CC BY
34
INTERWOVEN RECIPROCAL CYCLES (TIME SCALES) IN HUMAN “OBSERVERS” AND IN THEIR COSMOS
Franz Halberg*, Germaine Corn&issen*, George S. Katinas*,
Robert B. Sothern*, Othild Schwartzkopff*,
Sergei M. Chibisov**, Yoshihiko Watanabe***, Viktor A. Frolov**, Kuniaki Otsuka****, Earl E. Bakken*****, Dmitry G. Strelkov**,
Elena A. Romanova**, Tamara K. Breus******
*Halberg Chronobiology Center, University of Minnesota, Minneapolis, MN, USA **People’s Friendship University of Russia, Moscow, Russia ***Waseda University, Saitama, Japan ****Tokyo Women’s Medical University, Medical Center East, Tokyo, Japan *****North Hawaii Community Hospital Inc., Kamuela, HI, USA ******Space Research Institute RAS, Moscow, Russia.
Support: U.S. National Institutes of Health (GM-13981) (FH);
University of Minnesota Supercomputing Institute (FH, GC)
Abstract. Time, in relativistic terms in the context of the speed of light, depends not only on the speed of an observer as a whole. Several different time scales within an observer also relate differently to cycles in the cosmos, all of them assessed by spectral peaks with non-zero amplitudes. Thus, in many physiological, psychological, sociological, epidemiological and physical environmental variables, an inferential statistical transdisciplinary array of spectra unfolds, with reciprocal cycles as components with overlapping 95% confidence intervals in ever broader and diverse chronomes (time structures) that underlie the genetics of an evolving biosphere, representing a phylogenetic memory, and accumulating an as-yet fragile noosphere, to be recognized by its interactions with its cosmos, to be rendered compatible with human survival.
The view of relatively specific ranges of frequencies for physiological entities such as those of the nervous system or of the circulation was first extended to a spectrum consisting of components with different frequencies in any one biological variable such as a hormonal metabolite (17-KS) excretion [1] or heart rate. These intravariable and intradisciplinaiy biological spectra revealed similarities and differences and were eventually complemented by an interdisciplinary spectrum of components with reciprocal periods in biology and physics [2], such as those found with overlapping 95% confidence intervals of the periods involved in solar activity and in the excretion of hormonal metabolites or heart rate [2].
Transdisciplinarity seeks a commonality of spectral components as a key that leads to new insights and rules here proposed only as steps with the implications of the broader-than-interdisciplinary conclusions alluded to elsewhere [3; 4].
At least one or preferably several of the following tasks are indispensable in chronomic analyses [4-7] to validate, in any one discipline and transdisciplinarily, the recurrence of cycles and to explore their associations and mechanisms:
1. Step of (rhythm) demonstration (hypothesis testing).
A zero-amplitude test of a spectral component in an anticipated frequency range is rejected [1]. Rejection can apply to a frequency slightly different from that specified a priori, but one near it, such as when it is obtained by linear-nonlinear rhythmometry. By a nearby frequency, one means a frequency within the resolvable band allowed by the record's length and within an a priori specified frequency range; the latter condition is pertinent under circumstances of data acquisition when there is no known environmental synchronizer and the anticipated signal may “free-run” [1]. While this task of hypothesis testing is highly desirable routinely, it may be optional, when a given rhythm has been repeatedly quantified in the same variable under similar conditions or when single series are limited, but results can be summarized with statistical significance on a “population” basis, from multiple sparse and short series (imputations) from a given individual or from imputations on series from several or preferably many different individuals [1].
2. Step of (rhythm) quantification (parameter estimation).
The cycle is characterized by point as well as (95% confidence or other) interval estimates of its parameters (period whenever the time series permits, as well as MESOR, amplitude, phase, and waveform gauged, e.g., by the characteristics of harmonics of a fundamental frequency) [4] by linear-nonlinear rhythmometry [1] or simulated annealing [5], fitted or otherwise assessed concomitantly with other elements of time structures such as trends. Rhythms have also been shown to operationally characterize endpoints of chaos.
3. Step of phase-manipulation (shifting and -drifting of rhythms).
Phase alterations, such as phase-shifts, — drifts and —jumps are elicited in response to the manipulation (perturbation), including removal, of synchronizers. The tight “lock-in”-associated phase-shifts have characteristics of their own, such as differences in direction (polarity) and/or rate (asymmetry) of phase shift or drift among different variables in the same system, brought about, e.g., by the same manipulation of the artificial environment in organisms in the laboratory or occurring in adjustment after transmeridian flights or during shift-work; in the case of external and internal circadian desynchronization, multiple variables in the same system, e.g., in caves can show different frequencies within the organism, some similar to those of external environmental cycles [1].
4. Step of (rhythmically) changing “sensitivity”, i.e., of kind and/or texture of “response” (e.g., susceptibility and resistance in biology).
Phase-response curves are documented, e.g., of patients in response to a drug, such as the circadian acrophase-shift of human peak expiratory flow and of the excretion of chloride or potassium in response to a corticosteroid; or
• in rodents, an enhancement vs. inhibition of DNA labeling in response to an ACTH analogue; or
• survival vs. death from the same stimulus such as noise or ouabain occurring re-producibly along the 24-hour scale; or
• the changing relative solar cycle stage-dependent prominence of circaseptan versus circadian amplitude relations in human heart rate, or
• in population statistics on cardiac arrhythmia and sudden cardiac death, the solar cycle stage specific transient detection of either about 0.42- or about 1.6-year cycles. Interdisciplinary counterparts among environmental variables, such as helio- and geomagnetic activity, almost certainly exist, all as feedsidewards [6].
5. Step of subtraction and addition (for study of a rhythm's mechanism).
A mechanism underlying any spectral component is validated whenever possible by means of a remove-and-replace approach. The removal and replacement can be done
physiologically [1], e.g., in experiments involving procedures such as adrenalectomy, pinealectomy, or bilateral suprachiasmatic nuclear ablation and replacement of a hormone or transplant; it can occur naturally, such as the subtraction and thereafter addition of changes with a given frequency in the solar activity such as in Wolf numbers or in the speed of the solar wind and the corresponding absence (or damping) and then again the presence (or amplification) of about 7-day components in human heart rate or of transyears in human blood pressure.
Another example illustrates how a non-stationary signal in biology, in the case of near-transyears, may support the intermittent occurrence of transient yet recurrent natural environmental cyclic influences once a biological cycle is identified or vice versa [7].
6. Step of analysis of interactions among components with multiple frequencies, leading toward feedsidewards within a transdisciplinary array of spectra.
Whenever possible, steps 1-5 are repeated with assessment of one or more added components with other frequencies such as the documentation of an about 10.5-year cycle in human heart rate variability and in mortality from myocardial infarction in Minnesota, supporting the amplification of a solar cycle stage-dependent weekly component in heart rate by solar circaseptans. Usually at multiple frequencies, a moving cross-spectral analysis detects multiple loose since time- and intensity (coherence)-varying phase synchronization that represent lesser coupling than that by phase locking tight synchronization, yet may convey important information leading to associations, for example of sudden cardiac death with solar activity along the scales of a year [8] or of a transyear [7]. A 24-hour component may change in prominence (amplitude) or may disappear, presumably as a function of the stage of environmental cycles, as in the case of the circadian amplitudes of neonatal blood pressure or of circulating endothelin, respectively.
Amplitude, frequency, and/or acrophase modulations are other examples of interactions among multiple frequency components. For instance, there is the predictable change between fall and summer- (in nighttime data) or winter- (in daytime data) hypertension brought about by a yearly modulation of the circadian rhythm in blood pressure. That multiple frequency interactions are not trivial is also illustrated in studies of effects of repeated shifts of the lighting regimen at varying intervals, every 2, 3, 4, ..., and up to 14 days: drastic differences in lifespan are found in unicells, flies and springtails, the response showing an about 7-day pattern along a scale of inter-shift intervals.
7. Step from intra- and inter- to transdisciplinary reciprocity.
Components in spectra of different variables further validate a broad diversity of matching cycles, shown to characterize more than a single variable in an observer him/herself or in a population [2; 3; 6-8] in a plethora of biological and physical and/or other sociological, economic or historical environmental variables. As we turn from a given discipline with an intradisciplinary set of cycles to another discipline (interdisciplinary reciprocity, we eventually document the same cycles in several other disciplines, a circumstance leading to a broad transdisciplinary reciprocity of cycles in a noosphere underlying evolution and genetics as biospheric dynamics.
Inferences.
The question of where humanity goes, including its chances for survival, will have to include concern for the health of societies and nations, far beyond (but with) concern for the individual's health. We may have to manipulate or compensate for ill effects of the magnetic and other non-photic environments, just like heating or air conditioning, to meet the challenges of the thermally and photically changing cosmos.
In this perspective, a systematic, to start with 7-day, blood pressure and heart rate monitoring at the People’s Friendship University of Russia in Moscow is most welcome.
Faculty members at People’s Friendship University demonstrated phase-shifts of a circadian rhythm in cardiac function by magnetic storms, with effects of these storms at the electron-microscopic level. Moreover, the implementation of this self-help in health care can be disseminated as a message to the very many countries from which Friendship University draws students.
THE LITERATURE
1. Halberg F. Chronobiology. Annu Rev Physiol 1969; 31: 675-725.
2. Halberg F, Cornelissen G, Otsuka K, Watanabe Y, Katinas GS, Burioka N, De-lyukov A, Gorgo Y, Zhao ZY, Weydahl A, Sothem RB, Siegelova J, Fiser B, Dusek J, Syutkina EV, Perfetto F, Tarquini R, Singh RB, Rhees B, Lofstrom D, Lofstrom P, Johnson PWC, Schwartzkopff O, International BIOCOS Study Group. Cross-spectrally coherent -10.5- and 21-year biological and physical cycles, magnetic storms and myocardial infarctions. Neuroendocrinol Lett 2000; 21: 233-258.
3. Halberg F, Bakken EE, Katinas GS, Cornelissen G, Zaslavskaya RM, Blank MA, Syutkina EV, Breus TK, Watanabe Y, Masalov A, Chibisov SM. Chronoastrobiology: Vernadsky's future science? Benefits from spectra of circadians and promise of a new trans-disciplinary spectrum of near-matching cycles in and around us. Proceedings, IH International Conference, Civilization diseases in the spirit of V.I. Vernadsky, People's Friendship University of Russia, Moscow, Oct. 10-12, 2005, p. 4-25.
4. Halberg F, Cornelissen G, Schack B, Wendt HW, Minne H, Sothem RB, Watanabe Y, Katinas G, Otsuka K, Bakken EE. Blood pressure self-surveillance for health also reflects 1.3-year Richardson solar wind variation: spin-off from chronomics. Biomedicine & Pharmacotherapy 2003; 57 (Suppl 1): 58s-76s.
5. Czaplicki J, Cornelissen G, Halberg F. GOSA, a simulated annealing-based program for global optimization of nonlinear problems, also reveals transyears. J Appl Bio-med, in press.
6. Halberg F, Cornelissen G, Katinas GS, Watanabe Y, Otsuka K, Maggioni C, Perfetto F, Tarquini R, Schwartzkopff O, Bakken EE. Feedsidewards: intermodulation (strictly) among time structures, chronomes, in and around us, and cosmo-vasculo-neuroimmunity. About ten-yearly changes: what Galileo missed and Schwabe found. In: Conti A, Maestroni GJM, McCann SM, Sternberg EM, Lipton JM, Smith CC (eds.), Neuroimmunomodulation (Proc. 4th Int. Cong. International Society for Neuroimmuno-modulation, Lugano, Switzerland, September 29-October 2, 1999). Ann NY Acad Sei 2000; 917: 348-376.
7. Halberg F, Cornelissen G, Katinas G, Tvildiani L, Gigolashvili M, Janashia K, Toba T, Revilla M, Regal P, Sothem RB, Wendt HW, Wang ZR, Zeman M, Jozsa R, Singh RB, Mitsutake G, Chibisov SM, Lee J, Holley D, Holte JE, Sonkowsky RP, Schwartzkopff O, Del-more P, Otsuka K, Bakken EE, Czaplicki J, International BIOCOS Group. Chronobiology's progress: season’s appreciations 2004-2005. Time-, frequency-, phase-, variable-, individual-, age- and site-specific chronomics. J Applied Biomedicine 2006; 4: 1-38. Published online 20 January 2006. http://www.zsf.jcu.cz/vyzlcum/jab/4_l/halberg.htm.
8. Halberg F, Cornelissen G, Bingham C, Witte H, Ribary U, Hesse W, Petsche H, Engebretson M, Geissler H-G, Weiss S, Klimesch W, Rappelsberger P, Katinas G, Schwartzkopff O. Chronomics: Imaging in time by phase synchronization reveals wide spectral-biospheric resonances beyond short rhythms. (“Wenn man über kurze Rhythmen hinausgeht”) In memoriam - lost future: Dr.-Ing. habil. Dr. rer. nat. Barbara Schack: 1952-2003. Neuroendocrinol Lett 2003; 24: 355-380.
ЗАРОЖДЕНИЕ И ВЗАИМОДЕЙСТВИЕ РИТМОВ В ЧЕЛОВЕЧЕСКОМ ОРГАНИЗМЕ И В ОКРУЖАЮЩЕМ ЕГО КОСМИЧЕСКОМ ПРОСТРАНСТВЕ
Франц Халберг*, Жермен Корнелиссен*, Джорж С. Катинас*, Роберт Б. Сотерн*, Офилд Шварцкопф*,
Сергей М. Чибисов**, Ешихико Ватанабе***, Виктор А. Фролов**, Куниаки Отсука****, Эрл И. Баккен*****, Дмитрий Г. Стрелков**, Елена А. Романова**, Тамара К. Бреус******
*Хронобиологический центр Халберга,
Университет Миннесоты, Миннеаполис, МН, США **Российский Университет дружбы народов, Москва, Россия ***Университет Васеды, Сайтама, Япония ****т0кийский женский медицинский университет,
Восточный медицинский центр, Токио, Япония *****Северный Гавайский общественный госпиталь, Камуэла, США ******Институт космических исследований РАН, Москва, Россия
Поддержка: Национальный институт здоровья, США; Институт вычислительной техники Университета Миннесоты, США.
Время в релятивистской терминологии в контексте скорости света в целом зависит не только от скорости «наблюдателя». Несколько различных временных шкал внутри наблюдателя также различным образом связаны с ритмами космоса, каждый из которых оценивается по спектральным пикам с ненулевыми амплитудами. Таким образом, во многих физиологических, психологических, социологических, эпидемиологических и физических характеристиках окружающего пространства содержится выявленное статистическим путем множество междисциплинарных спектров с взаимодействующими ритмами как компонентами, перекрывающими интервал статистической достоверности 95% и даже более широкие и изменчивые временные структуры (хрономы). Эти хрономы определены генетически посредством эволюции в биосфере, представляя собой филогенетическую память и аккумулируясь в ноосфере. Их удается распознать через их взаимодействие с космосом, от которого зависит их совместимость с выживанием.
