Exploring the impact of protein intake on the association between oxidative balance score and lean mass in adults aged 20-59: NHANES 2011-2018.

BACKGROUND: Previous studies have established a correlation between the pathogenesis of oxidative stress and sarcopenia. The Oxidative Balance Score (OBS) is an integrated measure that reflects the overall balance of antioxidants and pro-oxidants in dietary components and lifestyle. However, there are limited reports on the association between OBS and lean mass and the impact of protein intake on the association between OBS and lean mass. METHODS: Using data from the National Health and Nutrition Examination Survey from 2011 to 2018, multivariate linear and logistic regression analyses were conducted to explore the associations between OBS and outcomes. The findings were then illustrated through fitted smoothing curves and threshold effect analyses. RESULTS: This study included 2,441 participants, demonstrating that higher OBS is significantly associated with an increased ratio of appendicular lean mass to body mass index. Key inflection points at OBS 31 mark pronounced changes in these associations, with age and protein intake notably affecting the association. The effect of OBS on lean mass varies among populations with high and low protein intake. CONCLUSIONS: Our findings suggest that OBS is significantly and positively associated with lean mass. A high protein intake of more than 84.5 g/day may enhance the role of OBS in influencing muscle health to improve muscle outcomes.

The association between non­high­density lipoprotein cholesterol to high­density lipoprotein cholesterol ratio (NHHR) and low muscle mass in adults aged 20-59: a population-based study in the United States.

BACKGROUND: The ratio between non-high-density lipoprotein cholesterol and high-density lipoprotein cholesterol (NHHR) is a reliable marker for assessing the risk linked to lipid metabolism disorders. Sarcopenia, characterized by age-related loss of muscle mass and strength/function, includes the assessment of muscle mass, muscle strength, and muscle-specific strength. However, research into NHHR's relationship with low muscle mass risk remains unexplored. METHODS: Our study utilized a cross-sectional approach, examining data derived from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018. Through multivariable linear and logistic regression, we investigated the relationships of the NHHR with muscle mass and low muscle mass. We visualized the results using smoothing curves and assessed threshold effects. We also performed various subgroup and sensitivity analyses. RESULTS: This research encompassed 9,012 participants and demonstrated significant nonlinear associations between NHHR and ALMBMI or low muscle mass risk in a generalized additive model (GAM), pinpointing critical NHHR values (3.328 and 3.367) where changes in NHHR significantly impacted ALMBMI and low muscle mass risk. CONCLUSIONS: The NHHR demonstrates a significant association with an increased risk of low muscle mass among middle-aged Americans. This ratio has potential as a predictive marker for low muscle mass. Further exploration of NHHR is expected to aid in advancing preventive and therapeutic measures for this condition.

Facilitating cooperation in human-agent hybrid populations through autonomous agents.

Cooperative AI has shown its effectiveness in solving the conundrum of cooperation. Understanding how cooperation emerges in human-agent hybrid populations is a topic of significant interest, particularly in the realm of evolutionary game theory. In this article, we scrutinize how cooperative and defective Autonomous Agents (AAs) influence human cooperation in social dilemma games with a one-shot setting. Focusing on well-mixed populations, we find that cooperative AAs have a limited impact in the prisoner's dilemma games but facilitate cooperation in the stag hunt games. Surprisingly, defective AAs can promote complete dominance of cooperation in the snowdrift games. As the proportion of AAs increases, both cooperative and defective AAs have the potential to cause human cooperation to disappear. We then extend our investigation to consider the pairwise comparison rule and complex networks, elucidating that imitation strength and population structure are critical for the emergence of human cooperation in human-agent hybrid populations.