevant risk factors are essential to enhance the stability and well-being of the nursing workforce.

CLINICAL TRIALS REGISTRATION INFORMATION

NCT04572347, on October 1, 2020. https://www.

CLINICALTRIALS

gov/ct2/show/NCT04572347.