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The gut–brain axis (GBA) plays a pivotal role in human health and wellness by orchestrating complex bidirectional regulation and influencing numerous critical processes within the body. Over the past decade, research has increasingly focused on the GBA in the context of inflammatory bowel disease (IBD). Beyond its well-documented effects on the GBA–enteric nervous system and vagus nerve dysregulation, and gut microbiota misbalance—IBD also leads to impairments in the metabolic and cellular functions: metabolic dysregulation, mitochondrial dysfunction, cationic transport, and cytoskeleton dysregulation. These systemic effects are currently underexplored in relation to the GBA; however, they are crucial for the nervous system cells’ functioning. This review summarizes the studies on the particular mechanisms of metabolic dysregulation, mitochondrial dysfunction, cationic transport, and cytoskeleton impairments in IBD. Understanding the involvement of these processes in the GBA may help find new therapeutic targets and develop systemic approaches to improve the quality of life in IBD patients.
The gut–brain axis (GBA) plays a pivotal role in human health and wellness by orchestrating complex bidirectional regulation and influencing numerous critical processes within the body. Over the past decade, research has increasingly focused on the GBA in the context of inflammatory bowel disease (IBD). Beyond its well-documented effects on the GBA–enteric nervous system and vagus nerve dysregulation, and gut microbiota misbalance—IBD also leads to impairments in the metabolic and cellular functions: metabolic dysregulation, mitochondrial dysfunction, cationic transport, and cytoskeleton dysregulation. These systemic effects are currently underexplored in relation to the GBA; however, they are crucial for the nervous system cells’ functioning. This review summarizes the studies on the particular mechanisms of metabolic dysregulation, mitochondrial dysfunction, cationic transport, and cytoskeleton impairments in IBD. Understanding the involvement of these processes in the GBA may help find new therapeutic targets and develop systemic approaches to improve the quality of life in IBD patients.
The purpose of this study was to determine the difference between estimated energy expenditure (EE) and self-reported dietary intake (EI), and factors associated with energy balance in deployed U.S. Army Special Operations Forces (SOF) Soldiers. Methods: Forty-six SOF Soldiers (age: 30.1 ± 3.5 yrs, body mass index: 27.7 ± 4.1 kg/m2) completed surveys on demographic data, mission activity characteristics, gastrointestinal issues, ration consumption, resilience, mood state, and dietary intake using a 127-question food frequency questionnaire at the end of a six-month deployment. EE was estimated using a SOF-specific prediction equation with a physical activity factor of 2.1. A paired t-test compared reported energy intake (EI) with estimated energy expenditure (EE). Pearson correlations identified significant variables associated with energy balance, which were then incorporated into a multiple linear regression model. The regression analysis included Profile of Mood States (POMS) anger and POMS depression as predictor variables to determine their influence on energy balance. Results: Reported mean EI was 2512 ± 1059 kcal·d−1, while estimated mean EE was 5272 ± 525 kcal·d−1. The mean energy imbalance was −2854 kcal/d (95% CI: −2655 to −3055, p < 0.001), with all participants in negative energy balance (range: −492 to −3813 kcal/d). POMS depression (r = 0.517, p < 0.01) and POMS anger (r = 0.363, p = 0.020) were associated with energy balance. The regression model was significant (R2 = 0.23, F (2, 38) = 7.02, p < 0.01), with POMS depression significantly predicting energy balance (β = 50.76, p = 0.011). Conclusions: Deployed SOF Soldiers reported high EE and limited EI, which may negatively impact performance. Higher POMS depression scores were associated with lower energy deficits. Future studies should investigate the relationship between mood and energy balance, using direct measures of EI and EE.
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