Introduction
Athletic competition, high-intensity training, non-habitual exercise, and other
high-load activities frequently lead to exercise-induced fatigue. This type of
fatigue not only results in perturbations to bodily tissues through metabolic and
mechanical stresses [1], but also
diminishes athletic performance[2] and
increases incidence of sports injuries [3]
[4]. The massive increase
in reactive oxygen species (ROS) caused by rigorous and/or prolonged exercise is
thought to be one of the contributors to the development of exercise fatigue [5]. When the amount of ROS exceeds the
scavenging ability of endogenous antioxidant substances, the oxidation-antioxidative
balance is disrupted, generating elevated oxidative stress [6]
[7], capable of inhibiting one or more proteins involved in
excitation-contraction coupling, leading to a reduction in the production of muscle
force (i. e. fatigue) [5]. Therefore,
strategies to reduce exercise-induced oxidative stress by increasing exogenous
antioxidants hold great promise for alleviating the degree of exercise fatigue and
maintaining the performance.
The hydrogen molecule is receiving increasing interest for its selective antioxidant
capabilities [8], anti-inflammatory
properties, and its role in regulating acid-base homeostasis [9]
[10]. Studies have shown that hydrogen molecules administered through the
inhalation of gas or oral intake of water (i. e. hydrogen-rich gas (HRG) and
hydrogen-rich water (HRW)) can penetrate cell membranes and diffuse rapidly into
organelles, thereby selectively reducing OH and ONOO−
[11]
[12]. It was observed that taking HRW and HRG can attenuate strenuous
exercise-induced oxidative damages in human, accelerate heart rate recovery, improve
muscular function, reduce exercise-induced fatigue perceptual and alleviate the
lactate (LA) response after exercise [13]
[14]
[15]
[16]
[17]. However,
administration of HRG through inhalation enables the rapid delivery of higher doses
of hydrogen to organisms compared to other delivery methods, including drinking HRW
[18]. Drinking HRW results in
hydrogen reaching peak levels within 10–20 minutes and remaining above baseline for
30–40 minutes [19], whereas the reaction
time of hydrogen in the body through inhalation may be up to 3 hours [20]. The longer response time of inhaled
HRG may potentially allow for pre-exercise ingestion to influence subsequent
exercise. However, it remains to be determined whether inhalation of HRG prior to
exercise will have specific effects on subsequent exercise-induced fatigue and
exercise performance.
We contend that inhaling HRG before high-load exercise would alleviate exercise
fatigue by eliminating exercise-induced excess ROS. Evaluating the impact of HRG
supplementation versus non-supplementation on fatigue after a specific exercise unit
of the same duration and intensity enables exercisers to discern HRG's efficacy
in diminishing fatigue following strenuous exercise. Lower fatigue means a lower
risk of injury and better athletic performance in subsequent exercise. Therefore, in
this double-blind, counterbalanced, randomized, and crossover-designed study, we
examined the effects of inhalation HRG or placebo prior to a specific high-intensity
cycling ergometer exercise unit on fatigue perceptual, functional performance and
metrics of blood sample (i. e. oxidative stress-related blood markers and serum LA)
in healthy young adults. Specifically, we hypothesized that compared to the placebo,
inhaling HRG before high-intensity exercise at the same load will result in lower
level of fatigue and better functional performance at the end of exercise; and such
effect would be associated with the reduced level of serum LA and oxidative
stress-related markers in the blood samples.
Materials and Methods
Participants
Twenty-four healthy, recreationally active adult men (21±3 yr, 177±5 cm, 71±7 kg;
[Table 1]) were recruited for
this study. The inclusion criteria were: regular exercise habits, involving
engagement in physical activity at least twice a week for one hour or more at a
moderate to vigorous intensity level; and the ability to complete high-intensity
cycling ergometer exercises. The exclusion criteria were: no history of lower
extremity injury in the six months prior to the experiment, no cardiovascular,
respiratory and endocrine disease. After a detailed instruction of the
experimental procedure, each participant signed an informed consent form. The
study protocol conformed to the Declaration of Helsinki and was approved by the
Ethical Review Board affiliated with one of the authors (approval number:
2021163H).
Table 1 Participant characteristics.
|
A group (n=12)
|
B group (n=12)
|
P-value
|
|
Age (years)
|
21.2±2.4
|
21.5±3.0
|
0.768
|
|
Height (cm)
|
177.8±4.0
|
176.9±5.1
|
0.631
|
|
Body weight (kg)
|
70.8±7.7
|
70.6±7.1
|
0.935
|
|
BMI (kg/m2)
|
22.4±2.0
|
22.5±1.9
|
0.862
|
|
Wmax (W)
|
213.3±35.0
|
205.0±25.8
|
0.513
|
|
Tmax (min)
|
19.0±6.9
|
22.0±9.5
|
0.394
|
Note: Wmax, the maximum cycling power; Tmax, the
maximum cycling time.
Protocol
In this double-blind and randomized study with crossover design ([Fig. 1]), participants completed
four study visits in the laboratory consisting of these tests: a maximum cycling
power (Wmax) test (Visit (I)), a maximum cycling time
(Tmax) test at 80%Wmax (Visit (II)), fatigue modeling
using a cycle ergometer following a 60-minute inhalation of HRG (HRG group) and
fatigue modeling using a cycle ergometer following a 60-minute inhalation of
placebo gas (standard air) (placebo group) (Visit (III) and (IV)). All
participants were instructed to avoid vigorous exercise, alcohol, coffee,
supplements, medicines, and any specific recovery treatments within 48 hours of
each trial period. On the morning of each study visit, all participants consumed
a standardized meal provided by the researchers, consisting of milk, bread, and
ham sausage. Furthermore, they abstained from consuming any additional food or
beverages prior to the visit.
Fig. 1 Crossover study design process.
The parameters of the fatigue model for each participant were determined on study
visit (I)and (II), with a minimum resting interval of 72 hours between them.
Once the parameters were determined, participants completed the fatigue modeling
after inhaling HRG or placebo (i. e. study visit (III) and (IV)) in a randomized
order. Visit order was randomly allocated according to balanced permutations
generated by a web-based computer program (www.randomizer.org). A resting period
of at least 7 days were provided between these two visits. On each of these two
visits, at the beginning and end of fatigue modeling task, participants
responded to Borg's scale. Additionally, the cycling frequency was required
to be maintained at 60–70 rpm throughout the fatigue modeling process. This was
continuously monitored and recorded to compare the effects of the two
interventions on cycling performance. Before each gas inhalation, participants
first completed a Visual Analogue Scale (VAS) test and had blood drawn from the
antecubital vein. This was followed by a counter-movement jump (CMJ) tests.
After completing the fatigue modeling task, participants first underwent the VAS
tests, then immediately performed the CMJ tests, and finally a blood sample was
taken (at approximately 2–3 minutes after completion of the fatigue modeling).
The VAS tests and blood collection were repeated 30 minutes and 60 minutes after
fatigue modeling task ([Fig. 2]).
The collected antecubital venous blood samples were analyzed for serum LA
levels, the ability to inhibit hydroxyl radicals, and glutathione peroxidase
(GSH-PX) activity. Considering the potential influence of women's
physiological cycles and endocrine hormone levels, we initially chose male
individuals as our research participants when investigating the impact of HRG on
blood metabolites.
Fig. 2 Experimental test sequence and procedure. Note: CMJ,
counter-movement jump; VAS, visual analogue scale; Wmax, the
maximum cycling power; Tmax, the maximum cycling time at
80%Wmax.
Hydrogen-Rich Gas (HRG)
HRG was prepared by a hydrogen gas generator Hydrogen-oxygen Convalescent machine
2.5 (Zhiheng Hydrogen Health Technology Co., Ltd., Fuzhou, China). The generator
can generate 1,800 ml/min of hydrogen-oxygen mixed gas (the composition ratio of
hydrogen and oxygen is 2:1). HRG was supplied through a nasal cannula attached
to a gas generator. Although we could not measure directly the concentrations of
hydrogen and oxygen entering the body due to technical limitations, it is
mathematically estimated that the average inspiratory flow rate of a healthy
young male at rest is about 500 ml/s, which far exceeds the flow rate of the
hydrogen gas generator, diluting the concentration of inhaled hydrogen, so that
the maximum concentration of hydrogen in the inhaled body is about 4.08%.
Similarly, the oxygen concentration is about 21.66% [15]. Compared to the oxygen content
of the air, the increased oxygen is extremely small. Placebo gas (ambient air,
0.00005% hydrogen, 20.9% oxygen) was supplied by a nasal cannula that was
connected to a hydrogen gas generator that did not initiate the hydrogen
production program.
Fatigue model
On study visit (I), the Wmax was tested by a preliminary incremental
exercise test. The test began with a load of 50 W for 2 minutes and then the
load incremented automatically in steps of 20 W every 2 minutes until volitional
exhaustion (operationally defined as a pedal frequency of less than 60 round per
minute (rpm) for more than 5 seconds despite strong verbal encouragement) on an
Ergoselect 100 cycle ergometer (Ergoline GmbH, Bitz, Germany) [21], participants were asked to
maintain the cycling frequency at 60–70 rpm throughout the process. The
Wmax was calculated according to the equation:
Wmax=Wout+(t/120)*20 (Wout: workload of the
last completed stage; t: time (seconds) in the final stage) [22]. Before the incremental exercise
test the position on the cycle ergometer was adjusted for each subject, and
settings were recorded so that they could be reproduced at each subsequent
experimental sessions. On study visit (II), the Tmax test consisted
of a 3-minute warm-up at 40% Wmax followed by cycling at 80%
Wmax. The test finished when the pedal frequency was less than
60 rpm for more than 5 seconds despite standardized verbal encouragement.
We then implemented a well-established protocol of fatigue model with equal
Wmax that has been widely used in previous studies [21]
[22]
[23]. Specifically, according to the
definition of exercise-induced fatigue outlined in the Fifth International
Biochemistry of Exercise Conference (1982), the inability to sustain the current
exercise load was considered as the criterion for fatigue. In order to ensure
that each participant reached a level of fatigue that was comparable for them,
the fatigue model employed isophysiological loads. Specifically, the fatigue
model consisted of cycling at 60–70 rpm and 40% of their Wmax for a
warm-up period of 3 minutes, then cycling at the same frequency and at 80% of
their Wmax for their Tmax. To control variables and ensure
that post-intervention tests can be compared to determine the effects of HRG,
participants performed the same duration of exercise (i. e. their own
Tmax) within both groups. Tmax was pre-determined
during a preliminary visit prior to the official experiment.
Measurements
The assessment of fatigue
The primary outcome of fatigue perception was the visual analogue scale
(VAS), which was used to examine the subjective feelings of fatigue [24]. Participants can specify
their psychometric fatigue level by indicating the location of a continuous
10 cm line between the two endpoints (starting point represents no fatigue,
end point represents extreme fatigue, and the midpoint of the line segment
represents moderate fatigue).
Secondarily, we also measured rating of perceived exertion (RPE). RPE was
used to quantitatively assess the degree of consciously perceived exertion
during the establishment of the fatigue model using a cycle ergometer. It is
an indicator of physical stress and subjective effort [25]. On study visit (I),
participants were also given standard instructions for overall RPE using the
modified version of the Borg CR10 scale [26]. The scale ranged from 0 to
11 with ratio-level properties, incorporating nonlinear spacing of verbal
descriptors of the level of intensity. Specifically, 0 indicates not
perceived, 0.5 is extremely weak, 3 moderate, 5 strong, 10 extremely strong,
and anything above 10 is denoted as 11, signifying the extreme.
The primary outcome of functional performance was CMJ. The CMJ test, a
commonly-used neuromuscular fatigue test [27], is utilized to evaluate
functional performance subsequent to the induction of post-exercise fatigue
[28]. This test can assess
an individual's neuromuscular efficiency. As high-intensity activities
often cause fatigue that impairs muscle contractile function and
neuromuscular coordination. Therefore, the CMJ test can provide a measure of
how these functions are affected by fatigue by measuring jump height. We
tested the CMJ using a stationary Kistler three-dimensional force platform
(Kistler Instrumente AG, Winterthur, Switzerland; collection frequency:
1,000 Hz) and Kistler BioWare 4.0.0 software. Participants were instructed
to practice the specific movements involved in the CMJ prior to the actual
test. During the CMJ, participants assumed a starting position on the force
platform, either upright or slightly squatting, with hands on hips. They
then performed a rapid and forceful squatting motion, flexing their knees to
approximately 90°, followed by an explosive extension to achieve maximum
height. Throughout the flight stage of the jump, participants were
instructed to extend their knees and keep their hands on their hips to avoid
any sideways displacements. When contacting the ground, participants were
instructed to land with their toes first. It was emphasized that
intentionally bending the abdomen and knees to prolong the time in the air
during landing was not allowed. Each participant completed three trials of
the CMJ. The time in the air, defined as the duration during which the
vertical ground reaction force was less than 10 N, was used to calculate
jump height [29]
[30]. The jump height averaged
across the three trials was then used in the subsequent analysis.
Secondarily, the entire fatigue modeling process for each participant was
divided equally into 10 segments. The cycling frequency during the last
30 seconds of each segment were recorded, and their average values were
taken as representing the cycling frequency performance for each respective
phase. Each participant cycled for an equivalent duration under identical
load conditions in the different intervention groups, thus the cycling
frequency performance responded to the participant's functional
performance affected by fatigue.
The assessment of blood sample markers
We conducted an analysis of serum LA, a major metabolite that can be affected
by hydrogen after strenuous exercise [14]. Additionally, we examined serum GSH-PX and hydroxyl
radicals, which serve as markers of blood oxidative stress and can reflect
the enzymatic and non-enzymatic reactions involved in the
oxidative-antioxidant balance [31]. Antecubital venous blood samples were collected from
participants using procoagulant tubes. Once the blood samples had naturally
coagulated, an Allegra X-30R high-speed cryogenic centrifuge (Beckman
Coulter, Inc., California, USA) was employed for centrifugation at 4°C,
3,000 r/min for 15 minutes, and the resulting supernatant was collected. The
ability to inhibit hydroxyl radicals and GSH-PX activity was measured using
a Hydroxyl Free Radical assay kit and Glutathione Peroxidase assay kit
(Nanjing Jiancheng Bioengineering Institute Co., Ltd., Nanjing, China) and
NANODROP 2000C spectrophotometer (Thermo Fisher Scientific, Waltham, USA).
Serum LA levels were measured using a detection kit (Beijing Leadman
Biochemical Co., Ltd., Beijing, China) and DxC-800 automatic biochemical
analyzer (Beckman Coulter, Inc., California, USA). All measurements were
performed following established standardized protocols (refer to
Supplementary Documents).
Statistical analysis
Statistical analyses were performed using SPSS 25.0 (IBM, Chicago, IL, USA). A
value of p<0.05 was considered statistically significant. Descriptive
statistics (i. e. mean, standard deviation (SD)) were used to summarize the
demographic characteristics of the participants. Shapiro-Wilk tests were used to
examine whether the data were distributed normally. Data distributed normally
were described using “mean±SD”, and those not distributed normally were
described using “median (interquartile range)” (M (P25, P75)). Since cycling
frequencies between 60–70 rpm meet the requirements, the existence of the
statistically significant differences in this range is not meaningful. Whereas
cycling frequency below 60 rpm indicates an inability to maintain cycling
requirements and can be used to distinguish differences in functional
performance. Paired t-test models were thus utilized to examine the difference
in the segments with the last 30 seconds cycling frequency of less than 60 rpm
during fatigue modeling process between the HRG group and placebo group. Two-way
(group×time) repeated measures ANOVAs were utilized to examine the outcomes that
were distributed normally; and generalized estimating equations (GEE) were
utilized to examine the outcomes that were not distributed normally. The model
factors for the two-way ANOVAs and GEE analyses included group, time, and their
interaction. Fisher's least significant difference (LSD) post-hoc analyses
were performed when a significant interaction was observed. Linear regression
analysis was used to explore the association between the percentage changes in
the outcomes of fatigue and functional performance, and the outcomes of blood
sample that were significantly affected by HRG within the HRG group.
Results
All 24 participants completed all study tests, and their data were included in the
analysis. Their anthropometric characteristics and Wmax, Tmax
results were presented in [Table 1].
Before the intervention, there were no significant differences in all test results
between the HRG group and placebo group (p>0.150, [Table 2]). Participants reported no
discernible discrepancy in their subjective feelings between the two inhalations,
suggesting a successful blinding. The CMJ, the cycling frequency during the last
30 seconds of the last segment in the fatigue modeling process, and blood sample
markers were distributed normally, and thus ANOVA models and paired t-test models
were used for the comparison in them. The VAS and RPE were not distributed normally,
therefore the GEE models were used.
Table 2 The results of the two trials before and after the
crossover of the main test indicators.
|
The first phase experiment
|
The second phase experiment
|
Overall after combination
|
|
A group (n=12) (HRG intervention)
|
B group (n=12) (placebo intervention)
|
A group (n=12) (placebo intervention)
|
B group (n=12) (HRG intervention)
|
HRG group (n=24)
|
placebo group (n=24)
|
|
RPE
|
Pre
|
1.3 (0.6, 2.4)
|
1.8 (0.63, 2.4)
|
2.0 (1.6, 2.0)
|
1.3 (1.0, 2.8)
|
2.0 (1.5, 2.0)
|
2.0 (1.6, 3.0)
|
|
0 min post
|
9.5 (8.3,10.8)
|
11.0 (10.0, 11.0)*
|
10.0 (9.3, 11.0)
|
9.0 (8.3, 10.0)*
|
9.0 (9.0, 10.0)
|
10.5 (10.0, 11.0)*
|
|
CMJ (cm)
|
Pre
|
33.26±7.18
|
34.12±3.93
|
32.16±9.05
|
34.85±4.74
|
34.06±6.01
|
33.14±6.90
|
|
0 min post
|
34.96±6.88
|
33.33±4.28
|
31.72±7.50
|
35.07±6.33
|
35.01±5.74
|
32.53±6.03*
|
|
VAS (mm)
|
Pre
|
12.5 (9.1, 18.5)
|
11.8 (4.0, 15.0)
|
10.5 (6.8, 30.0)
|
14.3 (7.9, 20.8)
|
12.5 (9.0, 19.3)
|
15.5 (11.0, 23.8)
|
|
0 min post
|
70.5 (53.2, 78.5)
|
75.8 (64.0, 88.3)
|
78.8 (71.1, 91.6)
|
73.5 (58.3, 80.9)
|
72.5 (55.0, 80.1)
|
76.8 (68.0, 89.0)*
|
|
30 min post
|
31.0 (17.6, 51.0)
|
27.5 (14.8, 50.9)
|
39.0 (17.3, 52.5)
|
20.0 (10.3, 35.5)
|
22.5 (15.8, 36.8)
|
31.3 (17.0, 50.9)
|
|
60 min post
|
17.3 (6.1, 25.0)
|
11.5 (7.1, 30.0)
|
21.3 (8.3, 34.8)
|
12.0 (6.5, 21.3)
|
15.3 (6.5, 24.6)
|
17.3 (8.3, 31.8)
|
|
LA (mmol/L)
|
Pre
|
2.52±0.69
|
2.36±0.55
|
2.40±0.63
|
2.85±0.76
|
2.68±0.73
|
2.38±0.58
|
|
0 min post
|
8.85±3.28
|
9.83±3.16
|
10.08±2.67
|
8.14±3.57
|
8.49±3.37
|
9.96±2.86
|
|
30 min post
|
2.47±1.05
|
3.24±0.79
|
3.67±1.20
|
2.72±1.14
|
2.60±1.08
|
3.46±1.02*
|
|
60 min post
|
1.77±0.63
|
2.20±0.79
|
2.77±0.84
|
2.14±0.89
|
1.95±0.75
|
2.49±0.85*
|
|
OH·- (U/ml)
|
Pre
|
474.29±247.35
|
401.86±157.94
|
499.26±194.38
|
542.57±236.36
|
501.38±242.43
|
445.21±188.26
|
|
0 min post
|
633.87±277.01
|
382.74±233.21*
|
494.79±152.59
|
647.14±150.38*
|
637.06±222.43
|
434.69±201.67*
|
|
30 min post
|
536.67±220.02
|
456.73±103.03
|
569.15±140.61
|
479.35±255.36
|
495.77±233.58
|
515.90±137.91
|
|
60 min post
|
512.30±256.27
|
457.77±280.95
|
505.48±203.00
|
155.58±176.77
|
485.96±221.96
|
493.63±243.92
|
|
GSH-PX (μmol/L)
|
Pre
|
222.67±67.33
|
218.59±76.15
|
202.24±64.43
|
213.29±61.85
|
219.17±64.58
|
210.41±70.31
|
|
0 min post
|
188.61±89.57
|
171.08±46.23
|
188.79±61.94
|
201.26±81.67
|
197.28±85.23
|
178.69±54.06 #
|
|
30 min post
|
206.36±70.60
|
191.88±54.75
|
199.63±48.46
|
205.95±83.74
|
209.24±76.02
|
195.78±51.91
|
|
60 min post
|
259.58±138.78
|
194.73±74.92
|
202.80±58.52
|
188.21±124.52
|
229.64±134.24
|
197.06±66.06
|
Note: Pre, before the intervention; 0 min post, immediately after the
intervention; 30 min post, 30 minutes after the intervention; 60 min post,
60 minutes after the intervention; OH·-, the ability to inhibit
hydroxyl radicals; GSH-PX, glutathione peroxidase activity;*indicates a
significant difference between the groups at the same time,
p<0.05.
The effects of HRG on fatigue perception
The GEE models demonstrated a significant interaction between group and time for
the primary outcome of fatigue perception, that is, the VAS (W=9.940, p=0.019).
Post-hoc analyses indicated that immediately post-exercise, the VAS of the HRG
group were significantly lower than those of the placebo group (p=0.008), but no
significant differences were observed between HRG group and placebo group at 30
and 60 minutes post-exercise (p>0.258). Similarly, the GEE models showed a
significant interaction between group and time for RPE (W=6.016, p=0.014).
Post-hoc analyses revealed that immediately post-exercise, the RPE of the HRG
group were significantly lower than those of the placebo group (p<0.001).
The effects of HRG on functional performance
The primary two-way repeated measures ANOVA models showed no significant
interaction between group and time for CMJ (F=2.723, p=0.113), although greater
performance in CMJ was observed after the intervention in HRG group than in the
placebo group (35.01 cm VS 32.53 cm). Secondarily, paired t-test models showed
that the cycling frequency during the last 30 seconds of the last segment in the
fatigue modeling process was significantly higher in the HRG group compared to
the placebo group (t=9.659, p<0.001). The cycling frequency during the last
30 seconds of all other segments in the fatigue modeling process were within the
range of 60–70 rpm ([Table 3]).
Table 3 Results for the last 30 seconds of cycling
frequency of ten phases throughout the fatigue modelling
process.
|
Phase 1
|
Phase 2
|
Phase 3
|
Phase 4
|
Phase 5
|
Phase 6
|
Phase 7
|
Phase 8
|
Phase 9
|
Phase 10
|
|
HRG group (n=24)
|
65.01±3.79
|
65.96±4.34
|
66.22±3.85
|
66.41±3.99
|
66.12±3.75
|
66.22±3.63
|
65.90±3.91
|
65.94±5.14
|
66.12±3.81
|
65.38±3.96
|
|
placebo group (n=24)
|
64.14±3.44
|
64.71±3.77
|
65.61±4.29
|
66.44±4.30
|
67.22±4.81
|
66.67±4.68
|
66.66±5.01
|
65.63±5.59
|
66.60±7.08
|
53.45±3.97*
|
Note: Cycling frequencies between 60–70 rpm meet the requirements, the
existence of the statistically significant differences in this range is
not meaningful; cycling frequency below 60 rpm indicates an inability to
maintain cycling requirements;*indicates a significant difference in
cycling frequency between the two groups, p<0.001.
The effects of HRG on blood sample markers
Two-way repeated measures ANOVA models showed a significant interaction between
group and time for LA and the ability to inhibit hydroxyl radicals (LA: F=8.993,
p=0.001; the ability to inhibit hydroxyl radicals: F=4.665, p=0.006), but not
for GSH-PX activity (F=0.314, p=0.815). Only main effect of time on GSH-PX
activity was observed (F=4.148, p=0.021). Post-hoc analyses revealed that there
were no significant differences between the LA of HRG group and placebo group
immediately after exercise (F=3.998, p=0.058), but the LA of HRG group was
significantly lower than that of placebo group at 30 minutes and 60 minutes
after exercise (F>5.500, p<0.028). The LA of HRG group returned to
pre-exercise levels at 30 minutes after exercise, while in the placebo group, it
returned to pre-exercise levels at 60 minutes after exercise. The ability to
inhibit hydroxyl radicals in HRG group was significantly higher than that in
placebo group immediately after exercise (F=8.671, p=0.009), but no significant
difference was observed at 30 minutes and 60 minutes after exercise (F<0.146,
p>0.707).
The association between the fatigue performance and the blood sample
markers
Based on the aforementioned results, we conducted a linear regression analysis to
examine the relationship between blood sample markers outcomes (i. e. LA, the
ability to inhibit hydroxyl radicals) and fatigue perception (i. e. VAS and RPE
scores) that were significant influenced by HRG within the HRG group. No
significant correlation between the percentage change in fatigue perception and
that in blood sample markers was observed (r<0.245, p>0.271).
Discussion
To our knowledge, this study is the first study to explore the effects of
pre-exercise HRG inhalation on exercise fatigue, functional performance and blood
markers after exercise. It was observed that the pre-exercise inhalation of HRG can
help alleviate the fatigue severity and to some extent improve functional
performance (i. e. the cycling frequency during the last 30 seconds of the last
segment in the fatigue modeling process) under the fatigue condition. Meanwhile, HRG
also accelerated the clearance of LA after strenuous exercise and enhanced the
ability to inhibit hydroxyl radicals, potentially demonstrating the underlying
mechanisms through which HRG can help alleviate the burden of fatigue after
exercise.
The primary findings here are that compared to the placebo, inhaling HRG before
exercise can significantly alleviate subjective fatigue perception after high-load
exercise, as assessed by VAS; and improve the ability to inhibit hydroxyl radicals.
This is in consistent with previous studies showing that hydrogen can alleviate the
fatigue and improve oxidative stress markers [15]
[17]
[32]. Additionally, the accelerated
recovery of LA by HRG was observed, which may be attributed to its capacity to
reduce excessive ROS, mitigate oxidative damage to mitochondria caused by ROS, and
enhance aerobic pathway utilization [33]. It has been suggested that HRW has an alkalizing effect that can help
neutralize LA [34], but it is still
unclear if HRG can have a similar effect, thus neutralizing LA and reducing its
concentration.
The development of exercised-related fatigue and decline in functional performance
may arise from increased ROS. The high-load physical exertion can disrupt electron
flow in mitochondria, trigger auto-oxidation of catecholamines, impede nicotinamide
adenine dinucleotide phosphate activity, or result in ischemia-reperfusion,
consequently inducing oxidative stress and elevating ROS generation [35]. The impact of ROS on mitochondrial
function is recognized as a significant contributor to fatigue [36]
[37]. Mitochondria are particularly susceptible to the effects of
ROS-induced oxidative damage of lipids, proteins, and DNA, resulting in a decline in
electron transfer and ATP synthesis. This leads to a decrease in the efficiency of
the aerobic pathway and an increase in the utilization of the anaerobic pathway,
which can result in elevated levels of inorganic phosphate and LA [33]. The changes in redox status caused
by increased ROS also trigger an increase in intracellular calcium ions and the
inactivation of intracellular enzymes, which can alter the action potential of
muscle contraction and interfere with the intramuscular potassium ion transport
system. Additionally, ROS can modify muscle contractile proteins (muscle
contraction) and calcium pumps (muscle control) [38], and damage one or more proteins
involved in excitation-contraction coupling, leading to a reduction in the
production of muscle force [5]. However,
HRG may counteract these issues by eliminating ROS [8]
[39]
[40] thus lead to the
observed improvement of the cycling frequency during the last 30 seconds of the last
segment in the fatigue modeling process in this work.
However, we did not observe a significant direct association between the HRG-induced
improvements in fatigue and the ability to inhibit hydroxyl radicals, indicating
that the observed fatigue alleviation may potentially arise from another potential
pathway. The prefrontal cortex (PFC) of the brain is considered a key area for
processing fatigue-related information [41]. Higher levels of fatigue are correlated with reduced activation in
the PFC [42]. In one of our recent
studies, we showed that the HRG helps significantly increase the excitability of the
PFC after the high-load exercise, and the changes in PFC excitability are associated
with the changes of the subjective perception of fatigue, as assessed by RPE [43]. This may reveal a “central” pathway
through which HRG can alleviate exercise-induced fatigue. Taken together, the
results here showed that the benefits of HRG for fatigue alleviation may not only
arise from alleviating oxidative stress in the periphery, but also from the
modulation of the excitability of the cortical regions, including the PFC. It is
thus highly demanded to comprehensively characterize the underlying pathways through
which intaking hydrogen can alleviate the exercise-related fatigue by measuring both
peripheral and central elements pertaining to the development of fatigue.
Several limitations should be acknowledged in our study. First, it is important to
note that the hydrogen generator utilized in this study also produces oxygen.
Although the concentration of oxygen inhaled into the human body is extremely minute
and does not independently impact fatigue performance (the minimum concentration of
oxygen required to affect fatigue and oxidative capacity is 70–96% [44]
[45]), there remains the possibility of a synergistic effect in
combination with hydrogen. Second, currently the appropriate dose and timing of HRG
has not been determined. In this study, we designed the HRG protocol based upon the
knowledge from previous studies [15],
which, however, did not induce expected significant improvement in CMJ height
(though higher height of the CMJ was observed after inhaling HRG than placebo). This
insignificance may be related to the insufficient statistical power due to
relatively small size, suggesting that future work with larger sample size of
participant is needed to determine the protocol that can maximize the benefits of
HRG. Third, the slightly higher concentrations of serum LA detected in this study
may be attributed to the freezing of blood samples at -80°C (the storage conditions
for oxidative markers of blood) and are not directly comparable to other studies.
But this did not affect the results of this study. Fourth, due to the considerable
individual variability and wide range of oxidative stress markers, the oxidative
stress biomarkers tested in this study were not comprehensive enough to fully
reflect the processes behind oxidative stress. Future study should employ
metabolomics and related methodologies to screen for hydrogen's metabolic
markers, aiming to elucidate these mechanisms through pathway enrichment analysis.
In addition, more research is needed in the future to validate the confidence and
validity of assays for their ability to inhibit hydroxyl radicals. Fifth, hydrogen
is not suitable for use in all situations. When the intensity of recreation and
training is low, the body's own ability to remove ROS is sufficient and
inhaling HRG will not produce an effect. Whether HRG can still improve performance
in elite athletes or play a decisive role in higher-level competitions remains to be
investigated. This also may affect whether hydrogen gas will be considered a banned
substance for performance enhancement.
