Journal of Physical Education and Sport ® (JPES), Vol. 24 (issue 8), Art 203, pp. 1823 - 1839, August 2024
online ISSN: 2247 - 806X; p-ISSN: 2247 – 8051; ISSN - L = 2247 - 8051 © JPES

Original Article

Neuro-endocrine, hemodynamic and metabolic accompaniments of effects ofbalneotherapy at Truskavets’ Spa on PWC in men with maladaptation
IGOR L. POPOVYCH1, WALERY ZUKOW2*, OKSANA I. MELNYK3, XAWERY ŻUKOW4,
OLGA SMOLEŃSKA5, ANNA MICHALSKA6, RADOSLAW MUSZKIETA7, MAGDALENA HAGNERDERENGOWSKA8
1
Bohomolets’ Institute of Physiology of NAS of Ukraine, Kyїv, UKRAINE; Ukrainian Scientific ResearchInstitute of Medicine of Transport, Odesa, UKRAINE
2,5,6,7,8Nicolaus Copernicus University, Torun, POLAND
3
Danylo Halytskyǐ National Medical University, Lviv, UKRAINE
4
Medical University of Bialystok, Bialystok, POLAND
Published online: August 31, 2024
Accepted for publication : August 15, 2024
DOI:10.7752/jpes.2024.08203
Abstract
Background. The researchers of the Truskavetsian Scientific School of Balneology have demonstrated that effectof balneotherapy at the Truskavets’ Spa on the physical working capacity of both healthy rats and different
categories of patients is ambiguous. It is shown that various variants of actotropic effects are accompanied bycharacteristic changes in a number of body parameters. The purpose of this study was to identify neuroendocrine, hemodynamic and metabolic accompaniments of actotropic effects of balneotherapy in men withmaladaptation. Material and methods. The object of observation were 34 men (aged 23÷70 years) withmaladaptation against the background of chronic pyelonephtis in remission phase, who came for rehabilitation at
the Truskavets' Spa. The object of study: PWC, hemodynamics, HRV, EEG, adaptation hormones, blood andurine metabolites. The survey was conducted twice: on admission and after 7-10 dais of rehabilitation. Results.
The analysis of individual changes revealed that balneotherapy in 18 patients did not significantly affect the levelof fitness. In 9 patients balneotherapy caused an increase in PWC150 (direct difference: 0.57±0.12 W/kg) whilein the other 9 patients the level of fitness decreased (direct difference: -0.42±0.03 W/kg). Discriminant analysis
revealed 24 variables as characteristic accompaniment of the three variants of actotropic effects ofbalneotherapy. Among them, 2 are hemodynamic, 13 are neural, which reflect the entropy of EEG and HRV as
well as delta-, theta- and beta-rhythms, 2 are endocrine, and 7 are metabolic. Classification accuracy is 100%.
Conclusion. The multivariate actotropic effects of balneofactors are due to their multivariate effects on neuroendocrine regulation and metabolism, which, apparently, is determined by the peculiarities of the individual
reactivity of the body.
Keywords: physical working capacity, hemodynamics, HRV, EEG, metabolism, Truskavets’ Spa.
Introduction
The researchers of the Truskavetsian Scientific School of Balneology have demonstrated that effect ofbalneotherapy at the Truskavets’ Spa on the physical working capacity is ambiguous. Multidirectional actotropic
effects were found in experiments on healthy female rats using the swim-to-exhaustion test (Ruzhylo et al.,
2003; Fihura et al., 2022), in clinical-physiological observations of children and adolescents of both sexes aged
10-17 with maladaptation by PWC170, assessed by the step test (Ruzhylo et al., 2003; Popovych et al., 2005;
Zukow et al., 2020), adult gastroenterology patients of both sexes (Popovych et al., 2005) and women (Zukow etal., 2024), patients with urate urolithiasis and chronic pyelonephritis (Hrinchenko, 1998; Hrinchenko et al., 1999;
Zukow et al., 2022) by PWC150, assessed by two-stage bicycle ergometry.
It is important to note that, firstly, various responses of fitness to balneofactors are accompanied bycharacteristic changes in metabolic, HRV, EEG, immune, and other parameters; secondly, based on theconstellation of such initial parameters, first of all, the level of fitness, as well as lipids and electrolytes, it ispossible to predict not only the direction, but also the severity of the fitness reaction (Popovych et al., 2005;
Zukow et al., 2021; Zukow et al., 2022).
In a comparative study, our group discovered sexual dimorphism in the neuro-endocrine regulation of
bicycle ergometric test parameters in untrained individuals with dysfunction of the neuro-endocrine-immune
complex (Ruzhylo et al., 2022).
The purpose of this study was to identify neuro-endocrine, hemodynamic and metabolic accompaniments ofactotropic effects of balneotherapy in men with maladaptation.
----------------------------------------------------------------------------------------------------------------------------------1823
Corresponding author: WALERY ZUKOW, e-mail: w.zukow@wp.pl

IGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------Material and methods
Participants. The object of clinical-physiological observation were 34 men (aged 23÷70 years, weight
65÷107 kg, height 160÷183 cm, body mass index 19,8÷32,0 kg/m2) with maladaptation against the backgroundof chronic pyelonephtis in remission phase, who came for rehabilitation at the Truskavets' Spa.
Procedure / Test protocol / Skill test trial / Measure / Instruments.
Systolic (Ps) and diastolic (Pd) blood pressure as well as heart rate (HR) was measured (by tonometer “Omron
M4-I”, Netherlands) in a sitting position three times in a row. On the basis of the received data, the Ps2/Ps1,
Ps3/Ps1, Pd2/Pd1, and Pd3/Pd1 indices recently proposed by our group (Popovych et al., 2022a) were calculated.
After that, the parameters of hemodynamics were determined (by echocamera “Toshiba-140”, Japan): ejection
time (ET), end-diastolic (EDV) and end-systolic (ESV) volumes of left ventricle with the following ejection
fraction (EF), cardiac output (CO), and general peripheral vessels resistance (GPVR), calculation by classic
formulas (Bobrov et al., 1997):
EF = 100•(EDV - ESV)/EDV; CO = (EDV - ESV)•HR; GPVR = 80•(0,67•Pd + 0,33•Ps)/HR•(EDV - ESV).
In addition, we calculated the Ruzhylo’s&Popovych’s contractile activity index (CAI) of left ventricle(Popovych et al., 2005):
RPCAI = 0,1332•(0,67•Pd + 0,33•Ps)•(EDV - ESV)/EDV•ET.
We recorded an electrocardiogram in II lead for 7 minutes in the supine position and 2 minutes after
transition from the supine to upright position (lying-to-standing test) to assess the parameters of heart ratevariability (HRV) (software and hardware complex "CardioLab+HRV" produced by "KhAI-MEDICA",
Kharkiv). For further analyses the following parameters HRV were selected. Temporal parameters (TimeDomain Methods): HR, the mode (Mo), the standard deviation of all NN intervals (SDNN), the square root of
the mean of the sum of the squares of differences between adjacent NN intervals (RMSSD), the percent ofinterval differences of successive NN intervals greater than 50 msec (pNN50); triangular index (TNN). Spectral
parameters (Frequency Domain Methods): absolute (msec2) and relative (%) power spectral density (PSD) bandsof HRV: high-frequency (HF, range 0.4÷0.15 Hz), low-frequency (LF, range 0.15÷0.04 Hz), very low-frequency(VLF, range 0.04÷0.015 Hz), and ultralow-frequency (ULF, range 0.015÷0.003 Hz). Calculated classicalindexes: LF/HF; (VLF+LF)/HF; LFnu=100%•LF/(LF+HF) as well as Baevsky’s Activity of Regulatory Systems
Index (BARSI) and Autonomous Reactivity Index (ARI) as the difference between BARSI in standing up andsupine positions (HRV, 1996; Berntson et al., 1997; Baevsky & Ivanov, 2001; Baevsky & Chernikova. 2017)
Than we quantitative EEG recorded at rest a hardware-software complex “NeuroCom Standard” (KhAI
Medica, Kharkiv, Ukraine) monopolar in 16 loci (Fp1, Fp2, F3, F4, F7, F8, C3, C4, T3, T4, P3, P4, T5, T6, O1,
O2) by 10-20 international system, with the reference electrodes A and Ref on the earlobes. Two minutes after
the eyes had been closed, 25 sec of artifact free EEG data were collected by computer. Among the options
considered the average EEG amplitude (μV), average frequency (Hz), frequency deviation (Hz), index (%),
absolute (μV2/Hz) and relative (%) PSD of basic rhythms: β (35÷13 Hz), α (13÷8 Hz), θ (8÷4 Hz) and δ (4÷0,5Hz) in all loci, according to the instructions of the device. In addition, we calculated coefficient of Asymmetry(As) and Laterality Index (LI) for PSD each Rhythm using equations:
As, % = 100•(Max – Min)/Min; LI, % = Σ [200•(Right – Left)/(Right + Left)]/8 (Newberg et al., 2001).
We calculated also for HRV and each locus of EEG the Entropy (h) of normalized PSD using Popovych’s(Popadynets et al., 2020; Gozhenko et al., 2021) equations based on classic Shannon’s (1948) equation:hEEG = - [PSDα•log2 PSDα + PSDβ•log2 PSDβ + PSDθ•log2 PSDθ + PSDδ•log2 PSDδ]/log2 4;
hHRV =- [PSDHF•log2PSDHF + PSDLF•log2PSDLF + PSDVLF•log2PSDVLF + PSDULF•log2PSDULF]/log2
4.
In portion of the venous blood the serum levels of major hormones of adaptation: Cortisol, Testosterone,
Aldosterone, Triiodothyronine, PTH and Calcitonin as well as Interleukins 1β and 6 assayed with ELISA kitsaccording to the SOP provided by the manufacturer (“Алкор Био”, XEMA Co Ltd, DRG International Inc,
“Vector-Best”) with the use of analyzers “RT-2100C” and “Stat Fax 303”.
In addition, we estimated a number of metabolic parameters.
Total cholesterol (by a direct method after the classic reaction by Zlatkis-Zack) and content of it incomposition of HDL (by the enzyme method by Hiller, 1987); VLDL (calculated by the level of triglycerides,
estimated by meta-periodate method, as ratio TG/2.1834); LDL (calculated by a difference between a totalcholesterol and cholesterol in composition HD and VLD lipoproteins); calculated the Dobiásová’s&Frohlich’s
atherogenic index (AGI) as TG/HDLP Ch ratio (Dobiásová et al., 2011).
State of lipids peroxidation assessed the content in the serum its products: diene conjugates(spectrophotometry of heptane phase of lipids extract) (Gavrilov & Mishkorudnaya, 1983) and malondialdehyde(test with thiobarbituric acid) (Andreyeva et al, 1988), as well as the activity of antioxidant enzymes: catalase
serum (by the speed of decomposition hydrogen peroxide) (Korolyuk et al, 1988) and superoxide dismutase
erythrocytes (by the degree of inhibition of nitroblue tetrazolium recovery in the presence of Nmethylphenazone metasulfate and NADH) (Dubinina et al, 1988).
Electrolytes: calcium (by reaction with arsenase III); magnesium (by reaction with colgamite); phosphates(phosphate-molybdate method); chloride (mercury-rhodanidine method); sodium and potassium (flamming
1824---------------------------------------------------------------------------------------------------------------------------JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------photometry). Nitrogenous metabolites: creatinine (by Jaffe's color reaction by Popper's method); urea (urease
method by reaction with phenolhypochlorite); uric acid (uricase method).
The same metabolic parameters, with the exception of lipids, were determined in daily urine collected the
day before. The analysis carried out according to instructions (Goryachkovskiy, 1998) with the use of analyzers"Reflotron" (BRD) and "Pointe-180" (USA) as well as flame photometer “СФ-47” and corresponding sets ofreagents. For estimation of physical working capacity (PWC) a bicycle ergometer “Tunturi” (Finland) was used.
The power of the first load was 0.5 W/kg, the second load (after 3 min) 1.5 W/kg at a pedaling frequency of 6075 rpm. We calculated submaximal PWC150 with the mechanical power in Watt per kilogram body weight(W/kg) as indicator of cardiorespiratory fitness (Finger et al., 2013; Steinhilber et al., 2022). In addition, for theassessment of cardiorespiratory fitness, the good old tests for the duration of breath retention after deep
inhalation (Stange's test) and exhalation (Henchy's test) were used.
After the initial testing, the patients received for 7-10 days standard balneotherapy: drinking of Naftussya
bioactive water by 3 mL/kg for 1 hour before meals three times a day; application of Ozokerite on the lumbar
region (temperature 450C, exposure 30 minutes, every other day, 5 procedures); baths with mineral water (Cl-SO42--Na+-Mg2+ containing salt concentration 25 g/L, temperature 36-370C, duration 8-10 minutes, every otherday, 5 procedures); therapeutic physical education (motion mode II).
The next morning after completing the treatment, retesting was performed.
Data collection and analysis / Statistical analysis.
Data were collected through various physiological measurements, including: Physical Working
Capacity (PWC150) assessed by bicycle ergometry. Hemodynamic parameters measured by echocardiography.
Heart Rate Variability (HRV) parameters recorded using ECG. Quantitative EEG recorded at rest. Serum levelsof adaptation hormones and interleukins measured by ELISA. Metabolic parameters in blood and urine.
Statistical processing was performed using a software package “Microsoft Excell” and “Statistica 6.4
StatSoft Inc” (Tulsa, OK, USA).
The following statistical methods were applied:
1. Descriptive Statistics: Means and standard errors (SE) were calculated for all variables.
2. Data Normalization: Raw parameters were normalized using Z-score transformation: Z = 4*(V - N)/(Max Min) = (V - N)/SD = (V/N - 1)/Cv, where V is the actual value, N is the normal (reference) value, SD is thestandard deviation, and Cv is the coefficient of variation. This allowed comparison of variables with different
units and variabilities.
3. Correlation Analysis: Pearson's correlation coefficients were calculated to examine relationships between
variables.
4. Cluster Analysis: Hierarchical clustering was used to group similar variables into clusters.
5. Discriminant Analysis: 5.1. Forward stepwise discriminant analysis was performed to identify variables
characteristic of the three variants of actotropic effects. 5.2. Discriminant functions were calculated and used tovisualize patients in the discriminant root space. 5.3. Mahalanobis distances between clusters were calculated.
5.4. Classification functions were derived for retrospective identification of actotropic effects. 5.5. Classification
accuracy was assessed.
6. Canonical Correlation Analysis: Used to examine relationships between sets of variables (e.g., EEG and HRVparameters). Canonical roots were calculated and their statistical significance was assessed.
7. Multiple Regression Analysis: Stepwise multiple regression was used to model relationships between
predictor variables and outcome variables. Regression coefficients, R2 values, and statistical significance ofmodels were reported.
8. Factor Analysis: Factor structure of canonical roots was examined. Factor loadings for variables werereported.
9. Calculation of Mahalanobis Distances: Squares of Mahalanobis distances between clusters were calculated. Ftests were used to assess the significance of differences between clusters.
The level of statistical significance was set at p < 0.05. Detailed statistical results, including correlation
coefficients, regression coefficients, discriminant function coefficients, factor loadings, etc., were provided intables and figures throughout the paper. This comprehensive statistical approach allowed for a thoroughexamination of the complex relationships between the studied variables and identification of characteristic
patterns accompanying various actotropic effects of balneotherapy.
Results
It was established that balneotherapy in most patients (18) did not significantly affect the level offitness: PWC150 (Mean±SE) was 2.01±0.15 W/kg and 1.98±0.15 W/kg before and after balneotherapy,
respectively (reference level: 2.67±0.09 W/kg). At the same time, in 9 patients balneotherapy caused an increase
in working capacity from 1.40±0.26 W/kg to 1.97±0.22 W/kg (direct difference: 0.57±0.12 W/kg) while in theother 9 patients the level of fitness decreased from 2.44±0.15 W/kg to 2.01±0.15 W/kg (direct difference: 0.42±0.03 W/kg).
----------------------------------------------------------------------------------------------------------------------------1825
JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------Adhering to the Truskavetsian Scientific School's analytical algorithm, in order to correctly compare
variables expressed in different units and with different variability, the actual/raw parameters were normalized
by recalculation by the equations:Z = 4•(V – N)/(Max – Min) = (V – N)/SD = (V/N – 1)/Cv, where
V is the actual value; N is the normal (reference) value; SD and Cv are the standard deviation and coefficient ofvariation respectively (Polovynko et al, 2016; Popovych et al., 2022).
Screening revealed a number of EEG, HRV, hemodynamic and metabolic variables, the changes of which
are unidirectional or inverse with respect to changes in PWC.
Further, profiles (Fig. 1) of changes in normalized values after balneotherapy were created.

Fig. 1. Profiles of changes (Z±SE) in PWC150 (Fitness) and accompanied variables after balneotherapy. See
please also Table 5 for details
At the next stage of the analysis, more or less homogeneous variables were condensed into 11 clusters (Fig. 2).

Fig. 2. Clusters of changes (number of variables below) in accompanied variables by various changes in PWC(Fitness) after balneotherapy. See please also Table 5 for details
In the first two clusters, variables whose changes under the influence of balneotherapy most directly (clusterA) or inversely (cluster B) approximate changes in PWC are collected. Excretion of creatinine, uric acid, andurea (cluster C) also increases with an increase in PWC, but to a lesser extent it also increases in the absence ofchanges in the latter, and does not change with a decrease in PWC (Figs. 2 and 3).

1826---------------------------------------------------------------------------------------------------------------------------JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA---------------------------------------------------------------------------------------------------------------------------------------

Fig. 3. Linear relationships between balneotherapy-induced changes in PWC and clusters A, B and C
variables
The next pair of clusters (Figs. 2 and 4) contains variables whose relationships with changes in PWC areconsistent but non-linear in nature. In particular, PSD of beta-rhythm in F7 locus as well as Entropy in F3 and T5
loci also decrease when PWC decreases, but increase both when it increases and when there is no change (cluster
D). On the other hand, a decrease in PWC is accompanied by an increase in the PSD of delta-rhythm in T5 andT4 loci as well as Ruzhylo’s&Popovych's and Baevsky's indices, however, the listed variables decrease bothwith positive and with quasi-zero actotropic effects of balneotherapy (cluster E).

Fig. 4. Non-linear relationships between balneotherapy-induced changes in PWC and clusters D&E
variables
The next pair of clusters illustrates the classic inverted U-shaped relationship between variables. In
particular, the increase in PWC occurs in the absence of significant changes in the variables of clusters both F
and G (Figs. 2 and 5). When cluster F variables increase or cluster G variables decrease, the PWC level does notchange. Instead, fitness decreases both as cluster F variables decrease and as cluster G variables increase.

Fig. 5. Inverted U-shaped relationships between balneotherapy-induced changes in PWC and clusters
F&G variables----------------------------------------------------------------------------------------------------------------------------1827
JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------The last pair of clusters illustrates the absence of relationships between changes in PWC and clusters H&I
variables (Figs. 2 and 6).

Fig. 6. Absence of relationships between changes in PWC and clusters H&I variables
Finally, the relationship between changes in calcium excretion and PWC has the form of a decaying
sinusoid and is generally weak, but could not be ignored by us (spoiler: calcium excretion will be included in thediscriminant model as a characteristic variable).

Fig. 7. Sinusoidal relationship between changes in Z-scores of calcium excretion (X axis) and PWC (Yaxis)
It is time to move on to the results of the discriminant analysis (Klecka, 1989). The first goal of such ananalysis is to find out which changes of the mentioned variables are a characteristic accompaniment of the threevariants of actotropic effects of balneotherapy. PWC itself was not the object of the analysis due to obviousness.
The forward stepwise program included only 24 variables in the discriminant model. Among them, first of all, 2
are hemodynamic, 13 are neural, which reflect the entropy of EEG and HRV as well as delta-, theta- and betarhythms, 2 are endocrine, and 7 are metabolic, which reflect the exchange of electrolytes and nitrogenous
metabolites (Table 1 and 2).
Table 1. Summary of the analysis of Discriminant Functions in relation to the changes in PWC andaccompanying neural, endocrine, hemodynamics and metabolic variables
Step 24, N of vars in model: 24; Grouping: 3 grps; Wilks’ Λ: 0,0003; approx. F(48,2)=18,5; p<10-6
Variables
currently
in the model
Heart Rate,beats/min
Ps3/Ps1
Ratio
PSD Fp1
Entropy
PSD F3
Entropy
PSD F4
Entropy
PSD T5
Entropy
PSD P3
Entropy
PSD HRV
Entropy
PSD F7-δ,%Clusters of changes
in Fitness (n)
F+
F0
F(9)
(16)
(9)

Parameters of Wilks’ Statistics
Wilks ΛParti-al ΛF-re-move(2,8)

plevelTole-rancy

-9,7
2,1
0,06
0,03
0,02
0,05
0,09
0,04
0,17
0,03
0,14
0,06
0,12
0,03
0,13
0,04
-11
10

0,009

0,034

114,9

10-6

0,024

0,001

0,366

6,929

0,018

0,045

-3

0,018

0,2
0,6
0,00
0,03
0,07
0,05
0,06
0,02
0,01
0,05
0,11
0,06
0,01
0,03
-0,02
0,03
-21
9

7,2
0,6
-0,04
0,03
-0,18
0,08
-0,14
0,05
-0,14
0,08
-0,15
0,08
-0,06
0,05
0,09
0,03
18
9

0,002

0,131

26,59

10

0,002

0,150

22,62

0,001

0,006

0,000

0,725

1,517

0,276

0,094

0,002

0,172

19,23

0,001

0,005

0,003

0,095

38,02

10-4

0,011

0,001

0,405

5,871

0,027

0,121

0,001

0,516

3,745

0,071

0,003

1828---------------------------------------------------------------------------------------------------------------------------JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------PSD T5-δ,%
PSD T3-δ,µV2/HzPSD F7-θ,%PSD T5-θ,%PSD T4-θ,%PSD F7-β,%Mode HRV,
msec
Calcitonin,
ng/LSuperoxide dismutase,
U/mL
Potassium Serum,
mM/L(Ca/K)0,5 Serum
Ratio
Calcium Excretion,
mM/24hCreatinineuria,
mM/24hUricosuria,
mM/24 hUrea Excretion,
mM/24h

-27
14
-140
76
-2,1
1,6
1,5
1,9
3,2
1,3
9,8
7,4
47
38
-1,3
1,3
-9,4
6,1
-0,11
0,25
0,02
0,02
2,41
1,38
4,29
1,55
1,28
0,50
198
58

-15
9
57
45
4,4
1,1
4,0
1,1
-2,1
1,4
6,7
6,1
5
14
2,6
2,0
5,2
5,1
0,50
0,17
-0,05
0,02
3,54
1,06
1,40
0,84
0,42
0,47
119
51

16
13
347
213
-1,8
1,6
-4,0
2,2
-5,4
4,1
-10,5
5,3
-136
28
4,2
2,3
8,0
3,2
-0,18
0,24
0,02
0,02
0,35
1,01
-0,34
1,01
0,08
0,42
-20
49

0,001

0,293

9,633

0,007

0,047

0,003

0,115

30,66

10-4

0,017

0,002

0,179

18,32

0,001

0,014

0,005

0,069

54,36

10-4

0,007

0,001

0,259

11,45

0,004

0,092

0,001

0,245

12,33

0,004

0,002

0,000

0,837

0,777

0,492

0,297

-5

0,021

0,005

0,061

61,47

10

0,001

0,240

12,65

0,003

0,042

-5

0,003

0,005

0,057

65,54

10

0,002

0,149

22,76

10-3

0,005

-3

0,050

0,003

0,124

28,23

10

0,006

0,050

76,09

10-5

0,014

0,001

0,322

8,416

0,011

0,039

0,001

0,360

7,116

0,017

0,077

Note: the mean direct difference and SE are given for the variables
Table 2. Summary of forward stepwise analysis. Variables ranked by criterion Λ
Variables
currently in the model
Heart Rate, beats/min(Ca/K)0,5 Serum Ratio
Calcitonin, ng/L
PSD HRV Entropy
PSD F7-θ, %PSD T5-θ, %PSD T3-δ, µV2/Hz
Creatinineuria, mM/24h
Ps3/Ps1 Ratio
Uricosuria, mM/24 h
Potassium Serum, mM/L
PSD F7-β, %PSD T5-δ, %Urea Excretion, mM/24h
PSD P3 Entropy
PSD T4-θ, %Mode HRV, msec
PSD F3 Entropy
PSD Fp1 Entropy
Calcium Excretion, mM/24h
PSD T5 Entropy
Superoxide dismutase, U/mL
PSD F7-δ, %PSD F4 Entropy

F
to
enter
49,0
6,36
4,19
7,29
3,02
3,38
2,06
1,29
1,78
1,32
1,18
2,54
2,72
2,96
1,60
2,16
1,69
1,61
2,42
4,31
3,64
6,67
2,56
1,52

plevel
10-6
0,005
0,025
0,003
0,065
0,050
0,148
0,294
0,191
0,287
0,327
0,104
0,091
0,077
0,230
0,148
0,217
0,236
0,128
0,039
0,061
0,014
0,132
0,276

Λ
0,240
0,169
0,131
0,086
0,070
0,056
0,048
0,043
0,037
0,033
0,030
0,024
0,019
0,014
0,012
0,009
0,008
0,006
0,004
0,003
0,002
0,001
0,000
0,000

Fvalue
49,0
21,5
17,0
16,9
14,9
14,0
12,7
11,4
10,6
9,83
9,10
9,09
9,24
9,57
9,30
9,37
9,25
9,13
9,52
11,1
12,7
17,0
18,5
18,5

plevel
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6
10-6

The rest of the variables were outside the discriminant model, probably due to duplication or redundancy ofidentifying information (Table 3).
Table 3. Summary of Discriminant Functions analysis. Variables currently not in the model
Variables

Ruzhylo’s&Popovych’s
Contr Activity Ind, kPa/sec
PSD F7
Entropy
PSD T3
Entropy
PSD T4
Entropy

Clusters of changes
in Fitness (n)
F+
F0
F(9)
(16)
(9)
-3,7
-2,2
1,4
2,2
1,3
1,3
0,07
0,17
-0,16
0,09
0,05
0,09
0,10
-0,04 -0,17
0,05
0,04
0,05
0,17
-0,02 -0,16
0,06
0,04
0,06

Parameters of Wilks’ Statistics
Wilks’
Λ
0,0003

Partial Λ
0,928

F to
enter
0,271

plevel0,770

Tole-rancy
0,235

0,0003

0,967

0,118

0,890

0,051

0,0003

0,847

0,635

0,558

0,129

0,0003

0,937

0,236

0,796

0,036

----------------------------------------------------------------------------------------------------------------------------1829
JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------PSD Fp2-δ,%PSD T4-δ,µV2/HzPSD T3-θ,%PSD O2-θ,%PSD Fp2-α,%Baevsky’s Activity Regula-tory Syst Ind up stand, unit
ULF band HRV,%
Cortisol,nM/L
HDLP Cholesterol,mM/LInterleukin-6,
ng/L
Stange’s test,
sec

-1,9
3,9
-126
62
2,4
1,1
-2,4
1,4
4,5
1,6
-1,18
0,61
2,3
1,4
-4
84
0,28
0,14
-0,95
0,33
16,5
4,6

-18,5
7,4
-88
52
0,3
1,3
1,4
1,1
7,8
3,7
-0,64
0,38
-1,3
1,8
-31
66
-0,05
0,11
0,53
0,43
-0,7
3,6

19,5
12,3
183
124
-3,3
1,4
-2,2
1,4
-6,3
5,7
1,37
0,28
3,3
2,4
142
73
-0,20
0,15
-0,71
0,61
-10,2
5,1

0,0003

0,998

0,006

0,994

0,092

0,0003

0,978

0,080

0,924

0,187

0,0003

0,981

0,068

0,935

0,352

0,0003

0,832

0,704

0,526

0,237

0,0003

0,911

0,343

0,721

0,162

0,0003

0,981

0,070

0,933

0,280

0,0003

0,891

0,428

0,668

0,062

0,0003

0,958

0,154

0,860

0,305

0,0003

0,841

0,663

0,545

0,364

0,0003

0,924

0,288

0,758

0,080

0,0003

0,907

0,360

0,710

0,259

The identifying information contained in the 24 discriminant variables is condensed into two roots. The
major root contains 99,0% of discriminatory opportunities (r*=0,999; Wilks' Λ=0,0003; χ2(48)=157; p<10-6),
while minor root 1,0% only (r*=0,916; Wilks' Λ=0,1615; χ2(23)=36; p=0,046).
The next goal of discriminant analysis is visualization of each patient in the information space of roots. It is
achieved by calculating the values of discriminant roots for each patient by the raw coefficients and the constant(Table 4).
Table 4. Standardized and raw coefficients and constants for discriminant EEG variables
Coefficients
Variables
Heart Rate, beats/min(Ca/K)0,5 Serum Ratio
Calcitonin, ng/L
PSD HRV Entropy
PSD F7-θ, %PSD T5-θ, %PSD T3-δ, µV2/Hz
Creatinineuria, mM/24h
Ps3/Ps1 Ratio
Uricosuria, mM/24 h
Potassium Serum, mM/L
PSD F7-β, %PSD T5-δ, %Urea Excretion, mM/24h
PSD P3 Entropy
PSD T4-θ, %Mode HRV, msec
PSD F3 Entropy
PSD Fp1 Entropy
Calcium Excretion, mM/24h
PSD T5 Entropy
Superoxide dismutase, U/mL
PSD F7-δ, %PSD F4 Entropy

Cumulative Proportion

Standardized
Root 1 Root 2
6,294-0,106-13,07 0,160
6,560
0,997
0,033
2,419
7,355
-2,514-11,55 1,012
6,980-2,078-8,114 0,777
3,388-1,7904,111-0,723-17,72 0,761
20,03
1,495
3,864
-0,505-2,723 1,050-9,173 -1,040
2,753
0,785
0,183
-0,784-11,43 -1,765
6,766
1,666
-4,063 -1,092
12,37
2,292
-4,170 -0,886
12,66
2,232
1,610
-0,625Constants
Eigenvalues

Raw
Root 1
1,724-174,5
0,937
0,282
1,760
-2,4530,022-2,211
34,98
2,861-26,97
1,053
0,123-0,015-76,71
0,396
0,002-110,739,08-1,03062,48-0,237
0,444
9,448
6,532
516,9
0,990

Root 2-0,029
2,131
0,142
20,85
-0,6020,215-0,006
0,212-18,48-0,503
1,158
0,079-0,016
0,006-8,696
0,113-0,010-17,109,625-0,277
11,57-0,0500,078-3,666
0,173
5,191
1

Localization in the left zone of the axis of the first discriminant root (Fig. 8) of patients in whombalneotherapy caused an increase in PWC, reflects a concomitant increase in their response of systolic bloodpressure to brachial artery cuff occlusion, duration of breath hold after inhalation (but not exhalation), HDLP
Cholesterol level, excretion of nitrogenous metabolites, as well as a number of EEG parameters, primarily
entropy in 6 loci and PSD of theta-rhythm in loci T3 and T4 and beta-rhythm in locus F7 (Table 5). Instead,heart rate and contractile activity index of left ventricle at rest, serum levels of circulating catecholamines(marker: 1/Mode HRV) and calcitonin, erythrocytes superoxide dismutase activity, PSD of delta rhythm in loci
T3, T4 and T5 as well as reaction of HRV parameters on standing decreased in these patients. At the opposite
pole are localized patients subject to the negative actotropic effect of balneotherapy. A decrease in PWC is
accompanied by a decrease/increase in the listed parameters, respectively. An intermediate position along theaxis of the first root is occupied by patients with a stable state of PWS. At the same time, changes in associatedparameters fluctuate around zero.
1830---------------------------------------------------------------------------------------------------------------------------JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------Additional separation of this cluster from the other two occurs along the axis of the second root. The lowest
localization of the neutral cluster reflects an increase in EEG entropy in loci Fp1 and F7, PSD of theta-rhythm inloci F7, O2 and T5 and alpha-rhythm in locus Fp2, serum levels of potassium and interleukin-6 as well as
calcium excretion. Instead, PSD of delta-rhythm in loci Fp2 and F7, PSD of ULF band HRV and its entropy aswell as serum cortisol and Ca/K ratio are reduced in these patients.
Table 5. Correlations between variables and roots, centroids of clusters and Z-scores of changes invariables
Correlations Variables-Roots
Variables
Root 1 (99,0%)
Physical Working Capacity
Ps3/Ps1 Ratio
PSD T3-θ relative
PSD P3 Entropy
HDLP Cholesterol
PSD F4 Entropy
Stange’s test
PSD T4 Entropy
PSD T3 Entropy
PSD T4-θ relative
PSD T3-δ absolute
Heart Rate
1/Mode HRVSuperoxide dismutase
Calcitonin
Creatinineuria
Uricosuria
Urea Excretion
PSD F7-β relative
PSD F3 Entropy
PSD T5 Entropy
Ruzhylo’s&Popovych’s CAI
PSD T5-δ relative
Baevsky’s ARSI up standing
PSD T4-δ absolute
Root 2 (1,0%)
PSD Fp1 Entropy
PSD F7 Entropy
PSD T5-θ relative
PSD Fp2-α relative
Cortisol
PSD Fp2-δ relative
PSD F7-δ relative(Ca/K)0,5 Serum Ratio
PSD ULF band HRV relative
PSD HRV Entropy
Potassium SerumPSD F7-θ relative
PSD O2-θ relative
Interleukin-6
Calcium Excretion

Root 1

Root 2-0,0160,045-0,0140,018-0,018-0,003-0,012
0,016
0,075
0,040
0,015
0,012
-0,020-0,013-0,020-0,013-0,028-0,0190,016
0,032-0,2200,068-0,104-0,0600,071
0,064-0,003-0,065-0,149-0,102

0,016

0,055

Root 1-0,017

Root 2-0,138-0,018-0,185

0,015
0,002

0,140
0,217

-0,001-0,005-0,0080,258-0,182-0,238-0,011-0,109

F+
(9)
-26,0
1,07±0,22
0,67±0,31
0,50±0,23
0,87±0,24
0,70±0,36
1,45±0,28
1,65±0,46
1,47±0,51
0,87±0,47
0,69±0,29-1,55±0,84-1,19±0,26-0,46±0,37-0,53±0,35-0,18±0,20
1,30±0,47
1,71±0,67
2,33±0,68
0,57±0,43
0,77±0,33
1,13±0,43-0,86±0,51-1,49±0,76-1,02±0,53-1,25±0,622,520,23±0,51
0,44±0,59
0,33±0,43
0,31±0,11-0,03±0,75-0,10±0,21-0,49±0,460,39±0,41
0,69±0,37
1,36±0,41-0,23±0,53-0,45±0,35-0,60±0,36-0,69±0,24
2,58±1,48

F0
(16)
-3,9
-0,05±0,03
0,00±0,31
0,06±0,26
0,05±0,26-0,14±0,27
0,07±0,40-0,07±0,36-0,18±0,37-0,36±0,32-0,46±0,31
0,63±0,50
0,02±0,07-0,05±0,140,29±0,29
0,38±0,30
0,42±0,26
0,56±0,50
1,40±0,60
0,39±0,35
0,53±0,21
0,88±0,44-0,52±0,29-0,83±0,47-0,56±0,33-0,88±0,51-2,270,67±0,47
1,12±0,30
0,88±0,25
0,53±0,25-0,28±0,59-1,01±0,41-0,93±0,40-0,84±0,33-0,41±0,41-0,20±0,34
1,05±0,35
0,95±0,25
0,35±0,28
0,38±0,31
3,72±1,13

F(9)
32,9
-0,79±0,05-0,50±0,42-0,68±0,30-0,47±0,36-0,54±0,36-1,17±0,64-1,02±0,51-1,42±0,51-1,49±0,48-1,16±0,89
1,36±0,95
0,88±0,07
1,33±0,27
0,45±0,18
0,61±0,33-0,10±0,310,11±0,55-0,23±0,57-0,61±0,31-1,28±0,43-1,17±0,66
0,32±0,30
0,85±0,69
1,19±0,25
1,82±1,23
1,52-1,80±0,84-1,04±0,60-0,88±0,49-0,43±0,38
1,27±0,65
1,07±0,67
0,79±0,40
0,29±0,36
0,84±0,61
1,00±0,35-0,39±0,51-0,39±0,34-0,57±0,37-0,51±0,440,37±1,08

8

16

24

Clusterof profile
Basic
A
A
A
A
A
A
A
A
A
B
B
B
B
B
C
C
C
D
D
D
E
E
E
E
F
F
F
F
G
G
G
H
H
H
I
I
I
I
J

Root 2(1%)

4
2
0
-2
-4
-28

-24

-20

-16

-12

-8

-4

0

4

Root 1 (99%)

12

20

28

32

F+
FF0

Fig. 8. Scattering of individual values of the first and second discriminant roots, which contain condensed
information about changes in neuro-endocrine, hemodynamic and metabolic accompaniment of various
effects of balneotherapy on fitness
The visual impression of a clear demarcation of the three clusters in the information field of the two roots is
documented by calculating the distances of Mahalanobis (Table 6).
----------------------------------------------------------------------------------------------------------------------------1831
JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------Table 6. Squares of Mahalanobis distances between clusters (above the diagonal) and F-criteria (df=24,8)
and p-levels (below the diagonal)
Clusters
F+
(9)
F(9)
F0
(16)

F+
(9)
0

F(9)
3462

F0
(16)
512

168
10-6
32
10-4

0

1363

84
10-6

0

Another consequence of discriminant analysis is the possibility to retrospectively identify each variant of theactotropic effect of balneotherapy in each patient. This goal of discriminant analysis is realized with the help ofcoefficients and constants of classification functions (Table 7).
Table 7. Coefficients and constants of classification functions
Clusters
Variables
Heart Rate, beats/min(Ca/K)0,5 Serum Ratio
Calcitonin, ng/L
PSD HRV Entropy
PSD F7-θ, %PSD T5-θ, %PSD T3-δ, µV2/Hz
Creatinineuria, mM/24h
Ps3/Ps1 Ratio
Uricosuria, mM/24 h
Potassium Serum, mM/L
PSD F7-β, %PSD T5-δ, %Urea Excretion, mM/24h
PSD P3 Entropy
PSD T4-θ, %Mode HRV, msec
PSD F3 Entropy
PSD Fp1 Entropy
Calcium Excretion, mM/24h
PSD T5 Entropy
Superoxide dismutase, U/mL
PSD F7-δ, %PSD F4 Entropy
ConstantsF+(9)p=,265-55,895732-30,1256,24-58,6380,87-0,715
72,79-1195-93,57885,1-34,18-4,078
0,506
2483-12,75-0,108
3560
-1252
33,09
-2017
7,727
-14,30-301,4-534,8F(9)p=,265
45,54
-4534
24,84
51,90
45,49
-63,67
0,559-57,52881,775,27-702,827,70
3,163-0,377
-2021
10,46
0,035
-2933
1038
-27,251647-6,14411,74
258,1-350,9F0(16)
p=,470-17,64
1865-10,09-37,57-16,8425,60-0,20822,88-332,5-27,89283,2-11,27-1,2860,149
829,0-4,529-0,011
1195-433,711,63-690,7
2,736-4,861-74,91-60,15Classification accuracy is 100%.
Discussion
So, in this study, the statement about the multivariate effect of balneotherapy at the Truskavets’ SPA on
physical performance was confirmed. We consider it necessary to note that the method of determining physicalcapacity based on the reaction of heart rate to dosed exercise is not direct, but is based on its close correlation
with VO2max. Essentially, the PWC150 reflects the state and reactivity of the autonomic nervous system rated for
HRV. This is confirmed by a close correlation between changes in PWC150 and HRV parameters (Table 8).
Table 8. Regression Summary for changes in PWC150
R=0.726; R2=0.527; Adjusted R2=0.480; F(3.3)=11.2; p<10-4
N=34
Variables
Heart Rate, beats/min
Baevsky’s ARSI up standing
PSD HRV Entropy

Beta
r
-0,68
-0,53
0,26

-0,537-0,2070,205

St. Err.
of BetaIntercpt
0,158
0,157
0,126

B
0,013
-0,022-0,0490,655

St. Err.
of B
0,057
0,007
0,037
0,405

t(30)
0,23
-3,40
-1,31
1,62

plevel
0,823
0,002
0,199
0,116

At the same time, we hasten to argue the reality of the actotropic effect of Naftussya bioactive water (as themain component of the resort's balneofactors) based on the results of an experiment on rats, in which physicalperformance was assessed by a test of the duration of swimming until exhaustion (Ruzhylo et al., 2003; Zukow
et al., 2022).
Returning to balneotherapy-induced changes in HRV parameters, we point out their close relationship withchanges in EEG parameters (Table 9 and Fig. 9).
1832---------------------------------------------------------------------------------------------------------------------------JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------Table 9. Factor structure of canonical roots of changes in EEG and HRV parameters
Left set
PSD T4 Entropy
PSD T3 Entropy
PSD T5 Entropy
PSD F3 Entropy
PSD F4 Entropy
PSD F7 Entropy
PSD Fp1 Entropy
PSD P3 Entropy
PSD Fp2-α, %PSD T3-θ, %PSD T5-θ, %PSD F7-θ, %PSD T4-θ, %PSD T3-δ, µV2/Hz
PSD Fp2-δ, %PSD T5-δ, %PSD F7-δ, %Right set
Heart Rate, beats/min
1/Mode HRV, 1/msec
Baevsky’s ARSI up standing
PSD ULF band HRV, %

R
0,726
0,719
0,646
0,583
0,573
0,567
0,563
0,426
0,521
0,457
0,442
0,415
0,331
-0,667-0,491-0,341-0,335R-0,907-0,872-0,472
0,166

1,5

1,0

0,5

Changes in HRV

0,0

-0,5

-1,0

-1,5

-2,0

-2,5

-3,0
-3,0

-2,5

-2,0

-1,5

-1,0

-0,5

0,0

0,5

1,0

1,5

Changes in EEG

R=0.987; R2=0.974; χ2(68)=92; p=0.028; Λ Prime<10-3
Fig. 9. Scatterplot of canonical correlation between changes in EEG (X-line) and HRV (Y-line) parameters
A number of publications are known, starting from Van Buren & Ajmone-Marsan (1960) and ending with
Borghesi et al (2024), including our group (Popovych et al., 2014; Babelyuk et al., 2017; Zukow et al., 2024),
about relationships between EEG and HRV parameters as well as between HRV and cortical thickness or brain
activity in selected CAN regions (Sakaki et al., 2016; Winkelmann et al., 2017; Yoo et al., 2018; Carnevali et al.,2020; Matusik et al., 2023).
Therefore, the close connections between balneotherapy-induced changes in EEG and HRV parameters
revealed in this study are quite expected. Although EEG changes are plotted along the X-axis as a factor featureand HRV changes along the Y-axis as an outcome feature, the actual cause-and-effect relationships arebidirectional and are realized within the framework of the central autonomic network (Benarroch, 1993; Thayer& Lane, 2009; Palma & Benarroch, 2014).
Cortisol and Interleukin-6, which appeared in the constellation of the characteristic accompanying actotropic
effects of balneotherapy, have long been known as one of the key elements of the neuro-endocrine-immune
network (Besedovsky & Sorkin, 1977; Besedovsky & del Rey, 1996). We found significant connections betweenchanges in serum Cortisol and EEG parameters as well as autonomic reactivity (Table 10 and Fig. 10).

----------------------------------------------------------------------------------------------------------------------------1833
JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------Table 10. Regression Summary for changes in serum Cortisol
R=0.788; R2=0.621; Adjusted R2=0.456; F(10.2)=3.8; p=0.004
N=34

Beta

Variables
PSD Fp1 Entropy
PSD F7 Entropy
PSD F3 Entropy
PSD F7-θ, %PSD Fp2-α, %PSD F7-δ, %PSD Fp2-δ, %PSD T3-δ, µV2/Hz
PSD T5-δ, %Baevsky’s ARSI up standing

r
-0,48
-0,41
-0,32
-0,43
-0,38
0,42
0,37
0,37
0,37
0,29

St. Err.
of BetaIntercpt
0,326
0,360
0,248
0,198
0,291
0,277
0,311
0,180
0,265
0,141

-1,3341,144
0,520-0,4600,353
0,610-0,425
0,388
0,638
0,226

B

St. Err.
of B
44,9
441
409
511
10,72
5,608
2,294
2,757
0,136
2,062
20,27

-27,5
-1806
1303
1071
-24,92
6,818
5,054-3,767
0,293
4,955
32,34

t(23)
-0,61
-4,09
3,18
2,10
-2,32
1,22
2,20
-1,37
2,15
2,40
1,60

plevel
0,547
10-3
0,004
0,047
0,029
0,236
0,038
0,185
0,042
0,025
0,124

2,5

2,0

Changes in Cortisol

1,5

1,0

0,5

0,0

-0,5

-1,0

-1,5

-2,0
-2,0

-1,5

-1,0

-0,5

0,0

0,5

1,0

1,5

2,0

2,5

Changes in EEG&HRV

R=0.788; R2=0.621; χ2(10)=26; p=0.004; Λ Prime=0.379
Fig. 10. Scatterplot of canonical correlation between changes in EEG&HRV parameters (X-line) andserum Cortisol (Y-line)
It is important that all EEG parameters, without exception, related to cortisol, are included in the factor
structure of the EEG-root, which is related to the HRV-root (Table 9, highlighted in bold). This suggests thatneural structures projecting to these loci regulate both HRV and Cortisol. The changes in serum Interleukin-6 arealso associated with changes in EEG and HRV parameters as well as Calcitonin (Table 10 and Fig. 10).
Table 11. Regression Summary for changes in serum Interleukin-6
R=0.768; R2=0.590; Adjusted R2=0.436; F(9.2)=3.8; p=0.004
N=34

Beta

Variables
PSD T3-δ, µV2/Hz
PSD Fp2-δ, %PSD T5-δ, %Heart Rate, beats/min
1/Mode HRV, 1/msec
PSD O2-θ, %PSD Fp1 Entropy
PSD Fp2-α, %Calcitonin, ng/L

r
-0,44
-0,33
-0,32
-0,42
-0,30
0,45
0,38
0,33
0,28

-0,346
0,653-0,290-1,060-0,999
0,300
0,224
0,404
0,194

-2

-1

St. Err.
of BetaIntercpt
0,172
0,329
0,218
0,329
0,364
0,158
0,179
0,285
0,142

B
-0,334-0,00140,030-0,012-0,140-0,012
0,102
1,578
0,041
0,036

St. Err.
of B
0,204
0,0007
0,015
0,009
0,043
0,005
0,054
1,262
0,029
0,026

t(24)
-1,64
-2,01
1,99
-1,33
-3,22
-2,75
1,90
1,25
1,42
1,37

plevel
0,115
0,055
0,059
0,195
0,004
0,011
0,069
0,223
0,168
0,184

3

Changes in IL-6

2

1

0

-1

-2

0

1

2

3

Changes in EEG&HRV

2

2

R=0.768; R =0.590; χ (9)=25; p=0.004; Λ Prime=0.410
Fig. 11. Scatterplot of canonical correlation between changes in EEG&HRV parameters (X-line) andserum Interleukin-6 (Y-line)
1834---------------------------------------------------------------------------------------------------------------------------JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------According to the concept of the Truskavetsian Scientific School of Balneology, the active factors of
Naftussya water are polyphenols/aryl hydrocarbons, fatty acids and autochthonous bacteria, which through thecorresponding receptors (Ah, GP40/120, TL/NL) affect neurons of the enteric nervous system and immunocytesof the gut-associated lymphoid tissue (GALT), as well as microbiota cells.
The neurotransmitters and cytokines released under this influence, in turn, exert autocrine and paracrine
effects on the same or neighboring neurons and immunocytes, as well as on neurons of the autonomic and central
nervous systems, reaching them through the blood and activating afferent terminals of n. vagus and n.
splanchnicus. Next, the corresponding nerve nuclei of the cortex, brainstem, and medulla exert a modulating
effect both on the immunocytes of the bone marrow, thymus, spleen, lymph nodes, and again GALT, and on theendocrinocytes of at least the adrenals, gonads, and thyroid and parathyroid glands, whose hormones, in turn,affect immunocytes and neurons. A direct effect of aryl hydrocarbons and fatty acids on endocrinocytes andblood/lymph immunocytes is also possible (Popovych, 2022; Popovych, 2022a; Popovych et al., 2022;
Popovych et al., 2022a). It is important that aryl hydrocarbons are also present in the composition of Ozokerite
and realize their effects through Ah receptors of immunocytes of the skin-associated lymphoid tissue. This ismanifested in the similarity of the effects of both Naftussya and Ozokerite on neuro-endocrine-immune complex(Ruzhylo et al., 2021).
The results obtained in our study fit into the presented concept. The applied balneofactors, through themediation of the central autonomic and neuro-endocrine-immune networks, affect the mechanisms responsible
for physical performance, or rather its marker. Note that our study incorporates the recommendations ofArmstrong et al. (2022) regarding research in this direction. The authors in review about overtraining syndrome
noted that complex systems in nature are not aptly characterized or successfully analyzed using the classic
scientific method (i.e., simplifying complex problems into single variables in a search for cause-and-effect)
because they result from myriad (often non-linear) concomitant interactions of multiple determinants.
Authors proposes evidence-based areas for future overtraining syndrome investigations, including
concomitant multi-domain analyses incorporating brain neural networks, dysfunction of hypothalamic-pituitaryadrenal responses to training stress, the intestinal microbiota, immune factors, and low energy availability. As
you can see, such recommendations are implemented in our study.
However, the question remains open, why the same factor(s) cause polyvariate actotropic effects? Thissituation has been known for a long time. Hildebrandt (1980) showed that a 4-week endurance training,
performed at different times of day, yields different results: an early-morning training did not evoke a significant
increase of the PWC130, whereas the afternoon training gave maximum results. In relation to our study, it isimportant to note that different responses to therapeutical stimuli depended on the circadian phase wereaccompanied by different states of autonomic reactivity, also subject to circadian rhythms. Earlier we discovereda features of reactions to acute stress of neuro-endocrine-immune complex, metabolome, ECG and gastricmucosa in rats with various state of innate muscular endurance and resistance to hypoxia (Fil et al., 2021;
Zukow et al., 2022; Melnyk et al., 2023).
In the next article, which has already been prepared for printing, we will show that using the method of
discriminant analysis, 25 initial parameters identified, based on the totality of which the nature of the actotropic
effect of balneotherapy can be predicted with 100% accuracy.
Conclusion
1. The multivariate actotropic effects of balneofactors are due to their multivariate effects on neuro-endocrine
regulation and metabolism, which, apparently, is determined by the peculiarities of the individual reactivity ofthe body.
2. Our study confirms the heterogeneity of responses to balneotherapy at Truskavets' Spa, with some patients
experiencing increased physical working capacity, others showing decreased capacity, and a third group
maintaining stable levels.
3. The discriminant analysis revealed 24 variables as characteristic accompaniments of the three variants ofactotropic effects, including hemodynamic, neural (EEG and HRV), endocrine, and metabolic parameters. This
comprehensive approach allows for a more nuanced understanding of the physiological changes associated withbalneotherapy.
4. The close connections between balneotherapy-induced changes in EEG and HRV parameters highlight theimportance of the central autonomic network in mediating these effects.
5. The involvement of cortisol and interleukin-6 in the characteristic accompanying effects underscores the roleof the neuro-endocrine-immune network in the body's response to balneotherapy.
6. The study demonstrates the potential of using initial physiological parameters to predict not only the direction
but also the magnitude of fitness response to balneotherapy. This could lead to more personalized and effective
treatment plans.
7. The observed sexual dimorphism in neuro-endocrine regulation of bicycle ergometric test parameters suggeststhat gender-specific approaches may be necessary when designing balneotherapy protocols.

----------------------------------------------------------------------------------------------------------------------------1835
JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------8. The findings support the concept of the Truskavetsian Scientific School of Balneology regarding the active
factors in Naftussya water and their effects on the enteric nervous system, gut-associated lymphoid tissue, andmicrobiota.
9. This research contributes to the growing body of evidence supporting the complex systems approach inunderstanding overtraining syndrome and related physiological adaptations.
10. Future studies should focus on longitudinal effects of balneotherapy, potential molecular mechanisms
underlying the observed changes, and the development of predictive models for individualized balneotherapy
protocols.
Acknowledgment
We express sincere gratitude to Korolyshyn TA and Kikhtan VV as well as administration and employees ofclinical sanatorium “Moldova” for help in carry out of tests. Special thanks to the volunteers.
Accordance to ethics standards
Tests in patients are carried out in accordance with positions of Helsinki Declaration 1975, revised andcomplemented in 2002, and directive of National Committee on ethics of scientific researches. During
realization of tests from all participants the informed consent is got and used all measures for providing ofanonymity of participants.
Conflicts of interest - No conflicts of interest to declare.
References
Andreyeva, L. I., Kozhemyakin, L. A., & Kishkun, A. A. (1988). Modification of the method for determining thelipid peroxide in the test with thiobarbituric acid [in Russian]. Laboratornoye Delo, 11, 41-43.
Armstrong, L. E., Bergeron, M. F., Lee, E. C., Mershon, J. L., & Armstrong, E. J. (2022). Overtraining
Syndrome as a Complex Systems Phenomenon. Frontiers in Network Physiology, 1, 794392.
https://doi.org/10.3389/fnetp.2021.794392
Babelyuk, V. Y., Dubkova, G. I., Korolyshyn, T. A., Holubinka, S. M., Dobrovol's'kyi, Y. G., Zukow, W.,
Popovych, D. V., Korsuns'kyi, I. H., Królczyk, G., & Popovych, I. L. (2017). Operator of Kyokushin
Karate via Kates increases synaptic efficacy in the rat Hippocampus, decreases C3-θ-rhythm SPD
and HRV Vagal markers, increases virtual Chakras Energy in the healthy humans as well asluminosity of distilled water in vitro. Preliminary communication. Journal of Physical Educationand Sport, 17(1), 383-393. https://doi.org/10.7752/jpes.2017.01057
Baevsky, R. M., & Chernikova, A. G. (2017). Heart rate variability analysis: physiological foundations and main
methods. Cardiometry, 10, 66-76. https://doi.org/10.12710/CARDIOMETRY.2017.10.6676
Baevsky, R. M., & Ivanov, G. G. (2001). Heart Rate Variability: theoretical aspects and possibilities of clinicalapplication [in Russian]. Ultrazvukovaya i funktsionalnaya diagnostika, 3, 106-127.
Benarroch, E. E. (1993). The central autonomic network: functional organization, dysfunction, and perspective.
Mayo Clinic Proceedings, 68(10), 988-1001. https://doi.org/10.1016/s0025-6196(12)62272-1
Berntson, G. G., Bigger, J. T., Eckberg, D. L., Grossman, P., Kaufmann, P. G., Malik, M., Nagaraja, H. N.,
Porges, S. W., Saul, J. P., Stone, P. H., & van der Molen, M. W. (1997). Heart rate variability:
Origins,
methods,
andinterpretive
caveats.
Psychophysiology,
34(6),
623-648.
https://doi.org/10.1111/j.1469-8986.1997.tb02140.x
Besedovsky, H. O., & del Rey, A. (1996). Immune-neuro-endocrine interactions: facts and hypotheses.
Endocrine Reviews, 17(1), 64-102. https://doi.org/10.1210/edrv-17-1-64
Besedovsky, H. O., & Sorkin, E. (1977). Network of immune-neuroendocrine interactions. Clinical andExperimental Immunology, 27(1), 1-12.
Bobrov, V. A., Stadnyuk, L. A., & Kryzhanivs'kyi, V. O. (1997). Echocardiography [in Ukrainian]. Kyiv:
Zdorovya.
Borghesi, F., Cremascoli, R., Chirico, A., Roveda, E., Castelnuovo, G., Manzoni, G. M., Marelli, S., Venturini,
E., Cavallotti, S., Sforza, M., Villani, L., Pala, F., Ferrucci, R., & Montano, N. (2024). Mind andbody connection in expert meditators: a computational study based on central and peripheral nervous
system. BMC Complementary Medicine and Therapies, 24(1), 117. https://doi.org/10.1186/s12906024-04413-5
Carnevali, L., Pattini, E., Sgoifo, A., & Ottaviani, C. (2020). Effects of prefrontal transcranial direct current
stimulation on autonomic and neuroendocrine responses to psychosocial stress in healthy humans.
Stress, 23(1), 26-36. https://doi.org/10.1080/10253890.2019.1625884
Dobiásová, M., Frohlich, J., Sedová, M., Cheung, M. C., & Brown, B. G. (2011). Cholesterol esterification andatherogenic index of plasma correlate with lipoprotein size and findings on coronary angiography.
Journal of Lipid Research, 52(3), 566-571. https://doi.org/10.1194/jlr.P011668
Dubinina, Y. Y., Yefimova, L. F., Sofronova, L. N., & Geronimus, A. L. (1988). Comparative analysis of theactivity of superoxide dismutase and catalase of erythrocytes and whole blood from newborn
children with chronic hypoxia [in Russian]. Laboratornoye Delo, 8, 16-19.
1836---------------------------------------------------------------------------------------------------------------------------JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------Fihura, O., Ruzhylo, S., & Zakalyak, N. (2022). Phytoadaptogen reverses the adverse effects of Naftussya
bioactive water on dynamic muscle performance in healthy rats. Quality in Sport, 8(2), 45-55.
https://doi.org/10.12775/qs.2021.08.02.004
Fil, V. M., Zukow, W., Kovalchuk, G. Y., Popovych, I. L., Kozyavkina, O. V., Kozyavkina, N. V., Barylyak, L.
G., Krivokulska, O. H., Hrytsan, I. I., & Gozhenko, A. I. (2021). The role of innate muscular
endurance and resistance to hypoxia in reactions to acute stress of neuroendocrine, metabolic andECGs parameters and gastric mucosa in rats. Journal of Physical Education and Sport, 21(Suppl. 5),
3030-3039. https://doi.org/10.7752/jpes.2021.s5391
Finger, J. D., Krug, S., Gößwald, A., Härtel, S., & Bös, K. (2013). Kardiorespiratorische Fitness bei
Erwachsenen in Deutschland: Ergebnisse der Studie zur Gesundheit Erwachsener in Deutschland(DEGS1). Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz, 56, 772-778.
https://doi.org/10.1007/s00103-013-1672-y
Gavrilov, V. B., & Mishkorudnaya, M. I. (1983). Spectrophotometric determination of plasma levels of lipidhydroperoxides [in Russian]. Laboratornoye Delo, 3, 33-36.
Goryachkovskiy, А. М. (1998). Clinical Biochemistry [in Russian]. Odesa: Astroprint. 608.
Gozhenko, А. I., Korda, M. M., Popadynets', O. H., & Popovych, I. L. (2021). Entropy, Harmony,
Synchronization and their Neuro-endocrine-immune Correlates [in Ukrainian]. Odesa: Feniks. 232.
Heart Rate Variability. (1996). Standards of Measurement, Physiological Interpretation, and Clinical Use. Task
Force of the European Society of Cardiology and the North American Society of Pacing andElectrophysiology. Circulation, 93(5), 1043-1065. https://doi.org/10.1161/01.CIR.93.5.1043
Hildebrandt, G. (1980). Chronobiological aspects of cure treatment. Journal of Japanese Society of Balneology,
Climatology and Physical Medicine, 44(1-2), 1-37.
Hiller, G. (1987). Test for the quantitative determination of HDL cholesterol in EDTA plasma with Reflotron®.
Klinische Chemie, 33, 895-898.
Hrinchenko, B. V. (1998). A comparative study of the effect of balneotherapy with the use of Krymskyi and
Bittner balms on physical performance and central hemodynamics [in Ukrainian]. Ukrainian
Balneological Journal, 1(4), 36-38.
Hrinchenko, B. V., Ruzhylo, S. V., Flyunt, I. S., Popovych, I. L., Zukow, W., & Gozhenko, A. I. (1999). The
effect of complex balneotherapy at the Truskavets' resort with the use of phytoadaptogen on
psychophysiological functions and physical performance [in Ukrainian]. Medical Hydrology andRehabilitation, 2(1), 31-35.
Klecka, W. R. (1989). Discriminant Analysis [trans. from English in Russian] (Seventh Printing, 1986). In:
Factor, Discriminant and Cluster Analysis. Moskva: Finansy i Statistika, 78-138.
Korolyuk, M. A., Ivanova, L. I., Mayorova, I. G., & Tokarev, V. E. (1988). The method for determining theactivity of catalase [in Russian]. Laboratornoye Delo, 1, 16-19.
Matusik, P. S., Zhong, C., Matusik, P. T., & Stein, P. K. (2023). Neuroimaging Studies of the Neural Correlatesof Heart Rate Variability: A Systematic Review. Journal of Clinical Medicine, 12(3), 1016.
https://doi.org/10.3390/jcm12031016
Melnyk, O. I., Chendey, I. V., Zukow, W., Popovych, I. L., & Gozhenko, A. I. (2023). The features of reactions
to acute stress of neuro-endocrine-immune complex, metabolome, ECG and gastric mucosa in rats
with various state of innate muscular endurance and resistance to hypoxia. Journal of Education,
Health and Sport, 38(1), 96-128. https://doi.org/10.12775/JEHS.2023.38.01.007
Newberg, A. B., Alavi, A., Baime, M., Pourdehnad, M., Santanna, J., & d'Aquili, E. (2001). The measurement ofregional cerebral blood flow during the complex cognitive task of meditation: A preliminary SPECT
study. Psychiatry Research: Neuroimaging, 106(2), 113-122. https://doi.org/10.1016/S09254927(01)00074-9
Palma, J. A., & Benarroch, E. E. (2014). Neural control of the heart: Recent concepts and clinical correlations.
Neurology, 83(3), 261-271. https://doi.org/10.1212/WNL.0000000000000605
Polovynko, I. S., Zajats, L. M., Zukow, W., Yanchij, R. I., Popovych, I. L., & Matiyishyn, G. Y. (2016).
Quantitative evaluation of integrated neuroendocrine and immune responses to chronic stress in rats
male. Journal of Education, Health and Sport, 6(8), 154-166. https://doi.org/10.5281/zenodo.60023
Popadynets, O., Gozhenko, A., Badyuk, N., Popovych, I., Skaliy, A., Hagner-Derengowska, M., Napierała, M.,
Muszkieta, R., Sokołowski, D., Zukow, W., & Rybałko, L. (2020). Interpersonal differences causedby adaptogen changes in entropies of EEG, HRV, immunocytogram, and leukocytogram. Journal of
Physical Education and Sport, 20(Suppl. 2), 982-999. https://doi.org/10.7752/jpes.2020.s2139
Popovych, I. L. (2022). Similarity effects of two types of adaptogens (transcutaneous electrical stimulation withthe device "VEB" ® and using of bioactive Naftussya water) on the human body. Journal of
Education, Health and Sport, 12(4), 213-258. https://doi.org/10.12775/JEHS.2022.12.04.019
Popovych, I. L. (2022). Similarity of adaptogenic effects of bioactive Naftussya water and phytocomposition"Balm Truskavets'". Journal of Education, Health and Sport, 12(12), 344-356.
https://doi.org/10.12775/JEHS.2022.12.12.052----------------------------------------------------------------------------------------------------------------------------1837
JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------Popovych, I. L., Gozhenko, A. I., Hrytsak, M. V., Barylyak, L. G., Korolyshyn, T. A., Kovalchuk, H. Y.,
Usyns'kyi, R. S., Zukow, W., & Khominskyi, P. Y. (2022). General non-specific effects ofbalneofactors of Truskavets' spa on parameters of neuroendocrine regulation, metabolism, immunity
and microbiota in patients with chronic pyelonephritis and cholecystitis. Journal of Education,
Health and Sport, 12(1), 368-384. https://doi.org/10.12775/JEHS.2022.12.01.032
Popovych, I. L., Gozhenko, A. I., Korda, M. M., Klishch, I. M., Popovych, D. V., & Zukow, W. (Eds.). (2022).
Mineral Waters, Metabolism, Neuro-Endocrine-Immune Complex. Odesa: Feniks. 252.
Popovych, I. L., Kozyavkina, N. V., Barylyak, L. G., Popovych, A. I., Kozyavkina, O. V., Gozhenko, A. I.,
Zukow, W., & Korsuns'kyi, I. H. (2022). Variants of changes in blood pressure during its threeconsecutive registrations. Journal of Education, Health and Sport, 12(4), 365-375.
https://doi.org/10.12775/JEHS.2022.12.04.032
Popovych, I. L., Kozyavkina, O. V., Kozyavkina, N. V., Korolyshyn, T. A., Lukovych, Y. S., & Barylyak, L. G.
(2014). Correlation between Indices of the Heart Rate Variability and Parameters of Ongoing EEG
in Patients Suffering from Chronic Renal Pathology. Neurophysiology, 46(2), 139-148.
https://doi.org/10.1007/s11062-014-9420-y
Popovych, I. L., Ruzhylo, S. V., Ivassivka, S. V., & Aksentiychuk, B. I. (Eds.). (2005). Balneocardioangiology.
The impact of balneotherapy in the spa Truskavets' on the cardiovascular system and physicalperformance [in Ukrainian]. Kyiv: Computerpress.
Ruzhylo, S. V., Fihura, O. B., Zakalyak, N. R., Popovych, I. L., Zukow, W., & Gozhenko, A. I. (2022). Sexual
dimorphism in the neuro-endocrine regulation of bicycle ergometric test parameters in untrained
individuals with dysfunction of the neuro-endocrine-immune complex. Journal of Education, Healthand Sport, 12(9), 971-984. https://doi.org/10.12775/JEHS.2022.12.09.110
Ruzhylo, S. V., Popovych, A. I., Zakalyak, N. R., Korda, M. M., Klishch, I. M., Popovych, I. L., & Zukow, W.
(2021). Bioactive water Naftussya and ozokerite have the same neuro-endocrine-immune effects inmale rats caused by aryl hydrocarbons. PharmacologyOnLine, 3, 213-226.
Ruzhylo, S. V., Tserkovnyuk, A. V., & Popovych, I. L. (2003). Actotropic Effects of BalneotherapeuticComplex of Truskavets Spa [in Ukrainian]. Kyiv: Computerpress.
Sakaki, M., Yoo, H. J., Nga, L., Lee, T. H., Thayer, J. F., & Mather, M. (2016). Heart rate variability is
associated with amygdala functional connectivity with MPFC across younger and older adults.
NeuroImage, 139, 44-52. https://doi.org/10.1016/j.neuroimage.2016.05.076
Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
Steinhilber, B., Seibt, R., Gabriel, J., Mayer, L., Seri, M., Reims, N., & Rieger, M. A. (2022). Effects of Face
Masks on Physical Performance and Physiological Response during a Submaximal Bicycle
Ergometer Test. International Journal of Environmental Research and Public Health, 19(3), 1063.
https://doi.org/10.3390/ijerph19031063
Thayer, J. F., & Lane, R. D. (2009). Claude Bernard and the heart-brain connection: Further elaboration of amodel of neurovisceral integration. Neuroscience & Biobehavioral Reviews, 33(2), 81-88.
https://doi.org/10.1016/j.neubiorev.2008.08.004
Van Buren, J. M., & Ajmone-Marsan, C. (1960). A correlation of autonomic and EEG components in temporal
lobe
epilepsy.
Archivesof
Neurology,
3,683-703.
https://doi.org/10.1001/archneur.1960.00450060071009
Winkelmann, T., Thayer, J. F., Pohlack, S., Nees, F., Grimm, O., & Flor, H. (2017). Structural brain correlates ofheart rate variability in a healthy young adult population. Brain Structure and Function, 222(2),1061-1068. https://doi.org/10.1007/s00429-016-1185-1
Yoo, H. J., Thayer, J. F., Greening, S., Lee, T. H., Ponzio, A., Min, J., Sakaki, M., Nga, L., Mather, M., &Koenig, J. (2018). Brain structural concomitants of resting state heart rate variability in the young
and old: evidence from two independent samples. Brain Structure and Function, 223(2), 727-737.
https://doi.org/10.1007/s00429-017-1519-7
Zukow, W., Gozhenko, O. A., Zavidnyuk, Y. V., Korda, M. M., Mysula, I. R., Klishch, I. M., ... & Skaliy, A.
(2024). Prevention of adverse effects of balneofactors at Truskavets' Spa on gastroenterologic
patients through phytoadaptogens and therapeutic physical education: mechanisms of rehabilitation.
Journal of Physical Education and Sport, 24(4), 791-810. https://doi.org/10.7752/jpes.2024.04093
Zukow, W., Fil, V., Kovalchuk, H., Popovych, I., Barylyak, L., Muszkieta, R., Napierała, M., HagnerDerengowska, M., Zukow, X., & Gozhenko, A. (2022). The role of innate muscular endurance andresistance to hypoxia in reactions to acute stress of immunity in rats. Journal of Physical Educationand Sport, 22(7), 1608-1617. https://doi.org/10.7752/jpes.2022.07202
Zukow, W., Flyunt, I.-S., Ponomarenko, R., Popovych, I., Padoshchak, A., Babelyuk, V., Dobrovolsky, Y.,
Gozhenko, A., Skaliy, A., & Zukow, X. (2020). Polyvariant change of step-test under the influenceof natural adaptogens and their accompaniments. Pedagogy and Psychology of Sport, 6(2), 74-84.
https://doi.org/10.12775/PPS.2020.06.02.007
1838---------------------------------------------------------------------------------------------------------------------------JPES ® www.efsupit.roIGOR L. POPOVYCH, WALERY ZUKOW, OKSANA I. MELNYK, XAWERY ŻUKOW, OLGA SMOLEŃSKA, ANNAMICHALSKA, RADOSLAW MUSZKIETA, MAGDALENA HAGNER-DERENGOWSKA--------------------------------------------------------------------------------------------------------------------------------------Zukow, W., Gozhenko, O., Zavidnyuk, Y., Popovych, I., Krasnyanska, R., Kindrat, I., Yanchiy, R., Zukow, X.,
Bilas, V., & Gozhenko, A. (2020). Role of organic carbon and nitrogen of mineral waters in theirneuro-endocrine effects at female rats. International Journal of Applied Exercise Physiology, 9(4),20-25.
Zukow, W., Muszkieta, R., Hagner-Derengowska, M., Smoleńska, O., Żukow, X., Melnik, O. I., ... & Popovych,
I. L. (2022). Effects of rehabilitation at the Truskavets' spa on physical working capacity and its
neural, metabolic, and hemato-immune accompaniments. Journal of Physical Education and Sport,
22(11), 2708-2722. https://doi.org/10.7752/jpes.2022.11345
Zukow, W., Muszkieta, R., Hagner-Derengowska, M., Smoleńska, O., Żukow, X., Fil, V. M., ... & Popovych, I.
L. (2022). Role of organic substances of Naftussya bioactive water in its effects on dynamic andstatic fitness in rats. Journal of Physical Education and Sport, 22(11), 2733-2742.
https://doi.org/10.7752/jpes.2022.11347----------------------------------------------------------------------------------------------------------------------------1839
JPES ® www.efsupit.ro