It has been well established that exertional stress promotes perturbations to gastrointestinal integrity and functional responses, potentially leading to gastrointestinal symptoms (GIS), and further clinical complications as a result of exercise-induced gastrointestinal syndrome (EIGS), previously described by Costa et al. (Costa, Snipe et al., 2017; Costa et al., 2020). In addition, it is recognized that heat exposure during exertional stress substantially exacerbates EIGS-associated perturbations to intestinal epithelial integrity (i.e., cellular injury and hyperpermeability; Gaskell et al., 2020; Snipe et al., 2018a, 2018b) but not necessarily gastrointestinal functional responses (Gaskell et al., 2022). Such degrading effects on the intestinal structure may result in pathogenic luminal content (e.g., whole bacterial and/or bacterial endotoxins) translocating into systemic circulation, and subsequently promoting local and/or systemic inflammatory responses (Young et al., 2022, 2023). These may be mild and transient in nature resulting in inconvenient GIS that may range from 59%–89% to 88%–92% in response to exertional to exertional-heat stress, respectively (Gaskell et al., 2020; Russo et al., 2021a, 2021b; Snipe et al., 2018a, 2018b; Snipe & Costa 2018), to more profound outcomes, such as acute colitis (Cohen et al., 2009), or even fatality due to systemic shock (Gill, Teixeira et al., 2015). It is, therefore, not surprising that active individuals and their support practitioners are exploring ways to mitigate EIGS and associated debilitating GIS (Gaskell et al., 2021; Scrivin et al., 2022).
To date, various EIGS prevention or management strategies have been studied in an attempt to identify effective countermeasures (Costa Snipe et al., 2017; Costa et al., 2020). Considering the role of protein in cell production, stability, and function, various protein and/or protein derivatives have been investigated using exertional or exertional-heat stress models. For example, glutamine supplementation has been proposed to support intestinal epithelial cell integrity and function, tight junction stability, and regulation, and regulate local and systemic inflammatory signaling pathways (Wang et al., 2014). Although some studies have reported modest protective effects of short-term glutamine supplementation, with or without other constituents (e.g., cystine), in response to exertional stress (Pugh et al., 2017; Tataka et al., 2022), others have not (Lambert et al., 2001). L-arginine, L-citrulline, and aligned nitrate interventions have been also proposed to stimulate the nitric oxide pathway in villi microvascularization, prompting vasodilation and potentially attenuation of exercise-associated hypoperfusion (Costa et al., 2014; Jonvik et al., 2019; van Wijck et al., 2014). To date, the most impressive results have been with the consumption of whole protein prior to and frequently (e.g., 15 g/20 min) during exertional-heat stress (2-hr running at 60% maximal oxygen uptake [
The acute intake of a novel commercial amino acid formulation (4.5 g/L: valine, aspartic acid, serine, threonine, and tyrosine) for up to 6-day supplementation period has been demonstrated to protect and restore murine intestinal epithelial barrier function in response to total body irradiation (Gupta et al., 2020; Yin et al., 2016) and severe exertional-heat stress (King et al., 2019). The formulation resulted in histological evidence of protected intestinal epithelium in association with reduced permeability, decreases in transmembrane claudin-2 protein expression, increases in occludin and e-cadherin proteins, improvements in crypt and villus morphology, and LGR5+ stem cell proliferation (Choi et al., 2017; Gupta et al., 2020; Yin et al., 2014, 2016). Another noncommercial amino acid formulation (6.4 g/L: aspartic acid, serine, valine, isoleucine, threonine, and tyrosine), designed to optimize intestinal fluid delivery (Funnell et al., 2023), may also offer protective functions (dual functionality) based on several key amino acid ratios but requires confirmation. To date, the impact of such amino acid beverages in a human population exposed to exertional-heat stress has never been explored.
With this in mind, the aim of the current study was to determine the effects of two differing amino acid beverage interventions on biomarkers of gastrointestinal integrity in response to exertional-heat stress. It was hypothesized that both amino acid beverages would ameliorate markers reflective of intestinal epithelial cell injury and epithelial hyperpermeability, and systemic inflammatory responses, but result in greater GIS and feeding intolerance, compared with water alone.
Methods
Participants
Twenty nonheat-acclimatized endurance running trained males (mean [SD]: age 32 [8] years, height 1.81 [0.05] m, nude body mass [BM] 77.7 [7.4] kg, fat mass 15.1% [5.1%], and
Preliminary Measures
One week before the first experimental trial, height and nude body mass (Seca 515 MBCA, Seca Group) were recorded. Maximal oxygen uptake (
Experimental Procedure
A schematic description of the heat exertion amino acid technology study and associated experimental procedures are depicted in Figure 1. Heat exertion amino acid technology was conducted in accordance with best practice guidelines for exercise gastroenterology as described in Costa et al. (2022). Participants were provided with an individualized diet low in fermentable oligo-, di-, and monosaccharide and polyols (FODMAP) for the 24-hr period before each experimental trial (10.9 [1.3] MJ/day, 406 [119] g/day carbohydrate [62%], 85 [16] g/day protein [13%], 47 [8] g/day fat [25%], 38 [5] g/day fiber, 2.5 [1.8] L/day water, and <5 g/day FODMAP) to suppress any confounding factors associated with the lead in diet. Participants were asked to refrain from consuming additional high FODMAP foods, alcohol, and caffeinated beverages during the diet-controlled period, and to refrain from strenuous exercise during the 48-hr period before each experimental trial. Compliance was determined by a dietary and exercise log. Participants reported to the laboratory at 8:00 hr after consuming the provided low-FODMAP breakfast (2.3 [0.6] MJ, 98 [27] g carbohydrate, 20 [5] g protein, 6 [3] g fat, 7 [2] g fiber, and <2 g FODMAP) with 500 ml of water (consumed at 07:00 hr). Participants were asked to void before nude body mass and total body water measurement determined via an 8-point multifrequency bioelectrical impedance analyzer (Seca mBCA 515, Seca Group). Thereafter, a breath sample was collected into a 250-ml breath collection bag (Wagner Analysen Technik), and a GIS assessment tool was completed using an exercise-specific modified visual analogue scale (Gaskell et al., 2019). Blood was then collected by venipuncture from an antecubital vein into a sterile 6-ml heparin and 6-ml EDTA vacutainer collection tube (Becton Dickinson Pty Ltd.). To monitor rectal temperature (Tre) during running, participants inserted a thermocouple between 12 and 15 cm beyond the external anal sphincter (Alpha Technics Precision Temperature 4,600 Thermometer).
Schematic illustration of the experimental procedures.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
Schematic illustration of the experimental procedures.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
Schematic illustration of the experimental procedures.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
After the preexercise measurement and preparation, in a double-blind randomized and counterbalanced order, participants completed two experimental trials separated by at least 1 week, consisting of 2 hr (initiated at 09:00 hr) running exercise on a motorized treadmill at the previously determined speed that elicited 60%
Heart rate, rating of perceived exertion, thermal comfort rating, Tre, GIS, ambient temperature, and relative humidity (RH) were measured every 20 min during running. Immediately after the exertional-heat stress exposure, blood and breath samples were collected, and nude body mass was recorded. Participants remained seated during the recovery period and were provided with water ad libitum. Blood samples were additionally collected 1 hr and 2 hr after ceased exposure to exertional-heat stress. In addition, breath samples were collected and GIS recorded every 15 min during the 2-hr recovery measurement period. To reduce any seasonal heat acclimatization, the experimental procedures were conducted over the cooler seasonal periods of the study location (Melbourne, Victoria, Australia), with temperatures consistently ≤20 °C.
Sample Analysis
Breath samples (20 ml) were analyzed in duplicate (coefficient of variation [CV]: 1.2%) for hydrogen (H2) content using a gas-sensitive analyzer in real-time (BreathTracker Digital Microlyzer, Quintron). Whole blood hemoglobin (HB201+, HemoCue AB) and capillary method hematocrit values were used to estimate changes in plasma volume relative to baseline, and used to correct plasma variables (Costa et al., 2014). Blood glucose concentration was determined pre- and postexercise by a HemoCue system (Glucose 201C, HemoCue AB) in duplicate (CV: 4.0%) from heparinized whole blood samples. The remaining blood samples were centrifuged at 4,000 rpm for 10 min within 15 min of sample collection. Plasma was aliquoted into microtubes and frozen at −80 °C until analysis, except for 50 μl that was used to determine plasma osmolality (POsmol), in duplicate (CV: 1.0%), by freezepoint osmometry (Osmomat 030, Gonotec). Plasma concentrations of cortisol (DKO001, DiaMetra), intestinal fatty acid protein (I-FABP; HK406, Hycult Biotech), soluble CD14 (sCD14; HK320, Hycult Biotech), and endotoxin core antibody IgM (HK504, Hycult Biotech) were determined by ELISA. Plasma concentrations of interleukin (IL)-1β, tumor necrosis factor (TNF)-α, IL-6, IL-8, IL-10, and IL-1 receptor antagonist (ra) were determined by multiplex analytical system (HCYTOMAG-60 K, EMD Millipore). All variables were analyzed in duplicate as per manufacturer’s instructions on the same day, with standards and controls on each plate, and each participant assayed on the same plate. The CVs for cortisol, I-FABP, sCD14, and IgM ELISA were 4.3%, 4.0%, 6.3%, and 5.6%, respectively. CV for 6-plex cytokine profile was 11.8% (i.e., IL-1β: 15.5%, tumor necrosis factor-α: 13.0%, IL-6: 11.9%, IL-8: 10.8%, IL-10: 10.7%, and IL-1ra: 9.2%), respectively.
Statistical Analysis
Based on the typical historical data (1,619 [1,398] pg/ml) for changes in plasma I-FABP concentration in response to exertional-heat stress (Gaskell et al., 2020; Snipe et al., 2018a, 2018b; Snipe & Costa 2018), and using standard alpha (.05) and beta values (0.80), the current participant sample size is estimated to provide adequate statistical power (n = 8; power × 0.80–0.99) for detecting significant trial differences (G*Power, version 3.1). Primary data in the text and tables are presented as mean and 95% confidence interval (CI), and mean ± SD for secondary descriptive data. Subjective GIS data are reported as accumulative score and individual participant range. For clarity, data in figures are presented as mean ± SEM, and box and whiskers plot. All data were checked for normal distribution by calculating skewness and kurtosis coefficients. Prior to data analysis, potential outliers were detected using box plot and removed. Participant numbers are reported in each variable data presentation. Variables with singular data points were examined using a paired sample t test or Wilcoxon signed-rank test, while variables with multiple data points were examined using a two-way (Trial × Time) repeated-measures analysis of variance, except for GIS that were examined using Friedman test. Assumptions of homogeneity and sphericity were checked, and when appropriate adjustments to the degrees of freedom were made using the Greenhouse–Geisser correction method. Significant main effects were analyzed using a post hoc Tukey’s HSD test or Wilcoxon signed-rank test for GIS. In addition, Cohen’s d measurement of effect size amino acid interventions and CON were determined as >0.50 and >0.80 for medium and large effects, respectively. Statistics were analyzed using SPSS statistical software (version 28.0, IBM SPSS Statistics) with significance accepted at p < .05.
Results
There was no significant difference in participant characteristics between those randomly assigned to VS001 and VS006, except for
Physiological and Thermoregulatory Strain
There were no significant Trial × Time interactions between respective CON versus VS001 and CON versus VS006 for heart rate, rating of perceived exertion, thermal comfort rating, Tre, and physiological strain index as a result of the exertional-heat stress (Table 1). However, a main effect of time was observed for all variables (p < .001), whereby, heart rate, rating of perceived exertion, Tre, thermal comfort rating, and physiological strain index increased as exertional-heat stress progressed. Peak and ΔTre did not significantly differ (p > .05) between respective CON (38.90 °C [38.29–39.50] and 2.21 °C [1.81–2.60], respectively) versus VS001 (38.85 °C [38.23–39.47] and 2.14 °C [1.73–2.55]), and CON (38.99 °C [38.65–39.32] and 2.10 °C [1.73–2.48]) versus VS006 (39.14 °C [38.83–39.44] and 2.38 °C [2.12–2.64]). Similarly, peak physiological strain index did not significantly differ (p > .05) between respective CON (7.5 [5.6–9.5]) versus VS001 (7.2 [5.7–8.6]) and CON (7.7 [6.2–9.3]) versus VS006 (8.3 [7.8–8.8]).
Markers of Physiological and Thermoregulatory Strain in Response to 2 hr of Exertional-Heat Stress With and Without an Amino Acid Beverage Intervention
| 20 min | 40 min | 60 min | 80 min | 100 min | 120 min | |
|---|---|---|---|---|---|---|
| HR (bpm)†† | ||||||
| CON | 143 [131, 156] | 149 [137, 160] | 151 [137, 164] | 152 [140, 164] | 151 [140, 162] | 154 [143, 164] |
| VS001 | 143 [133, 152] | 147 [137, 158] | 152 [141, 164] | 153 [142, 163] | 153 [143, 162] | 154 [145, 164] |
| CON | 142 [135, 148] | 149 [142, 156] | 152 [144, 160] | 152 [145, 160] | 153 [145, 162] | 157 [148, 165] |
| VS006 | 146 [139, 153] | 152 [146, 158] | 157 [153, 162] | 162 [157, 167] | 163 [157, 170] | 161 [153, 169] |
| RPE†† | ||||||
| CON | 11 [9, 12] | 12 [11, 13] | 12 [11, 14] | 13 [11, 15] | 13 [11, 15] | 14 [11, 16] |
| VS001 | 10 [8, 11] | 11 [9, 12] | 11 [10, 13] | 12 [11, 14] | 12 [11, 14] | 13 [11, 14] |
| CON | 10 [8, 11] | 11 [10, 13] | 12 [10, 14] | 12 [10, 14] | 12 [10, 14] | 13 [11, 14] |
| VS006 | 11 [9, 12] | 12 [11, 13] | 13 [12, 14] | 13 [12, 14] | 14 [11, 16] | 13 [11, 15] |
| TCR†† | ||||||
| CON | 8 [8, 9] | 9 [8, 10] | 9 [8, 10] | 8 [7, 9] | 8 [7, 9] | 8 [8, 9] |
| VS001 | 8 [7, 9] | 8 [7, 10] | 8 [7, 10] | 8 [7, 9] | 9 [8, 10] | 9 [8, 10] |
| CON | 8 [8, 9] | 10 [9, 11] | 11 [9, 12] | 10 [9, 10] | 10 [8, 12] | 10 [9, 10] |
| VS006 | 9 [7, 10] | 10 [8, 11] | 10 [9, 12] | 11 [9, 12] | 10 [8, 12] | 10 [8, 12] |
| Tre (°C)†† | ||||||
| CON | 37.6 [37.1, 38.1] | 38.3 [37.7, 38.9] | 38.4 [37.7, 39.1] | 38.5 [37.9, 39.1] | 38.6 [38.1, 39.2] | 38.5 [37.9, 39.0] |
| VS001 | 37.7 [37.1, 38.2] | 37.9 [37.4, 38.4] | 38.3 [37.7, 38.8] | 38.4 [37.7, 39.1] | 38.5 [38.0, 39.1] | 38.6 [37.9, 39.2] |
| CON | 37.7 [37.5, 37.9] | 38.3 [38.0, 38.6] | 38.7 [38.5, 39.0] | 38.8 [38.5, 39.1] | 38.7 [38.4, 39.0] | 38.8 [38.5, 39.1] |
| VS006 | 37.5 [37.0, 37.9] | 38.2 [37.7, 38.6] | 38.5 [38.1, 38.9] | 38.9 [38.6, 39.2] | 38.9 [38.5, 39.3] | 38.8 [38.4, 39.2] |
| PSI†† | ||||||
| CON | 4.2 [2.9, 5.6] | 5.9 [4.1, 7.6] | 6.1 [4.2, 8.0] | 6.4 [4.9, 8.0] | 6.7 [5.0, 8.4] | 6.7 [5.1, 8.2] |
| VS001 | 3.8 [2.8, 4.8] | 4.7 [3.6, 5.7] | 5.8 [4.4, 7.1] | 6.2 [4.9, 7.5] | 6.4 [5.2, 7.6] | 6.6 [5.3, 7.9] |
| CON | 3.6 [2.7, 4.5] | 5.3 [4.2, 6.4] | 6.3 [5.1, 7.5] | 6.6 [5.5, 7.8] | 6.6 [5.4, 7.8] | 7.1 [5.9, 8.4] |
| VS006 | 3.4 [2.4, 4.5] | 5.2 [4.3, 6.1] | 6.4 [5.7, 7.1] | 7.5 [7.0, 8.0] | 7.6 [6.9, 8.3] | 7.5 [6.5, 8.4] |
Note. Data are presented as mean [95% CI] (VS001 n = 10 and VS006 n = 10). CON = water control; CI = confidence interval; HR = heart rate; RPE = rating of perceived exertion; PSI = physiological strain index; TCR = thermal comfort rating; Tre = rectal temperature; MEOT = main effect of time.
††MEOT: p < .001.
No significant difference in pre- and postexercise blood glucose concentration was observed between trials (overall mean and 95% CI: preexercise 4.7 [4.4, 5.0] mMol/L and postexercise 5.0 [4.8, 5.2] mMol/L). No difference in preexercise resting plasma cortisol concentration was observed between VS001 and VS006 with their respective CON. There were no significant Trial × Time interactions between respective CON versus VS001 and CON versus VS006 for plasma cortisol concentration. However, a main effect of time was observed for CON versus VS001 (p = .030) and CON versus VS006 (p < .001), whereby plasma concentrations of cortisol increased from pre- to postexercise. Although plasma cortisol concentration increased pre- to postexercise on respective CON (206 [87–324] ng/ml) versus VS001 (225 [32–418] ng/ml), and CON (75 [−26–176] ng/ml) versus VS006 (241 [108–374] ng/ml), there was no significant difference in magnitude of response observed (p = .695 and p = .106, respectively).
Hydration Markers
There was no significant difference in preexercise total body and extracellular water (overall mean and 95% CI: 61.4% [60.4%, 62.4%] and 25.2% [23.9%, 26.6%], respectively) between trials. Exercise-associated BM loss was significantly higher (p = .024) on CON (1.7% [1.3%, 2.0%]) versus VS001 (1.2% [0.9%, 1.6%]), but was not significantly different (p = .690) between CON (1.2% [0.4%, 2.1%]) and VS006 (1.3% [0.7%, 1.9%]). There was no significant difference in exercise-associated change in plasma volume between trials (overall mean and 95% CI: −8.3 [−10.0%, −6.6%]), which returned to similar preexercise baseline levels 1 hr into recovery. Plasma osmolality did not significantly change from pre- to postexercise in all trials and was not significantly different between respective trials (overall mean and 95% CI: preexercise 295 [293, 298] mOsmol/kg and postexercise 295 [293, 297] mOsmol/kg).
Intestinal Epithelial Injury
No difference in preexercise resting plasma I-FABP concentration was observed between VS001 and VS006 with their respective CON. A Trial × Time interaction was observed for plasma I-FABP concentration for VS001 + CON (p < .001) and VS006 + CON (p<.001). Whereby, concentrations were lower on VS001 and VS006 in response to the exertional-heat stress challenge compared with respective CON (Figure 2a-i and 2b-i). Pre- to peak postexercise Δ was lower on VS001 (p < .001, d = 1.56) and VS006 (p = .006, d = 1.07) compared with respective CON (Figure 2a-ii and 2b-ii).
Plasma I-FABP response to exertional-heat stress on (a) VS001 (n = 9, ○) and (b) VS006 (n = 9, •) amino acid beverage intervention compared with respective CON (▪), including mean ± SEM response over measurement time points (i) and box and whiskers plot peak Δ (ii). **p < .01 versus preexercise. aap < .01 CON versus amino acid beverage intervention. I-FABP = intestinal fatty acid protein; CON = water control.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
Plasma I-FABP response to exertional-heat stress on (a) VS001 (n = 9, ○) and (b) VS006 (n = 9, •) amino acid beverage intervention compared with respective CON (▪), including mean ± SEM response over measurement time points (i) and box and whiskers plot peak Δ (ii). **p < .01 versus preexercise. aap < .01 CON versus amino acid beverage intervention. I-FABP = intestinal fatty acid protein; CON = water control.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
Plasma I-FABP response to exertional-heat stress on (a) VS001 (n = 9, ○) and (b) VS006 (n = 9, •) amino acid beverage intervention compared with respective CON (▪), including mean ± SEM response over measurement time points (i) and box and whiskers plot peak Δ (ii). **p < .01 versus preexercise. aap < .01 CON versus amino acid beverage intervention. I-FABP = intestinal fatty acid protein; CON = water control.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
Bacterial Endotoxin Translocation
No difference in preexercise resting plasma sCD14 and IgM concentrations was observed between VS001 and VS006 with their respective CON. A Trial × Time interaction was observed for plasma sCD14 concentration for VS001 + CON (p = .007) and VS006 + CON (p = .016). Whereby, concentrations were lower on VS001 and VS006 in response to the exertional-heat stress challenge compared with respective CON (Figure 3a-i and 3b-i). Pre- to peak postexercise Δ was lower on VS001 (p = .025, d = 1.03) and VS006 (p = .007, d = 1.13) compared with respective CON (Figure 3a-ii and 3b-ii). Similarly, a Trial × Time interaction was observed for plasma anti-endotoxin antibodies IgM concentration for VS001 + CON (p = .019) and VS006 + CON (p = .002). Whereby, concentrations were lower on VS001 and VS006 in response to the exertional-heat stress challenge compared with respective CON (Figure 4a-i and 4b-i). Pre- to peak postexercise Δ was lower on VS001 (p = .031, d = 0.63) and VS006 (p = .001, d = 1.37) compared with respective CON (Figure 4a-ii and 4b-ii).
Plasma sCD14 response to exertional-heat stress on (a) VS001 (n = 9, ○) and (b) VS006 (n = 9, •) amino acid beverage intervention compared with respective CON (▪), including mean ± SEM response over measurement time points (i) and box and whiskers plot peak Δ (ii). **p < .01 versus preexercise. aap < .01 and ap < .05 CON versus amino acid beverage intervention. sCD14 = soluble CD14; CON = water control.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
Plasma sCD14 response to exertional-heat stress on (a) VS001 (n = 9, ○) and (b) VS006 (n = 9, •) amino acid beverage intervention compared with respective CON (▪), including mean ± SEM response over measurement time points (i) and box and whiskers plot peak Δ (ii). **p < .01 versus preexercise. aap < .01 and ap < .05 CON versus amino acid beverage intervention. sCD14 = soluble CD14; CON = water control.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
Plasma sCD14 response to exertional-heat stress on (a) VS001 (n = 9, ○) and (b) VS006 (n = 9, •) amino acid beverage intervention compared with respective CON (▪), including mean ± SEM response over measurement time points (i) and box and whiskers plot peak Δ (ii). **p < .01 versus preexercise. aap < .01 and ap < .05 CON versus amino acid beverage intervention. sCD14 = soluble CD14; CON = water control.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
Plasma EndoCAb IgM response to exertional-heat stress on (a) VS001 (n = 9, ○) and (b) VS006 (n = 9, •) amino acid beverage intervention compared with respective CON (▪), including mean ± SEM response over measurement time points (i) and box and whiskers plot peak Δ (ii). **p < .01 versus preexercise. aap < .01 and ap < .05 CON versus amino acid beverage intervention. EndoCAb = endotoxin core antibody; CON = water control.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
Plasma EndoCAb IgM response to exertional-heat stress on (a) VS001 (n = 9, ○) and (b) VS006 (n = 9, •) amino acid beverage intervention compared with respective CON (▪), including mean ± SEM response over measurement time points (i) and box and whiskers plot peak Δ (ii). **p < .01 versus preexercise. aap < .01 and ap < .05 CON versus amino acid beverage intervention. EndoCAb = endotoxin core antibody; CON = water control.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
Plasma EndoCAb IgM response to exertional-heat stress on (a) VS001 (n = 9, ○) and (b) VS006 (n = 9, •) amino acid beverage intervention compared with respective CON (▪), including mean ± SEM response over measurement time points (i) and box and whiskers plot peak Δ (ii). **p < .01 versus preexercise. aap < .01 and ap < .05 CON versus amino acid beverage intervention. EndoCAb = endotoxin core antibody; CON = water control.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
Systemic Inflammatory Response Profile
No difference in preexercise resting plasma concentrations of measured cytokines was observed between VS001 and VS006 with their respective CON. No Trial × Time interaction was observed for measured cytokines. However, a main effect of time was observed for plasma IL-10 and IL-1ra concentrations on CON versus VS001; and plasma IL-6, IL-10, and IL-1ra concentrations CON versus VS006. Whereby, plasma concentrations of these cytokines increase from pre- to postexercise (Table 2). The pre- to postexercise response magnitude for systemic inflammatory cytokines measured did not differ between the respective CON, except for IL-10 (p = .037, d = 0.18) and IL-8 (p = .028, d = 0.29) that was significantly lower on VS001 versus CON (Table 2). The systemic inflammatory response profile was significantly lower immediately post and 1 hr postexercise on VS001 (Figure 5a-i and 5a-ii), but not on VS006 (Figure 5b-i and 5b-ii), compared with their respective CON.
Systemic Inflammatory Cytokine Responses to 2 hr of Exertional-Heat Stress With and Without an Amino Acid Beverage Intervention
| CON | VS001 | |||
|---|---|---|---|---|
| Preexercise | Postexercise# | Preexercise | Postexercise# | |
| IL-1β (pg/ml) | 2.3 [0.6, 4.0] | 4.7 [2.0, 7.4] | 2.7 [0.7, 4.8] | 4.2 [2.1, 6.4] |
| TNF-α (pg/ml) | 12.2 [6.5, 17.9] | 17.5 [9.9, 25.2] | 12.4 [8.7, 16.2] | 16.9 [11.0, 22.9] |
| IL-6 (pg/ml)‡ | 6.7 [3.6, 9.7] | 13.7 [5.9, 21.4] | 7.1 [3.4, 10.7] | 11.2 [7.6, 14.9] |
| IL-8 (pg/ml)‡ | 11.5 [6.2, 16.9] | 21.5 [8.8, 34.1] | 13.4 [8.7, 18.2] | 19.7 [10.3, 29.2] |
| IL-10 (pg/ml) | 31.1 [17.3, 44.9] | 86.7 [46.6, 126.8] | 29.1 [16.7, 41.5] | 73.6 [33.2, 113.9]a,† |
| IL-1ra (pg/ml) | 21.6 [13.5, 29.7] | 98.3 [26.3, 170.4] | 20.7 [14.5, 27.0] | 58.4 [33.8, 83.0]† |
| CON | VS006 | |||
|---|---|---|---|---|
| Preexercise | Postexercise# | Preexercise | Postexercise# | |
| IL-1β (pg/ml) | 1.8 [1.0, 2.5] | 2.2 [1.0, 3.4] | 2.0 [1.0, 3.0] | 2.2 [1.2, 3.2] |
| TNF-α (pg/ml) | 9.2 [7.8, 10.7] | 12.8 [9.7, 15.9] | 9.6 [6.7, 12.5] | 12.3 [9.1, 15.4] |
| IL-6 (pg/ml)‡ | 5.9 [0.7, 11.0] | 9.0 [2.8, 15.2] | 5.4 [1.1, 9.6] | 8.3 [4.2, 12.3]†† |
| IL-8 (pg/ml)‡ | 10.2 [4.9, 15.4] | 13.9 [8.1, 19.6] | 9.7 [5.5, 14.0] | 12.5 [8.6, 16.4] |
| IL-10 (pg/ml) | 21.4 [6.5, 36.4] | 70.0 [41.9, 98.1] | 22.1 [7.1, 37.1] | 53.2 [31.5, 74.8]†† |
| IL-1ra (pg/ml) | 14.7 [11.4, 18.1] | 33.1 [26.0, 40.3] | 16.9 [11.9, 21.9] | 32.8 [23.0, 42.5]†† |
Note. Data are presented as mean [95% CI] (VS001 n = 10 and VS006 n = 10; but VS001 n = 6 and VS006 n = 8 for IL-6 and IL-8). CI = confidence interval; CON = water control; EIGS = exercise-induced gastrointestinal syndrome; TNF = tumor necrosis factor; IL = interleukin; ra = receptor antagonist; MEOT = main effect of time.
MEOT: ††p < .01 and †p < .05, ap < .05 versus CON for Δ pre- to peak postexercise. #Peak postexercise value. ‡Participant with plasma IL-6 and IL-8 concentrations ≥twofold the upper 95% CI values previously established baseline plasma concentrations using a human cyto/chemokine multiplex analysis assay (n = 103; Costa et al., 2022) were removed period to data analysis (VS001 n = 4 and VS006 n = 2). Despite participants presenting proinflammatory cytokines IL-1β and TNF-α and anti-inflammatory cytokines IL-10 and IL-1ra within normative ranges for multiplex analysis (Costa et al., 2022; Young et al., 2023), values for inflammatory response and modulatory cytokine IL-6 and IL-8 are potential indicative of an underlying internal immune activation, asymptomatic and not related to EIGS, and subsequently not effecting other EIGS biomarkers (Cruz et al., 2021; Gentile et al., 2013; Li et al., 2021; Mendieta et al., 2016).
SIR-Profile to exertional-heat stress on (a-i, ii) VS001 (n = 10, ○) and (b-i, ii) VS006 (n = 10, •) amino acid beverage intervention compared with respective CON (▪), including mean ± SEM response over measurement time points (i) and box and whiskers plot peak Δ (ii) MEOT. ††p < .01 versus preexercise. ap < .05 CON versus amino acid beverage intervention. SIR-Profile = systemic inflammatory response profile; MEOT = main effect of time.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
SIR-Profile to exertional-heat stress on (a-i, ii) VS001 (n = 10, ○) and (b-i, ii) VS006 (n = 10, •) amino acid beverage intervention compared with respective CON (▪), including mean ± SEM response over measurement time points (i) and box and whiskers plot peak Δ (ii) MEOT. ††p < .01 versus preexercise. ap < .05 CON versus amino acid beverage intervention. SIR-Profile = systemic inflammatory response profile; MEOT = main effect of time.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
SIR-Profile to exertional-heat stress on (a-i, ii) VS001 (n = 10, ○) and (b-i, ii) VS006 (n = 10, •) amino acid beverage intervention compared with respective CON (▪), including mean ± SEM response over measurement time points (i) and box and whiskers plot peak Δ (ii) MEOT. ††p < .01 versus preexercise. ap < .05 CON versus amino acid beverage intervention. SIR-Profile = systemic inflammatory response profile; MEOT = main effect of time.
Citation: International Journal of Sport Nutrition and Exercise Metabolism 2023; 10.1123/ijsnem.2023-0025
GIS and Feeding Tolerance
The incidence and severity of GIS are presented in Table 2. Incidence of GIS on CON versus VS001 were 70% and 90%, respectively, and on CON versus VS006 was 80% and 80%, respectively. There was no significant difference between amino acid beverage interventions VS001 and VS006 with their respective CON for severity of gut discomfort, total GIS, lower GIS, and nausea (Table 3). Upper GIS was significantly higher on VS001 versus CON but not VS006 versus CON. No significant difference in breath H2 peak (p = .952) or AUC (p = .507) was observed between CON (5 [3–7] ppm and 327 [190–465] ppm/120 min, respectively] and VS001 (5 [2–7] ppm and 347 [224–469] ppm/120 min). Similarly, no significant difference in breath H2 peak (p = .676) or AUC (p = .484) was observed between CON (3 [2–3] ppm and 178 [124–231] ppm/120 min, respectively) and VS006 (3 [2–5] ppm and 223 [134–313] ppm/120 min).
Incidence and Severity of GIS in Response to 2 hr of Exertional-Heat Stress With and Without an Amino Acid Beverage Intervention
| CON | Severity# | VS001 | Severity# | CON | Severity# | VS006 | Severity# | |
|---|---|---|---|---|---|---|---|---|
| Incidence (%) | Incidence (%) | Incidence (%) | Incidence (%) | |||||
| Gut discomfort | NA | 8 (1–27) | NA | 14 (2–43) | NA | 10 (2–29) | NA | 13 (2–36) |
| Total GIS | 70 | 11 (1–42) | 90 | 22 (2–75) | 80 | 15 (2–49) | 80 | 19 (2–48) |
| Upper GIS | 50 | 3 (4–8) | 70 | 9 (2–35)a | 60 | 8 (3–29) | 60 | 8 (2–29) |
| Belching | 40 | 2 (4–8) | 40 | 3 (2–14) | 60 | 4 (3–17) | 50 | 5 (2–29) |
| Gastric acidosis | 10 | 1 (8–8) | 10 | 1 (15–15) | 0 | 0 (0–0) | 10 | 0 (2–2) |
| Upper abdominal bloating | 0 | 0 (0–0) | 30 | 2 (3–13) | 30 | 4 (6–19) | 40 | 4 (3–19) |
| Upper abdominal pain | 0 | 0 (0–0) | 20 | 2 (5–16) | 20 | 1 (1–4) | 0 | 0 (0–0) |
| Urge to regurgitate | 0 | 0 (0–0) | 0 | 0 (0–0) | 10 | 0 (1–1) | 10 | 0 (2–2) |
| Regurgitation | 0 | 0 (0–0) | 0 | 0 (0–0) | 0 | 0 (0–0) | 0 | 0 (0–0) |
| Projectile vomiting | 0 | 0 (0–0) | 0 | 0 (0–0) | 0 | 0 (0–0) | 0 | 0 (0–0) |
| Lower GIS | 30 | 5 (1–31) | 50 | 10 (1–47) | 50 | 3 (2–13) | 60 | 5 (2–18) |
| Flatulence | 20 | 1 (6–7) | 20 | 1 (1–8) | 30 | 1 (1–10) | 20 | 1 (3–9) |
| Lower abdominal bloating | 10 | 0 (4–4) | 30 | 2 (5–9) | 30 | 2 (3–8) | 40 | 2 (1–8) |
| Urge to defecate | 30 | 4 (1–27) | 30 | 6 (8–40) | 20 | 1 (5–6) | 40 | 3 (1–14) |
| Lower abdominal pain | 0 | 0 (0–0) | 20 | 2 (2–15) | 10 | 0 (2–2) | 20 | 1 (2–4) |
| Abnormal defecation | 0 | 0 (0–0) | 0 | 0 (0–0) | 0 | 0 (0–0) | 0 | 0 (0–0) |
| Nausea | 10 | 1 (11–11) | 10 | 0 (3–3) | 10 | 2 (16–16) | 20 | 2 (1–15) |
| Dizziness | 40 | 2 (2–9) | 20 | 1 (3–7) | 40 | 3 (1–23) | 40 | 2 (1–15) |
| Stitch | 10 | 0 (2–2) | 20 | 1 (2–10) | 0 | 0 (0–0) | 0 | 0 (0–0) |
Note. GIS = gastrointestinal symptoms; CON = water control; NA = not available.
ap < .05 versus CON.
#Mean of summative accumulation and range of participants reporting incidence (VS001, n = 10 and VS006, n = 10).
Discussion
The current study aimed to determine the effects of two differing amino acid beverage interventions on biomarkers of gastrointestinal integrity in response to exertional-heat stress. In accordance with our hypothesis, both amino acid beverage formulations (i.e., VS001 and VS006) ameliorated markers reflective of intestinal epithelial cell injury and hyperpermeability, with ameliorated systemic inflammatory responses also observed (i.e., VS001), compared with CON. On the contrary to our hypothesis, the amino acid beverage intervention did not result in any substantial GIS or feeding intolerance compared with CON. The findings from the current study suggest a 1-week intervention consisting of consuming 237 ml of either amino acid beverage (VS001 or VS006) twice daily, and before, plus frequently during exertional-heat stress provides beneficial and protective effects against EIGS and the potential clinical consequence arising from this condition.
Injury to intestinal epithelial cells commonly occurs as a result of exercise, likely associated with splanchnic hypoperfusion, as per the EIGS model, and highly exacerbated as exercise duration prolongs and with the addition of heat stress (Costa, Snipe et al., 2017; Costa et al., 2020). The current exertional-heat stress model (2-hr running at 60%
On a similar note, it is well established that exertional stress promotes intestinal epithelial hyperpermeability leading to the paracellular translocation of luminal pathogenic agents into systemic circulation, with potential serious clinical consequences (Gill, Hankey et al., 2015; Gill, Teixeira et al., 2015). Such hyperpermeability of the protective barrier between pathogenic luminal content and the pristine regulation of systemic circulation appears to be exacerbated with exercise duration and with exposure to heat (Costa, snipe et al., 2017; Costa et al., 2020, 2022). Using surrogate biomarkers of bacterial endotoxin translocation (i.e., sCD14 and endotoxin core antibody IgM), the data from the current study suggest that amino acid beverage intervention was able to suppress luminal-originated pathogen paracellular translocation (i.e., abolished response for sCD14 and IgM on VS001 and VS006) as a result of exertional-heat stress-associated increases in intestinal epithelial permeability, with CON showing pronounced responses (i.e., sCD14 + 3.7 μg/ml [+49%], and IgM + 92 MMU/ml [+55%]). These findings are in accordance with previous similar exertional-heat stress model studies that reported attenuated small intestine permeability and lower perturbations to bacterial endotoxin profile with whole protein ingestion frequently during exercise (∼15 g/20 min, ∼6% w/v; Snipe et al., 2017). It is speculated that the positive effects seen with amino acid beverage intervention on preventing the paracellular translocation of luminal-originating pathogenic agents into systemic circulation were likely due to not only the mechanisms previously mentioned for intestinal epithelial cell injury, but also prevention and/or maintenance of epithelial tight junction protein damage and/or dysfunction (Gupta et al., 2020; Yin et al., 2014, 2016).
A novel finding of the current study, not otherwise reflected in the majority of previous exercise gastrointestinal research, with or without an EIGS and GIS prevention or management intervention focus, was the lower systemic inflammatory responses with amino acid beverage intervention (Figure 5), but significance was only seen on VS001 versus the respective CON. Such statistically contradictory outcomes are likely due to the large individual response variability commonly observed with plasma cytokine concentration following exertional and exertional-heat stress (Costa et al., 2022; Peake et al., 2015; Suzuki et al., 2002; Young et al., 2023). The measurement of systemic inflammatory cytokines is a fundamental inclusion in such exercise gastroenterology research, as it reflects the endpoint of intestinal epithelial injury and permeability, and subsequent lumen to circulation pathogenic translocation. In addition, clinical consequence of such gastrointestinal integrity perturbation is associated with the overexaggerated systemic inflammatory responses (Gill, Teixeira et al., 2015). The systemic inflammatory response patterns in the current study mirror those of previous exertional-heat stress models (Gaskell et al., 2020; Snipe et al., 2018a, 2018b). Such outcomes are expected from healthy individuals, but warrant caution in those potentially immunocompromised and/or presenting an underlying immune response or modulatory predisposition, asymptomatic, and not otherwise related to EIGS (Cruz et al., 2021; Gentile et al., 2013; Mendieta et al., 2016; Li et al., 2021). This likely explains the unexpected and consistently high baselines and postexercise plasma IL-6 and IL-8 concentrations observed in six participants (n = 4 on VS001 and n = 2 on VS006), analyzed through the Magpix multiplex system (Luminex Corporation). Such cohort responses have previously been observed in other EIGS research using a multiplex system, whereby a select few participants present IL-6 and IL-8 values substantially above the expected reference ranges (Russo et al., 2021a, 2021b). These discussion points potentially highlight the importance of using direct pro- (e.g., IL-1β and tumor necrosis factor-α) and anti- (e.g., IL-10 and IL-1ra) inflammatory cytokines in EIGS inflammatory outcome assessment, and/or either using IL-6 and IL-8 markers as screening for identification of another non-EIGS underlying pathophysiology and/or identification for participant study inclusion or exclusion. Nevertheless, considering the exertional stress and heat exposure were mirrored between trials, and physiological plus thermoregulatory strain markers were not significantly different between trials, it appears plausible that the lower systemic inflammatory cytokine response with amino acid beverage interventions was likely due to a suppressed pathogen translocation, as a result of lower intestinal epithelial injury and/or permeability.
Based on previous research observations, one concern identified with the amino acid beverage intervention was the potential for exacerbated GIS and feeding intolerance compared with the equivalent water intake (Snipe et al., 2017). The study outcomes as a whole suggest the amino acid beverage volume and formulation did not substantially result in exacerbating GIS compared with the respective CON. GIS incidence was high on VS001, VS006, and CON, which is in accordance with the majority of laboratory-controlled experimental procedures using a validated and reliability-checked GIS assessment tool (Gaskell et al., 2019). As expected, there was large individual variation within and between trials for GIS incidence type and severity, generally explained by the subjective nature of GIS assessment. Nevertheless, no substantial difference in GIS severity was observed as a whole cohort between VS006 and respective CON. The only significant difference observed was between VS001 and CON for upper GIS. This was, however, a very modest difference and considered mild in nature. Good tolerance to the amino acid intervention suggests that amino acid beverages are a good option compared with whole protein intake during exercise, which results in substantial GIS and feeding intolerance (Snipe et al., 2017).
From a practical translation perspective, and considering a final negative outcome of EIGS may include exertional with/or without heat stress-associated sepsis and cascade-associated multiorgan failure with potential fatality (Hodgin & Moss 2008), it seems logical that activities that foster a septic systemic instigation may benefit from the application of the current amino acid beverage intervention. For example, ultra-endurance activities are notorious for presenting systemic bacterial pathogenicity and inflammatory responses, despite limited fatalities reported (Bosenberg et al., 1988; Brock-Utne et al., 1988; Camus et al., 1997, 1998; Gill Hankey et al., 2015; Gill, Teixeira et al., 2015; Roberts et al., 2021). Whereas, occupational population that is exposed to prolonged strenuous exertion in hot ambient conditions (e.g., military, mining, agriculture, and other field-based occupations) appear to present similar pathogenic translocation and systemic inflammatory responses; however, more frequent fatalities acknowledged (Donoghue, 2004; Hunt et al., 2013; Laitano et al., 2019; Nag et al., 2007; Rav-Acha et al., 2004; Roberts et al., 2021). In these populations, potential “at-risk” individuals (i.e., novel to activity, not fit for purpose, heat intolerance, presenting illness and/or inflection, cardiometabolic co-morbidities, and/or immune compromised), the data from the current study suggest 1-week supplementation and frequency intake during activity of amino acid containing beverages may reduce any potential adverse effect of EIGS in response to the activity. Moreover, from an exercise performance perspective, Ex-GIS is synonymous with negatively affecting exercise performance (Costa, Miall et al., 2017; Miall et al., 2018). The current amino acid beverage formulation did not substantially result in Ex-GIS, suggesting acceptable feeding tolerance, unlike the application of whole protein frequently during exercise resulting in substantial and performance impacting Ex-GIS (Costa, Miall et al., 2017; Snipe et al., 2017). It is, therefore, plausible that such beverage application may provide some protection against EIGS without negatively impacting exercise performance through instigative severe Ex-GIS.
Conclusions
The consumption of beverages containing an amino acid blend, ranging 4.5–6.4 g/L, twice daily for 7 days, immediately before, and during exertional-heat stress ameliorated the intestinal epithelial injury, lumen to circulation pathogenic translocation, and systemic inflammatory perturbations associated with exercising in the heat, but without exacerbating GIS.
Acknowledgments
First, the authors would like to thank all the participants that volunteered to take part in the study, as well as the Monash University Sports Dietetics & Extremes Physiology Group and collaborators for their assistance in the laboratory during data and sample collection, and/or sample analysis. The research study procedures were undertaken at BASE Facility, Department of Nutrition Dietetics & Food, Faculty of Medicine Nursing & Health Sciences, Monash University, Melbourne, Australia. The current heat exertion amino acid technology study (Heat Exertion Amino Acid Technology) was supported by Entrinsic Bioscience, LLC. Researchers within Entrinsic Bioscience (Cheuvront, Kenefick, and Blazy) were involved in the development of the experimental protocol. Apart from the industry-funded aspect of this research study, Costa, Henningsen, Gaskell, Alcock, Mika, and Rauch have no conflicts of interest to declare regarding the development, undertaking, and reporting of this research study. Cheuvront, Blazy, and Kenefick are employees of Entrinsic Bioscience, LLC. Due to intellectual property licensing and confidentially, disclosure of the amino acid profile for VS001 and VS006 is not possible on this occasion. Author Contributions: Chief investigation: Costa. Development and confirmation of the experimental design: Costa, Cheuvront, Blazy, Kenefick. Participant recruitment, experimental design, data collection, and sample collection, processing, and storage: Costa, Henningsen, Gaskell, Alcock, Mika, Rauch. Various aspects of sample analysis: Costa, Henningsen, Rauch. Independent aspects of data processing, management, and analysis: Costa. Preparation of the original draft manuscript: Costa. Review and final preparation of the manuscript: All authors.
References
Bosenberg, A.T., Brock-Utne, J.G., Gaffin, S.L., Wells, M.T., & Blake, G.T. (1988). Strenuous exercise causes systemic endotoxemia. Journal of Applied Physiology, 65(1), 106–108. https://doi.org/10.1152/jappl.1988.65.1.106
Brock-Utne J.G., Gaffin S.L., Wells M.T., Gathiram, P., Sohar, E., James, M.F., Morrell, D.F., & Norman, R.J. (1988). Endotoxemia in exhausted runners after a long-distance race. South African Medical Journal, 73, 533–536.
Camus, G., Nys, M., Poortmans, J.R., Venneman, I., Monfils, T., Deby- Dupont, G., Juchmes-Ferir, A., Deby, C., Lamy, M., & Duchateau, J. (1998). Endotoxemia production of tumor necrosis factor alpha and polymorphonuclear neutrophil activation following strenuous exercise in humans. European Journal of Applied Physiology, 79(1), 62–68. https://doi.org/10.1007/s004210050474
Camus, G., Poortmans J, Nys M, Deby-Dupont, G., Duchateau, J., Deby, C., & Lamy, M. (1997). Mild endotoxaemia and the inflammatory response induced by a marathon race. Clinical Science, 92(4), 415–422. https://doi.org/10.1042/cs0920415
Choi, W., Yeruva, S., & Turner, J.R. (2017). Contributions of intestinal epithelial barriers to health and disease. Experimental Cell Research, 358(1), 71–77. https://doi.org/10.1016/j.yexcr.2017.03.036
Cohen, D.C., Winstanley, A., Engledow, A., Windsor, A.C., & Skipworth, J.R. (2009). Marathon-induced ischemic colitis: Why running is not always good for you. American Journal of Emergency Medicine, 27(2), 255.e5–255.e7. https://doi.org/10.1016/j.ajem.2008.06.033
Costa, K.A., Soares, A.D., Wanner, S.P., Santos, R.D., Fernandes, S.O., Martins, F.S., Coimbra, C.C., & Cardoso, V.N.J. (2014). L-arginine supplementation prevents increases in intestinal permeability and bacterial translocation in male Swiss mice subjected to physical exercise under environmental heat stress. Journal of Nutrition, 144(2), 218–223. https://doi.org/10.3945/jn.113.183186
Costa, R.J.S., Crockford, M.J., Moore, J.P., & Walsh, N.P. (2014). Heat acclimation responses of an ultra-endurance running group preparing for hot desert based competition. European Journal of Sports Science, 14(S1), S131–S141. https://doi.org/10.1080/17461391.2012.660506
Costa, R.J.S., Gaskell, S.K., McCubbin, A.J., & Snipe, R.M.J. (2020). Exertional-heat stress associated gastrointestinal perturbations- management strategies for athletes preparing for and competing in the 2020 Tokyo Olympic Games. Temperature, 7(1), 58–88. https://doi.org/10.1080/23328940.2019.1597676
Costa, R.J.S., Gill, S.K., Snipe, R.M.J., Gaskell, S.K., Russo, I., & Burke, L.M. (2022). Assessment of exercise-associated gastrointestinal perturbations in research and practical settings: Methodological concerns and recommendations for better practice. International Journal of Sport Nutrition and Exercise Metabolism, 32(5), 387–418. https://doi.org/10.1123/ijsnem.2022-0048
Costa, R.J.S., Miall, A., Khoo, A., Rauch, C., Snipe, R., Camões-Costa, V., & Gibson, P. (2017). Gut-training: The impact of two weeks repetitive gut-challenge during exercise on gastrointestinal status, glucose availability, fuel kinetics, and running performance. Applied Physiology Nutrition and Metabolism, 42(5), 547–557. https://doi.org/10.1139/apnm-2016-0453
Costa, R.J.S., Snipe, R.M.J., Kitic, C., & Gibson, P. (2017). Systematic review: Exercise-induced gastrointestinal syndrome- Implication for health and disease. Alimentary Pharmacology and Therapeutics, 46(3), 246–265. https://doi.org/10.1111/apt.14157
Cruz, A.S., Mendes-Frias, A., Oliveira, A.I., Dias, L., Matos, A.R., Carvalho, A., Capela, C., Pedrosa, J., Castro, A.G., & Silvestres, R. (2021). Interleukin-6 Is a biomarker for the development of fatal severe acute respiratory syndrome Coronavirus 2 pneumonia. Frontiers in Immunology, 12, Article 613422. https://doi.org/10.3389/fimmu.2021.613422
Donoghue, A. (2004). Heat illness in the U.S. mining industry. American Journal of Industrial Medicine, 45(4), 351–356. https://doi.org/10.1002/ajim.10345
Funnell, M.P., Juett, L.A., Reynolds, K.M., Johnson, D.A., James, R.M., Mears, S.A., Cheuvront, S.N., Kenefick, R.W., & James, L.J. (2023). Iterative assessment of a sports rehydration beverage containing a novel amino acid formula on water uptake kinetics [abstract]. Medicine & Science in Sports & Exercise. Advance online publication.
Gaskell, S.K., Burgell, R., Wiklendt, L., Dinning, P., & Costa, R.J.S. (2022). Does exertional heat stress impact gastrointestinal function and symptoms? Journal of Science and Medicine in Sport, 25(12), 960–967. https://doi.org/10.1016/j.jsams.2022.10.008
Gaskell, S.K., Rauch, C.E., & Costa, R.J.S. (2021). Gastrointestinal assessment and therapeutic intervention for the management of exercise-associated gastrointestinal symptoms: A case series translational and professional practice approach. Frontiers in Physiology, 12, Article 719142. https://doi.org/10.3389/fphys.2021.719142
Gaskell, S.K., Snipe, R.M.J., & Costa, R.J.S. (2019). Test re-test reliability of a modified visual analogue scale assessment tool for determining incidence and severity of gastrointestinal symptom in response to exercise stress. International Journal of Sports Nutrition and Exercise Metabolism, 29(4), 411–419. https://doi.org/10.1123/ijsnem.2018-0215
Gaskell, S.K., Taylor, B., Muir, J., & Costa, R.J.S. (2020). Impact of 24-hour low and high fermentable oligo- di- mono- saccharide polyol diets on markers of exercise-induced gastrointestinal syndrome in response to exertional-heat stress. Applied Physiology Nutrition and Metabolism, 45(6), 569–580. https://doi.org/10.1139/apnm-2019-0187
Gentile, L.F., Cuenca, A.G., Vanzant, E.L., Efron, P.A., McKinley, B., Moore, F., & Moldawer, L.L. (2013). Is there value in plasma cytokine measurements in patients with severe trauma and sepsis? Methods, 61(1), 3–9. https://doi.org/10.1016/j.ymeth.2013.04.024
Gill, S.K., Hankey, J., Wright, A., Marczak, S., Hemming, K., Allerton, D.M., Ansley-Robson, P., & Costa, R.J.S. (2015). The impact of a 24- hour ultra-marathon on circulatory endotoxin and cytokine profile. International Journal of Sports Medicine, 36(8), 688–695. https://doi.org/10.1055/s-0034-1398535
Gill, S.K., Teixeira, A., Rama, L., Rosado, F., Hankey, J., Scheer, V., Hemmings, K., Ansley-Robson, P., & Costa, R.J.S. (2015). Circulatory endotoxin concentration and cytokine profile in response to exertional-heat stress during a multi-stage ultra-marathon competition. Exercise Immunology Reviews, 21, 114–128.
Gupta, R., Yin, L., Grosche, A., Lin, S., Xu, X., Guo, J., Vaught, L.A., Okunieff, P.G., & Vidyasagar, S. (2020). An amino acid-based oral rehydration solution regulates radiation-induced intestinal barrier disruption in mice. Journal of Nutrition, 150(5), 1100–1108. https://doi.org/10.1093/jn/nxaa025
Hodgin, K.E., & Moss, M. (2008). The epidemiology of sepsis. Current Pharmaceutical Design, 14(19), 1833–1839. https://doi.org/10.2174/138161208784980590
Hunt, A., Parker, A., & Stewart, I. (2013). Symptoms of heat illness in surface mine workers. International Archives of Occupational and Environmental Health, 86(5), 519–527. https://doi.org/10.1007/s00420-012-0786-0
Jonvik, K.L., Lenaerts, K., Smeets, J.S.J., Kolkman, J.J., van Loon, L.J.C., & Verdijk, L.B. (2019). Sucrose but not nitrate ingestion reduces strenuous cycling-induced intestinal injury. Medicine & Science in Sports & Exercise, 51(3), 436–444. https://doi.org/10.1249/MSS.0000000000001800
King, M.A., Dineen, S., Ward, J., Mayer, T., Plamper, M., Grosche, A., Xu, X.D., Sasidharan, A., Ward, M., Clanton, T., Vidyasagar, S., & Leon, L. (2019). Amino acid‐based oral rehydration solution mitigates exertional heat stroke severity but does not alter the innate immune response. The FASEB Journal, 33, Article 838.1.
Laitano, O., Leon, L.R., Roberts, W.O., & Sawka, M.N. (2019). Controversies in exertional heat stroke diagnosis, prevention, and treatment. Journal of Applied Physiology, 127(5), 1338–1348. https://doi.org/10.1152/japplphysiol.00452.2019
Lambert, G.P., Broussard, L.J., Mason, B.L., Mauermann, W.J., & Gisolfi, C.V. (2001). Gastrointestinal permeability during exercise: Effects of aspirin and energy-containing beverages. Journal of Applied Physiology, 90(6), 2075–2080. https://doi.org/10.1152/jappl.2001.90.6.2075
Li, L., Li, J., Goa, M., Fan, H., Wang, Y., Xu, X., Chen, C., Lui, J., Kim, J., Aliyari, R., Zhang, J., Jin, Y., Li, X., Ma, F., Shi, M., Cheng, G., & Yang, H. (2021). Interleukin-8 as a biomarker for disease prognosis of coronavirus disease-2019 patients. Frontiers in Immunology, 11, Article 602395. https://doi.org/10.3389/fimmu.2020.602395
Matheson, P.J., Wilson, M.A., & Garrison, R.N. (2000). Regulation of intestinal blood flow. Journal of Surgery Research, 93(1), 182–196. https://doi.org/10.1006/jsre.2000.5862
Mendieta, D., del la Cruz-Aguilera, D.L., Barrera-Villalpando, M.I., Becerril-Villanueva, E., Arreola, R., Hernández-Ferreira, E., Pérez-Tapia, S.M., Pérez-Sánchez, G., Garcés-Alvarez, M.E., Aguirre-Cruz, L., Velasco-Velázquez, M.A., & Pavón, L. (2016). IL-8 and IL-6 primarily mediate the inflammatory response in fibromyalgia patients. Journal of Neuroimmunology, 290, 22–25. https://doi.org/10.1016/j.jneuroim.2015.11.011
Miall, A., Khoo, A., Rauch, C., Snipe, R., Camões-Costa, V., Gibson, P., Costa, R.J.S. (2018). Two weeks of repetitive gut-challenge reduces exercise associated gastrointestinal symptoms and malabsorption. Scandinavian Journal of Medicine and Science in Sports, 28(2), 630–640.
Nag, P., Nag, A., Ashtekar, S. (2007). Thermal limits of men in moderate to heavy work in tropical farming. Industrial Health, 45(1), 107–117. https://doi.org/10.2486/indhealth.45.107
Peake, J.M., Della Gatta, P., Suzuki, K., & Nieman, D.C. (2015). Cytokine expression and secretion by skeletal muscle cells: Regulatory mechanisms and exercise effects. Exercise Immunology Review, 21, 8–25.
Pugh, J.N., Sage, S., Hutson, M., Doran, D.A., Fleming, S.C., Highton, J., Morton, J.P., & Close, G.L. (2017). Glutamine supplementation reduces markers of intestinal permeability during running in the heat in a dose-dependent manner. European Journal of Applied Physiology, 117(12), 2569–2577. https://doi.org/10.1007/s00421-017-3744-4
Rav-Acha, M., Hadad, E., Epstein, Y., Heled, Y., & Moran, D.S. (2004). Fatal exertional heat stroke: A case series. American Journal of the Medical Sciences, 328, 2, 84–87. https://doi.org/10.1097/00000441-200408000-00003
Roberts, W.O., Armstrong, L.E., Sawka, M.N., Yeargin, S.W., Heled, Y., & O’Connor, F.G. (2021). ACSM expert consensus statement on exertional heat illness: Recognition, management, and return to activity. Current Sports Medicine Reports, 20(9), 470–484. https://doi.org/10.1249/JSR.0000000000000878
Russo, I., Della Gatta, P.A., Garnham, A., Porter, J., Burke, L.M., & Costa, R.J.S. (2021a). Assessing overall exercise recovery processes using carbohydrate and carbohydrate-protein containing recovery beverages. Frontiers in Physiology, 12, Article 628863. https://doi.org/10.3389/fphys.2021.628863
Russo, I., Della Gatta, P.A., Garnham, A., Porter, J., Burke, L.M., & Costa, R.J.S. (2021b). Does the nutritional composition of a dairy-based recovery beverage influence post-exercise gastrointestinal and immune status, and subsequent markers of recovery optimisation in response to high intensity interval exercise? Frontiers in Nutrition, 7, Article 622270. https://doi.org/10.3389/fnut.2020.622270
Scrivin, R., Costa, R.J.S., Pelly, F., Lis, D., & Slater, G. (2022). An exploratory study of the management strategies reported by endurance athletes with exercise-associated gastrointestinal symptoms. Frontiers in Nutrition, 9, Article 1003445. https://doi.org/10.3389/fnut.2022.1003445
Snipe, R.M.J., & Costa, R.J.S. (2018). Does the temperature of water ingested during exertional-heat stress influence gastrointestinal injury, symptoms, and systemic inflammatory profile? Journal of Science and Medicine in Sport, 21(8), 771–776. https://doi.org/10.1016/j.jsams.2017.12.014
Snipe, R.M.J., Khoo, A., Kitic, C., Gibson, P., & Costa, R.J.S. (2017). Carbohydrate and protein intake during exertional-heat stress ameliorates intestinal epithelial injury and small intestine permeability. Applied Physiology Nutrition and Metabolism, 42(12), 1283–1292. https://doi.org/10.1139/apnm-2017-0361
Snipe, R.M.J., Khoo, A., Kitic, C., Gibson, P., & Costa, R.J.S. (2018a). Heat stress during prolonged running results in exacerbated intestinal epithelial injury and gastrointestinal symptoms. European Journal of Applied Physiology, 118(2), 389–400. https://doi.org/10.1007/s00421-017-3781-z
Snipe, R.M.J., Khoo, A., Kitic, C., Gibson, P., & Costa, R.J.S. (2018b). Mild Heat stress during prolonged running results in exacerbated intestinal epithelial injury and gastrointestinal symptoms. International Journal of Sports Medicine, 39(4), 255–263.
Suzuki, K., Nakaji, S., Yamada, M., Totsuka, M., Sato, K., & Sugawara, K. (2002). Systemic inflammatory response to exhaustive exercise. Cytokine kinetics. Exercise Immunology Review, 8, 6–48.
Tataka, Y., Haramura, M., Hamada, Y., Ono, M., Toyoda, S., Yamada, T., Hiratsu, A., Suzuki, K., & Miyashita, M. (2022). Effects of oral cystine and glutamine on exercise-induced changes in gastrointestinal permeability and damage markers in young men. European Journal of Nutrition, 61(5), 2331–2339.
Treskes, N., Persoon, A.M., & Zanten, A.R.H. (2017). Diagnostic accuracy of novel serological biomarkers to detect acute mesenteric ischemia: A systematic review and meta-analysis. Internal and Emergency Medicine, 12(6), 821–836. https://doi.org/10.1007/s11739-017-1668-y
Van Wijck, K., Wijnands, K.A.P., Meesters, D.M., Boonen, B., van Loon, L.J.C., Buurman, W.A., Dejong, C.H.C., Lenaerts, K., & Poeze, M. (2014). L-citrulline improves splanchnic perfusion and reduces gut injury during exercise. Medicine & Science in Sports & Exercise, 46(11), 2039–2046. https://doi.org/10.1249/MSS.0000000000000332
Wang, B., Wu, G., Zhou, Z., Dai, Z., Sun, Y., Ji, Y., Li, W., Wang, W., Liu, C., Han, F., & Wu, Z. (2014). Glutamine and intestinal barrier function. Amino Acids, 47(10), 2143–2154. https://doi.org/10.1007/s00726-014-1773-4
Xiao, H., Zha, C., Shao, F., Wang, L., & Tan, B. (2020). Amino acids regulate energy utilization through mammalian target of rapamycin complex 1 and adenosine monophosphate activated protein kinase pathway in porcine enterocytes. Animal Nutrition, 6(1), 98–106. https://doi.org/10.1016/j.aninu.2019.12.001
Yin, L., Gupta, R., Vaught, L., Grosche, A., Okunieff, P., & Vidyasagar, S. (2016). An amino acid-based oral rehydration solution (AA-ORS) enhanced intestinal epithelial proliferation in mice exposed to radiation. Scientific Reports, 6(1), Article 37220. https://doi.org/10.1038/srep37220
Yin, L., Vijaygopal, P., Menon, R., Vaught, L.A., Zhang, M., Zhang, L., Okunieff, P., & Vidyasagar, S. (2014). An amino acid mixture mitigates radiation-induced gastrointestinal toxicity. Health Physics, 106(6), 734–744. https://doi.org/10.1097/HP.0000000000000117
Young, P., Rauch, C.E., Russo, I., Gaskell, S.K., Davidson, Z.E., & Costa, R.J.S. (2022). Plasma endogenous endotoxin core antibody (EndoCAb) response to exertional and exertional-heat stress: Controlled-laboratory experimental exploration. International Journal of Sports Medicine, 43(12), 1023–1032. https://doi.org/10.1055/a-1827-3124
Young, P., Russo, I, Gill, P., Muir, J., Henry, R., Davidson, Z., & Costa, R.J.S. (2023). Reliability of pathophysiological markers reflective of exercise-induced gastrointestinal syndrome (EIGS) in response to 2-h high-intensity interval exercise: A comprehensive methodological efficacy exploration. Frontiers in Physiology, 14, 1–22. https://doi.org/10.3389/fphys.2023.1063335
