69ο NEWSLETTER

Οπγανιζμόρ Science Technologies

Έκδοζη Οκηυβπίος - Νοεμβπίος 2014

NEWSLETTER

Γεκέμβπιορ 2014

Σεύσορ 69

Πεπιεσόμενα

Πποπονηηική

Η επίδπαζη δπομικήρ πποπόνηζηρ ηασύηηηαρ ζε επικλινείρ επιθάνειερ

Γιώργος Παραδείζης Επίκοσρος Καθηγηηής Κλαζικού Αθληηιζμού – Δρόμοι Στολή Επιζηήμης Φσζικής Αγωγής & Αθληηιζμού - Ε.Κ.Π.Α

Άζκηζη

Δπγογενική επίδπαζη ςπεποξικήρ

αποκαηάζηαζηρ ζε ελίη κολςμβηηέρ

πος ππαγμαηοποιούν διαλειμμαηική

πποπόνηζη ςτηλήρ ένηαζηρ

Αθνινπζείζηε μαρ ζηο

Twitter

Βξείηε μαρ ζηο facebook

Γείηε ηο κανάλι μαρ

Δπηζθεθζείηε ηη ζελίδα

μαρ

Αγαπηηές –οί θίλες-οι,

Σαο παξνπζηάδνπκε κε κεγάιε ραξά ην 69ν ειεθηξνληθό καο πεξηνδηθό.

Σηηο ζειίδεο ηνπ πεξηνδηθνύ καο κπνξείηε λα πεξηεγεζείηε θαη λα

δηαβάζεηε δύν άθξσο ελδηαθέξνληα άξζξα: «Η επίδξαζε δξνκηθήο

πξνπόλεζεο ηαρύηεηαο ζε επηθιηλείο επηθάλεηεο» ηνπ Δπίθνπξνπ

Καζεγεηή Σ.Δ.Φ.Α.Α Γηώξγνπ Παξαδείζε θαη ην άξζξν «Δξγνγεληθή

επίδξαζε ππεξνμηθήο απνθαηάζηαζεο ζε ειίη θνιπκβεηέο πνπ

πξαγκαηνπνηνύλ δηαιεηκκαηηθή πξνπόλεζε πςειήο έληαζεο» όπνπ

ρξεζηκνπνηείηαη ε ζπζθεπή πξνζδηνξηζκνύ νμεηδσηηθνύ ζηξεο Form

CR 3000 (Callegari, Parma, Italy) ηελ αληηπξνζσπεία ηεο νπνίαο έρεη

ε εηαηξία καο.

Δπίζεο ζα έρεηε ηελ επθαηξία λα δείηε κηα ζεηξά από δξαζηεξηόηεηεο,

λέα, ηόζν γηα ηα ηεθηαηλόκελα ηεο εηαηξείαο καο όζν θαη γηα ησξηλά θαη

κειινληηθά δξώκελα ζηε Διιεληθή θαη Κππξηαθή Δπηθξάηεηα ζηνπο

ρώξνπο ηεο Υγείαο-Άζθεζεο-Γηαηξνθήο-Δπεμίαο!

Σας εστόμαζηε καλή ανάγνωζη

Με εκηίμηζη,

Ο γσρολόγος

69ο NEWSLETTER

1

ΠΕΡΙΛΗΨΗ

Σθνπόο ηεο έξεπλαο ήηαλ λα εμεηάζεη ηελ επίδξαζε ηεο πξνπόλεζεο ζε επηθιηλείο επηθάλεηεο (3ν) ζε

ζπγθεθξηκέλεο θηλεκαηηθέο θαη θπζηνινγηθέο παξακέηξνπο. Τξηαληαπέληε θνηηεηέο θπζηθήο αγσγήο ρσξίζηεθαλ

ηπραία ζε 4 νκάδεο πξνπόλεζεο (αλσθέξεηα-θαησθέξεηα, θαησθέξεηα, αλσθέξεηα θαη νξηδόληηα επηθάλεηα) θαη

κία νκάδα ειέγρνπ κε 7 ζπκκεηέρνληεο ζε θάζε νκάδα. Πξαγκαηνπνηήζεθαλ κεηξήζεηο πξηλ θαη κεηά ηελ

πξνπόλεζε γηα ηελ εμέηαζε ηεο επίδξαζεο 6 εβδνκάδσλ πξνπόλεζεο ζηελ κέγηζηε δξνκηθή ηαρύηεηα ζηα 35 m,

ηνλ ξπζκό δηαζθειηζκνύ, ην κήθνο δηαζθειηζκνύ, ηνλ ρξόλν επαθήο, ηελ έθθεληξε θαη ζύγθεληξε θάζε ηνπ

ρξόλνπ επαθήο, ηνλ ρξόλν πηήζεο, ζε ζπγθεθξηκέλα ραξαθηεξηζηηθά ηεο ζηάζεο ηνπ ζώκαηνο ηνπ δξνκηθνύ

θύθινπ θαη ζηελ κέγηζηε αλαεξόβηα ηζρύ. Η κέγηζηε δξνκηθή ηαρύηεηα θαη ε ζπρλόηεηα δηαζθειηζκνύ απμήζεθε

ζεκαληηθά κεηά ηελ πξνπόλεζε (p < 0.05) ζην ηεζη ησλ 35-m θαηά 0.29 m.s_1 (3.5%) θαη 0.14 Hz (3.4%) γηα

ηελ νκάδα ζπλδπαζκνύ αλσθέξεηαο-θαησθέξεηαο the combined θαη θαηά 0.09 m.s_1 (1.1%) θαη 0.03 Hz (2.4%)

γηα ηελ νκάδα θαησθέξεηαο, ελώ ν ρξόλνο πηήζεο κεηώζεθε κόλν γηα ηελ νκάδα αλσθέξεηαο-θαησθέξεηαο θαηά

6 milliseconds (4.3%). Γελ ππήξραλ ζεκαληηθέο δηαθνξέο ζηηο νκάδεο νξηδόληηαο επηθάλεηαο θαη ειέγρνπ.

Σπλνιηθά ηα ραξαθηεξηζηηθά ηεο ζηάζεο ηνπ ζώκαηνο θαη ε κέγηζηε αλαεξόβηα ηζρύο δελ άιιαμαλ κεηά ηελ

πξνπόλεζε. Γηαθαίλεηαη όηη ε ζπλδπαζηηθή κέζνδνο αλσθέξεηαο-θαησθέξεηαο είλαη ζεκαληηθά πην

απνηειεζκαηηθή ζηελ βειηίσζε ηεο κέγηζηεο ηαρύηεηαο ζηα 35 m θαη ηα ζπζρεηηδόκελα κε ηελ δξνκηθήο ηερληθή

ζηα ζπξηλη θηλεκαηηθά ραξαθηεξηζηηθά από όηη πη άιιεο πξνπνλεηηθέο κέζνδνη.

Τν άξζξν έρεη δεκνζηεπζεί σο:

Paradisis, G.P., and C.B. Cooke. The effects of sprint running training on sloping surfaces. Journal of

Strength and Conditioning Research 20(4):767–777. 2006

INTRODUCTION

any different sprint training programs,

including sprint-resisted and -assisted

methods, have been used with the aim of

improving maximal sprint running performance by

changing step length and step rate, which are the

components of speed (6). Sprinting up inclined

surfaces is one of the sprint-resisted training

methods that is commonly used, whereas sprinting M

Πποπονηηική

The effects of sprint running training on sloping surfaces

Η επίδξαζε ηεο δξνκηθήο πξνπόλεζεο ηαρύηεηαο ζε επηθιηλείο επηθάλεηεο

Παξαδείζεο Γηώξγνο

Δπίθνπξνο Καζεγεηήο Κιαζηθνύ Αζιεηηζκνύ – Γξόκνη

Σρνιή Δπηζηήκεο Φπζηθήο Αγσγήο & Αζιεηηζκνύ Δ.Κ.Π.Α

69ο NEWSLETTER

down inclined surfaces is among the most popular

sprint-assisted training methods.

Despite the wide use of these training methods,

little objective evidence is available regarding their

effects on performance, with almost no research

studies that have assessed objectively the kinematic

and physiological adaptations associated with these

forms of training. Even though there are some

unsubstantiated claims that uphill and downhill

training improved maximum running speed, as well

as step rate and step length (3, 5, 6, 23, 27), only

Tziortzis (27) has reported experimental data for

the effects of uphill and downhill training on

horizontal running. After 12 weeks of training on a

downhill slope of 8_, the maximum running speed

improved by 2.3% (8.97 ± 0.43 m.s_1 to 9.18 ±

0.36 m.s_1, p < 0.05) and the step length increased

by 1.4% (2.20 ± 0.09 m to 2.23 ± 0.09 m, p <

0.05). Uphill training on the same slope for 12

weeks produced a 3.3% increase in the maximum

running speed (from 8.92 ± 0.51 m.s_1 to 9.21 ±

0.48 m.s_1, p < 0.05) and a 2.4% increase for step

rate (from 4.2 ±0.4 Hz to 4.3 0.4 Hz, p < 0.05).

However, there were no data on the effects of sprint

training on sloping surfaces on postural

characteristics.

One important consideration of training on sloping

surfaces is the magnitude of the slope. Some

authors have recommended the use of sprinting

downhill on slopes as a stimulus to increase

maximum running velocity, suggesting slopes of

around 3ν (3, 6, 23, 27), although Milakov and Cox

(18) stated that in downhill sprinting, the slope

should not exceed 2.6ν .Dintiman (6) stated that too

steep a slope is likely to significantly change the

mechanics of sprint running, decreasing the

potential for transfer of such training to horizontal

sprinting performance. However, there was no

evidence presented to support these

recommendations in these publications or

elsewhere. Too steep a slope is also more likely to

lead to injury and falls due to a loss of control when

sprinting downhill.

The selection of a 3ν slope for the present study was

based on the middle of the range of slope

magnitudes recommended in the literature, even

though there is an acceptance that such

recommendations are not based on research

evidence. There is, however, evidence that such a

slope does change the maximum velocity of sprint

running (13, 14, 19, 25).

Given that both uphill and downhill running have

been suggested to improve sprint running

performance and that Tziortzis (27) has provided

some objective evidence to support this anecdotal

observation, one obvious development is to combine

these 2 different training stimuli in training. As was

the case for training either uphill or downhill, there

are statements in the sprint training literature that

the combination of uphill and downhill training

should result in greater increases in performance

than traditional forms of sprint training do (6, 18).

However, no study has systematically investigated

this combined uphill-downhill sprint training method

in terms of changes in performance coupled with an

evaluation of the kinematic and physiological

adaptations to training.

The aim of this study was to identify and quantify

the effects of 6 weeks of training on uphill (3ν ),

downhill (3ν ), horizontal, and novel combined uphill

and downhill (3ν ) surfaces on the kinematic and

posture characteristics of 35-m sprint running and

performance in the Wingate Anaerobic Test.

It was hypothesized that 6 weeks of sprint training

on uphill, downhill, the novel combined uphill-

downhill, and horizontal surfaces would result in

significant changes in maximum running velocity

and associated variables such as step rate, step

length, contact time, and flight time, but would lead

to no significant changes in posture variables. Given

the difference in training stimulus associated with

uphill and downhill slopes, it also was hypothesized

that the specific effects of training on uphill and

downhill surfaces might be different. Finally, it was

hypothesized that the novel combined condition

would produce an interactive effect between training

on uphill and downhill that would result in a greater

training benefit than the other training methods

would.

METHODS

Experimental Approach to the Problem

In order to test the hypotheses of the study

following research design was used: 1) aim: effects

of sprint training; 2) research design: five

independent randomly assigned training groups; 3)

training: 6 weeks, 3 times per week; 4) testing:

pretraining and posttraining; 5) data collected:

kinematic, posture characteristics, and Wingate

test.

69ο NEWSLETTER

FIGURE 1. The uphill-downhill platform

Subjects

Thirty-five students participated in this study (age,

23.8 ± 1.4 years; mass, 75.9 ± 9.5 kg; height,

1.76 ± 0.07 m). All subjects were active in different

sports, but none was a sprinter; their mean

maximum running speed was 8.10 ± 0.54 m·s_1.

However, in order to participate in this study, all

subjects were asked to terminate other sport

activity. Informed consent was obtained from each

participant before data collection. A wooden uphill-

downhill platform was used that was 80 m long and

1.20 m wide, and it was covered with synthetic

track surface. The platform consisted of 5 sections,

arranged in the following order: (a) a 20-m

horizontal section; (b) a 20-m uphill section at 3ν

slope; (c) a 10-m horizontal section; (d) a 20-m

downhill section at 3ν slope; and (e) a 10-m

horizontal section (Figure 1).

Training

The participants were assigned randomly to 5

groups: (a) U+D was trained on the uphill-downhill

platform; (b) U was trained on the uphill segment of

the platform; (c) D was trained on the downhill

segment of the platform; (d) H was trained on the

horizontal; (e) C was the control group and did not

perform any kind of training.

It is worth noting that when using randomization,

possible confounding variables such as differences

in sprint training experience, leg strength, and

power may influence the group data more with such

small groups than with larger group sizes. However,

a comparison of the groups showed no significant

difference at baseline in terms of the primary

performance variable of maximum running velocity

at 35 m, suggesting that the randomization process

had been effective.

All training groups were trained over the same total

running distance at maximal intensity, after

completion of a 20-minute warm-up. The combined

uphill-downhill and horizontal groups performed 6

repetitions of 80-m sprints 3 times a week, where

the recovery time between repetitions was 10

minutes, sufficient for the participants to recover

fully (15). The uphill and downhill groups each

performed 12 repetitions of 40-m sprints per

session, 3 times a week, with a 10-minute recovery

time between repetitions. This training program

continued until the fourth week. For each of the

remaining 2 weeks, 1 repetition was added for the

combined uphill-downhill and horizontal groups and

2 repetitions were added for the uphill and downhill

groups. The control group maintained its normal

physical activities throughout the 6-week

experimental period, without performing any kind of

training. A repeated-measures analysis of variance

(ANOVA) showed no significant differences between

the groups for all the pre-training tests.

Testing

Pre- and post-training tests were employed to

evaluate the effects of training on the kinematic and

posture characteristics of sprint running and peak

anaerobic power performance. In order to assess

the effects of training, the 35-m maximal sprint

running test was used (16). The sprints were

performed in a corridor 60 m long and 2.5 m wide in

the biomechanics laboratory, and the floor was

covered with a synthetic track surface (tartan) 55 m

long and 2.5 m wide. The corridor was well lit and

the ambient temperature was 25ν C. After

completion of a 20-minute warm-up, the

participants performed 3 maximal sprint runs over a

35-m distance, using a standing start. The adoption

of 3 trials for each participant was to establish the

magnitude of variability associated with repeated

trials.

A Kodak EktaPro 1000 high speed video camera

(Kodak, Hamburg, Germany) was used to collect

video recordings of the sagittal plane of a full stride

(2 consecutive steps) of all 3 maximal sprint runs,

sampling at 250 Hz. Filming was performed with the

camera placed at the 35-m distance and 10 m from

the performance plane, such that its optical axis

was approximately horizontal and formed an angle

69ο NEWSLETTER

of 90_ with the horizontal plane of running. The

time between repetitions (10 minutes) was

sufficient for the participants to recover fully (15). A

metal calibration frame (2 ρ 2 m) was filmed such

that the x axis was parallel to the horizontal and the

y-axis was perpendicular to the horizontal.

Wingate Anaerobic Test

A 6-second Wingate test was used to determine the

peak anaerobic power index and consisted of a 6-

second maximal sprint on a modified cycle

ergometer (Monark 814E; Monark, Vansbro,

Sweden) against a braking force of 0.075 kg.kg of

body mass_1. This test was included to establish

whether any adaptations to training transferred to a

different mode of exercise than that used in

training. These data will be useful in characterizing

the specific and general responses to sprint training

that uses running on sloping surfaces. Initially, the

participants were instructed to perform a warm-up

activity for 5 minutes by cycling at 60 rev.min_1 with

1.5-kg load. After a 5-minute rest period, each

participant performed 3 all-out trials and the best of

the 3 trials was analyzed. The participants were

instructed to attain an initial pedaling frequency of

80 rev.min_1 with 0.5-kg resistance. When this

pedal rate was achieved, the load was applied and

the participants accelerated, pedaling maximally for

6 seconds. The time between repetitions (10

minutes) was sufficient for the participants to

recover fully (15).

Analysis of the Video Data

The hardware of the digitizing system comprised a

video projector Imager LCD 15E (LG, Berkshire,

UK), a TDS graphic tablet and controller (TDS Ltd.,

London, UK; x,y resolution, 0.025 mm; active area

1.20 ρ 0.90 m), interfaced to a 486SX IBM

computer that ran the digitizing program DIGIT

(Leeds Metropolitan University, Leeds, UK). A

standard 17-point (24), 14-segment model based

on the data of Dempster (4) was used to represent

the human performer and to calculate the position

of the center of mass. Surface markers were used in

the process of digitization when clearly visible.

When the markers were not clearly visible, the

digitizer operator identified the points for

digitization based on superficial anatomical

landmarks and an understanding of axes of rotation

at the joints (2). Digitized points consisted of the

vertex of the head and both right and left joints

(glenohumeral, elbow, wrist, third

metacarpophalangeal, hip, knee, ankle, fifth

metatarsophalangeal). Additionally, 2 control points

also were digitized for each frame to compensate

for any movement of the projected image. The

following segments were defined: head and neck,

trunk, right and left upper arm, forearm, hand,

thigh, shank, and foot. Before storing the data on

disk, each frame was checked visually after

digitization using a stick figure drawn on the screen

of the computer to detect any digitizing errors. This

visual analysis checked that the points were

digitized in the correct order to represent the

appropriate landmarks.

FIGURE 2. Location of the body landmarks and

visualization of the angles. DCM _ the distance parallel to

the running surface between a line perpendicular to the

running surface which passes through the center of mass

and the contact point; δ = trunk to running surface; β =

angle of the hip;α = angle of the knee; γ = shank to

running surface.

For each trial, digitizing started 3 frames before the

touchdown of the ipsilateral foot and ended 3

frames after the touchdown of the contralateral

foot. This provided sufficient redundant data for

smoothing. ‘‘Touchdown’’ was defined as the instant

at which the participant made contact with the

ground and ‘‘takeoff’’ as the instant at which the

participant broke contact with the ground. The

appropriate frames defining touchdown and takeoff

were identified through visual inspection by the

researcher who digitized all the trials. Prior to

further processing, the displacement-time data for

the digitized joint landmarks were smoothed via a

second-order quintic spline curve-fitting program

(29).

The step cycle had as a starting point touchdown of

the ipsilateral foot; it continued through the flight

phase and terminated at touchdown of the

contralateral foot. The 3 recorded step cycles (1

step cycle from each of the 3 trials) for each

participant were digitized. Although there were no

explicit objective selection criteria, any trial not

69ο NEWSLETTER

considered by either the participant or the

researcher to be a maximum effort was excluded.

Contact time, flight time, step time, step length,

flight distance, step rate, and maximum running

speed were calculated according to the methods of

Mero and Komi (16). Contact time was defined as

the period of time from the touchdown of the

ipsilateral foot to the takeoff of the same foot. Flight

time was defined as the period of time from the

takeoff of the ipsilateral foot to the touchdown of

the contralateral foot. Step time was defined as the

period of time of a step. Step length was defined as

the horizontal distance covered by the center of

mass along the line of progression during a step.

Flight distance was defined as the horizontal

distance covered by the center of mass along the

line of progression from the takeoff of the ipsilateral

foot to the touchdown of the contralateral foot. Step

rate was defined as the number of steps per second.

Maximum running speed (MRS) was calculated in

terms of the average speed of a step cycle

according to the formula:

MRS = SL ‚ (CT + FT),

where SL is step length, CT is contact time, and FT

is flight time. Running speed was recorded at the

end of the 35-m distance so that it would be close

to maximal running speed, because the literature

has showed that maximal running speed is achieved

at about 30 m (20, 21).

For the touchdown and takeoff frames, we also

calculated the angles of the knee (α), hip (β), shank

to running surface (γ), trunk to running surface (δ;

trunk angle was determined by the line between the

hip and glenohumeral joints of the right side of the

body), thigh to running surface (ε) and that

between the two thighs (thighthigh; δ), and the

distance parallel to the running surface between a

line perpendicular to the running surface which

passes through the center of mass and the contact

point at touchdown (DCM TD) and at takeoff (DCM

TO; Figure 2).

FIGURE 3. Hierarchical model illustrating the possible

contribution of performance parameters to the criterion

performance variable of running speed, based on Hay and

Reid (10). DCM _ the distance parallel to the running

surface between a line perpendicular to the running

surface which passes through the center of mass and the

contact point at touchdown (TD) and takeoff (TO). A ‘‘#’’

indicates variables directly derived from video in the

present study.

Theoretical Model of Sprint Running

Figure 3 shows a hierarchical model for sprint

running based on a model proposed by Hay and

Reid (10). Any significant changes in measured

variables due to the effects of training can be

related back to this model to determine the

interaction of changes that combine to alter both

the performance criterion of maximum running

speed and the higher level performance parameters

of step length and step rate.

There were some differences between the model in

the present study and that proposed by Hay and

Reid (10). First, Hay and Reid (10) used time for a

set distance as the criterion measure, whereas the

present study focuses on the maximum running

speed measured at 35 m. In the present study,

body posture is further represented by angles of the

shank, knee, hip, thigh, and trunk, thus directly

influencing the DCM TO and DCM TD.

Figure 3 shows the performance parameters

measured in the present study. Although air

resistance, height at takeoff, and speed at takeoff

were not measured, changes in these variables will

be reflected by changes in flight distance and flight

time. As noted by Hay and Reid (10), this explains

in part why it is difficult to increase step length

without decreasing step rate. For the aims of the

present study, any changes measured in the higher

level performance parameters should account for

any changes in maximum running speed, with the

angles specifically reflecting any change in posture

69ο NEWSLETTER

as a consequence of the 3ν uphill and downhill

slopes. Reference to this model should assist in

evaluating the specific adaptations to sprint training

on horizontal, uphill, downhill, and combined sloping

surfaces.

Digitizing Reliability

Reliability of the digitizing process was established

in one of our previous studies (22) by repeated

digitizing of 1 sprint running sequence at the same

sampling frequency with an intervening period of 48

hours. The limits of agreement method (1) was

used to compare these repeated digitized sequences

and produced values for the mean ± standard

deviation (SD) of the differences of 0.004 ± 0.016

m (the boundaries of agreement were -0.015 m and

0.035 m, using the equation δ ± 1.96 ζ, where δ =

mean of differences between repeated digitized

sequences and ζ = standard deviation of these

differences, because the heteroscedasticity

correlation was close to zero). Based on these

values, the differences in the calculated parameters

between the repeated trials were 9 mm (0.46%) for

step length, 0.08 m·s_1 (0.50%) for maximum

running speed, 2 mm (0.50%) for the DCM, and 1 ±

0.63ν (0.81 ± 0.45%) for the calculated angles.

Statistical Analyses

A 3-way ANOVA with repeated measures on all

factors (trial ρ test group) was used to establish if

there were any significant differences between the

trials, the tests (pre- and post-training), and the

groups (training groups) and for any interactive

effects. Each dependent variable was analyzed using

a separate ANOVA. A multivariate ANOVA, used to

analyze all dependent variables, was not completed,

because there were insufficient participants for the

required degrees of freedom. In the event of

significant main effects, a post hoc Tukey test was

used to locate the differences. The significance level

for the tests was set at p < 0.05.

FIGURE 4. A Bland-Altman plot for the left and right step

contact time. The differences between the left and right

steps are plotted against each participant mean for the

left and right steps. The 95% limits of agreement also are

presented on the plot.

RESULTS

Comparison of the 3 Trials

To assess the consistency among the 3 trials, a

comparison was performed across the groups.

Factors that could affect the consistency include

fatigue, lack of familiarization, boredom, natural

variation, insufficient warm-up, and lack of

motivation. There was no significant difference in all

the analyzed variables among the 3 trials for all

groups.

Comparison of Left and Right Leg

In the analysis of the pre- and post-training tests,

contact time was measured from the left foot

throughout. This was justified through a comparison

of left and right foot contact times using the limits

of agreement method (1). The mean ± SD of the

differences between left and right feet was 0.001 ±

0.003 seconds, and the boundaries of agreement

were -0.008 and 0.005 seconds (based on the

equation δ ± 1.96 ζ , because the

heteroscedasticity correlation was close to zero;

Figure 4). Given these results, it was concluded that

there were no significant differences between the

contact times for the left and right foot.

Effects of Different Training Methods

Kinematic Characteristics. A repeated-measures

ANOVA showed a significant main effect for the pre-

and post-training tests for maximum running speed

(F = 18.97; p < 0.05), step rate (F = 9.68; p <

0.05), flight time (F = 8.76; p < 0.05), and step

time (F = 9.53; p < 0.05). Maximum running speed

increased significantly after 6 weeks of training for

the combined uphill-downhill (Tukey, p < 0.05) and

downhill (Tukey, p < 0.05) training groups by 3.5%

and 1.1%, respectively, whereas it was not

statistically significant for the uphill and the

horizontal groups (Table 1). In the combined uphill-

downhill training group, all participants produced

increases in the maximum running speed (range,

0.18–0.40 m·s_1), and in the downhill group, 4

participants increased their maximum running

speed (range, 0.10–0.17 m·s_1). In the uphill and

horizontal groups, however, 3 participants increased

their maximum running speed.

Similarly, step rate increased significantly (Tukey, p

< 0.05) for both combined uphill-downhill (3.4%)

69ο NEWSLETTER

and downhill (2.4%) groups, whereas it did not

increase significantly for the uphill, horizontal, and

control groups (Table 1). Six participants out of 7

increased their step rate for both the combined

uphill-downhill and downhill groups (range, 0.11–

0.39 Hz and 0.06–0.25 Hz, respectively), whereas 3

participants increased it for the horizontal group and

only 1 participant increased it in the uphill group.

The flight time shortened significantly (Tukey, p <

0.05) only for the combined uphill-downhill group (-

4.3%) after the 6 weeks of training; for the

downhill group it was not significantly different,

although the p value was near to the critical level (-

3.1%; p = 0.06). The changes for the other groups

were not significantly different (Table 1). Six

participants out of 7 shortened their flight time for

the combined uphill-downhill group (range, 2–17

milliseconds), 4 participants shortened it for the

downhill and horizontal groups, and 3 participants

shortened it for the uphill group.

Step time was shortened significantly (Tukey, p <

0.05) for both combined uphill-downhill (-3.3%) and

downhill (-2.5%) groups, whereas it was not

significantly different for the uphill, horizontal, and

control groups (Table 1). Six participants out of 7

shortened their step time for the combined uphill-

downhill and downhill groups (range, 6–17

milliseconds and 4–13 milliseconds, respectively), 3

participants shortened it for the horizontal groups,

and 2 participants shortened it for the uphill group.

Finally, step length and contact time did not show

any statistically significant change for all the groups

after the 6 weeks of training (Table 1).

Eccentric and Concentric Phases of Contact.

There were no significant changes in the eccentric

or concentric phases of contact time for the

different training groups after the 6 weeks of

training (Table 2).

Posture Characteristics. There was generally no

effect on the posture characteristics for touchdown

and takeoff after the 6 weeks of training. The only

significant change was in the shank angle (p <

0.05) during touchdown, which increased by 5ν in

the combined uphill-downhill group (Table 3 and

Table 4).

Peak Anaerobic Power. The results of the best

trial of the Wingate test are shown in Table 5. There

were no significant differences between the pre- and

post-training tests for the Wingate tests. These

findings suggested that the training had not

increased the ability to generate a higher peak

anaerobic power output in an alternative mode of

exercise (Table 5).

69ο NEWSLETTER

69ο NEWSLETTER

DISCUSSION

Three trials in both pre- and post-ηraining tests

were used to establish whether there was significant

variation in repeated trials for the same conditions.

The statistical analyses showed no significant

changes between the 3 trials for any of the groups,

suggesting that there was good consistency among

the 3 trials. Additionally, in order to calculate the

maximum running speed, the first step of the stride

was analyzed while assuming that there was no

significant difference between the first and the

subsequent step. The results showed that this

assumption was correct and there was very little

difference between the steps, as shown by the

analysis according to Bland and Altman’s (1) limits

of agreement method.

In one of our previous studies (22), the

repeatability of the calculated parameters was

established in terms of the magnitude of differences

in comparing the same variables across the tests

and groups used in this study. The variability from

the repeated digitization of the same trial was less

than 1% for all variables compared in the Results

section. The results, therefore, may be deemed

reliable to give confidence in the comparisons made

across the tests and groups in this study.

In the present study, there were no significant

differences between the pre- and post-training tests

for all the analyzed variables in the C group.

Tziortzis (27) performed a similar study and

observed 0.9% difference in maximum running

speed between pre- and post-training for the C

group, whereas the differences in step length and

step rate were 0% and 2.4%, respectively. Gutoski

(8) and Irwin (11) also reported similar results. It

can be concluded that the results of the present

study were not influenced by a learning effect,

which means that the familiarization of the

participants before the pre-training tests was

sufficient. Therefore, it can be argued that if any

differences between pre- and post-training tests

were observed for experimental groups, they would

be due to the effects of the training followed by

each group.

The horizontal group showed trends to increase

maximum running speed (1.8%), step rate (1.3%),

and contact time (1.6%) but these differences were

not statistically significant. Additionally, the

horizontal training method produced no significant

changes in posture characteristics after training.

The reason for the lack of statistical evidence to

support these changes was the large interparticipant

variation (3 out of 7 subjects improved the

maximum running speed). Dintiman (5, 6), after 8

weeks of horizontal training, observed an

improvement of 5.2% in performance for 50 m, and

Suellentrop (26) found a 2.5% improvement in 100

m performance after 6 weeks of training, but there

are no experimental data regarding changes in

maximum running speed, step rate, step length,

contact time, and flight time, in the literature.

Unfortunately, comparison of these studies with the

present study was not possible because not only the

training period and program were different but also

the criterion of the effects of training was

performance in 50 and 100 m, respectively. Even

though the correlation between maximum running

speed and performance is very high (r = 0.90) in

100-m races (9, 18), there are many parameters

that can affect performance, such as start,

acceleration, maintenance of maximum running

speed, and deceleration. The results of this study

showed that traditional horizontal training tended to

produce improvements in the analyzed variables,

but these improvements were not statistically

significant.

The uphill group showed trends to increase

maximum running speed (1.0%), step length

(1.6%), and contact time (2.4%) but these

differences were not statistically significant. The

eccentric phase of contact time decreased by 7.4%

and the concentric phase increased by 12.2%, but

these changes also were not significant. The reason

for the lack of statistical evidence to support these

changes was the large interparticipant variation.

Overall, uphill training tended to produce a shorter

eccentric phase and longer concentric phase. During

the eccentric (braking) phase, the leg muscles and

tendons oppose the downward movements of the

center of mass, whereas during the concentric

(propulsion) phase, the muscles generate force to

propel the body forward. Komi (12) classified

running as a stretch-shortening cycle exercise

(SSC). Komi (12) found that at high speeds (7–9.5

m·s_1) an appreciable fraction of the power appears

to be sustained by the mechanical energy stored in

the series elastic elements during stretching of the

contracted muscles and is released immediately

after, in the concentric phase. The trend for the

eccentric phase to decrease with uphill training

could mean that during contact, less mechanical

energy was stored in the series elastic elements and

consequently was released immediately after, in the

concentric phase, which may explain the reason

why a greater concentric phase occurred.

69ο NEWSLETTER

There are unsubstantiated claims that uphill training

increased maximum running speed and step length

(3, 7, 21, 22). Tziortzis (27) found a significant

increase in the maximum running speed by 3.3%

and step rate by 2.4%, although step length did not

change. However, the training period in the present

study was 6 weeks, whereas Tziortzis (27) used 12

weeks. Additionally, different slopes were used in

these 2 studies: the uphill slope in the present

study was 3ν, whereas Tziortzis (27) used 8ν. The

difference in the slope would be expected to

generate different demands on the musculoskeletal

and neural systems, because the external overload

is increased with the greater slope. According to

Milakov and Cox (18) and Dintiman (6), the uphill

slope should not exceed 3.4ν , otherwise the

running style could be changed dramatically.

Unfortunately, Tziortzis (27) did not examine the

effects of training on the posture characteristics, so

a definite conclusion cannot be made with regard to

such changes. Based on the data from these 2

studies and the limited information from the

literature, it can be concluded that the different

responses in step rate and length in these 2 studies

possibly were due to differences in the training

period and slope, with the latter probably being the

most important factor.

Uphill training did not produce any significant

changes in the posture characteristics, suggesting

no significant or consistent alteration in the running

pattern of the participants. Unfortunately, there are

no studies to provide experimental information on

the effects of specific training methods on posture

characteristics, so a comparison with the results of

the present study cannot be made. However, many

authors suggested that the aim of any training

method is to improve performance without

significantly altering the athlete’s running pattern

(4, 6, 21).

Downhill training produced a significant increase in

maximum running speed (1.1%) and step rate

(2.4%), but not in step length, which was similar to

the findings of Tziortzis (27). Even though the

relative magnitude of the improvement was similar

to that of the uphill and horizontal groups, the

downhill group produced significant differences

because all 7 participants increased their maximum

running speed (range, 0.10–0.17 m·s_1). In a

previous study, downhill running produced a greater

step length and almost the same step rate was

observed in comparison to horizontal running (22).

The effects of 6 weeks of training on a downhill

slope resulted in a greater step rate with no change

in the step length measured on the horizontal. After

training, the parameter that was assisted by the

downhill slope (step length) was not improved,

whereas the reverse happened to the parameter

that was overloaded (step rate). It seems that the

assisted (downhill) and resisted (uphill) methods

produce improvements in a similar way (the same

scenario occurred in the uphill training method, with

a tendency for the step length to improve with

training). In order for a parameter to be improved,

it has to be overloaded through the facilitation of

the second parameter. In uphill running, the

facilitated parameter was step rate and through the

repetition of this stimulus, the step length

(overloaded) tended to improve, whereas the

opposite occurred with downhill training.

The improvement in step rate was due to the

shorter step time, which decreased significantly by

2.5%. The step time is actually the sum of the

contact time and flight time (Figure 3). The contact

time was shorter by 0.8% and the flight time by

2.5%. However, these variables did not show any

significant changes even though their sum (step

time) was improved significantly.

The results for the concentric phase showed that 4

out of 7 participants produced a shorter concentric

phase, whereas the mean concentric phase for the

group produced a 6.4% decrease. This seems to be

the most important adaptation to downhill training,

which may account for the improvement in

maximum running speed. According to Dintiman

(6), a greater maximum running speed should be

achieved through a shorter contact time (Figure 3).

The effect of downhill training was a tendency for a

shorter concentric (propulsive) phase, which could

be interpreted as a suggestion of improved muscle

power (greater amount of force in a shorter period

of time). However, this suggestion of improvement

in the force-time characteristics of the muscle is

hypothetical and needs to be evaluated. The effects

of the downhill and uphill training methods on

contact time were different. The effect of uphill

training produced a tendency for a shorter eccentric

phase and a longer concentric phase, whereas the

effect of the downhill training was the reverse. The

results of the present study indicated that the

downhill training method appeared to be more

effective in terms of improving kinematic variables

than the uphill training method, even though the

differences were small.

69ο NEWSLETTER

The effect of downhill training on the posture

characteristics was not statistically significant. It

can be concluded that downhill training on a 3o

slope does not alter the participant’s running

pattern, which means that the changes observed

were not due to a different running style, but more

probably reflect changes in the muscle activation

and contractile characteristics.

From the hierarchical model of sprint running, the

major changes after downhill training were a

significant increase in the criterion performance

variable (i.e., maximum running velocity) and 2

performance parameters (i.e., step rate and step

time). This reflected the accumulated changes in

contact (eccentric and concentric phases) and flight

time (Figure 3).

The novel combined uphill-downhill training

produced a 3.2% overall increase in the kinematic

variables, with an increase in maximum running

speed at 35 m by 3.4%(range, 0.18–0.40 m·s_1).

The changes in maximum running speed were

accompanied by an increase of step rate by 3.4% (p

< 0.05), whereas the step length did not change.

The increase of step rate was mainly due to a

shorter flight time (-4.3%) and contact time (-

2.1%). However, these changes were not

statistically significant. The effects of the combined

uphill-downhill method on the eccentric phase and

concentric phase were similar to those of the

downhill group and opposite to those of the uphill

group, but there were no significant changes.

However, the concentric phase showed a trend to

be shorter, which produced a mean decrease of

8.9%. This adaptation appeared to be the main

reason for the improvement in maximum running

speed after training with the combined uphill-

downhill training method.

Despite the significant changes that occurred in

almost all the kinematic variables after the training

period, the combined uphill-downhill did not

produce significant changes in the posture

characteristics. The only exception occurred for the

shank angle at contact, which was 5o larger (5.1%).

This can be explained by the decrease of the trunk

angle by 4o , which produced a small forward lean of

the body during contact. However, this forward lean

did not affect the related angles (knee and hip). It

can be concluded that the combined uphill-downhill

training method did not alter the participant’s

running pattern.

There are few references in the literature

concerning the effects of combined uphill-downhill

training methods. Dintiman (6) proposed that a

combination of training methods (uphill and

downhill) should produce better results than any

other training method. Milakov and Cox (18)

indicated that a combination of uphill and downhill

training would improve all the running parameters

to the maximum. These suggestions are partly

supported by the findings of the present study,

which showed that the combined method of training

on the uphill, horizontal, and downhill produced

significant improvements in maximum running

speed and in step rate.

The results of the present study indicated that the

training employed did not improve performance in

the Wingate test. This supports the importance of

the principle of specificity of training. Training in the

same mode of exercise on sloping surfaces

translates to improved maximum horizontal

sprinting speed measured at 35 m, but does not

translate to improvements in sprint performance in

a different mode of exercise. This also suggests that

the training benefits are not related to generic

physiological adaptations to anaerobic power and

performance. If such generic adaptations had

occurred, these would have manifest themselves in

similar changes in both forms of sprinting (i.e.,

running and cycling).

Overall, the superiority of the combined uphill-

downhill training method was clear from the results.

Further statistical analyses revealed that the

changes produced by the combined uphill-downhill

training method were significantly greater than

those produced by the other training methods.

It can be argued that shortening the contact time

could produce a faster speed (Figure 3). However, if

the contact time was shortened and the muscle

force remained the same, the impulse (impulse =

force x time) produced by the muscles would

decrease. In such a scenario, producing a smaller

step length should lose the gain from a shortened

contact time. In order to produce a higher step

speed, the athlete has to decrease the contact time

and to increase the muscle force proportionally, so

the impulse should at least remain constant, if not

increase with the application of larger forces.

As previously mentioned, the step time can be

shortened, even though the contact time remained

constant, by decreasing the flight time (Figure 3).

In such a case, in order to achieve an increased

maximum running speed, the step length has to

remain the same. Effectively, if a shorter flight time

69ο NEWSLETTER

is required while the step length remains the same,

a faster movement of the limbs should be

performed (Figure 3). Mero and Komi (16, 17)

suggested that this could be achieved by increasing

the motor nerve conduction speed. By increasing

the speed of the current from the motor cortex of

the brain to the peripheral motor apparatus, the

movements could be performed faster.

Verkhoshanky (28) suggested that training using

combined slope methods favors the adaptive

changes of the central and peripheral regulators of

movement speed, activates the potential of other

physiological systems, and induces the development

of a new functional structure, thus allowing a higher

speed work regimen. In addition, Wood (30)

provided evidence that the limiting factor in

producing shorter flight time and greater speed is

the ability of the hamstring muscle group to

produce greater force.

It seems that there may be a link between the force

time characteristics of the muscles and the

production of shorter contact time and flight time

and eventually the production of greater maximum

running speed as measured at 35 m, but this needs

further evaluation.

In order to understand the effects of training, a

possible mechanism through which the adaptations

occurred should be identified. The mechanisms

through which uphill and downhill training produce

adaptations are known already. Uphill, as a resistive

training method, introduced an extra resistance

(overload). By repetitive application for a certain

time, the body would adapt to that extra load and

as a result some trends toward changes in the

kinematic characteristics might be expected to

occur.

In contrast, downhill running introduced a facilitated

environment. The body adapted in this facilitated

environment and an increase in maximum running

speed at 35 m is possible by improving some of the

kinematic characteristics. The results of the present

study showed that after a training period of 6

weeks, the body adapted to this new stimulus and

maximum running speed, step rate, and step time

were improved for horizontal running.

Finally, the combined uphill-downhill training

showed a more significant improvement in

kinematic characteristics compared with the other

methods. A straightforward explanation for the

mechanism through which the adaptations occurred

is the combination of the uphill and downhill training

mechanisms. However, the results did not indicate

such a trend, as some adaptations that occurred in

the uphill group did not occur in the combined

group.

During running on the platform, participants

experienced a resistive stimulus (uphill), followed by

a normal stimulus (horizontal), and then a

facilitative stimulus (downhill). During the first

stimulus, the neuromuscular system was

overloaded, whereas immediately afterward it was

progressively unloaded (horizontal - downhill). It

seems that this rapid transition from the first

stimulus to the second, from overloaded to

facilitative, benefited the neuromuscular system.

The immediate transition from the overload status

to the facilitated status seems to be the key factor

to the training adaptation. However, in order to

investigate some of the possible mechanisms that

produce this adaptation, further work is needed. It

is important to identify the effects of training on the

maximum force and the force-time characteristics

from the dominant muscles during sprinting in order

to have some information on possible cause and

effect.

PRACTICAL APPLICATIONS

Sprint training on sloping surfaces (3ν produced

significant increases in maximum running velocity

measured at 35 m. The present study provides

evidence, in the form of kinematic and posture data,

which describes the nature of adaptations to sprint

training for 6 weeks on sloping surfaces. The

combined uphill-downhill training method produced

a 3.2% overall increase in the kinematic variables,

with an increase in maximum running speed by

3.4% accompanied by an increase of step rate by

3.4%, although the step length did not change. The

downhill training method produced an increase in

maximum running speed (1.1%) and step rate

(2.4%), but not in step length; uphill and horizontal

training methods showed trends to increase

maximum running speed, step length, and contact

time, but these differences were not statistically

significant. Despite the significant changes that

occurred in the kinematic variables, training on

sloping surfaces did not produce significant changes

in the posture characteristics and performance in

the Wingate test. In order to improve maximum

running speed at 35 m one of its main components

(step rate and length) has to be overstressed

through the facilitation of the second parameter. In

downhill running the facilitated parameter was step

length and through the repetition of this stimulus

69ο NEWSLETTER

(training), the step rate (overstressed) was

improved, whereas the opposite occurred with uphill

training. The hypothesis that 6 weeks of sprint

training on downhill and the combined uphill-

downhill surfaces would result in significant changes

in the criterion measure of maximum running

velocity measured at 35 m was supported; the

major performance parameter that produced this

change was step rate and its associated lower level

variables in the hierarchical model (Figure 3). The

hypothesis that 6 weeks of sprint training on uphill

and horizontal surfaces would result in significant

changes in the criterion measure of maximum

running velocity was rejected. However, the

hypothesis that 6 weeks of sprint training on sloping

surfaces would result in no significant changes in

posture was supported. The hypothesis that the

specific effects of training on uphill and downhill

surfaces would be different was supported. Finally,

the hypothesis that the novel combined condition

would produce an interactive effect between training

on uphill and downhill that would result in a greater

training benefit than the other training methods was

supported also. In conclusion, it can be suggested

that the novel combined uphill-downhill training

method is significantly more effective in improving

the maximum running velocity at 35 m and the

associated horizontal kinematic characteristics of

the 35-m sprint running than the other training

methods. Additionally, because the correlation

between maximum running speed and performance

is very high (r = 0.90) in 100 m races (9, 18), we

speculate that the novel combined uphill-downhill

training method is more effective in improving

performance in short distance sprinting events,

which also is important in many team games such

as rugby, hockey, football, and netball.

REFERENCES

1. BLAND, J.M., AND G. ALTMAN. Statistical

methods for assessing agreement between two

methods of clinical measurement. Lancet i:307–

308. 1986.

2. CHALLIS, J., R. BARTLETT, AND M. YEADON.

Image-based motion analysis. In: Biomechanical

Analysis of Movement in Sport and Exercise. R.

Bartlett, ed. Leeds: British Association of Sport and

Exercise Sciences, 1997. pp. 7–30.

3. COSTELLO, F. Resisted and assisted training to

improve speed. Track Field Q. Rev. 81(2):27. 1976.

4. DEMPSTER, W.T. Space requirements of the

seated operator. WADC Technical Report. Dayton:

Wright-Patterson Air Force Base, 1955. pp. 55–159.

5. DINTIMAN, G. Effects of various training

programs on running speed. Res. Q. Rev. Exerc.

Sport 35:456–463. 1964.

6. DINTIMAN, G. Sprinting: What research tells the

coach about. Washington, DC: AAHPER publications,

1974.

7. FACCIONI, A. Assisted and resisted methods for

speed development. Mod. Athlete Coach 32(3):8–

12. 1994.

8. GUTOSKI, F.P. Effects of force treadmill sprint

training on selected physiological parameters.

Doctoral dissertation, University of Edmonton,

Alberta, Canada, 1974.

9. HARRE, D. Training. Athens: Scientific Publ.

Parisianou, 1989.

10. HAY, J.G., AND J.G. REID. Anatomy, Mechanics

and HumanMotion. Englewood Cliffs, NJ: Prentice-

Hall, 1988.

11. IRWIN, D. A study of stride length and stride

rate changes after high speed treadmill and sprint

training. Master’s dissertation, University of Alberta,

Alberta, Canada, 1974.

12. KOMI, P.V. Stretch-shortening cycle. In:

Strength and Power in Sport. P.V. Komi, ed.

London: Blackwell, 1992. pp. 169–179.

13. KUNZ, H., AND D. KAUFMANN. Biomechanics of

hill sprinting. Track Tech. 82:2603–2605. 1981.

14. MATVEYEV, L.P. Modern procedures for the

construction of macrocycles. Mod. Athletes Coach

30:32–34. 1992.

15. MCARDLE, W., F. KATCH, AND V. KATCH.

Exercise Physiology: Energy, Nutrition, and Human

Performance. London: Lea & Febiger, 1991.

16. MERO, A., AND P. KOMI. Effects of

supramaximal velocity on biomechanical variables in

sprinting. Int. J. Sport Biomech. 1: 240–252. 1985.

17. MERO, A., P. LUHTANEN, J.T. VIITASALO, AND

P.V. KOMI. Relationships between the maximal

running velocity, muscle fiber characteristics, force

69ο NEWSLETTER

production and force relaxation of sprinters. Scand.

J. Sports Sci. 3(1):16–22. 1981.

18. MILAKOV, M., AND V. COX. Improving speed by

training on sloping surfaces. Track Tech. 8:254–

255. 1962.

19. MILLIRON M., AND P. CAVANAGH. Sagittal plane

kinematics of the lower extremity during distance

running. In: Biomechanics of Distance Running. P.

Cavanagh, ed. Champaign, IL: Human Kinetics,

1990. pp. 65–100.

20. MORAVEC P., J. RUZICKA, P. SUSANKA, E.

DOSTAL, V. KODEJS, AND M. NOSEK. The 1987

International Athletic Foundation/IAAF scientific

project report: Time analysis of the 100-

meterevents at the 2nd World Championships in

Athletics. New Stud. Athletics 3:61–96. 1988.

21. MURASE, Y., T. HOSHIKAWA, N. YASUDA, Y.

IKEGAMI, AND H. MATSUI. Analysis of the changes

in progressive speed during 100-meter dash. In:

Biomechanics V-A. P.V. Komi, ed. Baltimore:

University Park Press, 1976. pp. 200–207.

22. PARADISIS, G.P., AND C.B. COOKE. Kinematic

and postural characteristics of sprint running on

sloping surfaces. J. Sports Sci. 19:149–159. 2001.

23. PAULETTO, B. Speed-power training. Scholastic

Coach 63(5):54–55. 1993.

24. PLAGENHOEF, S. Patterns of Human Motion: A

Cinematographic Analysis. Englewood Cliffs, NJ:

Prentice-Hall, 1971.

25. SEVENE, B. Hill training. Track Field Q. Rev.

86(3):26–27. 1986. SUELLENTROP, J.M. A variation

of Russian Downhill sprint training for selected

college students. Master’s dissertation. Southern

Illinois University, Carbondale, 1978.

27. TZIORTZIS, S. Effects of training methods in

sprinting performance. Doctoral dissertation.

University of Athens, Dept. of Physical Education

and Sport Science, Athens, Greece, 1991.

28. VERKHOSHANKY, Y.V. Speed training for high

level athletes. New Stud. Athletics 11(2–3):39–49.

1996.

29. WOOD, G. Data smoothing and differentiation

procedures in biomechanics. Exerc. Sport Sci. Rev.

10:308–362. 1982.

30. WOOD, G.A. Biomechanical limitations to sprint

running. Med.Sport Sci. 25:58–71. 1987.

Address correspondence to Giorgos Paradisis,

gparadi@phed.uoa.gr.

69ο NEWSLETTER

Η έξεπλα απηή εμεξεύλεζε ηελ ππόζεζε όηη ε εηζπλνή αέξα εκπινπηηζκέλνπ κε νμπγόλν (FiO2 = 1.00) θαηά ηελ

απνθαηάζηαζε βειηηώλεη ηελ κέγηζηε (Ppeak) θαη κέζε ηζρύ (Pmean) ζε επαλαιακβαλόκελε άζθεζε πςειήο

έληαζεο. Γώδεθα ειηη άλδξεο θνιπκβεηέο (21 ± 3 έηε, 192.1 ± 5.9 cm, 79.1 ± 8.2 kg) εηζέπλεπζαλ ππεξνμηθό

(HOX) ή normoxic (NOX) αέξα ζε πεξηόδνπο απνθαηάζηαζεο δηάξθεηαο 6-min ελδηάκεζα ζε ηα επαλαιήςεηο

πςειήο έληαζεο άζθεζε ζηνλ θνιπκβεηηθό πάγθν κε θάζε κία επαλάιεςε λα πεξηιακβάλεη 40 κέγηζηεο έληαζεο

ρεξηέο. Μεηξήζεθαλ ε κεξηθή πίεζε (pO2) θαη ν θνξεζκόο (SO2), [H1], pH, ππέξβαζε βάζεσλ θαη ζπγθέληξσζε

γαιαθηηθνύ νμένο πξηλ θαη κεηά όια ηα δηαιείκκαηα. Η παξαγσγή ησλ δξαζηηθώλ κνξθώλ νμπγόλνπ (ROS)

ππεξνμείδηνπ ηνπ πδξνγόλνπ was κεηξήζεθε πξηλ, ακέζσο κεηά θαη 15 ιεπηά κεηά ην ηεζη. Τα Ppeak θαη Pmean

κε απνθαηάζηαζε HOX ήηαλ πνιύ πςειόηεξα από όηη κε NOX θαζ’όιε ηε δηάξθεηα ηνπ ηξίηνπ, ηέηαξηνπ θαη

πέκπηνπ δηαιείκκαηνο (P<0.001–0.04). Με ην HOX, ε ειεθηξνκπνγξαθηθή δξαζηεξηόηεηα ήηαλ ρακειόηεξε θαηά

ηε δηάξθεηα ηνπ ηξίηνπ, ηέηαξηνπ θαη πέκπηνπ δηαιείκκαηνο απ’όηη ζην πξώην (P = 0.05–0.001), ρσξίο

αληίζηνηρεο αιιαγέο ζην NOX (P = 0.99). Γελ ππήξραλ δηαθνξέο ζην γαιαθηηθό νμύ, pH, [H1] ή ππέξβαζε

βάζεσλ θαη παξαγσγή ROS νπνηαδήπνηε ζηηγκή είηε κε ηελ απνθαηάζηαζε HOX είηε κε ηελ NOX. Τα επξήκαηα

δείρλνπλ όηη νη Ppeak θαη Pmean ειηη θνιπκβεηώλ πνπ πξαγκαηνπνηνύλ πςειήο έληαζεο δηαιεηκκαηηθή

πξνπόλεζε κπνξεί λα βειηησζεί κε έθζεζε θαηά ηελ απνθαηάζηαζε ζε εκπινπηηζκέλν κε νμπγόλν αέξα.

uring high-intensity exercise of different

durations, energy is produced in different

ways. During brief allout exercise ( ≤ 10 s),

energy for muscle contraction is obtained primarily

from stored adenosine triphosphate (ATP) and

phosphocreatine (Harris et al., 1976), as well as

concomitant glycolysis (Gaitanos et al., 1993;

Bogdanis et al., 1998). However, in the case of

longer sprints lasting at least 30 s and repeated

short sprints (e.g., 5–30 s), anaerobic energy

production decreases in inverse proportion to the

increasing amount of energy derived from aerobic

metabolism (Gaitanos et al., 1993; Bogdanis et al.,

1996). Hyperoxia [i.e., respiration of air containing

a higher partial pressure of oxygen (pO2) than

ambient air] enhances the level of arterial

hemoglobin saturation (SaO2) as well as the

amount of oxygen dissolved in the plasma (Powers

et al., 1993; Peltonen et al., 1995).

Hyperoxic (HOX) breathing is also known to

augment delivery of O2 to working skeletal muscle

cells (Knight et al., 1993; Prieur et al., 2002), as

well as the diffusion of O2 into the mitochondria

(Knight et al., 1993; Richardson et al., 1999; Prieur

et al., 2002). The well-documented improvements

in performance during exercise of longer duration

(43min) achieved with HOX (Adams & Welch, 1980;

Peltonen et al., 1997; Prieur et al., 2002) are

attributed to this elevation in oxygen uptake and

subsequent aerobic ATP production, in combination

with reduced accumulation of lactate in skeletal

muscle and blood, which helps to maintain the

normal contractile properties of muscles by reducing

metabolic acidosis (Linossier et al., 2000).

D

Άζκηζη

Δξγνγεληθή επίδξαζε ππεξνμηθήο απνθαηάζηαζεο ζε ειίη θνιπκβεηέο

πνπ πξαγκαηνπνηνύλ δηαιεηκκαηηθή πξνπόλεζε πςειήο έληαζεο

Το άρθρο έτει δημοζιεσθεί ως:

B. Sperlich, C. Zinner, M. Krueger, J. Wegrzyk, J. Mester, H.-C. Holmberg. Ergogenic effect of

hyperoxic recovery in elite swimmers performing high-intensity intervals Scand J Med Sci Sports

2011: 21: e421–e429 doi: 10.1111/j.1600-0838.2011.01349.x

SCIENCE TECHNOLOGIES 69ο NEWSLETTER

Moreover, HOX attenuates desaturation of arterial

oxyhemoglobin (Nummela et al., 2002) and

maintains muscle phosphate compounds (ATP, ADP)

at resting levels during maximal HOX exercise (60%

FiO2) (Linossier et al., 2000). In addition, HOX

significantly shortens the recovery time of PCr

(Haseler et al., 1999). Previous studies suggest that

the breathing of supplemental oxygen in exercise

consisting of shortterm high-intensity intervals

neither hastens recovery nor delays [H1] or lactate

accumulation (Nummela et al., 2002). Although the

use of oxygen appears to be beneficial in long-term

exercise (Weltman et al., 1978; Adams & Welch,

1980), its effects when administered during

recovery alone or during short-term intensive

intervals are controversial (Welch, 1982; Yamaji &

Shephard, 1985; Winter et al., 1989; Robbins et al.,

1992; Maeda & Yasukouchi, 1997).

During maximal exercise of short duration, the

maximal force produced, rate of force production

and relaxation (Bigland-Ritchie, 1981) and

integrated electrical activity in muscles (iEMG) are

reduced (Grimby et al., 1981). In contrast, during

prolonged submaximal exercise to exhaustion, iEMG

increases (Edwards, 1981). It has been proposed

that these changes in iEMG reflect differences in the

rate of motor unit firing and recruitment pattern

(Grimby et al., 1981). As hyperoxia may influence

power output during repeated high-intensity

exercise, it is of interest to investigate the role of

neuromuscular factors in regulating exercise

performance when FiO2 is altered.

Finally, when the O2 content of the inspired air is

elevated while exercising, oxidative damage must

also be considered. For instance, in experimental

animals oxidative damage to DNA is enhanced by

hyperoxia in a manner dependent on the duration of

exposure (Agarwal & Sohal, 1994). Moreover, in an

in vitro system, reactive oxygen species (ROS)

produced by the interaction of inhaled oxygen with

the mitochondrial electron transport chain caused

DNA damage within minutes of exposure to

hyperoxia (Cacciuttolo et al., 1993).

As aerobic metabolism makes a significant

contribution to energy production during brief

sprints, it is reasonable to propose that exposure to

HOX during repeated high-intensity sprint intervals

can enhance both the peak and mean power

outputs and reduce fatigue. The major goal of the

present investigation was to test this hypothesis.

Methods

Subjects

The 12 elite male swimmers [age = 21 ± 3 years;

height = 192.1 ± 5.9 cm, weight = 76.0 ± 5.9 kg

(means ± in this study were all highly experienced

in the performance of laboratory exercise

procedures, in particular swim bench exercise. Five

of them were members of the German national

swimming team and the others belonged to a West

German all-star team. The participants were

instructed to remain adequately hydrated and to

refrain from consuming alcohol for 24 h and food or

caffeine for 3 h before each test. Before the

inclusion, these athletes were informed of the

protocol and gave their written informed consent to

participate. All procedures were approved by the

Ethics committee of the German Sport University in

Cologne, Germany, and conducted in accordance

with the Declaration of Helsinki.

Experimental protocol

The three separate visits to the laboratory within a

3-week period that were required were at least 72 h

apart. In connection with their first visit, the

participants performed five trials of 40 maximal arm

strokes each, with a duration of approximately 50 s

per trial and 6 min of recovery between trials to

familiarize themselves with the test procedures

used. On the second visit, each individual performed

the same procedure under actual test conditions.

The procedure was repeated 7 days later, breathing

the variety of air that he had not been exposed to

during the first test. During each 6-min recovery

period, the participants were exposed to either O2-

enriched (FiO25 = .00) or normoxic (NOX) air from

a Douglas bag (Hans Rudolph Inc., Kansas,

Shawnee, USA) attached to their mouthpiece by

plastic tubing. All 40 maximal armstrokes were

performed in normoxia. The sequence of this

exposure to NOX or HOX in connection with the two

trials was assigned randomly and the participants

were not aware of which gas they were being

exposed to.

All testing of power output was conducted with an

isokinetic swim bench developed and validated by

the ‘‘Institut fur Forschung und Entwicklung von

Sportgeraten’’ (FES, Berlin, Germany). Lying in a

prone position on the bench allowed the athletes to

exert force with both arms on the hand paddles

attached to two independent strain gauges. All of

the swimmers had exercised on this same system

as part of their daily training for at least 3 years.

SCIENCE TECHNOLOGIES 69ο NEWSLETTER

All of these tests consisted of 40 ‘‘butterfly’’ arm

strokes with maximal effort and the power output

was determined by sampling the force and velocity

signals at a rate of 400Hz. Utilizing the software

provided by the FES training system (FES

Evaluation Program 3.3, FES), peak power output

was calculated as the highest power during a period

of 1 s (employing a moving average); the mean

power output recorded for all 40 strokes and the

fatigue index for both the trials calculated as

described previously (Inbar et al., 1996) according

to the following equation:

For the analyses of gases, 120 mL of blood samples

were collected from the right earlobe both before

and after the warm-up period as well as after 1 and

4 min of breathing NOX or HOX during the recovery

periods (Fig. 1). For the analyses of blood lactate

concentration, 20 mL of blood was collected from

the left earlobe into a capillary tube (Eppendorf AG,

Hamburg, Germany) before and after the warm-up

period, as

well as after 0:30, 1:30, 2:30, 3:30, 4:30 and 5:30

min of breathing NOX or HOX (Fig. 1).

Lactate was analyzed by an amperometric-

enzymatic procedure using the Ebio Plus system

(Eppendorf AG, Hamburg, Germany) and blood

gases measured with the AVL Omni 3 system

(Roche Ltd., Basel, Switzerland), in duplicate in all

cases, with the mean being utilized for statistical

analysis. At the same time points at which blood

was taken for lactate analysis, the participants were

also asked to rate their perceived exertion on Borg’s

6–20 scale (Borg, 1970).

Blood levels of oxidants were determined using the

free oxygen radicals test (FORT) (Callegari, Parma,

Italy), in which the radical species produced, which

are in direct proportion to the quantity of lipid

peroxides present, interact with a phenylenediamine

derivative to form a radical that absorbs at 505nm

(Form CR 3000, Callegari, Parma, Italy). The results

are expressed as FORT units, where one such unit

corresponds to 0.26 mg H2O2/L (Mantovani et al.,

2004).

Neuromuscular activity in the triceps brachii (caput

laterale and caput mediale), biceps brachii,

latissimus dorsi and teres major was recorded using

surface electromyography (EMG; TeleMyo 2400T,

Noraxon Inc., Scottsdale, Arizona, USA), involving

pre-gelled bipolar electrodes placed on the

corresponding muscle belly in alignment with the

fiber direction, according to international standards

(Hermens & Freriks, 1999), and a reference

electrode attached to the acromium. Before

electrode placement, the surface of the skin was

shaved, roughened slightly and disinfected with

alcohol. The positioning of the electrodes on the

skin during the first test was marked, so that the

electrodes could be replaced at the same positions

during the second test.

For normalization of EMG amplitude, the maximal

voluntary isometric contraction (MVC) was

determined for each muscle during exercises, which

SCIENCE TECHNOLOGIES 69ο NEWSLETTER

all subjects had practiced previously. All EMG

signals were amplified (differential amplifier,

Biovision, Werheim, Germany), filtered through a

hardware band-pass (10–500Hz at 3 dB), converted

to digital units (DAQ 700 A/D card-12 bit, National

Instruments, Austin, Texas USA), sampled at

2000Hz and analyzed with MyoResearch software

version 1.06.50 (Noraxon, Scottsdale, Arizona,

USA). Before further processing, all of these signals

were full-wave rectified. The calculation of MVC

values was performed using the moving-window

technique (stepwise value for value; window size

250 ms) with these rectified signals from each

exercise; the mean EMG values were calculated for

each window and the highest was used for

amplitude normalization. For each muscle, EMG

amplitude was quantified by calculating the

integrated EMG (iEMG) as an indicator of the

tension developed by and the mean power

frequency of the muscle, in order to compare the

intensities of activation of the different muscles. The

mean power frequency was calculated according to

the formula provided by the manufacturer’s

software:

These iEMG values were calculated from the

preprocessed signals normalized for MVC during

each interval of exercise and subsequently

expressed as %MVC. The mean power frequency for

all muscles together during each exercise interval

was also calculated.

Statistical analyses

Measurement of the peak and mean power output

on two different days before the experimental

sessions on the swim bench revealed technical

errors [%TEM] of 1.5% and 1.7%, respectively.

Under our laboratory conditions, the coefficient of

variation for repeated measurements of blood

lactate concentration is routinely 1.2% at

12mmol/L. For pO2 and pH, the corresponding

coefficients of variation are 3.2% and 3.6%.

All data were analyzed using standard procedures

and the results are presented as means ± standard

deviations (SD). All of the data were found to be

normally distributed, so that no further

transformation was necessary. Repeated measures

ANOVA was used to analyze differences in the

parameters examined under the two different

conditions (i.e., breathing NOX or HOX) and when

global significance was obtained, Bonferroni post

hoc analysis was utilized to identify significant

differences between different time -points. An a of

Po0.05 was considered to be statistically significant

and all analyses were carried out with the Statistica

(version 7.1, StatSoft Inc., Tulsa, Oklahoma, USA)

software package forWindows. The effect size

Cohen’s d [defined as (the difference between the

means)/the standard deviation (Cohen, 1988)] was

calculated for comparison of parameters associated

with breathing NOX or HOX and the thresholds for

small, moderate and large effects were defined as

0.20, 0.50 and 0.80, respectively (Cohen, 1988),

with the highest effect sizes being documented in

Table 1.

Results

Throughout the third, fourth and fifth intervals of

bench swimming, the peak and mean power outputs

associated with breathingHOX were significantly

higher than those with NOX (P<0.001–0.04; effect

sizes = 0.20–0.30; Table 1). In contrast, the fatigue

index was unaffected by the content of inspired air

at any time (P = 0.91; effect sizes = ± 0.00–0.14;

Table 1). After inhaling HOX, the SaO2 was elevated

significantly beyond the %TEM (from 95.6 ± 0.9%

to 99.9 ± 0.3%; P<0.01; effect size 6.40), and pO2

increased from 83 ± 6 to 483 ± 11mmHg (P<0.01;

effect size = 45.00), with no such changes in the

case of NOX (96.2 ± 0.7–97.2 ± 0.7% (P = 0.17;

effect size = 1.4) (Fig. 2).

There were no significant differences in pH, [H1],

base excess or lactate concentration at any time

point with NOX or HOX (Fig. 2). In both cases, the

lowest pH values were obtained after the fifth

interval of exercise (7.22 ± 0.04 for NOX and 7.22

± 0.05 for HOX; P50.91; effect size = 0.00; Fig. 2)

and the mean blood level of lactate peaked at

12.5mmol/L during the same period with both gases

(Fig. 3). The ratings of perceived exertion were

significantly lower toward the end of recovery when

breathing HOX than with NOX (P<0.01; effect size

= 0.45; Fig. 3). The iEMG decreased successively

from the first to the third, fourth and fifth intervals

when breathing HOX (P = 0.05–0.001; effect size =

0.10–0.13), with no such changes in the case of

NOX (P = 0.99; effect size50.01, Table 1). The

mean power frequency remained constant

throughout all of the intervals, independent of the

oxygen content of the inspired air (P = 0.27–0.99;

SCIENCE TECHNOLOGIES 69ο NEWSLETTER

effect size = 0.02–0.12; Table 1) and the level of

ROS was the same pre-exercise and postexercise

with both NOX and HOX air (P = 0.07–0.20, effect

size = 0.78–0.81; Table 2).

Discussion

The major conclusions to be drawn from the present

investigation are that breathing HOX air during

recovery from five intervals of high-intensity

exercise (1) reduces losses in peak and mean power

output, (2) enhances both arterial pO2 and the

degree of hemoglobin saturation with oxygen

(SaO2), (3) does not alter blood pH, [H1], base

excess or lactate concentration in association with

elevation of FiO2, (4) attenuates iEMG activity, (5)

reduces self-ratings of perceived exertion and finally

(6) has no evident effect on blood levels of

hydrogen peroxide (H2O2).

Our hypothesis that HOX recovery would increase

power output during subsequent high-intensity

exercise was based on extensive findings of

SCIENCE TECHNOLOGIES 69ο NEWSLETTER

improvements in performance by HOX (Adams &

Welch, 1980; Peltonen et al., 1997; Prieur et al.,

2002). However, these reported improvements are

usually evident with submaximal exercise for o3min,

rather than in connection with high-intensity

exercise of short duration, when anaerobic energy

production is more prominent.

The maximal oxygen consumption VO2max =

Q(CaO2 _CvO2 ), where Q denotes cardiac output

and CaO2 and CvO2 arterial and venous O2

contents respectively, and it can thus be expected

that breathing HOX air enhances VO2max by 5–

10% in healthy human subjects by increasing CaO2

(Margaria et al., 1961; Welch, 1982). In fact, an

elevation in VO2max of 8% and a corresponding 9%

increase in maximal work rate due to elevated CaO2

has been reported (Knight et al., 1993). These

findings support the conclusion that VO2max is

limited by O2 supply; when skeletal muscle is

provided with more oxygen, it can utilize this O2 to

perform more work.

Recently, Sperlich et al. (2010) showed that

preexposure to oxygen exerted no influence on peak

and mean power outputs in connection with

subsequent 15-s sprints of cycling. However, when

such sprints are performed for a longer period of

time or high-intensity exercise is repeated (e.g., the

five intervals of 40 armstrokes used here), the

relative contribution of anaerobic energy production

declines and aerobic energy production increases

(Gaitanos et al., 1993; Bogdanis et al., 1996), so

that inhalation of oxygen improves power output in

such situations (Adams & Welch, 1980; Peltonen et

al., 1997; Prieur et al., 2002).

Another source of the improvements in peak and

mean power output observed here could be the use

of arm exercise. Calbet et al. (2005) recently

reported that O2 extraction in the arms is lower

than in the legs in connection with double-poling ski

exercise at 76% of VO2max under NOX conditions.

For the arms, the mean capillary muscle O2

conductance was 14.5 ± 2.6 mL/min/mmHg and the

mean capillary pO2 47.7 ± 2.6mmHg, while the

corresponding values for the legs were 48.3 ±13.0

mL/min/mmHg and 33.8 ± 2.6 mmHg. These

investigators attributed these differences to higher

heterogeneity, shorter mean transit time, smaller

diffusing area and larger diffusing distance for blood

flow in the arms than in the legs. Unfortunately, we

did not investigate O2 extraction in the arms in the

present investigation. However, as O2 extraction in

the arms appears to be reduced during exercise, the

dramatic increase of pO2 from 83 ± 6 to 483 ±

11mmHg during recovery should favor the transfer

of O2 from the erythrocytes to the mitochondria and

subsequently enhanced utilization of O2 for energy

production.

In addition to the availability of oxygen, force

production may be influenced by a number of

factors, such as intracellular and extracellular pH

and neural input (Juel, 2008). The findings by

Adams and Welch (1980) that inhalation of HOX

mixtures of gas during exercise induces significant

changes in arterial pH indicates that the blood [H1]

plays an important role in connection with

performance and HOX recovery. During high-

intensity exercise, protons and lactate are

generated in the muscle cells and can either be

buffered and removed intracellularly to protect

against acidosis and lactate accumulation, or

released into the interstitium. Enhanced muscle

buffering and lactate clearance would enable more

energy production before this process becomes

limited by lactate accumulation and pH, thereby

improving work capacity (Messonnier et al., 2007;

SCIENCE TECHNOLOGIES 69ο NEWSLETTER

Juel, 2008). As no differences in [H1], pH or blood

lactate in the two situations were apparent, HOX

recovery appears not to enhance power output by

influencing buffering mechanisms.

Enhancement of performance by HOX has also been

proposed to reflect reduced accumulation of lactate

in the skeletal muscles and blood (Graham et al.,

1987), because blood levels of lactate are lower and

net glycogen breakdown slower during aerobic

exercise in connection with HOX breathing

(Stellingwerff et al., 2005). In association with

prolonged exercise, such attenuation of metabolic

acidosis should slow down the decline in muscle pH

and thereby delay inhibition of glycogen

phosphorylase and phosphofructokinase (Chasiotis,

1983; Spriet et al., 1987). Thus, the less

pronounced accumulation of lactate appears to

reflect deceleration of anaerobic energy production.

However, in the present case HOX did not influence

the blood concentration of lactate, indicating that

changes in anaerobic energy production cannot

explain the differences in mean and peak power

output.

Even in the absence of disease, the skeletal muscle

itself produces ROS, including superoxide anions

(Reid et al., 1992; Kolbeck et al., 1997), hydroxyl

radicals (Close et al., 2005) and H2O2 (Reid et al.,

1992). The rate of ROS production increases during

strenuous exercise and during high-intensity

exercise (Reid et al., 1992; McArdle et al., 2005;

Ferreira & Reid, 2008). In this context, ROS and

other metabolic culprits promote fatigue (Ferreira &

Reid, 2008). It is suggested that muscle

mitochondrion is one of the location of ROS

production in skeletal muscle (Jackson et al., 2007)

and that ROS is a major cause for cellular oxidative

damage (Brand et al., 2004). Several pathways are

included in molecular signaling within the skeletal

muscle. The ROS pathway is involved in contractile

protein expression, angiogenesis, mitochondrial

biogenesis and other adaptations (Lira et al., 2010).

Nevertheless, it is apparent that an increase in

oxygen consumption lowers the tissue oxygen

tension during muscle activity (Richardson et al.,

1995), which leads to heightened ROS production

(Zuo et al., 2003; Clanton, 2007). To date, it is not

clear whether a further increase in oxygen

consumption due to hyperoxia increases the rate of

ROS production in humans. In the present study,

the level of FORT was the same with hyperoxia and

NOX exposure. Furthermore, H2O2 production for

all subjects at all time-points was below the upper

limit of the normal range for healthy individuals of

2.36 mmol/L of H2O2. Although these findings

indicate that exposure to HOX did not elevate H2O2

production, it remains unclear whether a longer

period of HOX exposure could lead to oxidative

damage and how HOX breathing during recovery

will affect training induced signaling and muscle

adaptations. Further examination of this matter is

warranted.

EMG is frequently utilized to monitor the

development of fatigue during exercise (Amann et

al., 2006) and despite its limitations (Arendt-Nielsen

& Mills, 1985), such analysis does provide an

estimate of the development of peripheral

(Basmajian & De Luca, 1985) and central

(Gandevia, 2001) fatigue. In the case of peripheral

fatigue at constant work output, neural drive (EMG

activity) is elevated progressively over time, most

probably to compensate for tiring muscle fibers. In

connection with central fatigue, the fall in muscle

force or power is secondary to a centrally mediated

reduction in motor drive (reduction in EMG activity),

resulting in reduced recruitment of motor units.

As we observed a decrease in iEMG with a

concomitant increase in power output with HOX,

there may have been a centrally mediated reduction

in motor drive. One possible cause of this could be

the higher availability of O2 in the working muscles,

reducing the necessity for activation of muscle

fibers as a result of elevated peripheral metabolism.

Green and Patla (1992) have proposed that

accumulation of metabolites could augment

inhibitory feedback signals from working muscles

that would result in a reduction of neural drive,

which may shift the burden of fatigue from

peripheral to central processes (Green & Patla,

1992; Gandevia, 2001).

The participants’ ratings of perceived exertion,

which were lower with HOX, may support the latter

proposal. Nielsen et al. (1999) have reported that

when the O2 fraction inspired is elevated,

improvement in exercise performance is related to

maintenance of cerebral oxygenation. Although we

did not measure this oxygenation, HOX recovery

might have influenced prefrontal cortex activity and

in this manner influenced muscle activation.

Although this reduction in the perception of effort

suggests that HOX recovery might be beneficial in

connection with high-intensity work, this suggestion

requires further investigation.

Perspectives

SCIENCE TECHNOLOGIES 69ο NEWSLETTER

Our present findings demonstrate that HOX (FiO2 =

1.00) recovery from intervals of high-intensity

exercise enhances peak and mean power output.

Such HOX recovery enhances arterial pO2 5.8-fold

and elevates the degree of hemoglobin saturation

with oxygen without altering blood pH, [H1], base

excess, lactate concentration and H2O2 at any time

point. At the same time, iEMG activity was

attenuated as a result of HOX recovery. The present

findings indicate that the peak and mean power

outputs of elite swimmers performing high-intensity

intervals can be improved by HOX recovery.

Although the HOX recovery did not elevate H2O2

production, it remains unclear whether a longer

period of HOX exposure could lead to oxidative

damage and how HOX breathing during the

recovery will affect training induced signaling and

muscle adaptations.

References

Adams RP, Welch HG. Oxygen uptake, acid-base

status, and performance with varied inspired

oxygen fractions. J Appl Physiol 1980: 49(5): 863–

868.

Agarwal S, Sohal RS. DNA oxidative damage and life

expectancy in houseflies. Proc Natl Acad Sci USA

1994: 91(25): 12332–12335.

Amann M, Romer LM, Pegelow DF, Jacques AJ, Hess

CJ, Dempsey JA. Effects of arterial oxygen content

on peripheral locomotor muscle fatigue. J Appl

Physiol 2006: 101(1): 119–127.

Arendt-Nielsen L, Mills KR. The relationship between

mean power frequency of the EMG spectrum and

muscle fibre conduction velocity. Electroencephal

Clin Neurophysiol 1985: 60(2): 130–134.

Basmajian JV, De Luca CJ. Muscles alive: their

functions revealed by electromyography. Baltimore:

Williams & Wilkins, 1985.

Bigland-Ritchie B. EMG/force relations and fatigue of

human voluntary contractions. Exerc Sport Sci Rev

1981: 9: 75–117.

Bogdanis GC, Nevill ME, Boobis LH, Lakomy HK.

Contribution of phosphocreatine and aerobic

metabolism to energy supply during repeated sprint

exercise. J Appl Physiol 1996: 80(3): 876–884.

Bogdanis GC, Nevill ME, Lakomy HK, Boobis LH.

Power output and muscle metabolism during and

following recovery from 10 and 20 s of maximal

sprint exercise in humans. Acta Physiol Scand 1998:

163(3): 261–272.

Borg G. Perceived exertion as an indicator of

somatic stress. Scand J Rehabil Med 1970: 2(2):

92–98.

Brand MD, Affourtit C, Esteves TC, Green K,

Lambert AJ, Miwa S, Pakay JL, Parker N.

Mitochondrial superoxide: production, biological

effects, and activation of uncoupling proteins. Free

Radic Biol Med 2004: 37(6): 755–767.

Cacciuttolo MA, Trinh L, Lumpkin JA, Rao G.

Hyperoxia induces DNA damage in mammalian cells.

Free Radic Biol Med 1993: 14(3): 267–276.

Chasiotis D. The regulation of glycogen

phosphorylase and glycogen breakdown in human

skeletal muscle. Acta Physiol Scand (Suppl.) 1983:

518: 1–68.

Calbet JA, Holmberg HC, Rosdahl H, van Hall G,

Jensen-Urstad M, Saltin B. Why do arms extract less

oxygen than legs during exercise? Am J Physiol

Regul Integr Comp Physiol 2005: 289(5): R1448–

R1458.

Clanton TL. Hypoxia-induced reactive oxygen

species formation in skeletal muscle. J Appl Physiol

2007: 102(6): 2379–2388.

Close GL, Ashton T, McArdle A, Jackson MJ.

Microdialysis studies of extracellular reactive oxygen

species in skeletal muscle: factors influencing the

reduction of cytochrome c and hydroxylation of

salicylate. Free Radic Biol Med 2005: 39(11): 1460–

1467.

Cohen J. Statistical power analysis for the

behavioral sciences. Hillsdale, NJ: Lawrence

Erlbaum Associates, 1988.

Edwards RH. Human muscle function and fatigue.

Ciba Found Symp 1981: 82: 1–18.

Ferreira LF, Reid MB. Muscle-derived ROS and thiol

regulation in muscle fatigue. J Appl Physiol 2008:

104(3): 853–860.

SCIENCE TECHNOLOGIES 69ο NEWSLETTER

Gaitanos GC, Williams C, Boobis LH, Brooks S.

Human muscle metabolism during intermittent

maximal exercise. J Appl Physiol 1993: 75(2): 712–

719.

Gandevia SC. Spinal and supraspinal factors in

human muscle fatigue. Physiol Rev 2001: 81(4):

1725–1789.

Graham TE, Pedersen PK, Saltin B. Muscle and blood

ammonia and lactate responses to prolonged

exercise with hyperoxia. J Appl Physiol 1987: 63(4):

1457–1462.

Green HJ, Patla AE. Maximal aerobic power:

neuromuscular and metabolic considerations. Med

Sci Sports Exerc 1992: 24(1): 38–46.

Grimby L, Hannerz J, Borg J, Hedman B. Firing

properties of single human motor units on

maintained maximal voluntary effort. Ciba Found

Symp 1981: 82: 157–177.

Harris RC, Edwards RH, Hultman E, Nordesjo LO,

Nylind B, Sahlin K. The time course of

phosphorylcreatine resynthesis during recovery of

the quadriceps muscle in man. Pflugers Arch 1976:

367(2): 137–142.

Haseler LJ, Hogan MC, Richardson RS. Skeletal

muscle phosphocreatine recovery in exercise-

trained humans is dependent on O2 availability. J

Appl Physiol 1999: 86(6): 2013–2018.

Hermens HJE, Freriks BE. Future applications of

surface electromyography. Enschede: Roessingh

Research and Development, 1999.

Inbar O, Bar-Or O, Skinner JS. The wingate

anaerobic test. Champaign, IL: Human Kinetics,

1996.

Jackson MJ, Pye D, Palomero J. The production of

reactive oxygen and nitrogen species by skeletal

muscle. J Appl Physiol 2007: 102(4): 1664– 1670.

Juel C. Regulation of pH in human skeletal muscle:

adaptations to physical activity. Acta Physiol 2008:

193(1): 17–24.

Knight DR, Schaffartzik W, Poole DC, Hogan MC,

Bebout DE, Wagner PD. Effects of hyperoxia on

maximal leg O2 supply and utilization in men. J Appl

Physiol 1993: 75(6): 2586–2594.

Kolbeck RC, She ZW, Callahan LA, Nosek TM.

Increased superoxide production during fatigue in

the perfused rat diaphragm. Am J Respir Crit Care

Med 1997: 156(1): 140–145.

Linossier MT, Dormois D, Arsac L, Denis C, Gay JP,

Geyssant A, Lacour JR. Effect of hyperoxia on

aerobic and anaerobic performances and muscle

metabolism during maximal cycling exercise. Acta

Physiol Scand 2000: 168(3): 403–411.

Lira VA, Benton CR, Yan Z, Bonen A. PGC-1alpha

regulation by exercise training and its influences on

muscle function and insulin sensitivity. Am J Physiol

Endocrinol Metab 2010: 299(2): E145–E161.

Maeda T, Yasukouchi A. Blood lactate disappearance

during breathing hyperoxic gas after exercise in two

different physical fitness groups – on the work load

fixed at 70% VO2max. Appl Human Sci 1997:

16(6): 249–255.

Mantovani G, Madeddu C, Maccio A, Gramignano G,

Lusso MR, Massa E, Astara G, Serpe R. Cancer-

related anorexia/cachexia syndrome and oxidative

stress: an innovative approach beyond current

treatment. Cancer Epidemiol Biomarkers Prev 2004:

13(10): 1651–1659.

Margaria R, Ceretelli P, Marchi S, Rossi L. Maximum

exercise in oxygen. Int Z Angew Physiol 1961: 18:

465–467.

McArdle F, Pattwell DM, Vasilaki A, McArdle A,

Jackson MJ. Intracellular generation of reactive

oxygen species by contracting skeletal muscle cells.

Free Radic Biol Med 2005: 39(5): 651–657.

Messonnier L, Kristensen M, Juel C, Denis C.

Importance of pH regulation and lactate/H1

transport capacity for work production during

supramaximal exercise in humans. J Appl Physiol

2007: 102(5): 1936–1944.

Nielsen HB, Boushel R, Madsen P, Secher NH.

Cerebral desaturation during exercise reversed by

O2 supplementation. Am J Physiol 1999: 277(3 Pt

2): H1045–H1052.

Nummela A, Hamalainen I, Rusko H. Effect of

hyperoxia on metabolic responses and recovery in

intermittent exercise. Scand J Med Sci Sports 2002:

12(5): 309–315.

Peltonen JE, Rantamaki J, Niittymaki SP, Sweins K,

Viitasalo JT, Rusko HK. Effects of oxygen fraction in

SCIENCE TECHNOLOGIES 69ο NEWSLETTER

inspired air on rowing performance. Med Sci Sports

Exerc 1995: 27(4): 573–579.

Peltonen JE, Rusko HK, Rantamaki J, Sweins K,

Niittymaki S, Viitasalo JT. Effects of oxygen fraction

in inspired air on force production and

electromyogram activity during ergometer rowing.

Eur J Appl Physiol Occup Physiol 1997: 76(6): 495–

503.

Powers SK, Martin D, Dodd S. Exerciseinduced

hypoxaemia in elite endurance athletes. Incidence,

causes and impact on VO2max. Sports Med 1993:

16(1): 14–22.

Prieur F, Benoit H, Busso T, Castells J, Geyssant A,

Denis C. Effects of moderate hyperoxia on oxygen

consumption during submaximal and maximal

exercise. Eur J Appl Physiol 2002: 88(3): 235–242.

Reid MB, Haack KE, Franchek KM, Valberg PA,

Kobzik L, West MS. Reactive oxygen in skeletal

muscle. I. Intracellular oxidant kinetics and fatigue

in vitro. J Appl Physiol 1992: 73(5): 1797–1804.

Richardson RS, Leigh JS, Wagner PD, Noyszewski

EA. Cellular PO2 as a determinant of maximal

mitochondrial O(2) consumption in trained human

skeletal muscle. J Appl Physiol 1999: 87(1): 325–

331.

Richardson RS, Noyszewski EA, Kendrick KF, Leigh

JS, Wagner PD. Myoglobin O2 desaturation during

exercise. Evidence of limited O2 transport. J Clin

Invest 1995: 96(4): 1916–1926.

Robbins MK, Gleeson K, Zwillich CW. Effect of

oxygen breathing following submaximal and

maximal exercise on recovery and performance.

Med Sci Sports Exerc 1992: 24(6): 720–725.

Sperlich B, Schiffer T, Achtzehn S, Mester J,

Holmberg HC. Pre-exposure to hyperoxic air does

not enhance power output during subsequent sprint

cycling. Eur J Appl Physiol 2010: 110(2): 301–305.

Spriet LL, Soderlund K, Bergstrom M, Hultman E.

Skeletal muscle glycogenolysis, glycolysis, and Ph

during electrical stimulation in men. J Appl Physiol

1987: 62(2): 616–621.

Stellingwerff T, Glazier L, Watt MJ, LeBlanc PJ,

Heigenhauser GJ, Spriet LL. Effects of hyperoxia on

skeletal muscle carbohydrate metabolism during

transient and steady-state exercise. J Appl Physiol

2005: 98(1): 250–256.

Welch HG. Hyperoxia and human performance: a

brief review. Med Sci Sports Exerc 1982: 14(4):

253–262.

Weltman A, Katch V, Sady S. Effects of increasing

oxygen availability on bicycle ergometer endurance

performance. Ergonomics 1978: 21(6): 427–437.

Winter FD Jr., Snell PG, Stray-Gundersen J. Effects

of 100% oxygen on performance of professional

soccer players. JAMA 1989: 262(2): 227–229.

Yamaji K, Shephard RJ. Effect of physical working

capacity of breathing 100% O2 during rest or

exercise. J Sports Med Phys Fitness 1985: 25(4):

238–242.

Zuo L, Pasniciuc S, Wright VP, Merola AJ, Clanton

TL. Sources for superoxide release: lessons from

blockade of electron transport, NADPH oxidase, and

anion channels in diaphragm. Antioxid Redox Signal

2003: 5(5): 667–675.

69ο NEWSLETTER

Ημεπομηνία: 27-30 Νοεμβπίος 2014

The 8th Cyprus Dietetic and Nutrition Association (CyDNA) Conference with the theme ‘Nutrition Findings from Around the

Globe’ will take place in Nicosia, Cyprus in November 2014 (27-30/11/2014). We expect a participation of more than 200

dietitians and nutritionists. This will be a wonderful and multicultural encounter not only from a humanistic point of view but

also because it will make possible to exchange professional experiences among dietitians from Cyprus and abroad.

Δείτε περιςςότερα ςτο : http://www.cyda2014.com/

Ημεπομηνία: 13-14 Φεβποςαπίος 2014

9η ΔΠΙΣΗΜΟΝΙΚΗ ΓΙΗΜΔΡΙΓΑ ΠΑΥΤΑΡΚΙΑ, 13-14 ΦΔΒΡΟΤΑΡΙΟΤ 2015,

Στόχοσ τθσ ΕΙΕΠ είναι, μεταξφ άλλων, θ ςυνεχισ ενθμζρωςθ τθσ ιατρικισ κοινότθτασ, αλλά και του κοινοφ γενικά, για τθν καλφτερθ κατανόθςθ τθσ νόςου, τθν πρόλθψθ και τθ κεραπευτικι αντιμετϊπιςθ εκείνων, των οποίων θ ηωι ζχει επθρεαςκεί από τθν παρουςία και τισ ςυνζπειεσ τθσ παχυςαρκίασ. Μετά από το, κατά γενικι ομολογία, πετυχθμζνο ςυνζδριο που οργάνωςε θ ΕΙΕΠ το Φεβρουάριο του 2014, ςτόχοσ μασ και

ευχι είναι θ διθμερίδα που κα λάβει χϊρα ςτισ 13 με 14 Φεβρουαρίου του 2015 ςτο ROYAL OLYMPIC HOTEL, ςτθν Ακινα να

τφχει ανάλογθσ υποδοχισ και επιτυχίασ.

Δείτε περιςςότερα ςτο : http://www.eiepcongress2015.gr/

Επόμενα ςνέδπια

Νέα

69ο NEWSLETTER

Ημεπομηνία: 2 Δεκεμβπίος 2014

Ημεπομηνία: 18 Δεκεμβπίος 2014

Επόμενα Webinars Scienceweb

69ο NEWSLETTER

Αγοπά Webinars ζηο scienceweb.gr

Δπαζηηπιόηηηερ

69ο NEWSLETTER

ΕΚΘΕΕΙ - ΕΠΙΚΕΨΗ – ΕΞΟΠΛΙΜΟ - ΤΝΕΡΓΑΣΕ

Ημεπομηνία: 18-19 Οκηωβπίος 2014

Ο Πανελλινιοσ Σφνδεςμοσ Αντιπροςϊπων Ειςαγωγζων Καταςκευαςτϊν Μθχανθμάτων Αιςκθτικισ Φυςιοκεραπείασ &

Παραςκευαςτϊν Καλλυντικϊν (Π.Σ.Α.Μ.Κ.Α.) διοργάνωςε τθν 38θ CosmoEstetica που ζγινε το Σάββατο 18 & τθν Κυριακι 19

Οκτωβρίου 2014 ςτο ξενοδοχείο President .

69ο NEWSLETTER

Ημεπομηνία: 06-08 Νοεμβπίος 2014

Η Marathon Expo 2014, πραγματοποιικθκε και φζτοσ ςτο κλειςτό του Tae Kwon Do ςτο Π. Φάλθρο από 6 ζωσ 8 Νοεμβρίου

2014!

Για ακόμα μία χρονιά, ο Αυκεντικόσ Μαρακϊνιοσ “ςφράγιςε” τθ διεξαγωγι τθσ Ζκκεςθσ ςτισ 9/11, ςυγκεντρϊνοντασ

ςυμμετοχζσ από κορυφαίουσ εκπροςϊπουσ του διεκνοφσ και εγχϊριου επιχειρθματικοφ, πολιτικοφ και ακλθτικοφ κόςμου

κακϊσ και από Ζλλθνεσ και Ελλθνίδεσ κάκε θλικίασ, ο αρικμόσ των οποίων αυξάνεται εντυπωςιακά χρόνο με τον χρόνο.

69ο NEWSLETTER

ΣΑΣΟΪ club

Εξοπλιζμόρ και εκπαίδεςζη πποϊόνηων Polar

69ο NEWSLETTER

Ημεπομηνία: 20 Οκηωβπίος 2014

Ημεπομηνία: 17 Νοεμβπίος 2014

Πποηγούμενα Webinars Scienceweb

69ο NEWSLETTER

Προϊόντα σε προσφορά

Sciencemarket.gr

69ο NEWSLETTER

Νέα πποϊόνηα

Polar Μ400

GPS και καηαγραθή δραζηηριόηηηας 24/7

Γηα δξνκείο πόιεο θαη εμνρήο πνπ ζέινπλ αζιεηηθή εκθάληζε, πξνεγκέλεο ιεηηνπξγίεο GPS κε πξνπνλεηηθέο ιεηηνπξγίεο, πιήζνο επηινγώλ θαη 24σξε θαηαγξαθή ηεο δξαζηεξηόηεηαο.

• Παξαθνινπζήζηε ην ξπζκό, ηελ απόζηαζε θαη ην πςόκεηξν κε ην ελζσκαησκέλν GPS.

• Αθνινπζήζηε ηε δξαζηεξηόηεηά ζαο 24/7, ηηο ζεξκίδεο θαη ηα βήκαηά ζαο

• Οξγαλώζηε, ζπγρξνλίζηε θαη κνηξαζηείηε ηελ πξνπόλεζή ζαο κε ηελ εθαξκνγή Polar Flow γηα θηλεηά θαη ηε

δηθηπαθή ππεξεζία

• Βάιηε ζηόρνπο πξνθεηκέλνπ λα μεπεξάζεηε ην αηνκηθό ζαο ξεθόξ

• Βξείηε ην δξόκν ηεο επηζηξνθήο κε ην Back to Start

• Πξνπνλεζείηε ζηε ζσζηή έληαζε εληόο ησλ πξνζσπηθώλ ζαο δσλώλ θαξδηαθήο ζπρλόηεηαο (απαηηείηαη H7

αηζζεηήξαο θαξδηαθήο ζπρλόηεηαο)

69ο NEWSLETTER

Λειηοσργίες

Γηθηπαθή ππεξεζία Polar Flow

• Γεκηνπξγήζηε πξνθίι αζιεκάησλ θαη εηδηθέο πξνβνιέο γηα θάζε άζιεκα κε ην νπνίν αζρνιείζηε.

• Γεκηνπξγήζηε ιεπηνκεξείο ζηόρνπο πξνπόλεζεο, όπσο δηαζηήκαηα πξνπόλεζεο, θαη ζπγρξνλίζηε ηα κε ηε

ζπζθεπή ζαο.

• Δκβαζύλεηε αθόκα πεξηζζόηεξν θαη κάζεηε από απηά πνπ θάλεηε, αλαιύζηε θάζε ιεπηνκέξεηα ηεο

πξνπόλεζήο ζαο ζην Polar Flow.

Δθαξκνγή Flow γηα θηλεηά ηειέθσλα

69ο NEWSLETTER

• Απνθηήζηε κηα γξήγνξε νπηηθή πιήξε εηθόλα ηεο πξνπόλεζήο ζαο θαη αλαιύζηε ηα επηηεύγκαηά ζαο.

• Γηαηεξήζηε ην θίλεηξό ζαο κε αλαηξνθνδόηεζε πνπ ιακβάλεηε ακέζσο κεηά ηελ άζθεζε.

• Σπγρξνλίδεηαη εύθνια κε Bluetooth Smart.

Φαξαθηεξηζηηθά ζπζθεπήο

• Φσξεηηθόηεηα κλήκεο έσο 30 ώξεο πξνπόλεζεο κε GPS θαη θαξδηαθή ζπρλόηεηα

• Δπαλαθνξηηδόκελε κπαηαξία κε θαιώδην micro USB

• Γηάξθεηα δσήο κπαηαξηώλ: Έσο θαη 9 ώξεο πξνπόλεζεο (όηαλ ρξεζηκνπνηνύληαη ην GPS θαη ε θαξδηαθή

ζπρλόηεηα) 24 κέξεο ζε ηξόπν ιεηηνπξγίαο ξνινγηνύ κε θαζεκεξηλή παξαθνινύζεζε δξαζηεξηόηεηαο.

Πξνπνλεηηθά ραξαθηεξηζηηθά

Automatic lap recording

Αηνκηθά ξεθόξ

Φξνλόκεηξν δηαιεηκκαηηθήο πξνπόλεζεο

Δθηηκεηήο ρξόλνπ ηεξκαηηζκνύ

Ηκεξνιόγην πξνπόλεζεο Polar Flow web service

Μεηαθνξά δεδνκέλσλ

Σπκβαηό κε ηε δηθηπαθή ππεξεζία Polar Flow κέζσ θαισδίνπ micro USB (απαηηεί ινγηζκηθό FlowSync)

Η ζπζθεπαζία Polar Μ400 πεξηιακβάλεη:

• M400

• Αηζζεηήξαο Polar H7 θαξδηαθήο ζπρλόηεηαο

• Καιώδην USB

• Απνρξώζεηο: Γπλαηθείν – ιεπθό, Αλδξηθό - καύξν

69ο NEWSLETTER

Έμθαζη ζηην επισειπημαηικόηηηα, ηην καινοηομία, ηην εξωζηπέθεια, ηην ολοκλήπωζη ςποδομών και ηην ανηιμεηώπιζη

ηων κοινωνικών ζςνεπειών ηηρ κπίζηρ θα δίνει ηο νέο ΕΣΠΑ (2014-2020), πος ενέκπινε η Εςπωπαϊκή Ένωζη.

Το μεγαλύηεπο ππόγπαμμα (εκηόρ από ηο αγποηικό) θα είναι αςηό πος θα αθοπά ζηήπιξη ηων ζσεδίων ςθιζηάμενων και

νέων επισειπήζεων, με πποηεπαιόηηηα ζηην καινοηομία και ηην εξωζηπέθεια.

Τα θείκελα, ηα ζηνηρεία θαη νη πιεξνθνξίεο ηνπ πεξηνδηθνύ (newsletter) πξνζθέξνληαη κόλν γηα ελεκέξσζε θαη πξνζσπηθή ρξήζε ησλ αλαγλσζηώλ ηνπ θαη απνηεινύλ πλεπκαηηθή ηδηνθηεζία ηεο εηαηξίαο θαη ησλ ζπγγξαθέσλ ηνπο. Απαγνξεύεηαη ε αλαδεκνζίεπζε, αλαδηαλνκή, αλαηύπσζε θαη θαζ' νπνηνλδήπνηε ηξόπν εθκεηάιιεπζε ησλ θεηκέλσλ, ησλ πιεξνθνξηώλ θαη ησλ ζηνηρείσλ ηνπ πεξηνδηθνύ (newsletter). Οη πιεξνθνξίεο θαη ηα ζηνηρεία ηνπ πεξηνδηθνύ εθθξάδνπλ ηηο πξνζσπηθέο απόςεηο ησλ ζπγγξαθέσλ, δελ απνηεινύλ ππόδεημε ηαηξηθήο αγσγήο ή ζεξαπείαο θαη δελ ππνθαζηζηνύλ ηελ επαγγεικαηηθή ηαηξηθή ζπκβνπιή. Η επηινγή θαη ρξήζε ησλ ζηνηρείσλ θαη ησλ πιεξνθνξηώλ ηνπ πεξηνδηθνύ θαη ηα εμ' απηήο απνηειέζκαηα, γίλεηαη κε απνθιεηζηηθή επζύλε ηνπ αλαγλώζηε. Η εηαηξία SCIENCE TECHNOLOGIES, ν εθδόηεο θαη ν επηζηεκνληθόο ππεύζπλνο ηνπ Newsletter δελ θέξνπλ θακία νηθνλνκηθή ή εζηθή επζύλε γηα ηα γξαθόκελα ή γηα ηηο επηπηώζεηο από ηα γξαθόκελα ζην έληππν απηό. Οη ζπγγξαθείο θέξνπλ ηελ πιήξε επζύλε ησλ γξαθόκελσλ ζηα θείκελά ηνπο θαη ε ππνβνιή θεηκέλσλ πξνο δεκνζίεπζε ζην Newsletter ζεκαίλεη ηαπηόρξνλε απνδνρή ησλ παξαπάλσ όξσλ. Η αλάγλσζε ησλ θεηκέλσλ ζπλεπάγεηαη ηελ απνδνρή ησλ παξαπάλσ όξσλ.

Copyright 2014 | Science Technologies - All Rights Reserved

ύνηομα αναμένονηαι ηα ππώηα ππογπάμμαηα ζηα πλαίζια ηος νέος ΕΠΑ 2014-2020

Επιδοηούμενα ππογπάμμαηα