24 Popadynets’ Oleksandr O., Gozhenko Anatoliy I., Badiuk Nataliya S., Zukow Walery, Kovbasnyuk Marta M., Korolyshyn Tetyana A., Popovych Igor L. Relationships between changes in entropy of the EEG and parameters of the immunity. Pedagogy and Psychology of Sport. 2020;6(1):24-40. elSSN 2450-6605. DOI http://dx.doi.org/10.12775/PPS.2020.06.01.003 https://apcz.umk.pl/czasopisma/index.php/PPS/article/view/PPS.2020.06.01.003 https://zenodo.org/record/3661196 The journal has had 5 points in Ministry of Science and Higher Education parametric evaluation. § 8. 2) and § 12. 1. 2) 22.02.2019. © The Authors 2020; This article is published with open access at Licensee Open Journal Systems of Nicolaus Copernicus University in Torun, Poland Open Access. This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author (s) and source are credited. This is an open access article licensed under the terms of the Creative Commons Attribution Non commercial license Share alike. (http://creativecommons.org/licenses/by-nc-sa/4.0/) which permits unrestricted, non commercial use, distribution and reproduction in any medium, provided the work is properly cited. The authors declare that there is no conflict of interests regarding the publication of this paper. Received: 05.01.2020. Revised: 25.01.2020. Accepted: 10.02.2020. RELATIONSHIPS BETWEEN CHANGES IN ENTROPY OF THE EEG AND PARAMETERS OF THE IMMUNITY Oleksandr O. Popadynets’1, Anatoliy I. Gozhenko1, Nataliya S. Badiuk1, Walery Zukow2, Marta M. Kovbasnyuk3, Tetyana A. Korolyshyn3, Igor L. Popovych1,3 1Ukrainian Scientific Research Institute of Medicine for Transport, Odesa, Ukraine daddysbestmail@gmail.com 2Nicolaus Copernicus University, Torun, Poland w.zukow@wp.pl 3OO Bohomolets’ Institute of Physiology, Kyїv, Ukraine i.popovych@biph.kiev.ua Abstract Background. Previously, we have shown that the entropy of the normalized parameters of the HRV and spectral power density (SPD) of loci of EEG significantly correlate with the entropy and parameters of immunity, which testifies to their modulating regulatory effects. The purpose of this study is to analyze the relationships between changes in entropy and immunity under the influence of natural adaptogens. Material and methods. In basal conditions in 37 men and 14 women with chronic pyelonephritis and cholecystitis in remission as well as without clinical diagnose but with dysfunction of neuro-endocrine-immune complex and metabolism, we recorded twice, before and after balneotherapy at the spa Truskavets’, EEG (“NeuroCom Standard”) and HRV (“Cardiolab+VSR”). Than we evaluated immune status on a set of I and II levels recommended by the WHO. The Entropy of normalized SPD for each locus of EEG and HRV as well as Immunocytogram and Leukocytogram calculated using Shannon’s formula. Results. Preliminary analysis revealed different orientation of entropy changes in patients, so three clusters were created. Balneotherapy has a generalized negentropic effect on EEG of 2/3 patients. On the other hand, the members of the other two clusters have substantially increased EEG entropy overall, but there are significant differences with respect to individual loci. The immunotropic effects of balneotherapy are unrelated to changes in integral entropy of EEG. As a result of discriminant analysis were selected as characteristic entropy changes at only 9 loci out of 16, accompanied by changes in 10 partial parameters of immunity and integral immune index, as well as Popovych’s Leukocytogram Strain Index-2. Conclusion. Balneotherapy causes multivariate entropy changes of individual EEG loci, conditioned by a number of predictors. This is accompanied by characteristic changes in certain parameters of immunity in line with the concept of immune homunculus. http://dx.doi.org/10.12775/PPS.2020.06.01.003 https://apcz.umk.pl/czasopisma/index.php/PPS/article/view/PPS.2020.06.01.003 https://zenodo.org/record/3661196 mailto:daddysbestmail@gmail.com mailto:w.zukow@.wp.pl mailto:i.popovych@biph.kiev.ua 25 Key words: EEG, HRV, Immunity, Entropy, Relationships, Balneotherapy. INTRODUCTION Previously, we have shown that in patients with chronic pyelonephritis and cholecystitis in remission as well as without clinical diagnose but with dysfunction of neuro-endocrine-immune complex and metabolism entropy of the relative (normalized) parameters of the HRV and SPD of loci of EEG significantly correlate with the entropy and parameters of immunity, which testifies to their modulating regulatory effects [7,19-21,44]. The purpose of this study is to analyze the relationships between changes in entropy and immunity under the influence of balneotherapeutic factors. The choice of the latter is due to their ability as natural adaptogens to exert a modulatory effect on the neuroendocrine-immune complex [9-13,15,23,24,26-28]. IL Popovych [26] advanced conception about stresslimiting adaptogene mechanism of biological and curative activity of Naftussya Water that including participation of nervous, endocrine and immune systems closely interacting in the bounds of neuroendocrine-immune complex MATERIAL AND METHODS The object of observation were 37 men and 14 women aged 23-76 years old, who came to the Truskavets’ spa (Ukraine) for the treatment of chronic pyelonephritis and cholecystitis in remission as well as without clinical diagnose but with dysfunction of neuroendocrine-immune complex and metabolism. The survey was conducted twice, before and after standard balneotherapy (drinking bioactive water Naftussya three times a day, ozokerite applications, mineral baths every other day for 7-10 days) [28]. We recorded electrocardiogram in II lead (hardware-software complex "CardioLab+HRV" produced by "KhAI-MEDICA", Kharkiv, Ukraine) to assess the parameters of heart rate variability (HRV). For further analysis (Frequency Domain Methods) were selected spectral power (SP) bands of 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 ultra low-frequency (ULF, range 0,015÷0,003 Hz) [1,3,8]. Simultaneosly we recorded EEG (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 tassels of ears. Among the options considered the average EEG amplitude (μV), average frequency (Hz), frequency deviation (Hz), index (%), coefficient of asymmetry (%) as well as absolute (μV2/Hz) and relative (%) spectral power density (SPD) in the standard frequency bands: β (35÷13 Hz), α (13÷8 Hz), θ (8÷4 Hz) and δ (4÷0,5 Hz) in all loci, according to the instructions of the device. We calculated also for HRV and each locus EEG the Entropy (h) of normalized SPD using adapted formula [25,43] based on classical CE Shannon’s formula [35]: hHRV=[SPDHF•log2SPDHF+SPDLF•log2SPDLF+SPDVLF•log2SPDVLF+SPDULF•log2SPDULF]/log24 hEEG = - [SPDα•log2SPDα+SPDβ•log2SPDβ+SPDθ•log2SPDθ+SPDδ•log2SPDδ]/log24 In portion of capillary blood we counted up Leukocytogram (LCG) (Eosinophils, Stub and Segmentonucleary Neutrophils, Lymphocytes and Monocytes) and calculated two variants of Adaptation Index as well as two variants of Strain Index by IL Popovych [2,15,18]. Strain Index-1 = [(Eo/3,5-1)2 + (SN/3,5-1)2 + (Mon/5,5-1)2 + (Leu/6-1)2]/4 26 Strain Index-2 = [(Eo/2,75-1)2 + (SN/4,25-1)2 + (Mon/6-1)2 + (Leu/5-1)2]/4 Immune status evaluated on a set of I and II levels recommended by the WHO. For phenotyping subpopulations of lymphocytes used the methods of rosette formation with sheep erythrocytes on which adsorbed monoclonal antibodies against receptors CD3, CD4, CD8, CD22 and CD56 from company "Granum" (Kharkiv) with visualization under light microscope with immersion system. Subpopulation of T cells with receptors high affinity (“active” T Lymphocytes) determined by test of active rosette formation. The state of humoral immunity judged by the concentration in serum of Immunoglobulins classes G, A, M (ELISA, analyser “Immunochem”, USA) and circulating immune complexes (by polyethylene glycol precipitation method). We calculated also the Entropy (h) of Immunocytogram (ICG) and LCG using similar formulas: hICG = - [CD4•log2CD4+CD8•log2CD8+CD22•log2CD22+CD16•log2CD16]/log24 hLCG = - [Lymph•log2Lymph+Mon•log2Mon+Eos•log2Eos+SNN•log2SNN+StubN•log2StubN]/log25 Parameters of phagocytic function of neutrophils estimated as described by MM Kovbasnyuk [29]. The objects of phagocytosis served daily cultures of Staphylococcus aureus (ATCC N 25423 F49) as typical specimen for Gram-positive Bacteria and Escherichia coli (O55 K59) as typical representative of Gram-negative Bacteria. Both cultures obtained from Laboratory of Hydro-Geological Regime-Operational Station JSC “Truskavets’kurort”. Take into account the following parameters of phagocytosis: activity as percentage of neutrophils, in which found microbes - Hamburger’s Phagocytic Index; intensity as number of microbes absorbed one phagocytes - Microbial Count (MC) or Right’s Index; completeness as percentage of dead microbes - Killing Index (KI). Based of these parameters were calculated the Bactericidity of Neutrophils (BCN), contained in 1 L of blood, by formula [28]: BCN (109 Bacteras/L) = Leuk(109/L)•Neutrophils (%)•PhI (%)•MC (B/Phag)•KI (%)/104 Eleven key immune parameters were used to calculate the Immune Status Index (ISI) by the formula: ISI=(BCN vs St. aur.+BCN vs E. coli+CIC+IgM+IgG+IgA+B+NK+Th+Tc+Ta)/11. Results processed using the software package "Statistica 5.5". RESULTS AND DISCUSSION Preliminary analysis revealed different orientation of entropy changes in patients [22], so three groups were created, significantly different from each other in terms of entropy changes, while the differences between the members of each group were much smaller. In Fig. 1 shows the profiles of changes in the normalized entropy values for individuals of different clusters. 27 Fig. 1. Z-scores (M±SE) of changes in the entropy of SPD in loci of EEG as well as of HRV, LCG and ICG in members of different clusters As can be seen, individuals in the major first cluster (66,7% of the cohort) are characterized by a moderate and approximately equal decrease in SPD entropy at all EEG loci in the absence of significant changes in HRV, ICG, and LCG entropy. In individuals in the second cluster (19,6% of the cohort), the scope for the absence of significant entropy changes in HRV, ICG and LCG is supplemented by loci C4, C3, F3, F4, T4 and T3, and in the other 10 loci the entropy level is moderately increased. In members of the third cluster (13,7% of the cohort), with the similar entropy stability of HRV, ICG and LCG, balneotherapy does not significantly affect the entropy of SPD at F8 and O2 loci, increasing it at Fp2, T6, O1 loci to a lesser extent than in the second. clusters, at the F7, T5, Fp1, P3, P4, and T4 loci are almost similar, and at the T3, F4, F3, C3, and C4 loci are much more pronounced. Therefore, balneotherapy has a generalized negentropic effect on EEG of 2/3 patients. On the other hand, the members of the other two clusters have substantially increased EEG entropy overall, but there are significant differences with respect to individual loci. The integral proentropic effect of balneotherapy is greater in the members of the third cluster, but insignificantly. The entropy changes of HRV, ICG, and LCG are within ±0,5 σ, which we consider to be insignificant (Fig. 2). 28 Fig. 2. Changes in normalized entropy of SPD of loci of EEG, HRV, Immunocytogram and Leukocytogram in members of different clusters In view of the previously identified links between the parameters of EEG entropy and immunity [21] , the question is, do entropy changes affect the body's immune status? To find out, we compare the normalized profiles of integral entropy and the parameters of immunity before and after balneotherapy (Fig. 3). As we can see, in the members of the first cluster, the complete normalization of the upper boundary level of integral EEG entropy is accompanied by the normalization of the substantially reduced bactericidal ability of neutrophils against to both types of microbes. In this case, moderately elevated levels of B lymphocytes and IgM are almost unchanged, and other parameters of immunity remain stably normal. Instead, the opposite entropy effect of balneotherapy, namely, moving its level from the mid-normal zone to the upper boundary, is accompanied by a decrease in the initially normal levels of IgA, monocytes, and entropy of the leukocytogram, as well as an initially elevated level of eosinophils. Instead, the upper boundary level of B lymphocytes becomes even higher in the absence of significant changes in other immune parameters, irrespective of their initial levels. In the members of the third cluster complete normalization of the initial negentropy is accompanied by a normalizing decrease in the increased levels of IgA and bactericidal ability of neutrophils against E. coli, on the one hand, and a decrease in the normal levels of monocytes and bactericidity of neutrophils against Staph. aureus - on the other hand. However, the level of eosinophils rises from the lower normal zone to the upper, and moderately elevated levels of IgM and B lymphocytes become even higher. 29 Fig. 3. Profiles of normalized levels of integral EEG entropy and parameters of immunity in members of different clusters before and after balneotherapy It seems that the immunotropic effects of balneotherapy are unrelated to changes in integral entropy of EEG. Therefore, a discriminant analysis [14] was subsequently applied to identify, 30 firstly, those loci whose entropy changes differ clusters from each other, and second, constellations of immune parameters that change are characteristic of each cluster. The program selected as characteristic entropy changes at only 9 loci out of 16, accompanied by changes in 10 partial parameters of immunity and integral immune index, as well as Popovych’s Leukocytogram Strain Index-2. Interestingly, the entropies of immunocytogram, leukocytogram, and HRV were outside the discriminatory model (Tables 1 and 2). Table 1. Discriminant Function Analysis Summary for Changes in Variables of Entropy and Immunity in Clusters Step 21, N of vars in model: 21; Grouping: 3 grps Wilks' Lambda: 0,0187; approx. F(42)=8,4; p<10-6 Variables currently in the model Cluster No.2 (10) Cluster No. 3 (7) Cluster No.1 (34) Wilks' Λ Parti- al Λ F-re- move 2,28 p- level Tole- rancy O1H +0,251 +0,108 -0,071 ,025 ,736 5,0 ,014 ,331 P3H +0,103 +0,144 -0,039 ,033 ,559 11,0 ,0003 ,337 O2H +0,191 +0,022 -0,071 ,029 ,641 7,8 ,002 ,230 F7H +0,262 +0,176 -0,060 ,034 ,550 11,5 ,0002 ,264 T4H +0,038 +0,093 -0,127 ,024 ,763 4,4 ,023 ,536 T6H +0,172 +0,077 -0,066 ,029 ,637 8,0 ,002 ,175 F8H +0,220 -0,117 -0,111 ,034 ,546 11,6 ,0002 ,182 Phagocytose Ind vs Staph. aur., % +0,23 +0,24 +0,10 ,023 ,805 3,4 ,048 ,475 Immune Status Index-11 +0,11 -0,16 +0,41 ,035 ,541 11,9 ,0002 ,060 Leukocytes, 109/L -0,33 -0,42 +0,13 ,025 ,747 4,7 ,017 ,227 Stub Neutrophils, % -0,10 -0,07 +0,35 ,052 ,360 24,9 10-5 ,124 CD3+ T active Lymphocytes, % -0,6 +0,1 +0,7 ,030 ,625 8,4 ,001 ,356 C3H -0,012 +0,253 -0,065 ,034 ,549 11,5 ,0002 ,395 T3H -0,055 +0,156 -0,111 ,030 ,622 8,5 ,001 ,491 Eosinophiles, % -1,50 +0,91 -0,10 ,020 ,944 ,8 ,448 ,505 Popovych’s Strain Index-2, points -0,163 -0,004 -0,032 ,034 ,546 11,6 ,0002 ,346 Micr Count vs St. aur., Bact/Phag +0,6 +3,8 +0,35 ,030 ,630 8,2 ,002 ,292 CD4+ T-helper Lymphocytes, % +0,3 +1,3 +1,2 ,022 ,867 2,1 ,136 ,489 Killing Index vs Staph. aureus, % +3,0 -5,7 +6,2 ,041 ,453 16,9 10-4 ,107 Killing Index vs E. coli, % +5,5 -5,9 +7,7 ,022 ,845 2,6 ,095 ,264 Phagocytose Index vs E. coli, % +0,22 -1,12 +0,01 ,035 ,537 12,1 ,0002 ,223 Variables currently not in the model Df for all F-tests: 2,27 Cluster No.2 (10) Cluster No. 3 (7) Cluster No.1 (34) Wilks' Λ Parti- al Λ F to enter p- level Tole- rancy Immunocytogram H +0,018 -0,002 0,000 ,018 ,971 ,40 ,674 ,493 Leukocytogram H -0,026 -0,001 +0,005 ,019 ,995 ,07 ,935 ,370 HRV H -0,012 +0,011 +0,030 ,018 ,980 ,28 ,760 ,570 31 Table 2. Summary of Stepwise Analysis for Changes in Variables of Entropy and Immunity in Clusters. The variables are ranked by criterion Lambda Variables currently in the model F to enter p- level Λ F- value p- level C3H 25,4 10-6 ,486 25,4 10-6 O1H 14,8 10-5 ,298 19,5 10-6 T3H 3,8 ,030 ,256 15,0 10-6 Immune Status Index-11 4,0 ,025 ,217 12,9 10-6 Eosinophiles, % 3,0 ,058 ,191 11,3 10-6 F8H 2,9 ,067 ,168 10,3 10-6 T4H 3,7 ,033 ,143 9,8 10-6 Popovych’s Strain Index-2, points 2,0 ,151 ,131 9,1 10-6 Stub Neutrophils, % 2,4 ,104 ,117 8,6 10-6 Killing Index vs Staph. aureus, % 2,5 ,094 ,103 8,2 10-6 P3H 3,1 ,058 ,089 8,1 10-6 F7H 2,5 ,095 ,078 7,9 10-6 Phagocytose Index vs E. coli, % 2,0 ,152 ,071 7,7 10-6 T6H 2,9 ,067 ,060 7,7 10-6 Phagocytose Ind vs Staph. aur., % 2,7 ,085 ,052 7,7 10-6 CD4+ T-helper Lymphocytes, % 2,2 ,130 ,046 7,5 10-6 CD3+ T active Lymphocytes, % 2,0 ,153 ,041 7,4 10-6 O2H 3,4 ,047 ,034 7,7 10-6 Micr Count vs St. aur., Bact/Phag 3,8 ,035 ,027 8,0 10-6 Leukocytes, 109/L 3,2 ,056 ,022 8,3 10-6 Killing Index vs E. coli, % 2,6 ,095 ,019 8,4 10-6 Next, the 21-dimensional space of discriminant variables transforms into 2-dimensional space of canonical roots. The canonical correlation coefficient is for Root 1 0,945 (Wilks' Λ=0,019; χ2(42)=151; p<10-6) and for Root 2 0,909 (Wilks' Λ=0,174; χ2(20)=66; p=10-6). The major root contains 63,8% of discriminative opportunities and the minor is 36,2%. Table 3 presents standardized (normalized) and raw (actual) coefficients for discriminant variables. The calculation of the discriminant root values for each person as the sum of the products of raw coefficients to the individual values of discriminant variables together with the constant enables the visualization of each patient in the information space of the roots (Fig. 2). 32 Table 3. Standardized and Raw Coefficients and Constants for Canonical Variables Coefficients Standardized Raw Variables Root 1 Root 2 Root 1 Root 2 C3H ,047 -1,175 ,440 -10,95 O1H -,714 ,644 -4,569 4,120 T3H ,474 -,831 2,777 -4,868 Immune Status Index-11 -2,179 2,045 -3,624 3,401 Eosinophiles, % -,243 -,264 -,137 -,149 F8H 1,468 ,825 5,642 3,170 T4H -,649 -,286 -3,920 -1,726 Popovych’s Strain Index-2, points 1,209 -,080 3,945 -,259 Stub Neutrophils, % 2,315 -,670 1,598 -,463 Killing Index vs Staph. aureus, % 2,223 -,908 ,217 -,089 P3H -1,175 ,304 -10,81 2,794 F7H -1,317 ,437 -5,715 1,897 Phagocytose Index vs E. coli, % -1,429 ,551 -,854 ,329 T6H 1,038 -1,162 5,353 -5,993 Phagocytose Ind vs Staph. aur., % ,624 ,275 ,553 ,244 CD4+ T-helper Lymphocytes, % -,337 -,454 -,067 -,090 CD3+ T active Lymphocytes, % ,801 -,763 ,156 -,148 O2H -1,165 ,648 -7,457 4,145 Micr Count vs St. aur., Bact/Phag 1,019 -,640 ,113 -,071 Leukocytes, 109/L ,873 -,725 ,762 -,633 Killing Index vs E. coli, % ,806 -,077 ,060 -,006 Constants ,208 -,911 Eigenvalues 8,334 4,736 Cum. Prop ,638 1,000 Table 4 shows the correlation coefficients of entropy and immunity changes (discriminant variables) with canonical discriminant roots, the cluster centroids of both roots, and the normalized entropy and immunity change values of the discriminant variables, as well as not included in the discriminant model. The reason for the last step is our experience that not getting a variable into the model does not always indicate a lack of recognition ability, but may be a consequence of redundancy (duplication) of information. 33 Table 4. Correlations Variables-Canonical Roots, Means of Roots and Z-scores of changes in Variables for Clusters Change in Variables Correlations Variables-Roots II (10) III (7) I (34) Root 1 (63,8%) R1 R2 -4,43 -3,22 +1,97 O1H -,292 ,076 +1,38 +0,60 -0,56 P3H -,239 -,090 +0,83 +1,16 -0,46 O2H -,220 ,111 +1,06 +0,12 -0,53 F7H -,212 ,016 +1,64 +1,10 -0,59 T4H -,186 -,075 +0,32 +0,78 -1,27 T6H -,178 ,037 +1,16 +0,52 -0,61 F8H -,139 ,153 +1,29 -0,68 -0,78 Phagocytose Ind vs Staph. aureus -,019 -,005 +0,13 +0,13 +0,06 Fp2H currently not in model +1,51 +0,50 -1,10 T5H currently not in model +1,42 +1,15 -0,59 Fp1H currently not in model +1,41 +1,17 -0,62 P4H currently not in model +0,66 +0,70 -0,52 Immunocytogram H currently not in model +0,31 -0,03 -0,01 Immune Status Index-11 ,100 ,088 +0,11 -0,16 +0,41 Leukocytes ,072 ,023 -0,66 -0,85 +0,26 Stub Neutrophils ,051 ,006 -0,17 -0,12 +0,56 CD3+ T active Lymphocytes ,033 -,014 -0,42 +0,03 +0,14 HRV H currently not in model -0,10 +0,11 +0,41 Leukocytogram H currently not in model -0,55 -0,01 +0,10 Root 2 (36,2%) R1 R2 +2,67 -4,70 +0,18 C3H -,221 -,371 -0,13 +2,68 -0,89 T3H -,125 -,188 -0,53 +1,51 -1,24 C4H currently not in model +0,09 +2,82 -0,91 F4H currently not in model +0,49 +2,21 -0,77 F3H currently not in model -0,15 +1,74 -0,57 Eosinophiles ,056 -,175 -1,72 +1,04 -0,11 Popovych’s Strain Index-2 ,110 -,135 -4,06 -0,11 -0,79 Microbial Count vs Staph. aureus -,024 -,051 +0,06 +0,38 +0,04 CD4+ T-helper Lymphocytes ,018 -,024 +0,09 +0,40 +0,36 Immunoglobulins M currently not in model +0,05 +0,58 -0,10 CD22+ B Lymphocytes currently not in model +0,60 +1,02 +0,11 Killing Index vs Staph. aureus ,098 ,131 +0,36 -0,68 +0,73 Killing Index vs E. coli ,075 ,127 +0,57 -0,61 +0,80 Phagocytose Index vs E. coli ,024 ,113 +0,19 -0,95 +0,01 Monocytes currently not in model -0,64 -1,73 +0,28 Bactericidity vs E. coli currently not in model +0,39 -1,26 +1,67 Bactericidity vs Staph. aureus currently not in model +0,25 -0,98 +1,64 Immunoglobulins A currently not in model -0,55 -0,80 +0,03 0-Lymphocytes currently not in model -0,40 -0,75 -0,15 Popovych’s Adaptation Index-2 currently not in model +0,58 -0,14 +0,62 34 III I II Root 1 R oot 2 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 -6 -5 -4 -3 -2 -1 0 1 2 3 4 Fig. 2. Scatterplot of individual values of the first and second roots in which condensed information about of the changes in EEG Entropy and Immunity of the members of the three clusters The localization of the members of the first cluster along the first root axis (Figs. 2 and 3) in the extreme right zone reflects decrease in entropy of EEG loci as well as minimal increase in phagocytose activity vs Staph. aureus, i.e. in variables which are related to the root negatively, while maximal increase in immune parameters which are related to the root positively (Table 4). The members of the other two clusters occupy extreme left position and their projections on the axis are mixed. Nevertheless, more left shift of the centroid of the second cluster results, as a rule, in a larger entropy increase. Instead, along the second root axis (Figs. 2 and 4), members of these clusters are clearly deliminated due to the extremely lower position of the members of the third cluster, which reflects a significant increase in the entropy of the EEG loci as well as the immune parameters associated with the root negatively, combined with a decrease in the immune parameters related to the root positively. 35 Fig. 3. Patterns of changes in EEG entropy and immunity parameters, the information of which is condensed in the first root Fig. 4. Patterns of changes in EEG entropy and immunity parameters, the information of which is condensed in the second root In general, all three clusters on the planes of the roots are clearly delineated, which is documented by calculating the Mahalanobis distances (Table 5). Table 5. Squared Mahalanobis Distances between Clusters and F-values (for all p<10-5) III I II III 0 54 59 I 7,6 0 50 II 5,9 9,8 0 The same discriminant parameters can be used to identify the belonging of one or another person to one or another cluster. This purpose of discriminant analysis is realized with the help of classifying functions (Table 6). We can retrospectively recognize members of all clusters unmistakably (Table 7). 36 Table 6. Coefficients and Constants for Classification Functions of Clusters III I II Change in Variables p=,137 p=,667 p=,196 C3H 37,73 -13,51 -43,56 O1H 3,000 -,555 38,91 T3H 7,153 -2,234 -32,10 Immune Status Index-11 2,169 -,004 31,63 Eosinophiles, % 1,292 -,143 ,361 F8H -33,07 11,68 -16,51 T4H 17,58 -11,18 9,596 Popovych’s Strain Index-2, points -12,71 6,476 -19,39 Stub Neutrophils, % -3,813 2,210 -9,157 Killing Index vs Staph. aureus, % -,441 ,249 -1,356 P3H 30,18 -12,24 63,85 F7H 12,77 -7,594 33,66 Phagocytose Index vs E. coli, % 1,119 -1,701 4,581 T6H 5,829 4,302 -44,83 Phagocytose Ind vs Staph. aur., % -2,504 1,554 -1,375 CD4+ T-helper Lymphocytes, % ,580 -,207 -,004 CD3+ T active Lymphocytes, % ,046 ,129 -1,235 O2H 9,373 -9,038 48,95 Micr Count vs St. aur., Bact/Phag -,124 ,114 -,783 Leukocytes, 109/L -,816 ,044 -6,406 Killing Index vs E. coli, % -,190 ,093 -,304 Constants -15,63 -3,122 -19,36 Table 7. Classification Matrix for Clusters Rows: Observed classifications; Columns: Predicted classifications Percent Correct III I II Clusters p=,137 p=,667 p=,196 III 100 7 0 0 I 100 0 34 0 II 100 0 0 10 Total 100 7 34 10 At the final stage of the analysis, we created three patterns of relationships between induced by adaptogenic balneotherapy changes in the SPD entropy the individual loci of EEG on the one hand, and the immune parameters, the information of which is condensed in two canonical discriminatory roots, on the other hand (Fig. 5). 37 Fig. 5. Scatterplots of the correlations between changes in EEG entropy parameters and immunity parameters that are condensed in discriminative roots As you can see, both inverse patterns are quite clear, but direct coupling occurs only as part of the increase in entropy, while its decrease is accompanied by the absence of changes in immune parameters. Our data fits into the KJ Tracey’s [38] scheme of immunological homunculus by which the neural structures that are projected onto definite loci responsible for certain immune functions, that is the immune compartment cytokines release (F3 and/or F4), activation of memory B cells (Fp1 and/or Fp2), dendritic cells maturation (T3 and/T4), regulation of T cells (T5 and/or T6), clonal expansion (P3 and/or P4) and late cytokine release (P? or O?). We consider it appropriate to hypothesize that the immunomodulatory action of entropy of nerve structures is realized due to their effect on the tone of the vagus nerves, whose immunotropic effects are well documented [5,6,17,37,39]. In support of our hypothesis, we present the following provisions. It is believed that a hippocampus is projected at the C3 and C4 loci, and the T3 and T4 loci reflect the activity of the amygdala [34]. The frontal loci record the activity of anterior cingulate [4] as well as orbito-frontal cortex. It is shown that the cortical thickness of an area within these regions positively correlated with two HRV-markers of parasympathetic activity both HF [16,41] and RMSSD [42]. It is shown significantly positive correlations between HFnu and Fz-θ, FCz-θ and Cz-θ [36]. Previously we [31,32] also found correlations between HFnu and F4-θ and P4-θ, between HF relative and Fp1-θ and P4-θ also between RMSSD and P4-θ. Prinsloo GE et al. [33] found that less pronounced changes in HRV, due to work-related stress, accompanied by higher relative SPD Fz-θ, Pz-θ and Cz-θ, lower fronto-central relative β power and higher θ/β ratio. It is also perfectly consistent with our [31,32] data on a negative correlation LFnu, LFr and LF/HF with F4-θ, P4-θ, F7-θ, F8-θ and positive - with F7-β and F8-β - on the one hand, and a positive correlation HFr with Fp1-θ and P4-θ and negative - with P4-β - on the other side. ACKNOWLEDGMENT We express sincere gratitude to administration of JSC “Truskavets’kurort” and “Truskavets’ SPA” as well as clinical sanatorium “Moldova” for help in conducting this investigation. 38 ACCORDANCE TO ETHICS STANDARDS Tests in patients are conducted in accordance with positions of Helsinki Declaration 1975, revised and complemented 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 of anonymity of participants. For all authors any conflict of interests is absent. REFERENCES 1. Baevskiy RM, Ivanov GG. Heart Rate Variability: theoretical aspects and possibilities of clinical application [in Russian]. Ultrazvukovaya i funktsionalnaya diagnostika. 2001; 3: 106-127. 2. Barylyak LG., Malyuchkova RV, Tolstanov OB, Tymochko OB, Hryvnak RF, Uhryn MR. 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