Background: Trouble sleeping is one of the major health issues nowadays. Current evidence on the correlation between muscle quality and trouble sleeping is limited. Methods: A cross-sectional study design was applied and participants aged from 18 to 60 years in the National Health and Nutrition Examination Survey (NHANES) 2011–2014 was used for analysis. Muscle quality index (MQI) was quantitatively calculated as handgrip strength (HGS, kg) sum/ arm and appendicular skeletal muscle mass (ASM, kg) by using the sum of the non-dominant hand and dominant hand. Sleeping data was obtained by interviews and self-reported by individuals. The main analyses utilized weighted multivariable logistic regression models according to the complex multi-stage sampling design of NHANES. Restricted cubic spline model was applied to explore the non-linear relationship between MQI and trouble sleeping. Moreover, subgroup analyses concerning sociodemographic and lifestyle factors were conducted in this study. Results: 5143 participants were finally included in. In the fully adjusted model, an increased level of MQI was significantly associated with a lower odds ratio of trouble sleeping, with OR = 0.765, 95% CI: (0.652,0.896), p = 0.011. Restricted cubic spline showed a non-linear association between MQI and trouble sleeping. However, it seemed that the prevalence of trouble sleeping decreased with increasing MQI until it reached 2.362, after which the odds ratio of trouble sleeping reached a plateau. Subgroup analyses further confirmed that the negative association between the MQI and trouble sleeping was consistent and robust across groups. Conclusion: Overall, this study revealed that MQI can be used as a reliable predictor in odds ratio of trouble sleeping. Maintaining a certain level of muscle mass would be beneficial to sleep health. However, this was a cross-sectional study, and causal inference between MQI and trouble sleeping was worthy of further exploration.

The main topic of this research is the relationship between dietary intake of live microbe-containing (LMC) foods, recreational physical activity (RPA), and the systemic immune-inflammation index (SII). This study presented a cohort of 26,254 individuals in the National Health and Nutrition Examination Survey (NHANES), representing an estimated weighted population of 193,637,615 in the United States. Weighted multivariable linear regression models were used in consideration of the multi-stage sampling design. Results: The study found that medium-LMC foods were negatively associated with the SII [β (95% CI): −4.807 (−7.752, −1.862), p = 0.002], indicating that their intake was correlated with lower levels of the SII. However, no significant associations were found with low- or high-LMC foods. The study also explored the relationship between RPA and the SII, finding that more time spent in RPA was negatively associated with the SII [β (95% CI): −0.022 (−0.034, −0.011), p < 0.001]. A mediation analysis was conducted to investigate the role of RPA in the relationship between medium-LMC food intake and the SII. The analysis revealed that RPA had a notable indirect effect, contributing to 6.7% of the overall change in the SII. Overall, this study suggests that medium-LMC food intake and RPA may have beneficial effects on systemic immune inflammation.

The neurotoxicity of heavy metals received increasingly attention in recent years. Sleeping is regulated and coordinated by nervous system, however, the health hazard of heavy metal like cadmium (Cd) exposure on sleep health remained unknown. Rescue strategies like physical exercise (PE) has emerged to mitigate such influence. An epidemiological design with cross-sectional data from National Health and Nutrition Examination Survey 2007–2010 was applied. The relationship between three blood heavy metals [cadmium (Cd), lead (Pb), mercury (Hg)] and sleep disturbance was analyzed. A total of 8,751 participants were finally included in and the weighted participants were 330,239,463. Weighted quantile sum (WQS) regression indicated that mixed blood metals were positively related to risk of sleep disturbance and the mixture effect of exposure to heavy metals was mainly attributable to Cd (89.1%). Weighted logistic regression showed a significant positive association between the highest quartile of blood Cd and sleep disturbance [(OR (95% CI)): 1.191 (1.014,1.400), p = 0.036] in the fully adjusted model, while no association was found under Pb and Hg exposure. In the association between Q3 and Q4 level of blood Cd and sleep disturbance, moderate-to-vigorous physical exercise group had lower risks than none and low exercise group. In the restricted cubic spline model, it was also verified that higher PE participation was associated with the lowest incidence of sleep disturbance with the increment in Cd concentration. Our study suggested that both policy makers and the public should minimize heavy metal exposure. Moreover, conducting moderate to vigorous physical exercise is a protecting factor to mitigate Cd’s influence on sleep health.

Regulatory T cells (Treg), as members of CD4+ T cells, have garnered extensive attention in the research of tumor progression. Treg cells have the function of inhibiting the immune effector cells, preventing tissue damage, and suppressing inflammation. Under the stimulation of the tumor inflammatory microenvironment (IM), the reprogramming of Treg cells enhances their suppression of immune responses, ultimately promoting tumor immune escape or tumor progression. Reducing the number of Treg cells in the IM or lowering the activity of Treg cells while preventing their reprogramming, can help promote the body’s anti-tumor immune responses. This review introduces a reprogramming mechanism of Treg cells in the IM; and discusses the regulation of Treg cells on tumor progression. The control of Treg cells and the response to Treg inflammatory reprogramming in tumor immunotherapy are analyzed and countermeasures are proposed. This work will provide a foundation for downregulating the immunosuppressive role of Treg in the inflammatory environment in future tumor immunotherapy.

Prolonged sitting appears to accelerate aging, while optimal physical activity patterns have been found to delay the process. It is an emerging topic, and no conclusions have been reached regarding the relationship between physical activity patterns and biomarkers-measured aging. Hence, the aim of this study was to investigate the association between sensor-based objectively measured physical activity and phenotypic age using a nationwide population from the National Health and Nutrition Examination Survey (NHANES) in the United States. Weighted linear regression models were performed to evaluate the association between sedentary behavior, light-intensity physical activity (LPA), moderate-to-vigorous physical activity (MVPA) and phenotypic age. A total of 6439 eligible participants were included and the weighted respondents were 49,964,300. Results showed that prolonged sitting was positively associated with phenotypic age in the fully adjusted model [β (95% CI): 0.009(0.007,0.011), p < 0.001], while increasing volume of LPA and MVPA was associated with younger phenotypic age using the fully adjusted model [β (95% CI): −0.010(-0.013,-0.006), p < 0.001; −0.062(-0.075,-0.048), p < 0.001]. By utilizing the Isotemporal Substitution Model, it was found that replacing 30 min of sedentary behavior with 30 min of LPA or MVPA per day was associated with estimated 0.4 or 1.9 years of phenotypic age reduction. According to the study's findings, maintaining a certain level of physical activity could delay the process of aging and intensity matters.

Background: It has been demonstrated that elderly people’s cognitive capacities can be improved with exercise, and short sleep is linked to cognitive decline. However, the impact of physical exercise on cognitive performance in seniors who do not get enough sleep is largely unknown. This makes it an intriguing subject to explore further.Methods: This study consisted of elders (over 60 years old) who participated throughout the National Health and Nutrition Examination Survey’s 2011–2014 cycle (NHANES). Weighted linear regression model and restricted cubic splines analysis were performed to evaluate the association between physical exercise and cognitive function. In the end, 1,615 samples were scrutinized and the total number of weighted respondents was 28,607,569.Results: Results showed that in the Animal Fluency test and the Digit Symbol Substitution test, a positive association was found between physical exercise volume and scores in the fully adjusted model. A two-piecewise linear regression model was then applied to explore the threshold effect of exercise on cognitive performance. Before 960 and 800 MET-minutes/week, there were consistent positive relationship between exercise and scores of the Animal Fluency test [ß (95% CI): 0.233 (0.154, 0.312), p < 0.001] and Digit Symbol Substitution test [β (95% CI): 0.555 (0.332, 0.778), p < 0.001], respectively. However, there was a saturation effect where physical exercise volume reached the two inflection points.Conclusion: According to our research, the benefit of exercise did not always expand with the exercise volume increment under the short-sleep condition, which challenged existing knowledge. The short-sleep elder group could maintain cognitive performance with no more than 800 MET-minutes/week of physical exercise. Verification of these findings requires further biological investigations.