Document Detail

Acute metabolic responses to a 24-h ultra-marathon race in male amateur runners.
Jump to Full Text
MedLine Citation:
PMID:  21879351     Owner:  NLM     Status:  MEDLINE    
The study was conducted to evaluate the metabolic responses to a 24 h ultra-endurance race in male runners. Paired venous and capillary blood samples from 14 athletes (mean age 43.0 ± 10.8 years, body weight 64.3 ± 7.2 kg, VO(2max) 57.8 ± 6.1 ml kg(-1) min(-1)), taken 3 h before the run, after completing the marathon distance (42.195 km), after 12 h, and at the finish of the race, were analyzed for blood morphology, acid-base balance and electrolytes, lipid profile, interleukin-6 (IL-6), high-sensitivity C-reactive protein (hsCRP), and serum enzyme activities. Mean distance covered during the race was 168.5 ± 23.1 km (range 125.2-218.5 km). Prolonged ultra-endurance exercise triggered immune and inflammatory responses, as evidenced by a twofold increase in total leukocyte count with neutrophils and monocytes as main contributors, nearly 30-fold increase in serum IL-6 and over 20-fold rise in hsCRP. A progressive exponential increase in mean creatine kinase activity up to the level 70-fold higher than the respective pre-race value, a several fold rise in serum activities of aspartate aminotransferase and alanine aminotransferase, and a fairly stable serum γ-glutamyl transferase level, were indicative of muscle, but not of liver damage. With duration of exercise, there was a progressive development of hyperventilation-induced hypocapnic alkalosis, and a marked alteration in substrate utilization towards fat oxidation to maintain blood glucose homeostasis. The results of this study may imply that progressive decline in partial CO(2) pressure (hypocapnia) that develops during prolonged exercise may contribute to increased interleukin-6 production.
Zbigniew Waśkiewicz; Barbara Kłapcińska; Ewa Sadowska-Krępa; Milosz Czuba; Katarzyna Kempa; Elżbieta Kimsa; Dagmara Gerasimuk
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2011-08-31
Journal Detail:
Title:  European journal of applied physiology     Volume:  112     ISSN:  1439-6327     ISO Abbreviation:  Eur. J. Appl. Physiol.     Publication Date:  2012 May 
Date Detail:
Created Date:  2012-04-24     Completed Date:  2013-05-01     Revised Date:  2013-06-27    
Medline Journal Info:
Nlm Unique ID:  100954790     Medline TA:  Eur J Appl Physiol     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  1679-88     Citation Subset:  IM    
Department of Physiological and Medical Sciences, Academy of Physical Education, Katowice, Poland.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Acid-Base Equilibrium
Biological Markers / blood
C-Reactive Protein / analysis
Electrolytes / blood
Enzyme Assays
Interleukin-6 / blood
Lipids / blood
Muscle, Skeletal / metabolism,  physiology*
Physical Endurance / physiology*
Running / physiology*
Reg. No./Substance:
0/Biological Markers; 0/Electrolytes; 0/Interleukin-6; 0/Lipids; 9007-41-4/C-Reactive Protein

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Full Text
Journal Information
Journal ID (nlm-ta): Eur J Appl Physiol
Journal ID (iso-abbrev): Eur. J. Appl. Physiol
ISSN: 1439-6319
ISSN: 1439-6327
Publisher: Springer-Verlag, Berlin/Heidelberg
Article Information
Download PDF
© The Author(s) 2011
Received Day: 24 Month: 5 Year: 2011
Accepted Day: 16 Month: 8 Year: 2011
Electronic publication date: Day: 31 Month: 8 Year: 2011
pmc-release publication date: Day: 31 Month: 8 Year: 2011
Print publication date: Month: 5 Year: 2012
Volume: 112 Issue: 5
First Page: 1679 Last Page: 1688
ID: 3324692
PubMed Id: 21879351
Publisher Id: 2135
DOI: 10.1007/s00421-011-2135-5

Acute metabolic responses to a 24-h ultra-marathon race in male amateur runners
Zbigniew WaśkiewiczAff1
Barbara KłapcińskaAff1 Address: +48-32-2075170 +48-32-2516868
Ewa Sadowska-KrępaAff1
Milosz CzubaAff1
Katarzyna KempaAff1
Elżbieta KimsaAff1
Dagmara GerasimukAff1
Department of Physiological and Medical Sciences, Academy of Physical Education, Katowice, Poland
Communicated by footnote: Communicated by Susan A. Ward.


As ultra-endurance events have become increasingly popular, many athletes compete in single day races lasting 4 up to 24 h, or in multi-stage races performed over several days. Competing in ultra-endurance events imposes a severe metabolic stress and provokes acute cardio-respiratory responses to ensure adequate oxygen supply to the body. High level of physical demand during these events induces a wide range of metabolic changes, causes micro-injuries to the muscles and other tissues, which increases migration of white blood cells to the sites of injury, and induces acute phase inflammatory reactions (Kim et al. 2007; Tidball 2005; Bessa et al. 2008). Local response to tissue injury involves the production of a large number of acute phase proteins and cytokines. Among the latter, the muscle-derived interleukin-6 is considered important modulator of the immunological and metabolic responses to exercise (Fischer 2006; Pedersen and Febbraio 2008). Most studies on the metabolic responses to prolonged endurance effort have evaluated changes taking place immediately post-exercise and during the recovery period (Wu et al. 2004; Suzuki et al. 2003, 2006; Castell et al. 1997; Kratz et al. 2002), while only few reports focused on changes induced during ultra-endurance events (Kim et al. 2007, 2009; Wallberg et al. 2011), and very little attention has been devoted to arterial blood gas and [H+] homeostasis during endurance exercise performed under competitive conditions in the field (Hanson et al. 1982). The aim of the present study was to evaluate complex metabolic responses that develop during a competitive 24-h ultra-marathon run in male amateur endurance-trained runners. A special focus was put on the changes in serum interleukin-6 and its role in modulating the acute metabolic responses to prolonged, endurance exercise.


Fourteen male amateur runners (mean age 43.0 ± 10.8 years, body weight 64.3 ± 7.2 kg, height 171 ± 5 cm, percent body fat 13.9 ± 3.8%, weekly covered distance 81 ± 43 km, training history 8 ± 9 years) registered for a 24-h ultra-marathon, who volunteered to provide blood samples during the race, were enrolled for the study. Before the start of the race, after assessment of body composition by the bioimpedance method (InBody220, Biospace), the runners completed a questionnaire on their medical and training history, and signed their consent to participate in the study after being informed about the experimental procedures approved by the local ethics committee, in accordance with the Declaration of Helsinki. The runners competed on a 3,014 m long oval recreational walking trail located outside the town. Environmental conditions at the race start at 8 PM were 11°C and 67% relative humidity (RH), at 8 AM and 12 AM next day were 11°C (71% RH) and 15°C (55% RH), respectively, and at the completion of the race at 8:00 PM were 15°C (55% RH). The runners were allowed free access to food and liquids, but the actual food intakes were not recorded, which is a limitation of this study. Liquids consisted mainly of water, sport beverages, soft drinks and broth, while food supplements included sandwiches, cookies, bananas, and carbohydrate energy bars. Some days after the race, all competitors reported to the physical testing laboratory for an incremental running test on a treadmill (LE 200, Jaeger) to assess anaerobic threshold and peak oxygen uptake (VO2max) using a stationary breath-by-breath metabolic unit (MetaLyzer 3B-R2, Cortex). Performance characteristics of the runners are presented in Table 1.

Blood sampling and biochemical analyses

Samples of venous and fingertip capillary blood simultaneously collected 3 h before the race, after completing the marathon distance (42.195 km), after 12 h, and not later than 10 min after the race, were immediately transported to a clinical laboratory for biochemical analyses including blood morphology, blood gases and electrolytes, lipid profile, C-reactive protein (hsCRP), and selected serum enzyme activities. Blood morphology was assessed in venous blood samples (anti-coagulated with EDTA) on an Automated Hematology Analyzer XS-1000i™ (Sysmex), while measurements of blood gases, electrolytes, lactate and glucose in fingertip capillary blood were performed on the GEM Premier 3000 with IQM (Instrumentation Laboratory). Serum activities of creatine kinase (CK), aspartate aminotransferase (AST), alanine aminotransferase (ALT) and γ-glutamyl transferase (GGT), as well as serum concentrations of total cholesterol (TC), HDL-cholesterol, LDL-cholesterol, and triglycerides (TG) were measured using the clinical chemistry analyzer SYNCHRON CX 9 PRO (Beckman-Coulter). The intra-assay coefficients of variation (CV) for these assays were 5.8, 6.70, 5.30, 5.60% and 3.50, 6.10, 4.50%, respectively. hsCRP was assessed in serum by a turbidimetric immunoassay using a Dade-Behring (Marburg, Germany) kit (intra assay CV 3.45%). Total serum concentration of interleukin-6 (IL-6) was determined using quantitative Human High Sensitivity ELISA kit (Gen-Probe Diaclone SAS, France) (sensitivity <0.81 pg/ml, intra assay CV 4.4%). Serum free fatty acids (FFA), glycerol and β-hydroxybutyrate contents were assessed using commercially available manual test kits NEFA, Glycerol (GLY) and RANBUT (CV: 2.7, 1.34, 4.71%, respectively) from Randox Laboratories (Antrim, UK). To estimate the risk of coronary artery disease (CAD) in the ultra-marathoners, we calculated the lipid ratios (TC/HDL, LDL/HDL, TG/HDL) and plasma atherogenic index [atherogenic index of plasma (AIP) = log10(TG/HDL)] (Dobiášová and Frohlich 2001).


Data are presented as the mean (SD). The data were tested for homogeneity of variances by using the Levene test and then analyzed either by the nonparametric Wilcoxon test or by one-way repeated measures ANOVA followed, where appropriate, by the Tukey post-hoc test. Spearman’s rank order correlation analysis was used to assess relationships between selected variables. The level of significance of P < 0.05 was chosen for all statistical comparisons.

Ultra-marathon performance and physiological profile of the competitors

The running performance data of the competitors are presented in Table 2. The highest running velocity was attained at the first stage of the race, i.e. over the marathon (42.195 km) distance, then it decreased markedly to reach a significantly lower level both over the mid-race and over the whole distance covered. There were marked differences in individual race performance measures; however, running velocity was not significantly related to age, body mass, BMI, or lean body mass (LBM). Noteworthy, running velocity appeared to be positively correlated with individual anaerobic threshold IAT (R = 0.40, P < 0.01), VO2max (R = 0.33, P < 0.05) and with peak oxygen uptake expressed in relation to (body mass)0.75 (R = 0.38, P < 0.05), which is considered a more reliable measure of oxygen uptake when comparing individuals with different body mass (Bergh et al. 1991). The mean values of VO2max recorded in our younger (<40 years, N = 6) and older (>40 years, N = 8) runners during a progressive treadmill running test, which equaled 59.8 ± 6.7 and 56.3 ± 5.4 mlO2/kg/min, respectively, were comparable to those reported by Wilmore and Costill (2005) for younger (18–39 years) or older (40–60 years) endurance-trained runners (60–85 and 40–60 ml/kg/min, respectively). The importance of a high VO2max for performance in ultra-marathon events (Kreider 1991; Joyner and Coyle 2008; Millet et al. 2011) was additionally supported by our finding of significant correlations between VO2max or IAT and running velocity (see above) or distance covered during the race (R = 0.57, P < 0.05 or R = 0.74, P < 0.005, respectively), which proves that the higher is VO2max and anaerobic threshold, the easier is to run at a given submaximal velocity in long-distance events (Noakes et al. 1990). Although a high VO2max would contribute greatly to performance in endurance events at the highest level, other markers such as lactate threshold (LT) and running velocity at lactate threshold (vLT) are considered to be more predictive. The mean values for IAT, lactate threshold expressed as %VO2max and vLT tended to be higher in younger compared to older runners (51 vs. 45 ml/kg/min; 85 vs. 80%, and 13.5 vs. 12.0 km/h, respectively), but in all cases they were comparable to those achieved by well-trained athletes (Wilmore and Costill 2005). Notably, compared to the mean running velocity at the anaerobic threshold (13.1 ± 0.9 km/h), which has been assessed during graded treadmill running test, expressed as a percent of maximal oxygen uptake equal, on average, 84.2 ± 4.0 %VO2max (Table 1), the average speed sustained over the first 12 h or the whole 24 h race, corresponded to 51 or 40% VO2max, which is comparable to that (40% VO2max) found by Millet et al. (2011).

Biochemical data

Capillary blood gases and acid–base balance indices were within the normal ranges at rest, but they changed significantly with the progress of the race. A progressive respiratory alkalosis contributed to a mean increase in pH of 0.067 units from rest to the end of the competition, coincident with significant hypocapnia resulting from a 23% decrease in pCO2 (Table 3). This was accompanied by a progressive increases in pO2 of about 11 mmHg, oxygen saturation and plasma potassium, and a tendency towards lower free (ionized) calcium, while plasma sodium concentration remained unchanged (Table 3). It should be stressed that capillary blood gases accurately predict arterial carbon dioxide pressure, and arterial plasma lactate, glucose, pH, hemoglobin and electrolytes, but not arterial oxyhemoglobin saturation and arterial oxygen pressure (Zavorsky et al. 2005). Running the marathon distance led to a marked leukocytosis with significant increases in absolute neutrophil and monocyte counts and decreases in eosinophil count (Table 4). In contrast, no significant changes in any of the basic blood counts from baseline levels were found during the whole competition (Table 4).

Dramatic increases over the baseline values in muscle damage and inflammatory markers were observed (Table 5). Notably, serum activity of CK increased by 70 times, of AST—by 14 times, of ALT—by 4 times, while hsCRP level was over 20-fold and IL-6 concentration—30-fold higher at the finish than at the start of the race. In contrast, serum GGT activity and blood concentrations of lactate and glucose remained fairly stable (Table 5).

The ultra-endurance race was also associated with marked changes in circulating levels of FFA, β-hydroxybutyrate, glycerol, and TG (Table 6). This was accompanied by significant declines in serum total and LDL cholesterol levels and a significant increase in serum HDL cholesterol. Lipid ratios (LDL/HDL, TC/HDL, and TG/HDL), as well as AIP were significantly reduced post-race. In order to assess the impact of the ultra-endurance race on selected biochemical parameters, and on muscle damage and inflammatory markers, the Spearman rank correlation coefficients were calculated; selected statistically significant associations are shown in Table 7.


The present investigation used 24 h foot race to study metabolic responses during prolonged submaximal exercise. The current study confirmed previous findings that continuous, prolonged, moderate-intensity running exercise is associated with severe muscle damage, markedly elevated IL-6 and hsCRP concentrations, and favorable changes in serum lipid profile. The results of this study may imply that hyperventilation-induced respiratory alkalosis with a progressive hypocapnia might contribute, at least to some extent, to increased IL-6 cytokine production.

Metabolic responses to the 24 h race

The extreme caloric demand during ultra-endurance competition requires an adequate supply of metabolic fuels (Kreider 1991; Zaryski et al. 2005). Because carbohydrate stores in the body are limited, the long-duration muscle activity raises the need for carbohydrates not only as an energy source for muscles, but also for their role both in the rapid metabolizing of fats for energy and in providing glucose for normal functioning of the central nervous. Therefore, the adequate supply of carbohydrates is considered crucial for endurance athletes. Since the runners in the present study had free access to food during the entire event, no significant changes in blood glucose concentration were found, which implies adequate carbohydrate supply during the competition. On the other hand, it could be easily predicted that the ultra-endurance race will have a major impact on fat metabolism, and in particular will enhance fat oxidation (Helge et al. 2007; Jeukendrup et al. 1998). Since the athletes were not fed with large amount of lipids, our findings of a more than 50% decrease in serum triacylglycerols, associated with significant, almost threefold increases in circulating FFA, glycerol and β-hydroxybutyrate, reflect the use of fatty acids as fuels. These results support the view that marathon runners compared with normal individuals have a higher fat turnover rate at submaximal exercise intensities (Sjödin and Svedenhag 1985). It is worth to note that the decrease in TG was associated with significant decline in total and LDL cholesterol and a significant rise in HDL cholesterol. Moreover, highly significant negative correlations between the distance covered during the race and several lipid profile indices (serum TG, cholesterol total, LDL and HDL) strongly support the view of the beneficial effect of endurance effort on serum lipid profile. It should be stressed that not only concentrations of TG, total cholesterol and its fractions as the independent risk factors, but also the common cholesterol ratios (TC/HDL, LDL/HDL, and TG/HDL), which are considered better predictors of future coronary heart disease (Natarajan et al. 2003; Kinosian et al. 1994; Grover et al. 1999) were already relatively low at the start of the race, and reached the lowest levels at the finish. As expected, total and LDL-cholesterol were significantly positively related with age in the participating runners. Comparable changes in the lipid profile after prolonged exercise, suggesting reduction in cardiovascular disease (CVD) risk, were also observed by other authors (Gastmann et al. 1998; Ginsburg et al. 1996). We are aware that there are more accurate methods to estimate the risk of CVD and atherosclerosis, e.g. determining lipoprotein(a) level or particle size distribution in LDL (Superko 1996). However, a surrogate method for evaluation of the atherogenicity of plasma lipoproteins based on the assessment of the AIP calculated as log(TG/HDL-C) (with TG and HDL-C expressed in molar concentrations) may also be useful (Dobiášová and Frohlich 2001). The most recent findings from studies in a cohort of adult subjects on the negative correlation between AIP and particle sizes of HDL and LDL support the view that AIP is a reliable predictor of the cardiovascular risk (Dobiášová et al. 2011). It should be stressed, therefore, that negative AIP values, which have been found in a half of the runners at the start of the race and in all of them—at the finish, may indicate a lowered risk of CVD. Taking into account that changes in concentration of small dense LDLs are significantly correlated with changes in TG (Baumstark et al. 1993), it may be postulated that the reduction in pro-atherogenic small dense LDLs induced by prolonged endurance effort would be larger in subjects with larger reductions in serum TG.

Another important aspect of metabolic response to ultra-endurance efforts is the role of IL-6. The concentration of this cytokine correlated positively with serum FFA (R = 0.47, P < 0.005), glycerol (R = 0.42, P < 0.005) and HDL-C (R = 0.63, P < 0.005) levels, and negatively—with serum TG (R = −0.46, P < 0.05). These findings strongly support the view that IL-6 enhances lipid turnover by stimulating lipolysis and fat oxidation (Bruce and Dyck 2004; Petersen and Pedersen 2005), thus it may be considered as one possible mediator of the beneficial effects of physical activity on fatty acid metabolism. Data from the literature provide also a strong evidence that IL-6 is involved in mediating glucose homeostasis during exercise (Petersen and Pedersen 2005), notably that activation of the IL-6 gene during exercise may be sensitive to muscle glycogen content. Low muscle glycogen substantially enhances IL-6 gene transcription and IL-6 protein production in skeletal muscles, whereas carbohydrate ingestion during exercise attenuates increases in plasma IL-6 (Keller et al. 2001; Li and Gleeson 2005). With regard to the results of the present study, one should notice that free access to carbohydrate-rich food during the race did not preclude the possibility that muscle glycogen stores in our runners were depleted, which could activate IL-6 expression. Sustained supply of exogenous sugars allowed the competitors to complete the race with no impairment of glucose homeostasis, although well maintained glucose concentration could blunt the response of serum IL-6 (Li and Gleeson 2005).

Ventilatory and immune responses to ultra-endurance exercise

It is well known that a continuous long-lasting run elicits a ventilatory response. The most distinctive feature of the response is a tachypnea associated with variable degrees of hypocapnia and respiratory alkalosis (Hanson et al. 1982). The hypocapnia develops when a strong respiratory stimulus causes the lungs to remove more carbon dioxide than is produced in metabolically active tissues. Indeed, in the present study a variable degree of hypocapnia and respiratory alkalosis did develop during the race. Alkalosis at the completion of the race was evident in nine subjects, showing above-normal pH values (7.46–7.51) and pCO2 less than 35 mmHg. This was associated with a tendency towards a lowered free ionized calcium concentration. Hyperventilation-induced decreases in plasma concentrations of CO2, [H+] and available calcium, acting as potent vasodilators during exercise, may limit O2 delivery to locomotor skeletal muscle by causing vascular constriction and reducing blood flow (Chin et al. 2007). Of note, we have found in this study that serum IL-6 level correlated negatively with capillary blood pCO2 (R = −0.51, P < 0.001), while it correlated positively with capillary blood pH (R = 0.53, P < 0.0005). These findings may imply that the respiratory-induced hypocapnic alkalosis might, at least to some extent, modulate in vivo production of this cytokine. To our knowledge, there is but a single study providing evidence that CO2 concentrations modulated cytokine levels in endotoxin-stimulated human whole blood cell cultures (Kimura et al. 2008). Notably, those authors found that hypocapnic alkalosis stimulated IL-6 production, whereas the opposite effect, i.e. a reduced IL-6 concentration was observed after hypercapnic acidosis. Given that no detectable amounts of this cytokine were found by those authors in blood samples without endotoxin stimulation, one may presume that the elevated serum IL-6 evidenced during and after the 24 h race in all athletes in our study was, at least partly, due to exercise-induced muscle damage (Suzuki et al. 2006; Nieman 1997) and/or ensuing endotoxemia resulting from increased intestinal permeability (Jeukendrup et al. 2000). This presumption is strongly supported by positive correlations between serum IL-6 level and serum activities of CK (R = 0.65, P < 10−4), AST (R = 0.77, P < 10−4) and ALT (R = 0.79, P < 10−4) that are considered indirect markers of work-induced muscle damage. Abnormally high serum activities of these enzymes are indicative of their leakage from skeletal muscle or other tissues into the bloodstream due to mechanical damage or increased membrane permeability.

Recent research demonstrated that plasma IL-6 increases exponentially with exercise intensity and duration, and the mass of muscle recruited (Pedersen and Febbraio 2005, 2008). However, a fairly stable serum IL-6 concentration evidenced in the present study, as well as a significant correlation between IL-6 and distance covered (R = 0.68, P < 10−5), seem to support most recent finding of Wallberg et al. (2011) that IL-6 does not increase after 12 h of exercise, which suggests that the main determinant of the IL-6 response is the intensity of exercise.

The results of our study demonstrate that running a 24 h ultra-marathon resulted in highly significant increases in serum activities of CK, AST and ALT, emerging in the second half of the race (between 12 and 24 h). Substantial increases in serum activities of AST and ALT following prolonged exercise, and fairly stable serum GGT are indicative of significant skeletal muscle and minor hepatic damage (Noakes 1987;Whitfield 2001; Rosales et al. 2008). In our study, the highest increase was recorded (Table 5) for the mean serum activity of CK that is widely accepted as an indirect marker of muscle damage (Noakes et al. 1983; Kim et al. 2007, 2009; Miles et al. 2008; Brancaccio et al. 2010). However, there were remarkable inter-individual differences in the relative magnitude of the increase, amounting to 27-fold difference between the highest and the lowest response. The reason for this variability is not clear; however, one may suspect that the extreme increases in serum CK activity may be related to the development of exertional rhabdomyolysis (Skenderi et al. 2006).

The body’s response to tissue damage involves mobilization of immune cells and their migration towards sites of the injury (Tidball 2005; Kim et al. 2007; Bessa et al. 2008; Nieman 1997). In the present study, the immune response to muscle damage was characterized by a pronounced, almost twofold increase in total WBC count at the completion of the marathon distance, which persisted until the end of the race. The major components were neutrophils and monocytes, which reached counts almost three times those pre-race. It is known that increases in leukocyte counts during sustained moderate exercise, even in thermally comfortable environment (which was the case in the present study), are related mainly to elevations in plasma catecholamines, which induce a demargination of leukocytes (Brenner et al. 1998). It is well established that the release of leukocytes, and particularly neutrophils and monocytes, is stimulated by inflammatory mediators, such as IL-6 (Suzuki et al. 2003; Nieman 1997). This assumption is corroborated by our finding that IL-6 responses correlated significantly with ultra-endurance exercise-induced increases in total leukocyte (R = 0.56, P < 10−4), absolute neutrophil (R = 0.57, P < 10−4) and monocyte (R = 0.71, P < 10−7) counts, which seems to support the previous findings that IL-6 may mediate recruitment and activation of neutrophils and monocytes in response to exhaustive exercise (Suzuki et al. 2003). However, it is well documented that IL-6 is produced in skeletal muscles also in non-inflammatory conditions, and that muscle contraction per se is a major stimulus for de novo synthesis of IL-6 in myocytes (Hiscock et al. 2004; Pedersen and Febbraio 2008).

One important feature of IL-6 is that it induces the production of hepatocyte-derived CRP (Fischer 2006) that is involved in the induction of anti-inflammatory cytokines in circulating monocytes, in suppression of the synthesis of proinflammatory cytokines in tissue macrophages (Pue et al. 1996) and is responsible for the recognition and removal of damaged cells (Plaisance and Grandjean 2006). In our study, plasma hsCRP concentration during the first 42.195 km distance was fairly stable. Changes in plasma hsCRP content occurred later, i.e. after finishing the marathon distance, when it rose in an exponential pattern to reach, at the finish of a 24 h race, the level more than 20 times higher than the pre-race value. Significant correlation between plasma CRP and IL-6 found in our study (R = 0.51, P < 0.0005) supports the presumption of the role of IL-6 as a primary inducer of hepatic production of acute phase proteins (Fischer 2006).

In summary, the main metabolic responses to the 24-h ultra-marathon race were: (i) a marked shift in substrate utilization towards fat oxidation to maintain blood glucose homeostasis, and (ii) favorable changes in serum lipid profile. The ultra-endurance run led to a substantial skeletal muscle damage and an acute inflammatory response evidenced by a wide range of changes in muscle injury-related indices and dramatic elevations in serum interleukin-6 and hsCRP. These effects were more pronounced during the second half of the race, and the primary determinants of these changes were both the duration and intensity of the exercise. The predominant ventilatory response to the ultra-endurance effort of the 24 h race was a tachypneic, respiratory alkalosis associated with hypocapnia and hyperkalemia, but not hyponatremia. Some results of this study suggest that the elevation in serum IL-6, which likely is due to increased production, might be related to hypocapnia that develops during prolonged endurance exercise. However, the correlation between these phenomena may as well be an indirect, non-causal association related to the effects of prolonged muscle effort on both pCO2 and IL-6.

A preliminary report of this work was presented in the poster session of the 2010 Wingate Congress of Exercise & Sport Sciences at the Wingate Institute, Netanya, Israel. The authors thank all the athletes who volunteered to participate in this study. This study was supported by statutory funding from the Academy of Physical Education, Katowice, Poland.

Conflict of interest

The authors declare no conflicts of interest.

Open Access

This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Baumstark MW,Frey I,Berg A. Acute and delayed effects of prolonged exercise on serum lipoproteins. II. Concentration and composition of low-density lipoprotein subfractions and very low-density lipoproteinsEur J Appl Physiol Occup PhysiolYear: 19936652653010.1007/BF006343048354253
Bergh U,Sjödin B,Forsberg A,Svedenhag J. The relationship between body mass and oxygen uptake during running in humansMed Sci Sports ExercYear: 1991232052112017016
Bessa A,Nissenbaum M,Monteiro A,Gandra PG,Nunes LS,Bassini-Cameron A,Werneck-de-Castro JPS,Macedo D,Cameron LC. High intensity ultraendurance promotes early release of muscle injury markersBr J Sports MedYear: 20084288989310.1136/bjsm.2007.04378618203867
Brancaccio P,Lippi G,Maffulli N. Biochemical markers of muscular damageClin Chem Lab MedYear: 20104875776710.1515/cclm.2010.17920518645
Brenner I,Shek PN,Zamecnik J,Shephard RJ. Stress hormones and the immunological responses to heat and exerciseInt J Sports MedYear: 19981913014310.1055/s-2007-9718959562223
Bruce CR,Dyck DJ. Cytokine regulation of skeletal muscle fatty acid metabolism: effect of interleukin-6 and tumor necrosis factor-αAm J Physiol Endocrinol MetabYear: 2004287E616E62110.1152/ajpendo.00150.200415149950
Castell LM,Poortmans JR,Leclerq R,Brasseur M,Duchateau J,Newsholme EA. Some aspects of the acute phase response after a marathon race, and the effects of glutamine supplementationEur J Appl PhysiolYear: 199775475310.1007/s004210050125
Chin LMK,Leigh RJ,Heigenhauser GJF,Rossiter HB,Paterson DH,Kowalchuk JM. Hyperventilation-induced hypocapnic alkalosis slows the adaptation of pulmonary O2 uptake during the transition to moderate-intensity exerciseJ PhysiolYear: 200758335136410.1113/jphysiol.2007.13283717584832
Dobiášová M,Frohlich J,Šedová M,Cheung MC,Brown BG. Cholesterol esterification and atherogenic index of plasma correlate with lipoprotein size and findings on coronary angiographyJ Lipid ResYear: 20115256657110.1194/jlr.P01166821224290
Dobiášová M,Frohlich J. The plasma parameter log(TG/HDL-C) as an atherogenic index: correlation with lipoprotein particle size and esterification rate in apoB-lipoprotein-depleted plasma (FERHDL)Clin BiochemYear: 20013458358810.1016/S0009-9120(01)00263-611738396
Fischer CP. Interleukin-6 in acute exercise and training: what is the biological relevance?Exerc Immunol RevYear: 20061263317201070
Gastmann U,Dimeo F,Huonker M,Bocker J,Stainacker JM,Petersen KG,Wieland H,Keul J,Lehmann M. Ultra-triathlon-related blood-chemical and endocrinological responses in nine athletesJ Sports Med Phys FitnessYear: 19983818239638027
Ginsburg GS,Agil A,O’Toole M,Rimm E,Douglas PS,Rifai N. Effects of a single bout of ultraendurance exercise on lipid levels and susceptibility of lipids to peroxidation in triathletesJAMAYear: 199627622122510.1001/jama.1996.035400300550328667567
Grover SA,Levington C,Paquet S. Identifying adults at low risk for significant hyperlipidemia: a validated clinical indexJ Clin EpidemiolYear: 199952495510.1016/S0895-4356(98)00139-59973073
Hanson P,Claremont A,Dempsey J,Reddan W. Determinants and consequences of ventilatory responses to competitive endurance runningJ Appl PhysiolYear: 1982526156236802787
Helge JW,Rehrer NJ,Pilegaard H,Manning P,Lucas SJE,Gerrard DF. Increased fat oxidation and regulation of metabolic genes with ultraendurance exerciseActa PhysiolYear: 2007191778610.1111/j.1748-1716.2007.01709.x
Hiscock N,Chan MH,Bisucci T,Darby IA,Febbraio MA. Skeletal myocytes are a source of interleukin-6 mRNA expression and protein release during contraction: evidence of fiber type specificityFASEB JYear: 20041899299415059966
Jeukendrup AE,Saris WHM,Wagenmakers AJM. Fat mobilization during exercise: a review. Part I. Fatty acid mobilization and muscle metabolismInt J Sports MedYear: 19981923124410.1055/s-2007-9719119657362
Jeukendrup AE,Vet-Joop K,Sturk A,Stegen JHJC,Senden J,Saris WHM,Wagenmakers AJM. Relationship between gastro-intestinal complaints and endotoxaemia, cytokine release and the acute-phase reaction during and after long-distance triathlon in highly trained menClin SciYear: 200098475510.1042/CS1999025810600658
Joyner MJ,Coyle EF. Endurance exercise performance: the physiology of championsJ PhysiolYear: 2008586354410.1113/jphysiol.2007.14383417901124
Keller C,Steensberg A,Pilegaard H,Osada T,Saltin B,Pedersen BK,Neufer PD. Transcriptional activation of the IL-6 gene in human contracting muscle: influence of muscle glycogen contentFASEB JYear: 2001152748275011687509
Kim HJ,Lee YH,Kim CK. Biomarkers of muscle and cartilage damage and inflammation during a 200 km runEur J Appl PhysiolYear: 20079944344710.1007/s00421-006-0362-y17206443
Kim HJ,Lee YH,Kim CK. Changes in serum cartilage oligomeric matrix protein (COMP), plasma CPK and plasma hs-CRP In relation to running distance in a Marathon (42.195 km) and an ultra-marathon (200 km) raceEur J Appl PhysiolYear: 200910576577010.1007/s00421-008-0961-x19125286
Kimura D,Totapally BR,Raszynski A,Ramachandran C. The effects of CO2 on cytokine concentrations in endotoxin-stimulated human whole bloodCrit Care MedYear: 2008362823282710.1097/CCM.0b013e318186f55618766096
Kinosian B,Glick H,Garland G. Cholesterol and coronary heart disease: predicting risks by levels and ratiosAnn Intern MedYear: 19941216416477944071
Kratz A,Lewandrowski KB,Siegel AJ,Chun KY,Flood JG,Cott EM,Lee-Lewandrowski E. Effect of marathon running on hematologic and biochemical laboratory parameters, including cardiac markersAm J Clin PatholYear: 200211885686310.1309/14TY-2TDJ-1X0Y-1V6V12472278
Kreider RB. Physiological considerations of ultraendurance performanceInt J Sport NutrYear: 199113271844400
Li TL,Gleeson M. The effects of carbohydrate supplementation during the second of two prolonged cycling bouts on immunoendocrine responsesEur J Appl PhysiolYear: 20059539139910.1007/s00421-005-0024-516195883
Miles MP,Andring JM,Pearson SD,Gordon LK,Kasper C,Depner CM,Kidd JR. Diurnal variation, response to eccentric exercise, and association of inflammatory mediators with muscle damage variableJ Appl PhysiolYear: 200810445145810.1152/japplphysiol.00572.200718079262
Millet GY,Banfi JC,Kerherve H,Morin JB,Vincent L,Estrade C,Geyssant A,Feasson L. Physiological and biological factors associated with a 24 h treadmill ultra-marathon performanceScand J Med Sci SportsYear: 201121546110.1111/j.1600-0838.2009.01001.x19883385
Natarajan S,Glick H,Criqui M,Horowitz D,Lipsitz SR,Kinosian B. Cholesterol measures to identify and treat individuals at risk for coronary heart diseaseAm J Prev MedYear: 200325505710.1016/S0749-3797(03)00092-812818310
Nieman DC. Immune response to heavy exertionJ Appl PhysiolYear: 199782138513949134882
Noakes TD,Kotzenberg G,McArthur PS,Dykman J. Elevated serum creatine kinase MB and creatine kinase BB-isoenzyme fractions after ultra-marathon runningEur J Appl Physiol Occup PhysiolYear: 198352757910.1007/BF004290296686133
Noakes TD,Myburgh KH,Schall R. Peak treadmill running velocity during the VO2max test predicts running performanceJ Sports SciYear: 19908354510.1080/026404190087321292359150
Noakes TD. Effect of exercise on serum enzyme activities in humansSports MedYear: 1987424526710.2165/00007256-198704040-000033306866
Pedersen BK,Febbraio MA. Muscle as an endocrine organ: focus on muscle-derived interleukin-6Physiol RevYear: 2008881379140610.1152/physrev.90100.200718923185
Pedersen BK,Febbraio MA. Muscle-derived interleukin-6—a possible link between skeletal muscle, adipose tissue, and brainBrain Behav ImmunYear: 20051937137610.1016/j.bbi.2005.04.00815935612
Petersen AM,Pedersen BK. The anti-inflammatory effect of exerciseJ Appl PhysiolYear: 2005981154116210.1152/japplphysiol.00164.200415772055
Plaisance EP,Grandjean PW. Physical activity and high-sensitivity C-reactive proteinSports MedYear: 20063644345810.2165/00007256-200636050-0000616646631
Pue CA,Mortensen RF,Marsh CB,Pope HA,Wewers MD. Acute phase levels of C-reactive protein enhance IL-1 beta and IL-1ra production by alveolar macrophagesJ ImmunolYear: 1996156159416008568265
Rosales XQ,Chu ML,Shilling C,Wall C,Pastores GM,Mendell JR. Fidelity of gamma-glutamyl transferase (GGT) in differentiating between skeletal muscle from liver damageJ Child NeurolYear: 20082374875110.1177/088307380831436518354148
Sjödin B,Svedenhag J. Applied physiology of marathon runningSports MedYear: 19852839910.2165/00007256-198502020-000023890068
Skenderi KP,Kavouras SA,Anastasiou CA,Yiannakouris N,Matalas AL. Exertional rhabdomyolysis during a 246-km continuous running raceMed Sci Sports ExercYear: 2006381054105710.1249/01.mss.0000222831.35897.5f16775544
Superko HR. Beyond LDL cholesterol reductionCirculationYear: 199694235123548921770
Suzuki K,Nakaji S,Yamada M,Liu Q,Kurakake S,Okamura N,Kumae T,Umeda T,Sugawara T. Impact of competitive marathon race on systemic cytokine and neutrophil responsesMed Sci Sports ExercYear: 20033534835510.1249/01.MSS.0000048861.57899.0412569227
Suzuki K,Peake J,Nosaka K,Okutsu M,Abbiss CR,Surriano R,Bishop D,Quod MJ,Lee H,Martin DT,Laursen PB. Changes in markers of muscle damage, inflammation and HSP70 after an Ironmean triathlon raceEur J Appl PhysiolYear: 20069852553410.1007/s00421-006-0296-417031693
Tidball JG. Inflammatory processes in muscle injury repairAm J Physiol Regul Integr Comp PhysiolYear: 2005288R345R35310.1152/ajpregu.00454.200415637171
Wallberg L,Mattson CM,Enquist JK,Ekblom B. Plasma IL-6 concentration during ultra-endurance exerciseEur J Appl PhysiolYear: 20111111081108810.1007/s00421-010-1737-721113612
Whitfield JB. Gamma glutamyl transferaseCrit Rev Clin Lab SciYear: 20013826335510.1080/2001409108422711563810
Wilmore JH,Costill DL. Physiology of sport and exerciseYear: 20053ChampaignHuman Kinetics
Wu HJ,Chen KT,Shee BW,Chang HC,Huang YJ,Yang RS. Effects of 24 h ultra-marathon on biochemical and hematological parametersWorld J GastroenterolYear: 200410214271114716825
Zavorsky GS,Lands LC,Schneider W,Carli F. Comparison of fingertip to arterial blood samples at rest and during exerciseClin J Sport MedYear: 20051526327010.1097/01.jsm.0000171287.99174.b716003042
Zaryski C,Kin M,Smith DJ. Training principles and issues for ultra-endurance athletesCurr Sports Med RepYear: 2005416517015907270

[TableWrap ID: Tab1] Table 1 

Performance characteristics of the runners (N = 14)

Variable Mean ± SD Min–Max
VO2max (mL O2/kg/min) 57.8 ± 6.1 49.0–71.0
VO2max (mL O2/kg0.75/min) 164.7 ± 15.5 140.3–195.5
Individual anaerobic threshold (mL O2/kg/min) 48.9 ± 5.1 39.0–57.0
Lactate threshold (%VO2max) 84.2 ± 4.0 77–92
Velocity at lactate threshold (km/h) 13.1 ± 0.9 12–14
VEmax (L/min) 140.1 ± 19.4 117.0–193.4
Peak heart rate HRmax (bpm) 182.1 ± 10.0 165–198
Peak lactate concentration (mmol/L) 8.64 ± 1.91 5.90–11.64

[TableWrap ID: Tab2] Table 2 

Ultra-marathon (24 h) race performance measures

Variable Mean ± SD Median Min–Max
Marathon time (h) 4.6 ± 0.4 4.7 4.1–5.3
Marathon running velocity (km/h) 9.1 ± 0.7 9.0 8.0–10.2
12-h distance ( km) 94.6 ± 11.6 94.0 73.0–109.0
12-h running velocity ( km/h) 7.9 ± 1.0* 7.83 6.1–9.1
24-h distance ( km) 168.5 ± 23.1 165.9 125.2–218.5
24-h running velocity (km/h) 7.0 ± 1.0* 6.9 5.2–9.1

* Significantly different (P < 0.05) from the running velocity achieved at the marathon distance

[TableWrap ID: Tab3] Table 3 

Ultra-marathon-induced changes in acid–base balance indices and concentrations of electrolytes, lactate and glucose

Variable Pre-race Post-marathon Post 12 h Post-24 h
Mean (SD) Min–Max Mean (SD) Min–Max Mean (SD) Min–Max Mean (SD) Min–Max
pH 7.396 (0.028) 7.350–7.430 7.405 (0.025) 7.360–7.450 7.445** (0.029) 7.390–7.510 7.463** (0.026) 7.400 –7.510
pCO2 (mmHg) 42.5 (2.6) 39–48 41.2 (3.5) 37–49 35.6** (3.8) 29–42 32.6** (4.0) 25–39
pO2 (mmHg) 79.2 (10.9) 70–112 74.0 (7.4) 63–88 88.2 (7.2) 77–103 90.1* (13.2) 79–108
Standard bicarbonate (mmol/L) 25.6 (1.3) 23.7–27.4 25.6 (2.1) 22.4–29.4 25.4 (1.7) 22.7–27.7 25.1 (1.4) 23.4–28.0
BE (mmol/L) 1.0 (1.6) −1.5 to  +3.2 1.0 (2.7) −3.1 to +5.9 0.7 (2.2) −2.9 to +3.5 0.2 (1.9) −1.9 to +4.0
O2 saturation (%) 95.3 (1.2) 94–98 94.5 (1.6) 92–97 97.1** (2.6) 96–98 97.1** (1.7) 92–99
Sodium (mmol/L) 141.8 (4.1) 136–152 141.9 (2.5) 139–147 142.4 (2.6) 139–148 140.3 (2.8) 138–148
Potassium (mmol/L) 4.6 (0.4) 3.9–5.1 5.2* (0.6) 4.4–6.1 5.5** (0.5) 5.1–6.7 6.8** (1.1) 5.1–8.5
Ionized Ca (mmol/L) 1.25 (1.04) 1.17–1.42 1.21 (0.06) 1.08–1.31 1.17* (0.05) 1.06–1.23 1.19 (0.05) 1.08–1.26
Lactate (mmol/L) 3.1 (0.7) 2.3–4.4 3.4 (1.0) 2.5–5.6 3.4 (1.0) 2.0–4.9 4.1 (1.0) 2.0–5.9
Glucose (mmol/L) 6.6 (1.0) 5.1–8.9 6.0 (1.0) 5.0–7.7 6.5 (1.1) 4.6–8.5 7.5 (1.9) 5.2–12.0

P < 0.05; ** P < 0.005 versus the corresponding pre-race value

[TableWrap ID: Tab4] Table 4 

Ultra-marathon-induced changes in basic blood counts and circulating leukocytes and leukocyte subpopulations

Variable Pre-race Post-marathon Post 12 h Post-24 h
Mean (SD) Min–Max Mean (SD) Min–Max Mean (SD) Min–Max Mean (SD) Min–Max
Hb (g/dl) 14.2 (1.3) 11.9–16.4 14.6 (1.1) 12.8–16.1 14.4 (1.3) 12.2–16.7 14.3 (1.0) 12.6–16.5
Red cell count (×1012/L) 4.74 (0.32) 4.24–5.22 4.87 (0.23) 4.51–5.23 4.79 (0.28) 4.38–5.29 4.76 (0.20) 4.46–5.27
Hct (%) 41.9 (3.0) 36–47 42.4 (2.2) 39–45 41.6 (2.9) 37–47 41.2 (2.3) 37.0–46.0
MCV (fl) 88.5 (3.1) 82.0–93.9 87.1 (2.7) 81.6–91.3 86.9 (2.8) 80.7–90.4 86.5 (2.7) 81–89.8
MPV (fl) 11.5 (0.6) 10.3–12.6 11.5 (0.8) 10.0–12.9 11.5 (0.7) 10–12.5 11.5 (0.7) 10.3–12.2
Platelets (×109/L) 262.4 (34.2) 215–317 291.9 (56.6) 129–365 289.6 (40.0) 235–364 282.1 (34.4) 227–362
White cell count (×109/L) 7.67 (2.49) 4.4–14.0 14.51** (3.23) 9.5–21.5 13.86** (3.42) 7.7–19.9 14.84** (2.54) 11.3–18.7
Neutrophils (×109/L) 4.30 (2.26) 2.01–10.21 9.93** (3.21) 5.63–17.35 10.45** (3.04) 5.88–16.39 10.40** (2.49) 7.54–14.93
Lymphocytes (×109/L) 2.55 (0.94) 1.51–4.64 3.20 (1.10) 1.75–6.13 1.90 (0.53) 1.08–2.88 2.51 (0.67) 1.33–3.50
Monocytes (×109/L) 0.68 (0.18) 0.42–0.98 1.25* (0.36) 0.68–1.85 1.45** (0.45) 0.69–2,59 1.86** (0.52) 1.25–2.77
Eosinophils (×109/L) 0.11 (0.08) 0.02–0.31 0.09 (0.08) 0.01–0.30 0.01** (0.01) 0.00–0.04 0.02** (0.02) 0.00–0.06
Basophils (×109/L) 0.03 (0.02) 0.01–0.09 0.05 (0.04) 0.01–0.13 0.04 (0.03) 0.01–0.12 0.04 (0.03) 0.01–0.11

* P < 0.005; ** P < 0.0005 versus the corresponding pre-race value

[TableWrap ID: Tab5] Table 5 

Ultra-marathon-induced changes in serum markers of muscle damage and inflammation

Variable Pre-race Post-marathon Post 12 h Post-24 h
Mean (SD) Min–Max Mean (SD) Min–Max Mean (SD) Min–Max Mean (SD) Min–Max
Creatine kinase (U/l) 249.2 (136.1) 96–559 786.9** (821.9) 169.0–3361 4,284.0** (3,544.9) 533–11,653 17,502** (15,040) 922–50,440
Aspartate aminotransferase (U/L) 28.7 (7.7) 19–54 388.5** (295.8) 45–978
Alanine aminotransferase (U/L) 24.1 (6.4) 14–35 84.4** (50.7) 27–179
Gamma glutamyltransferase (U/L) 29.6 (35.1) 12–145 29.6 (34.7) 11.0–143 29.6 (34.5) 13–143 27.9 (31.2) 13–130
hsCRP (mg/dL) 1.7 (2.7) 0.3–10.6 1.7 (2.5) 0.3–10.0 8.7** (4.6) 2.0–20.1 39.2** (16.7) 16.3–79.0
IL-6 (pg/ml) 0.87 (0.68) 0.01–1.91 20.29*** (7.77) 11.99–34.58 27.36*** (7.67) 12.77–36.47 28.49*** (11.99) 16.70–50.25

P < 0.05; ** P < 0.005; *** P < 0.0005 versus the corresponding pre-race value

[TableWrap ID: Tab6] Table 6 

Ultra-marathon-induced changes in serum lipid profile

Variable Pre-race Post-marathon Post 12 h Post-24 h
Mean (SD) Min–Max Mean (SD) Min–Max Mean (SD) Min–Max Mean (SD) Min–Max
Cholesterol (mmol/L) 5.07 (0.72) 3.8–6.4 4.04** (0.84) 2.7–6.1
HDL (mmol/L) 1.43 (0.30) 1.0–2.0 2.01** (0.32) 1.3–2.6
LDL (mmol/L) 2.86 (0.76) 1.71–4.21 1.74** (0.73) 0.70–3.70
Triglycerides (mmol/L) 1.73 (1.22) 0.2–5.1 0.80* (0.13) 0.56–0.98
Free fatty acids (mmol/L) 0.60 (0.24) 0.12–0.96 1.86** (0.96) 1.20–4.43 1.91* (1.25) 0.60–4.0 1.79** (1.06) 0.801–4.591
β-hydroxy-butyrate (mmol/L) 0.17 (0.06) 0.08–0.32 0.38 (0.41) 0.13–1.68 0.36* (0.31) 0.11–1.19 0.58** (0.36) 0.13–1.32
Glycerol (μmol/L) 88.4 (26.7) 27.7–122.6 339.5** (147.3) 110.9–591.7 298.9** (216.3) 73.24–841.2 270.2** (93.3) 133.9–457.8
TC/HDL 3.68 (0.84) 2.24–5.09 2.03** (0.38) 1.48–2.94
LDL/HDL 2.07 (0.63) 1.19–3.06 0.90** (0.40) 0.30–1.76
TG/HDL 1.34 (1.14) 0.12–4.64 0.41* (0.10) 0.27–0.61
AIP [log10(TG/HDL)] –0.01 (0.39) –0.93 to (0.66) –0.40** (0.11) –0.57 to (–0.21)

P < 0.05; ** P < 0.005 versus the corresponding pre-race value

[TableWrap ID: Tab7] Table 7 

Spearman rank correlation coefficients between the distance covered during the 24 h ultra marathon race and selected hematological and biochemical indices

Variables R P
Distance and pH 0.69 <10−6
Distance and pCO2 –0.75 <10−6
Distance and ionized Ca –0.41 <0.005
Distance and K+ 0.80 <10−6
Distance and total WBC count 0.56 <10−5
Distance and neutrophil absolute count 0.60 <10−6
Distance and monocyte absolute count 0.74 <10−6
Distance and eosinophil absolute count –0.64 <10−6
Distance and hsCRP 0.82 <10−6
Distance and IL-6 0.68 <10−5
Distance and CK 0.87 <10−6
Distance and AST 0.82 <10−6
Distance and ALT 0.81 <10−6
Distance and total cholesterol –0.42 <0.05
Distance and LDL-Cholesterol –0.46 <0.05
Distance and HDL-Cholesterol 0.70 <10−4
Distance and TG –0.56 <0.005
Distance and FFA 0.50 <0.0005
Distance and β-hydroxybutyrate 0.46 <0.001
Distance and AIP [log10(TG/HDL)] –0.66 <0.0005

Article Categories:
  • Original Article

Keywords: Keywords Ultra-endurance exercise, Muscle damage, Inflammatory response, Interleukin-6.

Previous Document:  Frowning muscle activity and perception of effort during constant-workload cycling.
Next Document:  Effects of aerobic fitness on oxygen uptake kinetics in heavy intensity swimming.