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Psychophysical and genetic determination of quantum-field level of the organism functioning.

Abstract

The results of a complex study of quantum-field, molecular-genetic, and psychophysical levels of sportsmen's organism functioning are presented. For 179 sportsmen, parameters of GDV bioelectrography-evoked emission processes, ACE genotype, physiological and psychological indices, together with athletes' competitive effectiveness, were evaluated in several sessions during two years.

"The true physics is that which will, one day achieve the inclusion of humanity in a coherent picture of the world."

--Pierre Teilhard de Chardin

Analysis of experimental data allowed asserting that the quantum-field level of an organism's bioenergetics, as well as the substrate level, is subject to genetic determination, as well as environmental influences. Functional dependencies, revealed in this study, may be used for the screening control and predictions of psychophysical potential of athletes.

Introduction

The results of psychogenetic and molecular-genetic research in recent years has strongly proven and correlated the presence of a genetic underpinning of energy processes for humans with the adaptation to moving activities. Quite naturally, a question arises: Is the genetic preset specific only for the substrate level of the organism (human) energy, or is this regularity extending also to a quantum-field level of bioenergy processes directly connecting with electron-photon levels of molecular ensemble excitation--ensuring both the bio-oxidation processes and energy, matter, and information exchange of the organism with the environment?

This inquiry and the subject matter have both theoretical as well as direct practical importance for the understanding of self-genesis mechanisms and a wider category of human adaptation reactions. Experimental study requires a complex methodology, which combines the technology of quantum-emission and molecular-genetic investigation with modern methods of functional diagnostics. This has now been developed. The research group to explore these relationships in this article included experimental volunteer subjects who were top-level athlete members of St. Petersburg all-star sports teams.

Techniques and Methods

A set of methods was utilized for this study, which allowed the creation of a characteristic profile of the sportsmen's organism psychophysical condition and genetic status. They are the following:

1. Neuro-psychic status, typology (extraversion/introversion), neurotization level, psychoenergy potential, and physical activity evaluated with the Profile Of Mood State (POMS) test (1).

2. Functional state with maximum oxygen consumption test and tests using critical load holding (2,3).

3. Quantum-field level of organism bioenergetics based on measurements of Gas Discharge Visualization (GDV), bioelectrography-evoked emission processes with computerized complex "GDV-camera" (4). Average basic parameters of the finger's glow patterns (BEOgrams): area, density, spectrum, entropy, and fractality were calculated in accordance with the principles given in K. Korotkov and D. Korotkin (5), and P. Bundzen, K. Korotkov, and L.-E. Unestahlvi; parameters were calculated both for every finger and averaged by 10 fingers of the left and the right hands;

4. Integral logarithmic parameters of BEO-grams of the left (JSL integer) and the right (JSR integer) hands and also their dispersions (DJSL and DJSR) together with BEO-grams types (Ia, Ib, Ic, IIa, IIb) (7).

5. Genotype characteristics of the athletes, i.e., those attributed to II, ID and DD variants of the angiotensin-converting enzyme (ACE), shown to be correlated with an organism's energy balance (8). In this analysis, genome DNA was extracted with alkali from the cells of the oral mucous membrane, with the polymorph part of the gene amplificated by polymerize chain reaction, and these reaction products determined via electrophoresis in 8% polyacrilamid gel (9).

6. Physical endurance test exercises, measures of speed-strength qualities, and explosion force. Treadmill by "Quinton" (USA) was used in the following regimes: the athlete speeded 6 km/h at the first stage, 9 km/h at the second stage, and 12 km/h at the third stage. The inclination angle was 5% and duration of every step three minutes. Then the inclination angle was increased to 10.5% with duration one minute. At the last step, the angle was 12.5%, speed was 12 km/h, and the athlete was motivated to run as long as possible.

During this test, heart rate was continuously registered with a "Polar Electronic" tester and every third minute outward breath was analyzed with a "Bekkman" gas-analyzer.

7. Expert evaluations of athletes' readiness in the frames of track-and-field specialization (800 and 1500 meter middle-distance race, 50 meter sprint, hurdle race, hop, shotput, grenade throwing, high jump, and broad jump);

8. Rating of competitive effectiveness of participation in international and Russian championships.

The research was performed at the Olympic Reserve College and North-West Center of Olympic Training of St. Petersburg during 1999-2001 in several independent sessions. Groups of athletes demonstrating various levels of skills and specialization were tested, including members of the Russian Olympic team (10). Statistical analysis was done for several groups: 83 athletes, 27 athletes, 40 athletes (average age 17.8+3.7 years), and 29 students of Lesgaft State Academy of Physical Training, specializing in track-and-field athletics (average age 16.9+0.8 years). For this particular group of track-and-field students, measurements were performed three times during a year cycle of training activity (August, November, and May).

The results of the investigation were processed, using methods of multi-parametric analysis, by means of the statistics software package "STATGRAPH-5," using Fisher and Student criteria. Reliability of the test was accepted with p < 0.05.

Experimental Results and Discussion

Comparison of the data obtained with athletes' performance results demonstrated that for athletes having high psychophysical potential, BEO-grams have distinctive features that may be described with a set of quantitative parameters. Multiparametric correlation and factor analysis for a big set of the abovementioned parameters reveal highly reliable statistical correlations between physical, psychological, and quantum parameters of athletes' functioning.

Figure 1 demonstrates results of a statistical analysis of experimental data as a correlation graph. It is obvious that the functional parameter characteristic of the athlete's physical state (physical loading holding time) reveals direct differential correlation with the GDV bioelectrography parameter and ACE genotype. In particular, parameters dependent on cardio-respiration endurance (heart rate variability), as well reveal correlation both with GDV parameters and ACE genotype. Detailed analysis demonstrated the most stable correlation indexes with the GDV parameters of the left hand fourth finger. Parameters characteristic of the psychic endurance measured by POMS correlated with the GDV Stress Index, but directly neither with cardio-vascular indexes nor with genotype. Of particular note are the very strong correlations of the GDV parameters with the effectiveness of competition activity. It has direct correlation with the heart rate variability indexes as well.

[FIGURE 1 OMITTED]

Functional loads (treadmill training and ideomotor modeling of competition performance elements) exerted a pronounced influence both on BEO-gram types and on GDV integral indexes. After the load, the GDV parameters of the right hand had higher weight factors as they are correlated with physical activity (6). At the same time, after the load the correlation with the coefficient of psycho-energy by the "POMS" test increased. This data statistically confirmed a concept of the importance of a psychological factor in the effectiveness of purposeful physical activity. It was previously demonstrated that the high coefficient of psycho-energy corresponds to the "iceberg-type" of the "POMS" test, with the peak value of quality "vigor" and suppression of the qualities "anxiety" and "uncertainty" (9). Based on the data obtained, it is possible to conclude that the GDV method gives a practical way to objective instrumental measurement of these qualities.

To further explore these revealed regularities, a longitudinal complex study was undertaken of track-and-field athletes during the course of a yearly cycle of training activities relative to their ACE genotype differentiation by methods of molecular-genetic analyses.

At the outset, it became clear that as a result of multiple independent measurements of this large group of athletes, a credible correlation of effectiveness for physical exercise performance related to endurance quality with their individual ACE genotype and GDV parameters was statistically demonstrated (p<0.01). This dependence was revealed for the majority of BEO-gram basic parameters, in particular, for integral parameters JS (Figure 2). Distribution of athletes according to their sport results corresponded to the type of genotype in compliance with the series II-ID-DD (8,9).

[FIGURE 2 OMITTED]

Therefore, the results of the analysis of BEO-gram parameters give a reason to speculate that genotype features of a person, defining endurance quality, reveal a connection with specifics of functional organization of quantum-field level of an organism's bioenergetics.

This conclusion is confirmed by the results shown in Figure 3. They demonstrate differentiation of one more GDV-parameter: BEO-gram types in accordance with classification by K. Korotkov (6). As it is seen from the picture, for the ID genotype athletes' group Ib and Ic, BEO-gram types dominate, while for the DD genotype group, IIb and Ic types prevail. The differences mentioned are most distinctly revealed on the left hand fingers' BEO-grams: 3L, 4L, and 5L. It is worth mentioning that the specificity of functional organization of the right and left hands fingers' BEO-grams was also discovered within the investigation of relation between the bioenergetics quantum-field level and the psychophysical readiness of skilled athletes, training their endurance (10).

[FIGURE 3 OMITTED]

Presented results allowed the development of a computer analysis of BEO-grams of athletes using "Data Mining" methods with the purpose of automatic classification. Analysis was based on the Bayes' self-training classification system (11). A total of 180 BEO-grams passed expert evaluation--two groups of 90 sportsmen with ID and DD genotypes. BEO-grams were distributed in two groups in accordance with their GDV parameters, and classification results in 92% of cases coincided with the genotype distribution of the athletes. This approach opens perspectives for the computerized evaluation of athletes based on measurements of their bioelectrographic parameters.

According to the results of statistical analysis, genetic conditionality of GDV-parameters has a relatively stable character and is revealed within a year training cycle, in spite of reliable changes of bioenergetic status of the investigated athletes' groups (Figure 4). The curves given show that all student athletes from the group in Figure 2 demonstrated improvement of integrated GDV-parameters. However, the absolute values in the II-ID genotype group were much higher.

[FIGURE 4 OMITTED]

In that way, organization of bioenergetic processes on the quantum-field level is apparently quasistochastic in its character and along with genetic determination (relatively "strict factor") depends on the changes of the objects' psychophysical potential during short- and long-term adaptation to environmental factors.

Results of the multi-parametric data factor analysis, as compared to sport effectiveness, in three separate measurements during the year (Table 1) demonstrated the presence of reliable functional correspondences between the ACE-genotype, integrated GDV-parameters, and middle-distance (800-1500 meter) race results--i.e., sport potency that connected with endurance quality. In this case, maximum effectiveness was characteristic of II and ID genotype athletes and minimum of DD genotype ones (p < 0.05).

Thus, the above given research provides compelling reasons to assume that the quantum-field level of bioenergetics of the human organism, as well as a substrate level composed of the biochemically aerobic and anaerobic processes of maintenance of muscle activity, is subject to genetic determination.

A second factor of Table 1 reveals correlations between types of sport connected with explosive loads, psychological characteristics, measured by POMS, and bilateral ratio, measured from right and left hand fingers. The weight of the last factor increases in the process of training. This tells about the importance of mental and psychological preparation in these types of sport.

As indicated by the results of statistical analysis, correlations are revealed within the whole period of research, i.e., a year cycle of training activity, which is the confirmation of the relative stability of the genotype influence. However, this data discloses a very relative stability, albeit statistically reliable, which suggests that the degree of influence of the genetic factor (ACE subtype) on the parameters of bioenergetic of quantum-field level progressively decreases within a year cycle of training, as shown by the correlation and factor analysis data. Thus, factor values of parameters of BEO-grams JSL and JSR in a year cycle decrease from 0.83 and 0.76, respectively, to 0.49 and 0.55 (see Table 1). From the functional viewpoint, these changes can be interpreted as the influence of the so-called "medium" factor on the effectiveness of sport activity. In our case this factor is the training process, forming functional psychophysical reserves of sportsmen during long-term adaptation to physical loads.

The last statement was tested independently on two groups: 27 and 40 sportsmen. BEO-grams of all fingers were measured and GDV-parameters were calculated. Figure 5 demonstrates experimental data presented in complex GDV-parameters' coordinates for the first group. This assessment enabled the determination of three groups of athletes having expressed differences in their adaptation to long-term physical loads. Comparison with other data revealed that the groups reliably differed in genotype characteristics, psychophysical potential, and sport activity effectiveness. In particular, R axis at Figure 5 represents athletes' competition rating during the year. It is worth mentioning clear correlation of the difference of left and right hands' activity (JSL-JSR) with sport activity effectiveness. This may be interpreted as a higher interrelation of the brain hemispheres for more effective sportsmen.

[FIGURE 5 OMITTED]

Useful results might be received presenting experimental data in multiparametric space. The results of cluster analysis of 40 athletes' data in a three-dimensional space of BEO-gram parameters--entrophy, normalized area, and fractality--are given in Figure 6. As demonstrated in the figure, there is a well-defined distribution of data by GDV-parameters into three groups. Again, according to the analysis, each group consists of sportsmen distinguished by psychophysical characteristics, effectiveness and, to a certain extent, by genotype.

[FIGURE 6 OMITTED]

As we see from the presented data, regardless of the type of analysis (Figures 3-6) and for different tested groups, athletes are distributed to groups in accordance with their quantum parameters, which correlate with their psychophysical potential and sport effectiveness.

In conclusion, it is worth emphasizing that the dependencies between the genotype characteristics of an individual according to ACE, parameters of GDV-evoked emission processes, as well as the growth of psychophysical potential of athletes in the course of training activity found in the present research are quite explicable, if we take into account the specific character of ACE genotypes. These genotypes determine functional resources of both the cardio-respiratory system of the organism (12,13) and the central nervous system (14).

It should be mentioned that all experiments were carried out under double-blind test mode: experimental groups, which were involved in collecting data, computer processing, and analyzing athletes' efficacy, were not connected with each other, and they were working in different institutions. What is more, the possibility to measure athletes' genotype status appeared after carrying out two cycles of GDV-parameters' measurement and their full processing.

Conclusions

1. The above-mentioned experimental data give good reason to assert that the quantum-field level of an organism's bioenergetics, as well as the substrate level, is subject to genetic determination. The substrate level involves biochemical aerobic and anaerobic processes providing muscle activity. Quantum-field level is determined by electron-photon levels of stimulation of molecular and structural ensembles revealed by the GDV-method.

2. The phenomenon of genetic determination of parameters of GDV-evoked emission processes, correlating with the quantum-field level of human organism bioenergetics, was found to be statistically reliable in the process of the annual research cycle.

3. Integrated GDV-parameters and BEO-gram types of bioelectrography-evoked emission processes reveal dependence on the factors having different levels of "rigidity," including both genetic and functional factors, as well as environmental influences, which fact enables to indicate their nature stochasticity.

4. Functional dependencies between the GDV parameters, genotype characteristics of athletes, and the sport activity effectiveness revealed, determine the diagnostic importance of parameters of quantum-field level of an organism's bioenergetics for the creation of a system of early sport specialization and screening control of highly skilled athletes' psychophysical potential.

5. Diagnosis of an individual's psychophysical potential according to GDV parameters cannot be reduced to using a single (even integral) BEO-gram parameter, and hence should be implemented using a complex parameter assessment.

Glossary

Angiotensin-converting enzyme (ACE)--As it is indicated by G. Taubes (2000): "The most controversial research and the most highly publicized candidate for the performance gene is the one known as ACE, which stands for angiotensin-converting enzyme. It appears to play a role in regulating blood pressure, cell growth, and the growth of heart muscle. In the early 1990s French researchers discovered that the ACE gene could be found in the general population in two distinct variations: one with an extra fragment of DNA (called the Insertion, or I, variant) and the other without it (called the Deletion, or D, variant). The two variants evidently influence the amount of ACE that may be found in tissue. Individuals with two I variants, one from their mother and one from their father, have significantly less ACE activity than do individuals with one I and one D, who in turn have less ACE activity than do individuals who have two D variants.

"At University College, London, physiologist Hugh E. Montgomery and his colleagues studied the effect of ACE variants first on young army recruits, then on high-altitude mountain climbers. They found that individuals with two I variants (known as II) were, on average, more efficient in endurance exercise as compared to either ID or DD individuals and also seemed to be more trainable. Their bodies became considerably more efficient with exercise."

Taubes, G. Towards Molecular Talent Scouting. Scientific American. 2000, 11(3), 26-31

The principle of Gas Discharge Visualization (GDV) technique might be described as follows: under the influence of a high-intensity electromagnetic field, the subject under study emits a burst of electrons and photons. In the gaseous medium of the contact between subject and dielectric covering the electrodes, an avalanche and/or sliding gas discharge develops, which serves as an amplifier of the weak subject's emission. This process is very similar to the amplification processes in photomultipliers. With the help of an optical system and a CCD-camera, (charge-coupled device), the discharge's fluorescence is transformed into video-signals, which are recorded in the form of single shots (GDV-grams) or AVI-files in the computer. The data processing allows the calculation of the system of parameters and, therefore, the possibility of drawing diagnostic conclusions.

BEO GDV--Biological Emission and Optical radiation, stimulated by electromagnetic field, amplified by Gas Discharge with Visualization through computer data processing. BEO-gram--computer picture received by Gas Discharge Visualization processing (GDVgram), pertaining to a biological subject, particularly to a human. Biological Energy Field--complex of physical fields of known and unknown origin, including electromagnetic field (EMF), gravitational field, field of emission, etc. that provides exchange of information between particular subject, environment, and other subjects.

Entropy--a measure of the disorder or chaos in a system, on the one hand, and the measure of diversity, multiplicity of different states of a system, on the other; measure of diversity in biophysics and informational theory.

Fractal--a geometric shape that can be separated into parts, each of which is a reduced-scale version of the whole. Fractals are used especially in computer modeling of irregular patterns and structures in nature, like the blood vessels system, snowflakes, gaseous discharges, etc.

POMS--Profile Of Mood State is a well-known psychological questionnaire.

Psychophysical potential--the level of an athlete's organism psycho-physiological functional reserves, developed in the course of long-term adaptation to the training process and mobilization potentialities that determine the effectiveness and reliability of competition activity.

Acknowledgements

The authors thank M. Babitsky, V. Zagranzev, O. Kolody, G. Kunchina, T. Maschianova, and D. Muromzev for taking part in collecting and processing research material, and V. Kirillova and T. Bugno for preparing the manuscript.

References

(1.) McNair ,D., Lorr, M., and Droppleman, L. (1992). Profile of mood states manual. San Diego, CA: EdITS/Educational and Industrial Testing Service.

(2.) Karpman, V., Belotserkovski, Z., and Gudkov, I. (1988). Testing in sport medicine. Moscow: Fiskultra I Sport Publishing House.

(3.) Lear, S., Brozic, A., Myers, J., and Ignaszewski, A. (1999). Exercise stress. Sport Medicine, 2(5), 275-345.

(4.) Korotkov, K. (1998). Aura and consciousness--new stage in scientific understanding. SPb. Kultura Publishing House of Russian Ministry of Culture.

(5.) Korotkov, K., and Korotkin, D.(2001). On concentration dependence of gas discharge around drops of non-organic electrolytes. J of Applied Physics, 89(9), 4732-4737.

(6.) Bundzen, P., Korotkov, K., and Unestahl, L.-E. (2002). Altered states of consciousness: review of experimental data obtained with a multiple techniques approach. Journal of Alternative and Complementary Medicine, 8(2), 212-225.

(7.) Korotkov, K. (2002). Human energy field: study with GDV bioelectrography. New York: Backbone Publishing.

(8.) Montgomery, H., et al. (1999). Angiotensin-converting-enzyme gene insertion/deletion polymorphism and response to physical training. Lancet, 353, 541-545.

(9.) Nazarov, I., et al. (2001). The angiotensin converting enzyme I/D polymorphism in Russian athletes. European Journal of Human Genetics, 9, 797-801.

(10.) Bundzen, P., Korotkov, K., Massanova, F., and Kornycheva, A. (2000). Diagnostics of skilled athletes rpsychophysical fitness by the method of GDV. Fifth Annual Congress of the European College of Sport Science, Finland, Jyavaskyla, 186.

(11.) Kononenko, I. (2001). Machine learning for medical diagnosis: history, state of the art and perspective. Artificial Intelligence in Medicine, 23, 89-97.

(12.) Danser, A., et al. (1996). Angiotensin-converting enzyme in the human heart: Effect of the deletion/insertion polymorphism. Circulation, 92, 1387-1388.

(13.) Hagberg, J., Ferrell, R., McCole, S., Wilund, K., and Morre, G. V. (1998). O2 max is associated with ACE genotype in postmenopausal women. J. Applied Physiology, 85(5), 1842-1846.

(14.) Arinami, T., Li, L., Mitsushio, H., Itokawa, M., Hamaguchi H., and Toru M. (1996). An insertion/deletion polymorphism in the angiotensin converting enzyme, associated with both brain substance, contents and affective disorders. Biol. Psychiatry, 40(11), 1122-1127.

Bundzen P. *, Korotkov K. **, Nazarov I. *, Rogozkin V. *

* State Research Institute of Sport; St. Petersburg, Russia.

** State Technical University SPIFMO; St. Petersburg, Russia, e-mail: Korotkov@mail.admiral.ru
Table 1. Factor analysis of competitive activity
effectiveness in different sport disciplines,
ACE genotype, psychological characteristics
and integrated GDV-parameters of highly
skilled athletes taken during the year.

 Factors

 Parameters 1 2

Sport Middle-distance race 0,49 0,09
competition (800 and 1500 _)
results Shotput -0,27 0,26
 Broad jump -0,05 0,33
 Sprint -0,40 0,52
 High jump -0,53 0,01
 Step and jump -0,66 0,20
 Grenade throw 0,01 0,70

ACE genotype 0,72 0,26
Level of dis-adaptation -0,82 -0,24
Extravert - introvert -0,28 -0,04
Neurotization 0,16 0,28
POMS activity -0,22 -0,58
POMS psycho-energetic factor 0,05 -0,66

GDV indices JSL 0,83 0,30
measurement JSR 0,76 0,27
August 1999 JSL / JSR -0,34 -0,43

GDV indices JSL 0,63 -0,46
measurement JSR 0,60 -0,24
Nov 1999 JSL / JSR 0,44 0,51

GDV indices JSL 0,49 -0,34
measurement JSR 0,55 -0,02
May 2000 JSL / JSR 0,16 0,62

Factor weights 0,27 0,14
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Author:Bundzen, P.; Korotkov, K.; Nazarov, I.; Rogozkin, V.
Publication:Frontier Perspectives
Article Type:Report
Geographic Code:4EXRU
Date:Sep 22, 2002
Words:3787
Previous Article:Eugene Mallove, Ph.D.
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