

Citation: Parshukova, O.I.;
Varlamova, N.G.; Potolitsyna, N.N.;
Lyudinina, A.Y.; Bojko, E.R. Features
of Metabolic Support of Physical
Performance in Highly Trained
Cross-Country Skiers of Different
Qualiﬁcations during Physical
Activity at Maximum Load. Cells
2022, 11, 39. https://doi.org/
10.3390/cells11010039
Academic Editor: Robert Wessells
Received: 1 December 2021
Accepted: 21 December 2021
Published: 23 December 2021
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cells
Article
Features of Metabolic Support of Physical Performance in
Highly Trained Cross-Country Skiers of Different
Qualiﬁcations during Physical Activity at Maximum Load
Olga I. Parshukova *
, Nina G. Varlamova
, Natalya N. Potolitsyna
, Aleksandra Y. Lyudinina
and Evgeny R. Bojko
Institute of Physiology of Komi Science Centre of the Ural Branch of the Russian Academy of Sciences,
FRC Komi SC UB RAS, 50 Pervomayskaya Str., 167982 Syktyvkar, Russia; nivarlam@physiol.komisc.ru (N.G.V.);
potol_nata@list.ru (N.N.P.); salu_06@inbox.ru (A.Y.L.); boiko60@inbox.ru (E.R.B.)
* Correspondence: olga-parshukova@mail.ru
Abstract: The purpose of our study was to identify the features of metabolic regulation in highly
trained cross-country skiers of different qualiﬁcations at different stages of the maximum load
test. We examined 124 highly trained cross-country skiers (male, ages 17–24). The group consisted
of two subgroups based on their competition performance: 61 nonelite athletes (Group I) and
63 elite athletes (group II), who were current members of the national team of the Komi Republic
and Russia. The bicycle ergometer test was performed by using the OxyconPro system (Erich
Jaeger, Hoechberg, Germany). All the examined athletes performed the exercise test on a cycle
ergometer “until exhaustion”. The results of our research indicate that the studied groups of athletes
with high, but different levels of sports qualiﬁcations are a convenient model for studying the
molecular mechanisms of adaptation to physical loads of maximum intensity. Athletes of higher
qualiﬁcations reveal additional adaptive mechanisms of metabolic regulation, which is manifested in
the independence of serum lactate indicators under conditions of submaximal and maximum power
from maximal oxygen uptake, and they have an NO-dependent mechanism for regulating lactate
levels during aerobic exercise, including work at the anaerobic threshold.
Keywords: nitric oxide; lactate; heart rate; oxygen uptake; arterial blood pressure; exercise test on a
cycle ergometer; cross-country skier
1. Introduction
Moderate physical activity has a positive effect on the morphology and work of
the cardiovascular system of athletes due to the manifested adaptive response of the
myocardium [1]. However, at the same time, a violation in the consistency of the functional
state of the system associated with the work of the heart rhythm leads to an overstrain of
the cardiovascular system of athletes [2]. Systematically exercising athletes usually develop
myocardial hypertrophy. Pathological hypertrophy is based on dystrophic changes in
the myocardium and deterioration of the microvasculature, which leads to difﬁculty in
contraction of the left ventricular wall, which ultimately affects the decrease in the athletic
performance of the body [3]. Cross-country skiers have a very high maximal oxygen uptake,
and they are able to perform submaximal exercise at a rather high metabolic rate, and
with cardiac output levels similar to or higher than the cardiac output levels achieved by
untrained humans at maximal exercise [4]. The role of the molecular gas nitric oxide (NO)
in the cardiovascular system is well established, where NO regulates a multitude of cellular
processes. Endothelial cells synthesize and release NO, which mediates diverse effects,
including vessel tone, haemostasis, blood pressure and vasculature remodelling [5]. The
signiﬁcance of NO for cardiomyocyte function is well known because it plays a role in the
regulation of ion channels, Ca2 homeostasis, contractility, energetics, cell growth, and it
has antioxidant effects and prevents endothelial cells from oxidative stress [6].
Cells 2022, 11, 39. https://doi.org/10.3390/cells11010039
https://www.mdpi.com/journal/cells
Cells 2022, 11, 39
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The “gold standard” of cardiorespiratory exercise testing—a test with increasing
load—allows you to determine the maximum oxygen uptake, assess the level of aerobic
capacity of the body and identify the reasons for limiting physical performance [7]. Cur-
rently, there are many protocols for exercise testing. However, at different stages of the test,
there is practically no information about the functional parameters of the cardiorespiratory
system and human biochemical markers, such as heart rate, blood pressure, QRS complex,
QT interval, oxygen uptake, carbon dioxide production, respiratory rate and the levels of
stable nitric oxide metabolites (nitrites, nitrates) and lactate. This signiﬁcantly complicates
the analysis, comparison and prediction of available data. The purpose of our study was
to identify the features of metabolic regulation in highly trained cross-country skiers of
different qualiﬁcations at different stages of testing at physical maximum load.
2. Materials and Methods
2.1. Ethical Approval
The Ethics Committee of the Institute of Physiology of the Russian Academy of
Sciences, Syktyvkar approved the experimental design and protocol of the study. The
study conformed to the Code of Ethics of the World Medical Association (Declaration of
Helsinki). The volunteers were made aware of all the information about the experimental
protocol, experimental procedures, and probable risks and inconvenience associated with
performing the exercise test on a cycle ergometer “until exhaustion”. After the necessary
interpretations, the volunteers gave their written informed agreement to participate in
the test. Participants were aware that they were free to leave the study at any time and
without consequence.
2.2. Participants
The observation group included 124 highly trained cross-country skiers (male, ages 17–24).
The group consisted of two subgroups based on their competition performance: Group I in-
cludes 61 nonelite athletes who occupied the last ten places at official competitions, and Group
II includes 63 elite athletes who occupied the first ten places at official competitions, who were
current members of the national team of the Komi Republic and Russia, had no signs or history
of chronic diseases. All participants had more than 5 years of cross-country skiing practice as
part of their main training schedule and had extensive experience in endurance events.
2.3. Experimental Protocol
The study was performed during the morning after a low-nitrate breakfast. It excluded
foods and drinks that are the main sources of nitrates in human food (meat and ﬁsh
products, vegetables (mainly beets, leafy green vegetables), marinades, (spirits, fruit and
mineral drinks). Additionally, the night before the test all the participants consumed a
standardized meal (1,674,400–1,757,420 kJcal) consisting of (in units of the percentage of
the total energy supplied by the entire meal, En%) 78 En% carbohydrate, 14 En% fat and
8 En% protein. The dietary intake of the participants was assessed using a food frequency
questionnaire. Calories consumed at breakfast were not standardize by body weight. The
height and body weight of the athletes were measured using a medical weight growth
meter (Accunig, SELVAS Healthcare, Daejeon, Korea). At rest (sitting), at the anaerobic
threshold (AT) level, during peak load and during the recovery period (5th minute) in each
of the athletes examined were determined by the following parameters: systolic blood
pressure (SBP), diastolic pressure (DBP), heart rate (HR), Q wave, R wave, and S wave (QRS)
complex, QT interval (QT), oxygen uptake (V’O2), carbon dioxide production (V’CO2),
respiratory rate (Rer), and the levels of stable metabolites of NO and lactate in capillary
blood samples. Blood pressure was measured by the Korotkov method on the right arm
using the Microlife model BRAG-1-30 device (Widnau, Switzerland). An electrocardiogram
(ECG) was recorded in 12 leads: standard according to Einthoven (I, II, III), reinforced from
the extremities according to Goldberger (aVR, aVL, aVF), and thoracic according to Wilson
(V1-6). Manual measurements of ECG characteristics were performed using a ruler for
Cells 2022, 11, 39
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measuring and evaluating electrocardiograms from “Heinrich Mack Nachf” (Karlsruhe,
Germany). Heart rate, oxygen uptake, carbon dioxide production, and respiratory rates
were obtained from test protocols.
2.4. Exercise Test on a Cycle Ergometer “until Exhaustion”
On an ergometer bike (“Ergose-lect-100”, Ergoline GmbH, Hoechberg, Germany)
was performed aerobic capacity (V’O2 max) testing in the “breath by breath” mode. The
parameters were averaged over 15-s segments. The test included one minute of cycling
without load (for adaptation of participants) followed by stepwise load increases of 40 W
in 2 min increments. The ﬁrst load started from 120 W. During the test, the pedalling
speed was 60 rpm. The anaerobic threshold (AT) was determined by reaching a respiratory
coefﬁcient of 1 [8,9].
2.5. Determination of NOx
The NO levels in the plasma were measured using the Griess reaction, by evaluating
the stable metabolites of NO, including nitrites (NO(2)(−)) and nitrates (NO(3)(−)), which
were pre-sorted as an index [NOx]. As described earlier in our article [5], nitrite and
nitrate are the terminal products of NO in human plasma. It is known that a strong
correlation between endogenous NO production and NOx levels exist in plasma [10]. Blood
samples with a volume of two ml were collected into tubes with heparin and centrifuged
for 20 min at 2500× g. The separated plasma was stored at −40 ◦C until analysis. After
deproteinization of plasma samples by precipitation in ethanol and centrifugation, the
supernatants were incubated for 30 min at 37 ◦C with vanadium chloride to convert nitrate
to nitrite. Next, the samples were mixed with Griess reagent. Samples were measured
at a wavelength of 540 nm using a Spectronic Genesys-6 Spectrophotometer (Thermo
Electron Scientiﬁc Instruments LLC, Madison, WI, USA). Total nitrite was measured using
the Griess reagent. Samples were measured twice against a standard nitrite curve with a
known concentration. The plasma nitrate concentration was calculated by subtracting the
primary nitrite concentration from the total nitrite concentration. All chemicals used for
NO determination were obtained from Sigma (St. Louis, MO, USA). The detection limit
for NO was 0.001 µmol/L. The NO3/NO2 index was calculated as the ratio between NO3
and NO2.
2.6. Determination of Lactate
Plasma lactate levels were measured using a lactate pulmonary alveolar proteinosis
(PAP) enzymatic colorimetric method with “Chronolab” commercial kits (Chronolab Sys-
tems, S.L. Barcelona, Spain) with an intra-assay coefﬁcient of variance (CV) of 8%. Mea-
surements were performed using a spectrophotometer at a wavelength of 546 nm.
2.7. Statistical Analysis
Statistica software (STA862D175437Q, version 6.0, StatSoft Inc., 2001, Tulsa, OK, USA)
was used for statistical analysis. The mean (Me) and standard deviation (SD) were calcu-
lated. Differences in the dynamics of each parameter were tested by Friedman’s ANOVA.
The Wilcoxon test was used to deﬁne the correlation coefﬁcients between two variables.
The Spearman rank analysis determined the correlation coefﬁcients between two variables.
A value of p < 0.05 was accepted as statistically signiﬁcant.
3. Results
The characteristics of the examined groups of athletes are presented in Table 1.
The groups of the examined athletes did not have signiﬁcant differences in age, weight
or height (Table 1). At the same time, load power on the anaerobic threshold and maximal
load power increased signiﬁcantly (p < 0.05) with an increase in sports activity (Figure 1).
Cells 2022, 11, 39
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Table 1. Characteristics of the subjects by group, ME ± SD.
Parameters
Group I (n = 61)
Group II (n = 63)
AGE, YEARS
19.1 ± 2.1
21.0 ± 3.1
WEIGHT, KG
69.1 ± 4.8
71.1 ± 4.6
HEIGHT, CM
174.9 ± 4.7
175.4 ± 4.9
 
3. Results 
The characteristics of the examined groups of athletes are presented in Table 1. 
Table 1. Characteristics of the subjects by group, ME ± SD. 
Parameters 
Group I (n = 61) 
Group II (n = 63) 
AGE, YEARS 
19.1 ± 2.1 
21.0 ± 3.1 
WEIGHT, KG 
69.1 ± 4.8 
71.1 ± 4.6 
HEIGHT, CM 
174.9 ± 4.7 
175.4 ± 4.9 
The groups of the examined athletes did not have significant differences in age, 
weight or height (Table 1). At the same time, load power on the anaerobic threshold and 
maximal load power increased significantly (p < 0.05) with an increase in sports activity 
(Figure 1).  
 group I
 group II
Load power on anaerobic threshold
Maximal Load power
180
200
220
240
260
280
300
320
340
360
380
400
420
 Load power / Watts
Group I: p=0.0191
Group II: p=0.0193
*
*
 
Figure 1. Load power in cross-country skiers during the exercise test on a cycle ergometer “until 
exhaustion” (Mean; Box: Mean ± 2 * SD; Whisker: Min–Max). 
When performing the test “until exhaustion”, all cross-country skiers showed a sta-
tistically significant increase in oxygen uptake during the passage of the anaerobic thresh-
old (p = 0.001) compared with indicators at rest (Figure 2). At the level of the AT and peak 
load, group II was characterized by higher values of oxygen uptake (p < 0.01 and p < 0.001, 
respectively). During the recovery period, oxygen uptake values decreased significantly 
in both groups (p < 0.001). During rest and during the recovery period, the oxygen uptake 
did not differ significantly in the study groups. 
Figure 1. Load power in cross-country skiers during the exercise test on a cycle ergometer “until
exhaustion” (Mean; Box: Mean ± 2 SD; Whisker: Min–Max). * p < 0.05.
When performing the test “until exhaustion”, all cross-country skiers showed a statis-
tically signiﬁcant increase in oxygen uptake during the passage of the anaerobic threshold
(p = 0.001) compared with indicators at rest (Figure 2). At the level of the AT and peak
load, group II was characterized by higher values of oxygen uptake (p < 0.01 and p < 0.001,
respectively). During the recovery period, oxygen uptake values decreased signiﬁcantly in
both groups (p < 0.001). During rest and during the recovery period, the oxygen uptake
did not differ signiﬁcantly in the study groups.
Cells 2022, 11, x FOR PEER REVIEW 
5 of 17 
 
 
Figure 2. Oxygen uptake during the exercise test on a cycle ergometer “until exhaustion” in cross-
country skiers. Statistical significance levels between groups: ** p < 0.01; *** p < 0.001.Statistical sig-
nificance levels between stages of the load: ### p < 0.001. 
3.1. Cardiorespiratory Parameters 
All cross-country skiers showed some similar dynamics of SBP during the test “until 
exhaustion”: an increase at AT and at peak load and a decrease at recovery (p < 0.001) 
(Table 2). At rest, Group I was characterized by higher SBP than Group II (p < 0.05). 
During the period of AT, at the peak load and at the recovery period, the DBP was 
Figure 2. Oxygen uptake during the exercise test on a cycle ergometer “until exhaustion” in cross-
country skiers. Statistical signiﬁcance levels between groups: ** p < 0.01; *** p < 0.001. Statistical
signiﬁcance levels between stages of the load: ### p < 0.001.
Cells 2022, 11, 39
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3.1. Cardiorespiratory Parameters
All cross-country skiers showed some similar dynamics of SBP during the test “until
exhaustion”: an increase at AT and at peak load and a decrease at recovery (p < 0.001)
(Table 2). At rest, Group I was characterized by higher SBP than Group II (p < 0.05).
Table 2. Cardiorespiratory parameters at different stages of the load in cross-country skiers, Me ± SD.
Parameters
Stages of the Load
At Rest
Anaerobic
Threshold
Peak Load
Recovery
Systolic blood pressure,
mm Hg
I
118.6 ± 11.7
168.5 ± 16.1 ###
188.6 ± 15.9 ###
122.2 ± 12.2 ###
Ii
115.2 ± 8.9 *
163.9 ± 13.2 ###
185.8 ± 18.6 ###
125.3 ± 14.3 ###
Diastolic blood pressure,
mm Hg
I
77.6 ± 7.6
70.6 ± 13.9 ###
75.2 ± 16.4 ###
62.6 ± 13.5 ###
Ii
77.9 ± 8.8
77.1 ± 11.5 **
83.4 ± 14.7 *,###
67.5 ± 15.4 **,###
Heart rate,
beats/min
I
62.8 ± 13.1
166.3 ± 13.3 ###
180.2 ± 17.6 ###
108.2 ± 13.3 ###
Ii
56.1 ± 10.1 **
165.1 ± 15.0 ###
177.8 ± 17.3 ###
99.9 ± 14.6 *,###
QRS complex,
ms
I
103.8 ± 8.9
191.8 ± 95.8 ###
216.6 ± 76.3 #
123.4 ± 41.9 ###
Ii
106.4 ± 8.9
187.4 ± 83.6 ###
213.3 ± 87.3 #
113.6 ± 19.7 ###
QT interval,
ms
I
394.2 ± 24.9
328.5 ± 93.5 ###
361.8 ± 80.4 #
316.8 ± 41.6 ###
Ii
412.5 ± 29.4 ***
316.8 ± 84.3.1 ###
345.4 ± 93.6 #
311.1 ± 28.4 ##
Carbon dioxide production,
L/min
I
0.3 ± 0.1
3.6 ± 0.5 ###
4.7 ± 0.6 ###
0.8 ± 0.2 ###
Ii
0.3 ± 0.1
3.9 ± 0.6 **,###
4.8 ± 0.7 ###
0.8 ± 0.2 ###
Respiratory rate,
breaths per minute
I
13.9 ± 3.8
35.6 ± 8.2 ###
50.2 ± 10.1 ###
25.8 ± 5.8 ###
Ii
13.6 ± 3.9
36.8 ± 8.7 ###
50.8 ± 12.4 ###
25.7 ± 4.9 ###
Statistical signiﬁcance levels between groups: * p < 0.05; ** p < 0.01; *** p < 0.001 Statistical signiﬁcance levels
between stages of the load: # p < 0.05; ## p < 0.01; ### p < 0.001.
During the period of AT, at the peak load and at the recovery period, the DBP was
signiﬁcantly higher in the athletes of Group II than in the skiers of Group I (p < 0.01; p < 0.05
and p < 0.01, respectively) (Table 2). The level of AT in Group I was decreased in DBP
compared with the rest of the period (p < 0.01). Athletes in both groups showed an increase
in DBP at the peak load compared with the AT Group (p < 0.001) and a decrease after ﬁve
minutes of completion of the test (p < 0.001). There were no differences in DBP at rest or
during the recovery period between the study groups (p > 0.05).
All cross-country skiers showed some similar dynamics of heart rate during the test
“until exhaustion”: an increase at the AT and at peak load and a decrease at recovery
(p < 0.001) (Table 2). At rest and during the recovery period, Group I was characterized by
a higher heart rate than Group II (p < 0.01 and p < 0.05, respectively).
The dynamics of changes in the QRS complex in the two groups were similar; specif-
ically, signiﬁcant increases during the period of AT passage (p < 0.001) and at peak load
(p < 0.05) and a decrease 5 minutes after the end of the test was noted (p < 0.001) (Table 2).
There were no signiﬁcant differences in the QRS complexation during the test “until exhaus-
tion” between the study groups (p > 0.05). A signiﬁcant decrease in QT interval was found
in both groups of cross-country skiers during the passage of the AT and at the recovery
period (p < 0.001) and an increase at the peak of the load (p < 0.05). Signiﬁcant differences
in QT interval between groups were found only at rest (p < 0.001).
All cross-country skiers showed some similar dynamics of carbon dioxide production
and respiratory rate during the test “until exhaustion”: an increase at AT and at peak load
and a decrease at recovery (p < 0.001). AT Group II was characterized by higher carbon
dioxide production than Group I (p < 0.01).
3.2. Biochemical Parameters
At rest and during the test “until exhaustion”, the values of NOx in Group II were
signiﬁcantly higher than the values of NOx in Group I (p < 0.01) (Figure 3). For athletes,
Cells 2022, 11, 39
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Group I and Group II showed an increase in NOx at the AT compared with the rest
(p < 0.001 and p < 0.05, respectively) and a decrease for athletes in group II at peak load
(p < 0.05). During the recovery period, the NOx level in the examined groups did not
change compared to the peak load.
 
tion and respiratory rate during the test “until exhaustion”: an increase at AT and at peak 
load and a decrease at recovery (p < 0.001). AT Group II was characterized by higher car-
bon dioxide production than Group I (p < 0.01). 
3.2. Biochemical Parameters 
At rest and during the test “until exhaustion”, the values of NOx in Group II were 
significantly higher than the values of NOx in Group I (p < 0.01) (Figure 3). For athletes, 
Group I and Group II showed an increase in NOx at the AT compared with the rest (p < 
0.001 and p < 0.05, respectively) and a decrease for athletes in group II at peak load (p < 
0.05). During the recovery period, the NOx level in the examined groups did not change 
compared to the peak load. 
 
Figure 3. NOx level (µmol/L) during the exercise test on a cycle ergometer “until exhaustion” in 
cross-country skiers. Statistical significance levels between groups: ** p < 0.01. Statistical significance 
levels between stages of the load: # p < 0.05; ### p < 0.001. 
 
 
Figure 3. NOx level (µmol/L) during the exercise test on a cycle ergometer “until exhaustion” in
cross-country skiers. Statistical signiﬁcance levels between groups: ** p < 0.01. Statistical signiﬁcance
levels between stages of the load: # p < 0.05; ### p < 0.001.
At rest, the NO2 value in Group II was signiﬁcantly higher than the NO2 value in
Group I (p < 0.05) (Table 3). The NO2 value between the studied groups of athletes at the
AT, at peak load and at the recovery period did not show statistically signiﬁcant changes
(p > 0.05). A signiﬁcant increase in the level of NO2 was detected only in Group I during
the AT period compared with rest (p < 0.01). At rest and during the test “until exhaustion”,
the values of NO3 in Group II were signiﬁcantly higher than the values of NO3 in Group I
(p < 0.01). A statistically signiﬁcant (p < 0.01–0.001) increase in NO3 was observed in all
study groups during the passage of AT compared with the values at rest. In Group II,
during the passage of the load peak, the NO3 value decreased signiﬁcantly in comparison
with the AT (p < 0.01). At the same time, in Group I, a statistically signiﬁcant decrease in
NO3 was observed during recovery compared to the peak load (p < 0.05).
Table 3. Nitric oxide and lactate levels at different stages of the load in cross-country skiers, ME ± SD.
Parameters
Stages of the Load
At Rest
Anaerobic
Threshold
Peak Load
Recovery
NO2, µmol/L
I
8.1 ± 3.6
10.2 ± 4.9 ##
9.8 ± 3.9
10.7 ± 4.5
Ii
11.6 ± 5.2 *
11.6 ± 6.1
11.1 ± 5.4
11.5 ± 5.7
NO3, µmol/L
I
8.2 ± 4.0
12.3 ± 6.9 ###
11.9 ± 6.2
10.2 ± 5.8 #
Ii
17.2 ± 8.6 **
20.0 ± 10.6 **,##
18.9 ± 11.3 **,#
17.3 ± 10.5 **
NO3/NO2 index
I
1.5 ± 0.5
1.6 ± 0.9
1.6 ± 0.2
1.3 ± 0.8
Ii
2.3 ± 0.6 *
2.2 ± 0.6 *
2.2 ± 1.3 *
1.9 ± 0.5 *
Lactate, µmol/L
I
2.9 ± 0.9
6.2 ± 1.6 ###
9.6 ± 2.2 ###
9.7 ± 2.3
Ii
2.0 ± 0.8 **
6.4 ± 1.8 ###
10.3 ± 1.8 ###
9.8 ± 2.7
Statistical signiﬁcance levels between groups: * p < 0.05; ** p < 0.01 Statistical signiﬁcance levels between stages of
the load: # p < 0.05; ## p < 0.01; ### p < 0.001.
Cells 2022, 11, 39
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The subjects of both groups showed no changes in the dynamics of the NO3/NO2
index during the test “until exhaustion”. At the same time, Group II was characterized by
higher values of the NO3/NO2 index than Group I (p < 0.05).
In representatives of different sports qualiﬁcations, the level of lactate in the blood
increased during the test, while it did not recover after 5 min of the end of the test (p < 0.001)
(Table 3). At rest in Group I, the lactate value was higher than the lactate value in Group II
(p < 0.01).
3.3. Interrelationship of Cardiorespiratory Parameters and Biochemical Parameters
Correlation analysis between biochemical and cardiorespiratory parameters at differ-
ent stages of the cross-country skiers in Groups I and II are presented in Tables 4 and 5,
respectively. After correlation analysis, skiers of Groups I and II at rest showed a negative
relationship between the values of NOx and lactate (r = −0.26, p < 0.05; r = −0.44, p < 0.001,
respectively), and Group II had a negative relationship between the values of NO3 and
lactate (r = −0.30, p < 0.05) (Table 4). However, in Group II, the relationship between NOx
and lactate during the AT period became positive (r = 0.30, p < 0.01), and during the peak
load period, the relationship between NOx and lactate again became negative (r = −0.26,
p < 0.05). In Group I, during the period of the peak load, a positive relationship was found
between lactate and NO2 (r = 0.39, p < 0.01), and a negative relationship was found with
the NO3/NO2 index (r = −0.35, p < 0.01). During the recovery period, no correlations were
found between nitric oxide and lactate in the examined groups. In general, during the
AT period, most of the correlations between nitric oxide and cardiorespiratory parameters
were found in Group II.
Table 4. Correlations between biochemical and cardiorespiratory parameters at different stages of
cross-country skiers in Group I.
Stages of the Load
Parameters
Spearman Rank Order Correlations
NOx
NO2
NO3
Before load,
at rest
SBP
−0.32 *
DBP
HR
QRS
QT
Lactate
−0.26 *
V’O2
V’O2 max
0.30 *
V’CO2
Rer
Anaerobic threshold
SBP
−0.25 *
−0.36 **
DBP
HR
QRS
QT
Lactate
V’O2
0.36 **
0.28 *
V’O2 max
0.29 *
V’CO2
0.34 **
Rer
Cells 2022, 11, 39
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Table 4. Cont.
Stages of the Load
Parameters
Spearman Rank Order Correlations
NOx
NO2
NO3
Peak load
SBP
DBP
HR
QRS
QT
Lactate
0.39 **
V’O2
V’O2 max
V’CO2
Rer
Recovery
SBP
DBP
HR
0.29 *
QRS
QT
Lactate
V’O2
V’O2 max
V’CO2
Rer
Statistical signiﬁcance levels: * p < 0.05; ** p < 0.01. SBP-systolic blood pressure, DBP-diastolic blood pressure,
HR-heart rate, QRS-QRS complex, QT-QT interval, V’O2-oxygen uptake, V’O2 max-maximal oxygen uptake,
V’CO2-carbon dioxide production, Rer-respiratory rate.
Table 5. Correlations between biochemical and cardiorespiratory parameters at different stages of
cross-country skiers in Group II.
Stages of the Load
Parameters
Spearman Rank Order Correlations
NOx
NO2
NO3
Before load,
at rest
SBP
DBP
HR
QRS
0.37 **
QT
Lactate
−0.44 ***
−0.30 *
V’O2
V’O2 max
V’CO2
−0.30 **
Rer
−0.26 *
−0.26 *
Anaerobic threshold
SBP
0.26 *
DBP
HR
0.31 **
0.43 ***
QRS
QT
Lactate
0.30 **
0.26 *
V’O2
0.33 **
0.32 **
V’O2 max
V’CO2
0.26 *
0.25 *
Rer
0.26 *
0.26 *
Cells 2022, 11, 39
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Table 5. Cont.
Stages of the Load
Parameters
Spearman Rank Order Correlations
NOx
NO2
NO3
Peak load
SBP
−0.29 *
−0.26 *
DBP
0.27 *
HR
QRS
QT
Lactate
−0.26 *
V’O2
V’O2 max
0.26 *
V’CO2
Rer
Recovery
SBP
DBP
HR
0.27 *
QRS
QT
Lactate
V’O2
V’O2 max
V’CO2
Rer
−0.29 *
−0.28 *
Statistical signiﬁcance levels: * p < 0.05; ** p < 0.01; *** p < 0.001. SBP-systolic blood pressure, DBP-diastolic blood
pressure, HR-heart rate, QRS-QRS complex, QT-QT interval, V’O2-oxygen uptake, V’O2 max-maximal oxygen
uptake, V’CO2-carbon dioxide production, Rer-respiratory rate.
Correlation analysis between maximal oxygen uptake and cardiorespiratory param-
eters at different stages of the cross-country skiers in Groups I and II are presented in
Table 6.
Table 6. Correlations between maximal oxygen uptake and cardiorespiratory parameters and lactate
at different stages of cross-country skiers in Groups I and II.
Stages of the Load
Parameters
Spearman Rank Order Correlations
Groups I
Groups II
Before load,
at rest
SBP
DBP
HR
QRS
QT
Lactate
V’CO2
Rer
Anaerobic threshold
SBP
−0.34 **
DBP
HR
QRS
QT
0.26 *
Lactate
0.26 *
V’CO2
Rer
Cells 2022, 11, 39
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Table 6. Cont.
Stages of the Load
Parameters
Spearman Rank Order Correlations
Groups I
Groups II
Peak load
SBP
DBP
HR
QRS
QT
Lactate
0.33 **
V’CO2
Rer
Recovery
SBP
DBP
−0.26 *
HR
QRS
QT
Lactate
0.33 **
V’CO2
Rer
Statistical signiﬁcance levels: * p < 0.05; ** p < 0.01. SBP-systolic blood pressure, DBP-diastolic blood pressure,
HR-heart rate, QRS-QRS complex, QT-QT interval, V’CO2-carbon dioxide production, Rer-respiratory rate.
During the AT, the peak load and during the recovery period showed a positive
relationship between the maximal oxygen uptake and lactate in Group I (r = 0.26, p < 0.05,
r = 0.33, p < 0.01, r = 0.33, p < 0.01, respectively). In Group II, no correlations were found
between maximal oxygen uptake and cardiorespiratory parameters.
4. Discussion
The main goal of our study was to identify the features of metabolic regulation in
highly trained cross-country skiers of different qualiﬁcations at different stages of testing
at physical maximum load. The study showed that elite athletes with higher results at
ofﬁcial competitions were characterized by a higher anaerobic threshold and maximal
oxygen uptake. Compared to the group, the athlete was not elite, which is comparable to
the literature data [11,12].
Cross-country skiers are known to have a very high maximal oxygen uptake and
have equally trained upper and lower body muscles [4]. Thus, they are able to perform
submaximal exercise at a rather high metabolic rate and with cardiac output levels similar
to or higher than the cardiac output levels achieved by untrained humans at maximal
exercise. Thus, this group of athletes is a successful model for studying metabolic effects in
humans during intense physical work, especially since trained skiers can actually perform
this intensive work, revealing subtle regulatory mechanisms. For example, elite Swedish
skiers had a maximum oxygen uptake of 5.1 ± 0.3 L/min [13], which is 7.8% more than
among the Group II skiers we examined. Our data on the maximum oxygen uptake also
differ signiﬁcantly in elite athletes from V’O2 max of Norwegian representatives of world-
class winter sports [14,15], which are characterized by a maximum V’O2/kg from 80 to
90 mL/min/kg or 6.5 L/min, which is higher than in Group II surveyed by us by 27.6%.
Most likely, this difference can be explained by different methodological approaches for
determining the V’O2 max and higher anthropometric indicators of elite Swedish skiers
(height 180 ± 2 cm, weight 74 ± 2 kg) [13] and Norwegian representatives of world-class
winter sports [14,15].
The physical efﬁciency of athletes and the state of their cardiorespiratory system play
leading roles among cross-country skiers in achieving high sports results. Physical aerobic
exercise inﬂuences vascular remodelling, promoting angiogenesis, positively affecting
the number of capillaries and therefore the gas exchange area, while improving oxygen
diffusion and increasing vagus tone [14]. In the athletes examined in our study, SBP at rest
Cells 2022, 11, 39
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corresponded to the norm [16]. At the same time, in Group I at rest, the SBP was statistically
higher (p < 0.05) than in Group II, but during the exercise test, signiﬁcant differences in SBP
between the groups disappeared. A higher SBP in skiers of the 1st group, compared with
Group II, could be associated with the incompleteness of the processes of the formation of
the cardiovascular system against the background of signiﬁcant sports loads.
At rest, DBP in all groups of cross-country skiers was above the norm, in com-
parison with the data obtained from students from a physical education department
(64.0 ± 4.7 mm Hg) [16]. It is known that prolonged training in open cold air can lead to an
increase in peripheral vascular resistance and, as a consequence, to an increase in DBP [17].
Short-term (one-hour) cold exposure induces hypercoagulation in young healthy people,
which can also cause a higher level of DBP [18]. According to the literature [19], cold air can
indirectly lead to an increase in cardiovascular risks through its effect on the sympathetic
and renin-angiotensin systems, blood pressure, and risk factors for atherosclerosis, such
as blood viscosity, the amount of ﬁbrinogen, lipids and uric acid. In our study, during the
period of AT, at the peak load and at the recovery period, the DBP was signiﬁcantly higher
in the athletes of Group II than in the skiers of Group I (p < 0.01; p < 0.05 and p < 0.01,
respectively) (Table 2).
According to our data, the heart rate at rest in the skiers of Group I was 10.7% higher
than the heart rate at rest in Group II (p < 0.01), which indicates the formation of bradycardia
as a result of sports training, which was more pronounced with an increase in sports
activity. This assumption is conﬁrmed by the higher values of the QT interval at rest
in Group II compared with Group I. Aerobic exercise [20] affects the parasympathetic
nerve, reducing the heart rate, which has a positive effect on reducing cardiovascular
diseases. With an increase in sportsmanship, lower heart rate values may indicate [3]
higher functional reserves.
On the one side, it was shown that low intensity exercise could improve antioxidant
defences and lower lipid peroxidation levels [21]. On the other side, it is known that in
the body of professional athletes under intense and strenuous physical exertion, oxidative
stress [22] can occur, leading to the accumulation of lipid peroxidation products, including
free radicals. Oxidative stress is the main reason for the decrease in the activity of NO syn-
thase (NOS) through a decrease in the availability of the cofactor NOS-tetrahydrobiopterin
and, subsequently, the inhibition of the enzymatic synthesis of NO. In our study, lower
values of the NOx level during the test “to exhaustion” were observed in Group I skiers
compared with athletes in Group II, which may indicate a decrease in the enzymatic synthe-
sis of NO in athletes of Group I. The adaptive capacity of the body reduction with a decrease
in the level of NO in the tissues, and pathological changes in metabolism are observed,
leading to diseases. The primary cause of the pathogenesis of coronary heart disease and
atherosclerotic vascular damage is a deﬁciency of NO in the vascular endothelium and
myocardium [23]. There are several factors causing endothelial NO deﬁciency: a decrease
in eNOS activity [24], destruction or capture of NO by free radicals, and/or a weakening of
the effect of NO on smooth muscle [25].
In general, oxidative stress and hypoxia are believed to cause overproduction of
NO, often exceeding its physiological level [26,27]. In the body under oxidative stress,
NO processes take place; for example, NO covalently binds to a cysteine residue in the
beta-chain of Hb to form S-nitrosohaemoglobin, as well as other proteins, which has
a regulatory effect on the local tissue blood supply during hypoxic vasodilation [28].
With gradual adaptation to oxidative stress (hypoxia), the plasma level of stable NO
metabolites—nitrates and nitrites—progressively increases, correlating with an increase
in the vascular NO depot [29]. Perhaps this mechanism of adaptation to the gradually
increasing hypoxia caused by physical exertion of maximum power was observed in the
elite athletes we examined.
Physiological effects [30] aimed at improving oxygen supply during hypoxia are
well documented and include increased ventilation and cardiac output, erythropoiesis,
and tissue vascularization [31]. Since V’O2 is determined by the interaction of several
Cells 2022, 11, 39
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factors—blood ﬂow, blood O2 carrying capacity, diffusion of O2 from blood to tissues, ATP
demands and O2 utilization by mitochondria—it is clear that the result of changes in NO
production on V’O2 depends on the balance between often opposite effects at different
levels of the phenomena occurring.
Lactate levels in blood and tissues are assumed to increase during hypoxia. After 8 h
of breathing in a chamber with hypoxic conditions of 12% O2, a moderate increase in lactate
levels of 29% was observed [32]. In our study, athletes of different sports classiﬁcations
showed an increase in the level of lactate in the blood during the period of maximum
exercise. Compared with the indices at rest in Group I, lactate increased by 3.3 times, and
in Group II by 5.2 times (p < 0.001); therefore, the athletes examined by us experienced
hypoxia during physical activity. Moreover, in Group II, hypoxia had a more pronounced
character and a higher increase in V’O2 during the period of maximum load. As shown
earlier, including our own study, ﬂuctuations in the level of NO in the human body trigger
various adaptive reactions under conditions of acute hypoxia [33,34].
Our data indicate that the baseline lactate level before the test “until exhaustion” is
also signiﬁcant, and this indicator is negatively correlated with the NOx indicator. In the
literature, in some clinical conditions, there is a negative correlation between lactate and
NO; for example, in acute brain injury [35] and in major surgical operations [36], although
with septic shock, the use of L-NMMA, an iNOS inhibitor, increases the level of lactate in
the thigh muscle [37]. NO is a mediator of skeletal muscle function, especially NO, which
affects cellular respiration and contractility, and in working skeletal muscle, inhibition of
NOS improves the economy of muscle contraction and leads to a decrease in the outﬂow of
lactate from the muscles by reducing oxygen cost [38].
Thiol reactions or reactive metal centres in proteins can cause NO responses for further
biological events in skeletal muscle. The NO-mediated response inhibits haeme-containing
proteins such as cytochrome c oxidase, thus inhibiting the function of cytochrome c oxidase
and cell respiration [39]. Cytochrome c oxidase and the sarcoplasmic reticulum Ca21-
ATPase in fast-twitch and slow-twitch skeletal muscle inhibits by NOS activity which
in turn leads to inhibiting mitochondrial respiration in skeletal muscle [40]. Moreover,
aconitase and complex I of the respiratory chain can be additional targets of NO [41].
NO is crucial for the activation and inhibition of ryanodine receptors (RyRs) [42]. For
muscle contraction and excitation, the release of Ca2+ into the cytosol is necessary, the
RyR play a decisive role in this process. In recent years, special properties of NO2 have
been shown, which make it possible to recognize it as the most signiﬁcant biologically
active signalling molecule [43]. The signiﬁcant vasodilatory response observed in vivo
and in vitro experiments upon administration of NO2 solutions suggests that it can be
an alternative source of NO [44]. NO2 was also reported to participate in adaptation to
physiological conditions of hypoxia, for example, caused by physical exertion [45]. Modern
concepts of nitrite-dependent mechanisms of adaptation to hypoxia are based on data on
the participation of NO2 in oxygen-dependent and hypoxia-dependent nitrite reductase
processes. NO released as a result of these processes is involved in the regulation of vascular
tone, modulation of mitochondrial redox reactions [46], changes in the sensitivity of heart
contractile proteins to oxygen [47] and calcium ions [48], and inhibition of induced NOS.
Due to the cyclic metabolic transformations of NO, NO2 and NO3, the optimal level of
NO is maintained, which is necessary for the normal functioning of the cardiovascular
system in conditions of impaired functioning of NO synthases. However, excess NO is
removed by the formation of an NO depot in the form of NO2, which protects tissues from
oxidative and nitrosative stress. The source of vasoactive NO has now been established
to also be NO2. It is always present in the blood and can be enzymatically reduced to
NO under the action of xanthine oxidoreductase and nonenzymatic under conditions
of low pH and pO2 [49]. Nitrate is reduced to nitrite and nitric oxide, which activate
soluble guanylate cyclase [50]. Exercise has been shown to increase plasma nitrite levels by
increasing NO synthesis in endothelial cells [51,52]. Plasma nitrite is oxidized to nitrate.
This process is signiﬁcantly accelerated by the presence of haeme proteins [53]. Nitrates are
Cells 2022, 11, 39
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stable in plasma until excreted in the urine. The circulation of nitrite, rather than nitrate,
indicates endothelial-dependent synthesis of NO [54]. Increased NO production during
exercise is likely controlled by increased nitrate excretion as a possible mechanism for
controlling plasma homeostasis [55]. When oxygen pressure decreases, nitrite reduction by
deoxyhaemoglobin produces NO. The generation and release of NO by erythrocytes, along
with the oxygen concentration gradient, can be associated with the role of nitrite bound to
erythrocytes in the processes of vasodilation in response to hypoxia.
The indicators of correlation between the studied indices are of particular interest for
discussion. Notably, there was a positive relationship between the parameters of V’O2max
and lactate in Group 1 at all stages of testing. However, in Group II, correlations between
these indicators were not revealed at all.
It is also necessary to consider the correlation relationship between indicators of
metabolites of nitric oxide and lactate during testing. Initially, at rest, NOx and lactate in
both groups showed a signiﬁcant negative correlation. In Group I, at the AT, correlation
disappeared, and at the maximum load, the correlation was revealed between NO2 and
lactate opposite direction. In Group II, at the AT, there was a positive relationship between
NOx and lactate indicators, which inverted at maximum load. Thus, among skiers of
Group II, a positive correlation of NO and lactate indicators was detected at the AT, and
in Group I, the positive correlation of NO2 and lactate indicators was detected only at
the maximum load. This observation suggests the existence of an adaptive mechanism
for regulating the level of lactate at the AT in highly skilled skiers. The methodology of
the training process in cyclic sports is known to be based on the principle of increasing
the aerobic performance of the body of athletes. The phenomenon identiﬁed by us, in
our opinion, may be reﬂects the positive effect of NO on the production of lactate, which
provides an increase in aerobic performance. At the same time, at maximum load, on
the contrary, it is required to maximize the activity of glycolysis and, accordingly, the
production of lactate. In our opinion, activation of the reroute pyruvate away from pyruvate
dehydrogenase (PDH) in an NO-dependent mechanism may be a possible mechanism
explaining what is happening at the testing stage of highly skilled skiers at the AT (thereby
promoting glutamine-based anaplerosis). The capability of this process was established in
a recently published post [56]. To a certain extent, this hypothesis can be evidenced by our
materials presented in Table 6. At rest, there was no correlation between lactate and V’O2
max in either group. However, in Group I, during exercise, a positive correlation of V’O2
max and lactate indices was manifested, which increased during the test until the recovery
period. In contrast, in Group II during the entire test, there was no signiﬁcant correlation
between V’O2 max and lactate. In our opinion, this lack of signiﬁcant correlation indicates
that the level of lactate in the blood of highly qualiﬁed skiers–racers, in contrast to less
qualiﬁed athletes with submaximal and maximum physical activity, does not depend on
the parameters of the V’O2 max. It is likely that these athletes have developed additional
adaptive mechanisms for regulating the production of lactate, one of which may be the
activation of pyruvate abstraction through pyruvate dehydrogenase under conditions of
aerobic work.
5. Conclusions
The results of our research indicate that the studied groups of athletes with high but
different levels of sports qualiﬁcations are a convenient model for studying the molecular
mechanisms of adaptation to physical loads of maximum intensity. Athletes of higher
qualiﬁcations reveal additional adaptive mechanisms of metabolic regulation, which is
manifested in the independence of serum lactate indicators under conditions of submaximal
and maximum power from V’O2 max, and they have an NO-dependent mechanism for
regulating lactate levels during aerobic exercise, including work at the AT. Limitation: 1. The
sample is small to suggest solid conclusions. However, our study included 124 highly
trained cross-countries skiers, who, at the time of testing, were current members of the
national team of the Komi Republic and Russia. All participants were exposed to hard
Cells 2022, 11, 39
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screening for a number of indicators and were uniﬁed. 2. An “until exhaustion” assessment
needs further investigation due to the low degree of inter-sample analysis. 3. NO is not the
only protagonist to guide the metabolic pathways. In the literature, much attention is paid
to studying the role of the participation of nitric oxide interaction during inﬂammatory
in rats [57,58]. At the same time, in our paper, we tried to reveal the mechanisms of the
participation of nitric oxide in the process of adaptation to regular, hard and intense physical
activity of healthy highly qualiﬁed athletes, who have developed speciﬁc mechanisms of
adaptation to these loads.
Author Contributions: All authors participated in designing the experiment. O.I.P. participated in
the experimental procedure, carried out the biochemical studies, performed the statistical analysis
and drafted the manuscript; N.G.V. participated in the experimental procedure, involved in data
collection, and drafted the manuscript; N.N.P. carried out the biochemical studies, helped to draft
the manuscript; A.Y.L. helped the statistical analysis; E.R.B. oversaw the experimental procedures,
provided coordination, helped with drafting of the manuscript. All authors have agree with the
order of presentation of the authors. All authors have read and agreed to the published version of
the manuscript.
Funding: The study was carried out at the expense of subsidies for the implementation of State
Assignment No. GR 1021051201877-3-3.1.8.
Institutional Review Board Statement: The study was conducted in accordance with the Declaration
of Helsinki, and approved by the Ethics Committee of Institute of Physiology of Komi Science Centre
of the Ural Branch of the Russian Academy of Sciences (date of approval: 23.10.2013).
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: The data that were generated and/or analyzed during the current
study are available from the corresponding author upon reasonable request.
Conﬂicts of Interest: The authors declare no conﬂict of interest.
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Features of Metabolic Support of Physical Performance in Highly Trained Cross-Country Skiers of Different Qualifications during Physical Activity at Maximum Load.
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