ECSS Paris 2023: CP-PN14
INTRODUCTION: Diets high in saturated fat promote obesity, chronic inflammation, dysregulated lipid metabolism, and endoplasmic reticulum (ER) stress in metabolically active tissues, including liver and visceral adipose tissue (VAT). Extra-virgin olive oil (EVOO), rich in Oleocanthal and Oleacein, exhibits antioxidant and anti-inflammatory effects and protects skeletal muscle mitochondrial function when combined with endurance training during high-fat feeding. However, whether EVOO phenolic content exerts dose-dependent protection in liver and VAT, and whether endurance exercise further enhances these effects, remains unclear. This study examined the independent and combined effects of EVOO phenolics and endurance exercise on metabolic dysfunction induced by a high-fat diet (HFD). METHODS: 60 Female Sprague–Dawley rats (4 weeks old) completed a 12-week intervention and were assigned to HFD (43% kcal from milk fat), HFD supplemented with low-phenolic EVOO (100 mg/L Oleocanthal/Oleacein; LO), LO plus endurance exercise (LO+E), HFD supplemented with high-phenolic EVOO (1000 mg/L Oleocanthal/Oleacein; HO), or HO plus exercise (HO+E). Plasma total cholesterol and TNF-α were measured by ELISA. Liver and VAT were collected for gene expression analyses of lipid metabolism (acetyl-CoA carboxylase [ACC], fatty acid synthase [FASN], carnitine palmitoyltransferase-2 [CPT2]), inflammatory markers (IL-6, TNF-α, MCP-1), anti-inflammatory markers (IL-10, Arg1), and ER stress markers (immunoglobulin heavy chain-binding protein [BiP], C/EBP homologous protein [CHOP]). Data were analyzed using one-way ANOVA. RESULTS: HFD significantly increased plasma total cholesterol and TNF-α, which were attenuated by EVOO supplementation and endurance exercise (HFD vs LO+E and HO+E, p<0.05). In the liver, IL-6 expression was reduced in LO and HO groups in a dose-dependent manner compared with HFD, with the greatest reduction observed in HO+E (p=0.015). Combined high-phenolic EVOO and exercise further reduced lipogenic signaling (ACC; p=0.015) and increased fatty acid oxidation markers (CPT2; trend p=0.08). ER stress markers BiP and CHOP were reduced by exercise, with significant effects observed only in the high-phenolic EVOO group (HO vs HO+E, p<0.05). In VAT, endurance exercise reduced MCP-1 and TNF-α in the LO group (LO vs LO+E, p<0.05), while high-phenolic EVOO reduced TNF-α expression (LO vs HO, p<0.01). Arg1 expression was higher in the LO group than in HFD (p < 0.05) but decreased in the corresponding exercise group (LO+E, p < 0.01). CHOP expression was reduced by endurance exercise in the LO group (LO+E vs LO, p<0.05). CONCLUSION: High-phenolic EVOO provides dose-dependent protection against HFD-induced metabolic dysfunction, with endurance exercise conferring additive benefits. Together, EVOO phenolics and exercise improve lipid metabolism, reduce inflammation, and alleviate ER stress in both liver and VAT, supporting their combined use as complementary strategies to prevent obesity-related metabolic disease.
Read CV Tianou ZhangECSS Paris 2023: CP-PN14
INTRODUCTION: Optimizing carbohydrate intake during prolonged endurance events is critical for maintaining performance and glycemic stability. However, real-world adherence to planned race-day nutrition strategies and the associated glycemic responses in recreational female endurance athletes remain underexplored. Continuous glucose monitoring (CGM) may provide valuable insights into glucose dynamics during competition. METHODS: A 30-year-old recreational female runner (52 kg, 5 years of running experience) completed a 42.6 km mountain marathon with 1100 m of elevation gain in 5 hours 43 mins. A personalized pre-race carbohydrate loading and in-race nutrition strategy was developed in accordance with current endurance nutrition guidelines. Dietary intake was recorded before and during the race, and compliance with the planned strategy was evaluated. Interstitial glucose concentrations were continuously monitored using a CGM device for 14 days, including the pre-race period, race day, and post-race recovery. Planned carbohydrate loading was set at 8 g·kg⁻¹·day⁻¹ for the final two days before the race. Race-morning carbohydrate intake was planned as 2.5 g·kg⁻¹ consumed 2.5 hours before the start. In-race targets were 75 g·h⁻¹ carbohydrate, 500 mL·h⁻¹ fluid, and 300 mg·h⁻¹ sodium. Actual intake was quantified and compared with planned targets. CGM data were analyzed descriptively to assess glycemic trends before and during the race. RESULTS: The athlete achieved high compliance with the carbohydrate-loading protocol, consuming 8.5 and 7.5 g·kg⁻¹ on the final two days pre-race. Race-morning carbohydrate intake matched the planned target (2.5 g·kg⁻¹). During the race, mean carbohydrate intake was 69 g·h⁻¹, slightly below the planned 75 g·h⁻¹, while fluid (550 mL·h⁻¹) and sodium intake (310 mg·h⁻¹) closely matched planned values. CGM data indicated transient hyperglycemia during the first two hours of the race, coinciding with a high early carbohydrate intake (~80-100 g·h⁻¹). Subsequent adjustment and reduction in carbohydrate intake were associated with more stable glycemic profiles during the latter stages of the race. CONCLUSION: This case study demonstrates high real-world compliance with planned nutrition strategies in a recreational female runner and highlights the impact of early race carbohydrate intake on glycemic responses. CGM appears to be a promising tool for evaluating and individualizing endurance nutrition strategies in prolonged, real-world competition settings. This study was supported by TÜBİTAK (The Scientific and Technological Research Council of Türkiye).
Read CV Selin AktitizECSS Paris 2023: CP-PN14
INTRODUCTION: The EAT-Lancet diet is a reference dietary guideline developed by the EAT-Lancet Commission (Willett et al., 2019), designed to adopt a diet that supports both human health and environmental sustainability. Individuals with higher levels of physical activity have increased energy and nutrient requirements, which will likely impact the EAT-Lancet index (ELI) score. The present study aimed to investigate whether the ELI of habitual dietary intake in healthy male and female adults is associated with their energy intake and energy expenditure. METHODS: A total of 101 participants were included, comprising 51 males (23.5 + 1.6 years) and 50 females (24.6 + 1.4 years). Participants recorded all their food intake and physical activities during 3 consecutive days (i.e., 1 weekend day and 2 weekdays). Dietary diaries were analyzed with the Belgian food databank NUBEL, allowing the calculation of energy intake and the ELI score, following the formula proposed by Stubbendorf et al. (2022). Energy expenditure was calculated using metabolic equivalent of task (MET) values (Ainsworth et al., 2011). Pearson (parametric) and Spearman (non-parametric) correlation analyses were used to examine associations between the ELI score and energy intake and expenditure. Participants were further categorized into three ELI-based groups: LOW (<17), MODERATE (18–21), and HIGH (>22). Group differences in energy expenditure and intake were analyzed using a one-way ANOVA (parametric) or Kruskal Wallis test (non-parametric). Alpha was set at 0.05. RESULTS: A significant negative association (ρ = -0.34) was observed between ELI and energy intake. Similarly, a significant negative association (ρ = -0.27) was observed between ELI and energy expenditure. Furthermore, energy intake was significantly higher in the LOW (2652 ± 801 Kcal) compared to both the MODERATE (2089 ± 611 kcal) and HIGH (2074 ± 557 kcal) ELI group. Energy expenditure was significantly higher in the LOW (3267 ± 948 Kcal) compared to both the MODERATE (3011 ± 666 kcal) and HIGH (2657 ± 507 kcal) ELI group. CONCLUSION: Higher energy intake and expenditure were associated with lower ELI scores. These findings suggest that individuals who are more physically active may face greater challenges in following a diet that is both healthy and environmentally sustainable. Consequently, strategies are needed that balance the trade-offs between a nutritious, sustainable diet and the energy demands of physical activity. REFERENCES 1. Willett, W. et al. Food in the Anthropocene: the EAT–Lancet Commission on healthy diets from sustainable food systems. Lancet. 2019; 393:447-492. 2. Stubbendorff, A. et al. Development of an EAT–Lancet index and its relation to mortality in a Swedish population. Am J Clin Nutr. 2022; 115:705-716. 3. Ainsworth B.E. et al. Compendium of Physical Activities: a second update of codes and MET values. Med Sci Sports Exerc. 2011; 43(8):1575-81.
Read CV Dirk AerenhoutsECSS Paris 2023: CP-PN14