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Open Access Library Journal
2024, Volume 11, e11264
ISSN Online: 2333-9721
ISSN Print: 2333-9705
DOI:
10.4236/oalib.1111264 Feb. 29, 2024 1
Open Access Library Journal
Embryonic Development in Light of Controlled
Chaos Dynamics and Quantum Electrodynamics
Claudio Messori
U.S.L Company, Parma, Italy
Abstract
Biological systems are necessarily dissipative structures in the long run, and
dissipative structures are far from equilibrium and homeostasis: order (peri-
odicity) and disorder (non-linear variability) are “
coexisting
dynamic
states
”.
The common epistemological habit of modern molecular biology is to reduce
an observed phenotype or function to a molecular entity, such as a gene, pro-
te
in or pathway, which have become the embodiment of causation in biology.
In the emerging framework of gene network architecture the
attractor
nature
of distinct cell phenotypes, explains a series of cell behaviors that are not eas-
ily accounted for by linear molecular pathways. It explains why cell-type spe-
cific genome-
wide expression profiles, defined by the values of thousands of
variables, are so reliably establish
ed during differentiation as if orchestrated
by an invisible hand: the
self-organizing
and
self-stabilizing
property of bio-
logically significant gene expression pr
ofiles is a natural feature conferred by
attractors
. In the
human
placental
mammal
, the embryonic cell cycle and
intrauterine development process rests on one of the most effective dynamics
to regulate the living, sometimes approaching and sometimes diverging
chaos,
i.e.
a
controlled
chaos
dynamics
. Biological system’s development
,
namely each stage of the embryo development, is characterized by the pres-
ence of one-to-many
attractors
, toward which the developmental dynamic
variables trajectories are rapidly approaching from all the points of its phase
space. Symmetry propagation and symm
etry breaking are essential processes
in biological morphogenesis, in metazoan evolution and development. With-
in embryogenesis, the
amniotic
fluid
(AF) should be treated as biological wa-
ter in a super-coherent state and may act as an inherently dynamical e
ntity
endowed by a proper non-
linear dynamics, that creates a biochemistry not
governed by random collisions between molecules, but by a code of mutual
recognition and recall among molecules based on long-distance electromag-
netic interaction. For convenien
ce, a GLOSSARY of terms extrapolated from
the body of the text can be consulted at the end of the article.
How to cite this paper:
Messori, C. (2024
)
Embryonic Development in Light of
Controlled Chaos Dynamics and Quantum
Electrodynamics
.
Open Access Library
Journal
,
11
: e11264.
https://doi.org/10.4236/oalib.1111264
Received:
January 26, 2024
Accepted:
February 26 , 2024
Published:
February 29, 2024
Copyright © 20
24 by author(s) and Open
Access Library Inc
.
This work is licensed under the Creative
Commons Attribution International
License (CC BY
4.0).
http://creativecommons.org/licenses/by/4.0/
Open Access
C. Messori
DOI:
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Subject Areas
Bioengineering, Biophysics
Keywords
Controlled Chaos Dynamics, Attractors, Super-Coherent State of Biological
Water, Gene Regulatory Network, Symmetry Breaking
1. Premises
The epistemological bases of experimental science (natural philosophy) are laid
in Europe by G. Galilei, F. Bacone, I. Newton, G. W. Leibniz, R. Descartes, J.
Kepler. Strengthened by the idea that the universe is a work created by God, the
fathers of modern science thought that doing experimental science meant re-
searching the laws of nature put into place by the creative and ordering mind of
God the creator. Thus, modern science was born in the light of theology with a
view to determining the rules and principles of the divine universal order. The
necessity of the divine order of nature translated, therefore, into the necessity of
the logical order of scientific knowledge (theological empiricism). The presence
of the theological and teleological order in the structure and dynamics of natural
phenomena influenced the thought of biologists and doctors to such an extent
that C. Bernard, a great nineteenth-century physiologist, considered the found-
ing father of experimental medicine, dictated the rule of “Constancy of the mi-
lieu intérieur”, or the law of “constant equilibrium in living matter”. The Ber-
nardian conception was defined with the term “homeostasis” by G. W. Cannon,
meaning the return of biological functions to the “quo ante” state after stimula-
tory or inhibitory perturbations. The homeostatic vision of vital phenomena has
had as an epistemological consequence a systematization, structural and topo-
logical, of biological systems in “linear axes”, that is, in axial systems to action
(feed-forward) and to retroaction (feed-back), with an active and responsive dy-
namics of the type proportionate, one-to-one, and therefore linear. Furthermore,
the homeostatic view of biological physiology has had as a methodological con-
sequence the mathematical and statistical conception of biological systems in
phenomena with dynamism and limited variability of a predictable and, there-
fore, linear type. In fact, only by virtue of the linearity in dynamism and varia-
bility could it be conceived that each action of the “actor” component should
correspond to a proportionate reaction of the “reactor” component, which
would lead to the return to the original equilibrium. (…)
The serious epistemological error of modern science lies precisely in the fact
that it has not taken into due consideration that in every variable phenomenon,
especially if it has complex dynamics, there is a certain degree of intrinsic un-
predictability that we can call “disorder or chaos”. The disorder, in this case,
must be understood as unpredictable variability that is found in the structure of
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all the dynamic phenomena of nature, or a number of states of the system that
are not predictable. Therefore, disorder must be seen as an attribute of nonlinear
variability in dynamic phenomena, including biological ones. Consequently, the
disorder should not be confused with the “noise” which represents the unpre-
dictable result of the randomness of “chance”. The unpredictability of chaos
should therefore not be confused with the unpredictability of the case. From this,
it follows that the order (periodicity) is not “neg-entropic”, the opposite of the
entropy disorder of evolving systems. In other words, the variability is not a var-
iation of the equilibrium, but the equilibrium is, if anything, the loss of the va-
riability.
The disorder,
i.e.
non-linear variability, has been and is still being assimilated
to randomness, error, noise, which probabilistically affect all measurements,
even the most precise, if repeated. It follows that the methods of Euclidean ana-
lytical mathematics and conventional parametric statistics of modern science, in
principle, consider extreme anomalous phenomena (the singularities or catas-
trophes of the mathematics of chaos), which are found in the dynamics of inor-
ganic and organic events, as a result of randomness, and, therefore, as not being
part of the variable structure of the system (outliers). In fact, “chance” has no
structure, it is disorganized, it is amorphous. It is evenly arranged in the regions
furthest from the center of the mean value. The “chaos”, on the other hand, de-
nounces a structure that is arranged with an orientation starting from a point of
minimal difference. The order, therefore, lies in what lies within certain bounda-
ries of variability around the most frequent value or the central location value of
the distribution. As in the analytical approach, also in the probabilistic statistical
approach, everything that lies beyond the extreme limits of distribution is con-
sidered a probable result of chance. Ultimately, both the analytical and the statis-
tical approaches are valid and capable of studying the “centrality” of repeating
phenomena, but, in principle, they are unable to study the “peripherality” of
what is repeated. The unpredictable, therefore, is such due to the methodological
limitation of current scientific methods which are not suitable for documenting
the unpredictability. (…)
Biological systems are necessarily dissipative structures in the long run, and
dissipative structures are, by definition, far from equilibrium and homeostasis:
order (periodicity) and disorder (non-linear variability) are “coexisting dynamic
states”. The structure of the disorder is the fractal (see GLOSSARY). The fractal
iteration of the disorder is perfectly periodic. Disorder, therefore, finds its way of
being simultaneous with order in the iterative structure of a periodic variation
[1] (translation from Italian is mine).
2. Introduction
The countless structural and functional solutions that characterize biological va-
rieties, produced in the course of phylogenetic (see GLOSSARY) diversification
via pre-adaptation (
exaptation
– see GLOSSARY) and adaptation dynamics,
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represent as many
dissipative
systems
(see GLOSSARY) far from thermodynam-
ic equilibrium, that rely on the availability of
anticipatory
systems
(see
GLOSSARY). That is, biological systems are
non-linear
dissipative
systems
[2]
embedded by
super-complex
anticipatory
systems
(see GLOSSARY) relying on
thermodynamics of non-equilibrium, at the phase boundary between chaotic
and ordered (coherent) regimes. The state maintained at the verge of chaos turns
out to be, in some sense, rather stable. This peculiar state is defined as a
self-organized
criticality
[3].
In the
human
placental
mammal
, the embryonic cell cycle and intrauterine
development process rests on one of the most effective dynamics to regulate the
living, sometimes approaching and sometimes diverging chaos,
i.e.
a
controlled
chaos
dynamics
[4] (also coined as
deterministic
chaos
).
Each stage of embryo development is characterized by the presence of
one-to-many
attractors
[5] (see GLOSSARY), toward which the developmental
dynamic variables trajectories are rapidly approaching from all the points of its
phase-space, and occurs among three main phases or periods, namely the
pre-embryonic
period
(zygote → merula → blastocyst), ranging from fertilization
to the 9th gestational day; the
embryonic
period
(blastocyst → embryo), from the
10th gestational day to the 12th week of gestation; the
fetal
period
(embryo → fe-
tus), from the 13th week of gestation to term.
The primary structure of the embryo is trilaminar, consisting of endoderm,
mesoderm and ectoderm, and the morphogenesis of the main apparatus of the
body starts during the first half of the embryonic period. The development, first
embryonal and then fetal [Figure 1], takes place inside a bag (ectodermal amni-
otic membrane or
amnios
→ mesodermal chorionic membrane → amniochorio-
nic membrane → chorionic villi epithelial mantle →
placenta
) filled with
amniot-
ic
fluid
(AF), composed for 98% by a
glassy
and
super-coherent
state
of
biologi-
cal
water
(see par. 2), mineral salts, amino acids, lipids and various kinds of ions,
stem cells and proteins.
The AF increases progressively in relation to embryonic/fetal growth, and un-
til the 10th week of gestation is formed essentially by maternal plasmatic ul-
tra-filtrate. From the 10th to the 20th gestational week, it has a composition very
similar to that of the fetal plasma, which diffuses into the amniotic fluid through
the thin and nonkeratinized embryonic/fetal skin. The third quarter is largely
formed by the urine and by cutaneous and lung transudation of the fetus.
Commonly, the function assigned to AF is that of cushion and settling tank of
embryonic and fetal metabolic degradation, nevertheless, recent studies have re-
vealed that it also performs an immune action [6] and occupies a leading role in
the
embryo
morphogenesis
[7],
neurogenesis
(AF contains numerous neuro-
trophic factors secreted by amniotic cells, thus exerts a neurotrophic effects on
fetal neurodevelopment during pregnancy [8]) and
CNS
morphogenesis
. Fur-
ther, within embryogenesis AF may act, as will be discussed in paragraph 2, as an
inherently dynamical entity endowed by proper non-linear dynamics, that
creates a biochemistry not governed by random collisions between molecules,
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Figure 1. Embryonic development from 2nd to 8th gestational week. Between 2nd and
5th gestational week is observable an amniotic cavity in which it welcomed the embryo,
and a chorionic cavity (extraembryonic coelom) in which the yolk sac is incorporated.
From the 8th gestational week the yolk sac undergoes a rapid process of involution, cho-
rionic cavity is progressively reduced becoming interstitial space/interstitial fluid, located
between the amnion and chorionic membrane, which between the 12th and 13th week
shape the amnio-chorionic membrane. Image source:
http://clinicalgate.com/placenta-and-extraembryonic-membranes/.
but by a code of mutual recognition and recall among molecules based on
long-distance electromagnetic interaction.
In multicellular organisms of the animal kingdom (from
Metazoa
to
Homo
),
the distribution of the various functions among different and increasingly spe-
cialized tissues is integrated by the
Nervous
Tissue
(NT), whose functional unit
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(in association with
glial
cells
1) is the
nervous
cell
,
i.e.
:
- A
generator
of
electromagnetic
radiation
in ultrahigh range of frequencies
with the wavelength comparable with linear dimensions of the cell itself;
- A
rhythmogenic
center
with exogenic modulated frequency;
- A
receptor
unit
playing selective function on
state
variations
(stimuli) and
functional
interface
between innervated tissues;
- Engaged in supporting and integrating the
energy-transfer
function exerted
by the catalytic cellular core (CCC), formed by the Golgi apparatus, the cen-
trosome (MTOC, Microtubule Organizing Center [13]) and microtubules2
(the structural units of the cell cytoskeleton, polymerized protein highly po-
larized).
In the human placental mammal
embryo
neurogenesis
is a complicated
process of generating functional neurons from neural (→neurospheres, com-
posed of free-floating clusters of neural stem or progenitor cells) [8] and glial
precursors, very active in the pre-natal period (→CNS development) and rela-
tively active in post-natal period (→neuronal repair processes) [15], which in-
volves, in addition to neural and glial precursors, mature glial cells, the
cere-
brospinal
fluid
(CSF), the AF and ependymal cells3. Glial cells, and in particular
astroglyal
cells
(astroglyal lineage), occupy a prominent place both in
neuroge-
nesis
and in the evolution and architecture of the CNS, its
morphogenesis
, a
complex process that takes place through the same sequence of stages in all ver-
tebrate embryos, which involve two of the three germ layers: mesoderm and ec-
toderm (the first induces morphological changes in the latter so that it can diffe-
rentiate to become neural tube). The CNS appears at the beginning of the 3rd
gestational week as stretched ectodermal thickening, the neural plate, located in
the dorsal-central region of the embryo, in front of Hensen’s node and the pri-
mitive streak. The neural plate is lifted, forming two reliefs, the neural crests.
These crests are then joined incorporating part of the AF in which the embryo is
immersed, giving shape to a tubular structure, the neural tube [Figure 2]. The
AF incorporated in the neural tube is then turned into CSF [Figure 3], initially
by the
neuroepithelial
cells
(NECs) and by the
radial
glial
cells
(RGCs), and sub-
sequently by the
choroid
plexuses
(CHPs), small vasculo-nervous spongy struc-
tures located in the cerebral ventricles (in the laterals two, in the third and fourth
ventricle), which start to develop when the embryo reaches the 8 mm (9th week
of gestation).
1
Until recent times it was thought that the nerve cell was the only functional unit of the Nervous
System (NS). It is now believed that this role should be partly shared with other cells belonging to
the NS, the
glial cells
[9]
(e.g. they regulate the neuronal synaptic responses associated with learning
and memory processes, and share with neurons the role of mediators in the genesis of brain fun
c-
tional skills [10] [11] [12]).
2It should be noted that Hameroff and Penrose’s
Orchestrated objective reduction
(Orch OR) theory
attributes
consciousness
to “orchestrated” quantum computations in microtubules inside brai
n
neurons, rather than the conventional view that it is a product of connections between neurons [14].
3
Specialized epithelial cells, which create a selectively permeable barrier (ependyma) between the
CSF and nervous tissue, and that, according to recent studies, can generate
neuro-stem cells
(NSCs),
pluripotent cells that can differentiate and become neurons or glial cells.
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Figure 2. The CNS originates in the 3rd gestational week from the neural plate, a thicken-
ing of the fetus dorsal ectoderm in the shape of racket, in front of Hensen’s node and the
primitive streak. The neural plate thickens and bends becoming neural groove, which by
closing form the neural tube, inside of which is incorporated the AF, which is converted
into CSF, initially by neuroepithelial cells (NECs) and by radial glial cells (RGCs), and
subsequently by the choroid plexuses (CHPs). Image source (modified):
http//www.albinismo.it/info-scientifiche-albinismo-35/melanociti.
Figure 3. Cerebrospinal fluid (CSF) early development from amniotic fluid (AF). As the
neural
tube
closes, it envelops AF that fills the lumen and is later actively modified. Early
in development,
neuroepithelial
cells
(NECs) and
radial
glial
cells
(RGCs) contribute to
the composition of this liquid milieu, but this task soon falls to the
choroid
plexuses
(ChPs). The ChPs are folded structures residing in the brain ventricles that consist of a
single layer of highly active epithelium sandwiching an elaborate vascular network. This
vascular-neural composite controls the passage of molecules into the CSF, which impacts
neurogenic
zones
throughout life. Image source (modified):
http://vector.childrenshospital.org/2015/12/how-amniotic-and-cerebrospinal-fluids-talk-t
o-the-developing-brain-proteomics/.
During embryonic development, the vast majority of neurons and a large
number of glial cells are generated in the germinal zones or germinal matrices or
Neurogenic
Niche
[16] [17], the micro-anatomical environment that depending
on the period of neuronal development (prenatal → postnatal) may contain en-
dothelial cells, ependymal cells, stem cells, astrocytes, microglia, neurons and
mature descendants of adult neural precursors, and that functionally controls
their development
in
vivo
. In the early phases of cytogenesis, the germinal zones
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are located primarily at the ventricles surface (
ventricular
zone
, VZ). While em-
bryonic development proceeds, on the surface of VZ forms a germinal
subven-
tricular
zone
(SVZ)4, which together form the
ventricular-subventricular
zones
(V-SVZs) [18] [19] [20].
As the cerebral hemispheres enlarge, and the distance to be travelled by the
cells increases, most of the neurons that will form the cerebral cortex migrate to
their destinations along specialized
radial
glial
fibers
(RGFs) that span the entire
thickness of the hemisphere from the ventricular surface to the pia5.
After birth neurogenesis is carried out by the specialized activity of the neu-
rogerminative
subgranular
zone
(SGZ) of the dentate gyrus of the hippocampus
[17] [21] [22].
3. Long-Range Spatial Organization during Embryo
Development
The stages of embryo development require the integration of two ordering ac-
tions, namely a network that generates sustained oscillations (patterns for the
cell-cycle clock in developmental processes) and a control mechanism that pro-
duces robust spatial synchronization. While considerable research has addressed
oscillatory behavior in different biological contexts, the question of how em-
bryos are synchronized across large spatial dimensions has yet to be addressed,
namely:
how
genes
are
activated
in
certain
spatial
regions
and
how
the
distribu-
tion
of
functional
biomolecules
and
cell
types
is
orchestrated
and
coordinated
to
result
in
large-scale
pattern
and
its
regulation
?
Simple diffusion alone and short-range forces are insufficient to communicate
the stage of the cell cycle over typical embryonic length scales (0.1 - 1 mm), even
if morpho-mechanochemical models are of different opinion. Indeed, these
models imply the existence of long-lived mechanical stresses, mainly tensile and
compressive stresses (which depend, according to [23], on the elasticity of the
cell surface, linear tensions at the junctions between individual cells and the ac-
tive contractility of the cell perimeter caused by the action of actomyosin rings)
which through chains of short-range interactions, create at any stages mechani-
cally stressed multicellular communities (permanently maintained normal ten-
sile patterns are indispensable for providing a long-range morphological order),
that bind together the different level processes [2].
One system-focused answers on how embryos are synchronized across large
4
The cells that will form the deep cerebellar nuclei and the Purkinje cells of the cerebellar cortex are
generated in germinal zones in the subventricular region of the fourth ventricle.
The cells that form
the deep cerebral nuclei are formed along the ventricular surface of the diencephalon (the future
third ventricle) and from the ganglionic eminence of the telencephalon (the future site of the ca
u-
date nucleus). The diencephalic germinal zone will produce cells that form the thalamus, hyp
o-
thalamus, and globus pallidus, whereas the cells produced in the ganglionic eminence will form the
striatum (caudate nucleus and putamen), amygdaloid complex, and claustrum.
5The orderly production and m
igration of the cells, from the germinal zone to the cerebral cortex
along the RGFs, led to the concept of
neuronal-glial vertical units
. This units includes the germinal
zone which produces the cells destined for a certain region of the cortex, the cells
themselves, and
the bundles of radial glial fibers which guide the cells to their final destination.
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spatial dimensions is provided, e.g., by the so-called
morphogenic
field
theory
[24] [25] [26] [27], which suggests that a pervasive field of influence induces
long-range
spatial
organization
in plant and animal development [28] [29] and
guides both structure and function. That is, the formation of new space-temporal
structures during the development of organisms and the behavior of both indi-
vidual cells and rudimentary organs is controlled by a field of forces common to
all elements of an embryo [30].
What this force field consist of? The morphogenic field theory suggests that
chemical signaling is supplemented by electromagnetic signaling in driving and
organizing the structure and function of cells, tissues, organs and the whole or-
ganism [31] [32].
The electromagnetic signalling role in relation to embryogenesis can be better
understood within the Quantum Field Theory (QFT) system of correlations,
with biological fields having a very complex
chreod
(attractor path) from the
zygote to the fully grown individual, pierced by many points of symmetry
breaking, and within the Quantum ElectroDynamic’s (QED) properties of the
super-coherent
state
of
biological
water
[33] [34], of which the AF is mostly
composed (until the 10th week of gestation its composition is given by maternal
plasmatic ultra-filtrate and from the 10th to the 20th gestational week by a fluid
very similar to that of the fetal plasma).
As discussed in [33] [34], over the last 80 years evidence has been accumu-
lated on the influence of electromagnetic fields (EMFs) on living organisms,
showing that the electrodynamic field plays an important role in the establish-
ment of coherence, directional transport, organization of morphological struc-
tures, interactions, information sharing, and brain activity. The frequencies of
the involved EMFs cover different intervals corresponding to the different scales
present in the organisms. The exceptional electrical polarity of biological objects
and long-range interactions suggest a basic role of the endogenous EMF gener-
ated by living cells, a role that finds its place in a physical vision that addresses
biological dynamics as an interplay of chemical processes and EMF interactions,
that is, as an array of EMF assisted biochemical reactions. Excited longitudinal
polar oscillations in microtubules in eukaryotic cells generate the endogenous
EMF [35]. The metabolic activity of mitochondria connected with
water
order-
ing
, forms conditions for excitation.
Liquid water molecules cannot be assumed to be bound by purely static inte-
ractions (H-bonds, electric dipole-dipole interaction). Their binding is actually
induced by the time-dependent radiative long-range endogenous EMF.
Short-range static bonds, such as H-bonds, then set in as a consequence of the
molecule condensation induced by such long-range radiative fields. An ensemble
of molecules interacting with the radiative EMF acquires, above a density thre-
shold and below a critical temperature, a new non-trivial minimum energy state,
different from the usual one where the oscillations of the molecules are uncorre-
lated and the EMF is vanishing. The new minimum energy state implies a
configuration of the system where all molecules enclosed within a variable re-
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gion, denominated Coherence Domain (CD) if its wavelength
λ
is that of the
trapped EMF and Exclusion Zone (EZ) if wider (coherence among multiple
CDs), oscillate in unison in tune with an EMF trapped within the CD/EZ. The
persistence in time of extremely low frequency (ELF) magnetic fields guarantees
a steady excitation of the
glassy
and
super-coherent
state
of
biological
water
CD/EZ and correspondingly of the biochemical activity catalyzed by them.
CD/EZ oscillates on a frequency common to the trapped EMF and the biological
water molecules and this frequency changes when energy is stored in the CD/EZ.
When the oscillation frequency of the CD/EZ matches the oscillation frequency
of some non-aqueous molecular species present on the CD/EZ boundaries, these
“guest” molecules become members of the CD and are able to catch the whole
stored energy, which becomes activation energy of the guest molecules; conse-
quently, the CD/EZ gets discharged and a new cycle of oscillation could start
[36]. In order to load energy in the
super-coherent
state
of
biological
water
CD/EZ,
i.e.
in order to energetically excite the cloud (vortex) of quasi-free elec-
trons kept orbiting at the periphery of the water CD/EZ by the internal EMF in-
homogeneity6 (residual positively charged ionized molecules sink toward the
centre of the CD/EZ and the CD/EZ become a spherical - or a hybrid between a
circular cavity and a dipole, an excitable unit made of two complementary
phase-points capacitor of quantum nature, able to trap electromagnetic energy
through coherence), a resonant alternating magnetic field is needed. In animals,
such as the humans, this field can be produced by the Nervous System (nervous
cell is a
generator
of
electromagnetic
radiation
in ultrahigh range of frequencies
with the wave length comparable with linear dimensions of the cell itself). Ele-
mentary organisms, such as bacteria and virus, but also plants (
vegetal
cell
net-
work
) should use environmental fields. Good candidates are the Schumann
modes of the geomagnetic field. These modes are the stationary modes produced
by the magnetic activity (lightnings or else) occurring in the shell whose boun-
daries are the surface of the Earth and the conductive ionosphere, which acts as a
mirror wall for the wavelengths higher than several hundreds of meters7 [36].
6
Ions close to water CD/EZ are attracted by the EMF trapped in the domains and kept orbiting
around the domain moving at a circular speed proportional to the so called cyclotron frequency
νc
.
Since DNA and also proteins are polyelectrolytes, they are
surrounded by a cloud of positive
counter-ions; ions having a cyclotron frequency in the interval between 1 and 100 Hz play an i
m-
portant role. By applying a magnetic field, having a frequency which matches the ion cyclotron fr
e-
quency, on a system where ions are present, these ions are extracted from their orbits [37] [38]
. Due
to the conservation of angular momentum, the extraction of ions from the cyclotron orbits produces
a rotational motion of the
quasi free
electrons of the water CDs, which therefore become energet
i-
cally excited [39] [40].
7It is interesting to observe that, should the cyclotron orbits around the water shell be saturated
by
an ion species which does not match the Schumann resonances, the activity of the biological system
would be inhibited. This prediction is in agreement with facts since we know that there are ions
promoting biological activity and ions inhibiting it. The
above conclusion holds, of course, if the
only EMF background is the natural one (Schumann modes) or an artificial EMF background with
frequencies similar to the Schumann ones; should an artificial EMF background with a different
frequency distribution be pr
esent, a reshuffling of the favorable and unfavorable ion species would
occur. This feature could provide a rationale for the observed impact of ELF fields on the physi
o-
logical activity.
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Due to its composition (at least until the 20th gestational week), AF should be
treated as
biological
water
in
a
super-coherent
state
, and within embryogenesis
may act as an inherently dynamical entity endowed by a proper non-linear dy-
namics, that creates, as discussed above, a biochemistry not governed by random
collisions between molecules, but by a code of mutual recognition and recall
among molecules based on long-distance electromagnetic interaction. This is
also the role that continues to be played throughout life by the CSF (which, as
earlier mentioned, is AF incorporated in the neural tube and turned into CSF
during the early phase of CNS formation) in relation to the CNS activity. This
consideration implies that chemical interactions are highly dependent on the
dynamics governing the field, which can modify and eventually supersede clas-
sical chemical reactions [41], and that the overall chemical reactivity can be sig-
nificantly modulated by biophysical – not chemical – factors, such as
long-distance electromagnetic interaction.
We have, therefore, a
non-stationary
coherent
regime
, but that evolves over
time, generating in turn a time-dependent biochemical framework whose func-
tion is to optimize the intrauterine development process, e.g.:
Allow for aggregation in response to nutrient deprivation,
Allow for the transmission of information over large length scales at rates far
greater than allowed by simple diffusion,
Give rise to complex spatial patterns linked to high-order torus (fractal-like)
topology8 (fractal algorithm with the development of a set of similar
scale-invariant modules is an effective way of morphogenesis based on a rela-
tively small genetic program [42]).
Such
non-stationary
coherent
regime
can be drawn as a macroscopic system
described by QFT in terms of
coherent
Bose-Einstein
condensate
(BEC – see
GLOSSARY) [43].
4. Gene Regulatory Network’s Basin of Attraction
The common epistemological habit of modern molecular biology is to reduce an
observed phenotype or function to a molecular entity (Democritus atomistic
ontology), such as a gene, protein or pathway, which have become the embodi-
ment of causation in biology. This reductionist-mechanistic and Darwinist view,
obviates the need for a more encompassing and integrative view for examining
morphogenesis in the broader context of development. Instead, any novel phe-
notypic feature (
hall
mark
) that a cell acquires is conveniently explained by a
specific lasting molecular mechanics. Interestingly, while one will automatically
8According to the theorem of elementary topology, any closed surface in three-
dimensional space is
homeomorphic (topologically equivalent) to the sphere with a certain number (
p) of handles. If
there are no topological surgeries (cutting and gluing of epithelial sheets), the genus of
the surface
(
p
) is a topological invariant, and any geometrical deformations such as surface curvature, linear and
angle values are not essential. The closed surfaces of the genus
p
= 0 (sphere),
p
= 1 (torus),
p
= 2
(double torus, or
pretzel
) and so on give a topological classification. The topological differences b
e-
tween these surfaces are fundamental and qualitative. Mechanical stress
p
is a vector and is defined
as the average force per unit area
S
that some particle of a given body exerts on adjacent pa
rticle
across an imaginary surface that separates them [2].
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seek to determine the gene driving the molecular mechanics responsible for a
cell’s novel phenotypic feature, nobody will doubt that normal cells as distinct as
a stem cell, a mature neuron, a blood cell, or an epithelial cell, all share the very
same genome. This opens an intriguing question:
how
can
the
same
set
of
genet-
ic
instructions
produce
a
variety
of
discrete
,
persistent
(
non-genetically
inhe-
rited
)
cell
phenotypes
? [44].
Following this epistemological habit, the claim that the course of development
is “genetically programmed” is commonly accepted as an absolute truth, even in
spite of the lack of proper understanding of what the “program of development”
actually means. So exciting were the successes in deciphering the key roles of
genes in “controlling” the development of embryonic rudiments that all the in-
structions for “make it through” looked to be in our hands. Only closer to our
days, it became realized that our belief to govern development by switching on
or off any genes or signaling pathways is the same as operating an electronic de-
vice by pushing its buttons without having even a slight idea on how it actually
works. Anyway, our present-day image on genetic regulation of development
contains two great negations [2]: 1) even complete knowledge of genome struc-
ture cannot tell us what gene will be expressed in a given space/time location; 2)
even from exhaustive knowledge of space/temporal schedule of genes expres-
sion, one cannot predict what morphological structures will be formed in these
definite locations.
Actually, such a situation is in generally acknowledged, but the conclusion is
in most cases expressed in an allegoric form, by claiming that genes action is
“context-dependent”.
A gene expression pattern reflects the state of a
gene
regulatory
network
(GRN), and as a whole, is dynamic: it develops in time due to the mutual regula-
tion between the genes of each others’ expression and settles down into an
equi-
librium
state
that complies with the regulatory interactions. The ability of small
gene regulatory circuits to produce more than one
stable
equilibrium
state
(sta-
ble pattern of expression of all genes in the circuit) was first proposed by Max
Delbruck in 1948 [45], and later by Jacob and Monod [46] and others to explain
differentiation into a multitude of
stable
phenotypic
states
. In the 1960s Kauff-
man showed that a complex network of up to hundred thousand of mutually
regulating genes can under certain conditions produce hundreds of stable equi-
librium states, termed
attractors
[47] [48]. Kauffman proposed that attractor
states correspond to the gene expression profiles associated with each cell type
[49].
The
state
space
of a GRN is therefore the space that contains all theoretically
possible gene expression patterns (network states of that GRN). Each point in
the (high-dimensional) state space represents one gene expression pattern of the
GRN and moves around as the expression patterns change. The attractor state is
a particular point in the state space and has particular properties: as a stable
equilibrium state, it resembles that of a
lowest
energy
state
at the bottom of a
potential
well
which represents the
basin
of
attraction
. Thus the attractor state is
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surrounded by unstable states and is
self-stabilizing
. A new perspective not
available in the traditional paradigm of linear causative pathways takes shape. In
the emerging framework of gene network architecture the attractor nature of
distinct cell phenotypes, most obviously, the cell types, explains a series of cell
behaviors that are not easily accounted for by linear molecular pathways. It ex-
plains why cell-type specific genome-wide expression profiles, defined by the
values of thousands of variables, are so reliably established during differentiation
as if orchestrated by an invisible hand: the
self-organizing
and
self-stabilizing
property of biologically significant gene expression profiles is a natural feature
conferred by attractors. Hence, cell-type specific gene expression patterns are
robust to noise, re-establishing themselves after small perturbations (imposed
changes of expression levels of individual genes) and can be reached in principle
via an almost infinite number of paths. Conversely, they are capable of under-
going drastic quasi-discontinuous transitions to other specific stable expression
profiles via genome-wide changes of gene expression. Such transitions occur
when cells encounter the proper cell fate regulatory signals that, via branching
signal transduction pathways change the expression of a specific set of genes of
the network, or due to sufficiently high random fluctuations of gene expression
levels. In a simplified picture, attractor transitions underlie the cell phenotype
switching during development [50].
The existence of high-dimensional attractor states defined by N = thousands
of genes across the genome and their correspondence to particular cell types has
recently been experimentally verified. Using microarrays for dynamic gene ex-
pression profiling the “attraction” of trajectories from different directions in
state space towards a common final state of a differentiated cell, as well as the
relaxation back to the bottom of the potential well after local perturbations are
both indicative of attractors [51]. Such self-propelled convergence of
high-dimensional trajectories (gene expression profile change) is a necessary
signature of an attractor [52]. The biochemical cascade underlying the cell cycle,
i.e.
the dynamic behavior of this biochemical system, it can be visualized by a
limit cycle, a double limit cycle, or a strange attractor, traced out by its trajectory
in phase space [4].
Within this overall framework, the simple clock, representing the
embryonic
cell
cycle
, is described as a
limit
cycle
. A doubling of the limit-cycle period takes
place during embryonic development. Subsequently, a breakdown of the double
cycle occurs, and a strange attractor is born, whose attraction domain is
sufficiently large enough to stabilize the process of cell divisions. The transition
to a system with strange attractor means that complicated nonperiodic oscilla-
tions, whose details are very sensitive to small changes in the initial conditions,
can be observed. In other words, phase trajectories on the strange attractor are
unstable. However, the average characteristics of this behavior are stable and do
not depend on the initial conditions (they vary within a given domain). From a
general point of view, and using computer simulations, one can see that the sys-
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tem of a single or a double limit cycle, as well as that of a strange attractor are
structurally stable (robust) systems. The property of structural stability is absent
only for the bifurcation values of the system’s parameters [4].
5. Morphogenesis Rest on Symmetry Breaking
The existence of a strange attractor with an unlimited reservoir of periods may
be an important property of multicellular organisms, where the proper structure
and function of the adult organism is depends strongly on intricate develop-
mental processes as well as on sophisticated
homeostatic
mechanisms
. It seems
that chaos is able to favor the sudden emergence of partial synchronization
processes related to different realities significant for the system in which it acts.
Therefore, by increasing the degrees of freedom of the system, it would seem to
play a functional role of flexibility in switching to different stable activation
states for some time variation (∆t) other than zero. This functional role finds a
partial one confirms, for example, when the state of activation of the cerebral
cortex is observed during an epileptic seizure [53]. In these conditions, in fact,
the system appears strongly synchronized in rather large areas and for relatively
longer times than the changes of state that they occur as a result of other mental
events.
The functional role played by (deterministic) chaos on the system resembles
that of the officer giving the order to break the pass when a military platoon is
about to cross a bridge. The synchronized walk would quickly bring the whole
structure to oscillate with a destructive resonance. In this case, the duty officer
gives the order to desynchronize the gear to avoid disastrous effects.
It is possible that the nervous system, like any other biological system, in their
evolutionary history, has developed its own internal strategies to “randomize”
the states of activation and avoid the disastrous effects of the synchrony that we
can observe, e.g., during epileptic attacks. The importance of desynchronization
is even more evident when considering the phenomena of muscle activation
where a vast synchronization of activation in different motor neurons would
lead to undesirable tremors [54], thus preventing the fine adjustment of move-
ment and orientation in space.
Embryonic development occurs when a single cell (the fertilized egg) reliably
self-assembles a highly complex model appropriate to its species. During later
life, multicellular creatures must maintain their pattern – an active process of
morphostasis
that works to maintain the whole while individual tissues age or
are damaged by diseases or traumatic injury.
The early
amniote
embryo
is shaped by unabated tissue motion. In particular,
all early developmental milestones in amniotes involve large (millimeter-scale)
morphogenetic movements, including gastrulation, left-right symmetry break-
ing, neurulation, segmentation and caudal axis extension. These early landmark
events create the foundation for organogenesis by sculpting the vertebrate body
plan and transporting organ precursors to appropriate destinations within the
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embryo.
Morphogenesis
,
i.e.
the ability of living systems to self-organize simulta-
neously on many scales to produce the exquisitely complex pattern that under-
lies function, is one of the most interesting aspects of biology. In morphogenesis,
intricate, mathematically precise natural architectures develop from simple,
symmetrical initial states that show no traces of the patterns to come. Symmetry
propagation and symmetry breaking are essential processes in biological mor-
phogenesis, in metazoan evolution and development. Analyzing the behavior
and property of individual cells alone cannot unravel the complexities of mor-
phogenesis: fluctuating
extracellular
matrix
(ECM) material properties and col-
lective biological motion govern the tissue-scale deformations that shape early
amniote embryos and their organ primordia. An appreciation of both
cell-autonomous and tissue-level motion perspectives is needed to understand
the biomechanical mechanisms that shape amniote embryos and, potentially,
non-amniote embryos [55] [56].
Symmetry Theory (ST) it may be regarded as a compact model of any
law-oriented science, aiming to search for invariable basis within a set of varying
events. ST therefore is dealing with the so-called invariable transformations,
keeping constant some properties of a body which in other relations is changing.
The transformations used for testing the invariability are the movements in a
broad sense, including so-called isometric transformations keeping the form and
the dimensions of the object constant as well as the different kinds of deforma-
tions.
The symmetry orders exchange between different levels is directly related to
morphogenesis. In classical biology (both zoology and botany), the notions of
symmetry are used in most cases for comparing static forms belonging to dif-
ferent taxonomic groups. Accordingly, the compared symmetries are related as a
rule to higher structural levels only.
Classical self-assembly relates mostly to preservation and increase rather than
decrease of the symmetry order. For creating a complicated space-temporal or-
ganization of embryos, the reverse dynamics associated with symmetry breaks
will be necessary. Symmetry breakdown is one of the fundamental processes of
development. Like breaking a mirror, the initially smooth, continuous surface or
shape with a high degree of symmetry is transformed into one with less symme-
try due to the appearance of new structures and forms. With continued growth
and development, the pattern may remain essentially the same in its general
characteristics, but it is initially composed of hundreds, then tens of thousands,
and then millions to billions of cells in the final mature form. Various scalar and
vector fields on subcellular, cellular, and supracellular levels of biological organ-
ization are manifested in heterogeneous distribution of structural components,
in biochemical gradients, in vectorized subcellular transport and other function-
al activities, in ionic fluxes and accompanying electric fields, in fields of me-
chanical tensions, in directed cell movement, etc.
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The self-reduction of symmetry order is linked to
cell
polarization
9 and is also
referred to as
spontaneous
breakdown
of
symmetry
(SBS), or spontaneous
breaking symmetry. In Quantum Field Theory (QFT) it is well known that the
ordering of the elementary components of a system is achieved as a result of the
SBS and constitutes the observable manifestation of coherence. According to
QFT, the dynamics of a system is described by a set of field equations that are
postulated to contain all the characteristic features of the system. The fields
represent the elementary components of the system, e.g., the electromagnetic
field (EMF), the atomic and molecular system’s constituents, their electric
charges, and dipole moments, etc. In general, one may consider transformations,
e.g. rotations, reflections, and translations (linear shifts), of the fields such that
the field equations do not change their form when the fields undergo the said
transformations. The dynamics is then said to be invariant under the considered
transformations, and these are named symmetry transformations of the dynam-
ics. It may happen that under the action of some external perturbation, the state
of minimum energy of the system (vacuum), is not symmetric under the sym-
metry transformations of the dynamics. Then, the symmetry is said to be spon-
taneously broken. Spontaneously means that the system is driven into the
non-symmetric state by its own (internal) dynamics, not forced by the external
perturbation which only acts as a trigger. SBS allows the transition from the mi-
croscopic scale of the elementary components to the macroscopic scale of the
system behavior.
Topological and symmetry transformations are determined genetically and
epigenetically. Molecular genetics and biochemistry have focused on unraveling
the role of biochemical messengers in this process, and are beginning to under-
stand the role of tensile forces [2] and adhesion [57]. It is well established that
molecular signals and genetic expression play essential roles in both plant and
animal development. While the involvements of specific genetic expressions are
well established in plant animal organogenesis, it remains largely unknown how
genes are activated in certain spatial regions and how the distribution of func-
tional biomolecules and cell types can form in dynamic spatial patterns (the spa-
tial organization of evolutionary advanced animals may be represented topolog-
ically as an outer epithelial envelope of a certain genus p embracing a number of
inner closed epithelial surfaces embedded inside the outer envelope [42]).
Physiologically, symmetry breaking in biological systems is guided by certain
cues
, stimuli that are either intrinsic, also known as
landmarks
, or extrinsic, such
as gradients of signaling molecules detected by sensors. Stimulus-induced transi-
tions provide the ability to sense and amplify environmental cues that exceed the
9
Cell polarity is based upon a complicated and up to now not completely untangled web of negative
and positive feedbacks related to different levels; among them, mechanical feedbacks, in most cases
tensile, seem to play the leading role in a large-scale integration of lower levels ones. For these fee
d-
backs to be effective, the entire cell should be either in an unstable state, or on the verge of stability.
In both cases, it behaves as a nonlinear system. Being still rudimentary on the levels of cytoskeleton
and single molecular structures, nonlinear properties are expressed in full scale at the upper stru
c-
tural levels of cell organization.
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level of background noise. Under normal physiological conditions, biological
systems are maintained within the region of parameters corresponding to the
bistable
state
posed for the stimulus-induced symmetry breaking, and are en-
dowed by the existence of
spontaneous
cell-intrinsic
symmetry-breaking
me-
chanisms
to initiate the symmetry-breaking transition [58].
6. Conclusions
In light of controlled chaos dynamics and Quantum Electrodynamic we dis-
cussed how the embryo development is characterized by the presence of
one-to-many
attractors
, by symmetry propagation and symmetry breaking
processes and by the
amniotic
fluid
acting as an inherently dynamical entity en-
dowed by a proper non-linear dynamics, that creates a biochemistry not go-
verned by random collisions between molecules, but by a code of mutual recog-
nition and recall among molecules based on long-distance electromagnetic inte-
raction.
We therefore attempted to answer two main questions:
- How genes are activated in certain spatial regions and how the distribution of
functional biomolecules and cell types is orchestrated and coordinated to re-
sult in large-scale pattern and its regulation?
- How can the same set of genetic instructions produce a variety of discrete,
persistent (non-genetically inherited) cell phenotypes?
The solution to the first question is provided by assuming that at least until
the third quarter gestational period the
glassy
and
super-coherent
state
of amni-
otic fluid (AF) may act as an inherently dynamical entity endowed by a proper
non-linear dynamics, that creates a biochemistry not governed by random colli-
sions between molecules, but by a code of mutual recognition and recall among
molecules based on long-distance electromagnetic interaction. A role that con-
tinues to be played throughout life by the CSF (which is AF incorporated into
the neural tube during the early phase of CNS formation) in relation to the CNS
activity.
The solution to the second question is provided by assuming that a gene ex-
pression pattern reflects the state of a
gene
regulatory
network
(GRN), and as a
whole, is dynamic: it develops in time due to the mutual regulation between the
genes of each others’ expression and settles down into an
equilibrium
state
,
termed
attractor
, that complies with the regulatory interactions. The
state
space
of a GRN is therefore the space that contains all theoretically possible gene ex-
pression patterns (network states of that GRN). Each point in the
(high-dimensional) state space represents one gene expression pattern of the
GRN and moves around as the expression patterns change. The attractor state is
a particular point in the state space and has particular properties. Thus the at-
tractor state is surrounded by unstable states and is
self-stabilizing
. The attractor
nature of distinct cell phenotypes explains why cell-type specific genome-wide
expression profiles, defined by the values of thousands of variables, are so relia-
C. Messori
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bly established during differentiation, as if orchestrated by the
self-organizing
and
self-stabilizing
property of biologically significant gene expression profiles
conferred by attractors.
Statement
The author warrants that the article is original, does not infringe on any copy-
right or other proprietary right of any third part, is not under consideration by
another journal, and has not been previously published.
Conflicts of Interest
The Author does not have any known or potential conflict of interest including
any financial, personal or other relationships with other people or organizations
within three years of beginning the submitted work that could inappropriately
influence, or be perceived to influence, their work.
Funding
This article did not receive any specific grant from funding agencies in the pub-
lic, commercial, or not-for-profit sectors.
Declaring
This article does not contain any studies with human participants or animals
performed by the Author.
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Glossary
Fractal
: In structures that on a small scale repeat the structure examined on a
larger scale, the minimized iteration of the real can take place inside or outside
the object itself, so that the parts will always be similar to their whole, as well as
the parts of the parts, and so on (geometric synecdoche). In other words, the
whole is reflected in its parts and vice versa. In the repetition of itself, the object
is assumed as a “dimension to be minimized”, so that it topologically produces
its shrunken image, similar in shape and orientation, which is a fraction of it, it
is its “fractal”. The fractal of itself iterates in the space of states for “geometric
relationships” between the points that make up the image in terms of “affine
transformations” (AT) that do not alter the basic structure of what it iterates
(topological representation). Affine transformations are functions that maintain
the similarity and homothety of the object being iterated (topological homeo-
morphism), consisting of rotations, translations, elongations, shortenings, etc.
The fractal has immeasurable magnitude and imperfect proportions.
Phylogeny
:
Phylogeny
should be understood as the process of diversification
and integration to which undergoes the Earth’s biological phenomenon, as a
coral unit, from its origin, in relation to all the intermediate solutions between
adaptation
and
exaptation
, to all the
dissipative
/
anticipatory
structures/systems
solutions and to all the
state
transitions
(bifurcations), induced by macroscopic
and microscopic
state
variations
, that have affected it, relying on the
poietic
ac-
tion
(which produces development and structure) exerted by
self-organization
,
and maintained in a state at the verge of chaos (
self-organized
criticality
) by a
basin
of
attraction
of
the
chaotic
type
with
different
attractors
(
riddled
basin
of
attraction
).
Exaptation
: The concept of
exaptation
was introduced by paleontologists
Stephen Gould and Elisabeth Vrba in 1982, to indicate the possibility that in na-
ture the relationship between organs and functions is potentially redundant, in
order to allow that a tract developed for a certain adaptive reason, can be
“co-opted” or converted to a function even completely independent from the
previous one. This functional cooptation, which complements and does not re-
place the gradual action of implementation of natural selection, was named by
Charles Darwin “
pre-adaptation
” and was renamed by Gould and Vrba with the
neologism
exaptation
, means precisely that some innovations, appeared during
the course of phylogeny, may not be the result of a process of selection toward
that specific function, but the reuse for other purposes of an existing structure.
Dissipative
systems
: Far from equilibrium, the smallest fluctuations of a sys-
tem’s stationary state can lead to completely different behaviors on a macros-
copic scale. A myriad of crisis or bifurcations points can lead the system, in an
apparently random way, to new stationary states. These not uniform states of
structural organization, varying in time or space (or both), were called by Ilya
Prigogine
dissipative
structures
, and their spontaneous evolution,
self-organization
.
Anticipatory
systems
: Anticipatory systems are commune to all biological
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systems. The ability shown by natural anticipatory systems consists in being able
to foresee, with a variable but still significant margin of uncertainty, to which
environmental perturbations the biological system could undergo, and behave
accordingly.
Super-complex
anticipatory
systems
: Complexity, as usually understood,
refers to chaotic systems,
i.e.
to systems which are deterministic and sensible to
their initial conditions. So understood, complex systems are entirely past-governed
and are apparently unable to include anticipatory behaviour. In order to distin-
guish anticipatory systems from entirely past-governed systems, the concept of
super-complexity
has been introduced. Super-complexity can be regarded as the
most general property of living systems, including aspects like their constitution,
reproduction and autonomy. In short, complex systems are systems: 1) requiring
a double form of composition (the
bottom-up
type of composition from ele-
ments to the system), and the
top-down
form from (a previous stage of) the sys-
tem to its elements; 2) capable of both regeneration and self-reproduction by re-
producing the elements of which they are made (
autopoiesis
); 3) endowed with
autonomy.
Attractor
: A pole of syntropic stabilization, locally unstable but globally sta-
ble, which introduces a variable and convergent quota of in-formation in the
dynamics of a system, favouring the establishment of correlative patterns (cohe-
rence). In performing its polarizing action on the dynamics of the confinement
processes, attractor stabilizes a warp of polarized hysteresis domains embedded
by a weft of self-recombining mnesic-like processes of a chaotic type. The quan-
titative measure of its ability to stabilize a warp of polarized hysteresis domains
embedded by correlative patterns between self-recombining mnesic-like
processes of the chaotic type, is referred to as
mnemotropy
, while the qualitative
measure of its ability is referred to as
mnemotropic
action
. It is very common for
dynamical systems to have more than one attractor. For each such attractor, its
basin
of
attraction
is the set of initial conditions leading to long-time behavior
that approaches that attractor. Thus, the qualitative behavior of the long-time
motion of a given system can be fundamentally different depending on which
basin of attraction the initial condition lies in (e.g., attractors can correspond to
periodic
,
quasiperiodic
or
chaotic
behaviors of different types).
Bose-Einstein
condensate
: The bosons that condense in a crystal are called
the
phonons
,
i.e.
the
quanta
of
the
elastic
waves
responsible of the ordering in
crystals; in the magnets, they are called the
magnons
, namely the
quanta
of
the
spin
waves
in magnets; in water, they are called “
dipole
wave
quanta
” (DWQ),
the
quanta
of
the
fluctuating
molecular
dipole
waves
; and so on. The ordered
patterns we observe at a macroscopic scale in these systems are sustained and
generated by
long
range
correlations
maintained by these waves. One would
never be able to construct any of these systems by using short range interaction
among the nearest neighbours. Short range interaction, if it is there, is made
possible by the long range one which brings “near” the components (e.g., mak-
ing possible the formation of H-bonds in water). Decoherence in Quantum Me-
