After switching to the life sciences - not wholly voluntarily as DCU had stolen all my software and to this date has returned nothing despite promising to do so - I began to write in a new idiom. This became the book "One magisterium". you can find a free extract here;
The eminent Stuart Kauffman had this to say about these papers, the former of which was reprinted on this blog in 2012 and the latter of which is below;
that point us ever in new directions. These are not final thoughts,
scientist, philosopher, poet singing to us to evoke. Read them, and be
Remarks on the foundations
of biology
Seán
O Nualláin, visiting scholar, molecular and cell biology, Berkeley
Abstract
This
paper attempts, inevitably briefly, a
re-categorization and partial resolution of some foundational issues in
biology. An initial ground-clearing exercise extends the notion
of causality in biology from merely the efficient cause to include also final
and formal causality.
The
HGP can be looked on as an attempt to
ground explanation of the phenotype in terms of an efficient cause rooted in a
gene. This notion gives rise to the
first section discussing the computational metaphor and epigenesis and
suggesting ways to extend this metaphor. The extended notion of causality
alluded to above is necessary, but not sufficient, to demarcate a specific
explanatory realm for the biological.
While the universe can ultimately, perhaps,be explained by quantum fluctuations being computed
through the laws of nature, the origin of life remains a mystery. The ground-clearing exercise refers to
coincidences that motivate the cosmological anthropic
principle,
before raising an alert about the possibility of similar thermodynamic laws
facilitating the emergence of life.
Life
itself seems to involve symbolic operations that can be described by the
grammatical rules within tightly -defined limits of complexity. The nascent field of biosemiotics has
extended this argument, often in a Peircean direction. Yet, even here, the task involved needs to be
specified. Is the organism creating proteins to launch an immune counter-attack
? Alternatively, is a pluripotent stem
cell generating an entire organism? We
consider what these separate tasks might look like computationally.
The
paper ends with further delimitation of the specifically biological. At what point in the infinitesimal does life
refuse to reveal its secrets?
Conversely, at what specific levels in increasing size and complexity do
boundary conditions emerge with hierarchy becoming immanent?
1. Introduction
To
say Biology is in “crisis” is, paradoxically, a complement. It is to state that
the discipline has progressed to the point where contradictions between its
putative founding principles, actual
practices, and results are apparent enough
to suggest salutary root-and-branch reform. This paper will issue such
categorical prescription in the area of Genomics. Much of the rest of what
follows is simply reflecting best practice in various subfields of biology.
Yet
that is a non-trivial task, particularly as biology becomes invaded by
researchers from other disciplines like statistics or, as in the case of the
present writer, computer science. A first stumbling-block is the nature of
causal explanation in biology. We refugees from the informational sciences tend
to think only in terms of Aristotle's “efficient cause”. Wiser heads have
pointed out that the final, teleological cause was necessary as an explanatory
gambit for explaining the role of the heart in the circulation of the blood;
similarly, the role of whole-properties associated with entities like the cell,
echoing Aristotle, has given rise for
about a half-century to the notion that organization might itself be a cause in
the matter.
Keller
(1995) famously explicated some of the metaphors underlying genomics, at a time
when the HGP was quickening its pace. While the intellectual fireworks
surrounding the argument about gene-as-Cartesian-homunculus were indeed
spectacular, their glare perhaps blinded us to the apparently more prosaic
speculations about the nature of the gene-as-computer-program. This is
particularly the case as “computation” has undergone a deconstruction at least
as significant as that of “cause”, particularly in the work of Brian Smith
(1996); see also O Nualláin (2007a). Echoing again the Aristotelian distinctions,
what underlies genomics is the notion of efficient computability; the purely
syntactic operations it assumes cannot yield phenotypes while maintaining their
formal purity as context-independent operations. Ó Nualláin (2004, p. 174)
summarises the situation as an essential tension between the formal
requirements of syntax and the real-world exigencies of intentionality,
reference in the real world, be that world a perceptual one, as cognitivism
would be concerned with, or the biological phenotype. Yet, as we shall see
below, that is just the beginning.
Elsewhere
(O Nualláin,2007d), this author specified the lacunae in current biology. The
failure of the cognitive, neural and social sciences to explain cognition and
consciousness; intelligent design/creationism versus “Darwinism”; the HGP and
its problems, wherein biochemistry examples can be given to show the critical
importance of metabolism (Strohman, 2003). On a more fundamental level, we have
the observer paradox in biology, whereby
reductionism results in losing life itself in a mass of physicochemical detail.
The “Where is the program?” theme addresses itself to the massively complex
interactions of hox, epigenetic factors,
types of rns called sirna and microrna, both of which modulate gene expression,
and so on . All these have consequences for the university-industrial complex,
and how to rectify matters there in terms of faculty hires and other
strategies.
Wrt
health and ageing there is ongoing work
by Bortz (2005), Veech and others (2003)
on metabolism (particularly as it interacts with diabetes 2, a new epidemic
based on insulin resistance) and health. In both his academic and more popular work, Bortz
(forthcoming) argues that the attempt to find a “silver bullet” drug for
diabetes 2 by targeting the biochemical networks involved in getting glucose
into the cell is misguided; insulin itself is unnecessary if the organisms's
metabolism is, aided by exercise,
functioning as it should. Of course, there now is evidence that exercise
prompts neurogenesis, thus alleviating depression.
In
cancer research, there is an ongoing tension between oncogene (the notion that
cancer is due to gene mutations) and
aneuploid (the notion that cancer is due to gross abnormailities at the
chromosomal level) stories, perhaps soon to be resolved by the examination of
carcinogenesis in the very aneuploid sufferers of “Gulf war disease”. The
metaphysical ground specified as above, it should be stated that the purpose here is avoiding methodological blind alleys, and orienting toward appropriate sciences and technologies
of medicine and agriculture. Too often
has the discussion ended here with an invocation of chaoplexity concerns, and
deep regret about the direction of biological research. The path here is to be
different.
We
are also concerned with bioethics, and the difficult issue of how precisely to
think about our ecosystem in order to preserve it. According to Eliot Sober (Ó
Nualláin, 2004, 143-149), there can be no bioethics simpliciter, no derivation
of “ought” from “is”; rather, in the
manner of Peter Singer (ibid.) with preference utilitarianism, one approaches
the phenomena from traditional moral standpoints. Obviously, we need a
bioethics and indeed a green politics. This writer believes that we will not be
able to prescribe any lifestyle and political organisation in our lifetime from
a science recognisably continuous with that of tradition. There are massive
consequences of this, including a privileged position for freedom of conscience
that precedes any scientific fact in the future. So this is also a
counterargument to eliminative materialism; the political will forever precede
the “scientific”
Pace
titles like “From molecules to metaphor” (Feldman, 2006), let alone the strange political momenta
seen therein in the abandonment in 2998
of the George Lakoff Rockridge institution, we are highly unlikely
to have descriptions of mind in our
lifetimes of sufficient cogency for
political prescriptions. However, Green parties can exploit the formal
limits that ecology sets on market
capitalism to propose more just and
sustainable societies.This will take a larger role in our concluding
discussion.
It
will be taken as given that the entire apparatus of that heterogeneous body of
theory and disparate findings we label, variously, as “chaoplexity”, “dynamical
systems”, “emergence”, and so on and discussed below applies to biological
systems as it does to the realm dealt with in physics. Biology has many better
claims for special treatment. First of all, there indeed are codes in biology,
and the nascent science of biosemiotics is well-begotten. Secondly, while phase
transitions of course exist in the non-biological world, it does seems
the case that both they and phase boundaries are interrelated in biology with a
fundamental notion of hierarchy. Thirdly, the nature of life does seem to
invite a biological uncertainty principle, whereby the very existence of investigative
devices at the nano level and smaller might require us eventually to specify at
what scale the investigation is purely physics, rather than biology. This, of
course, requires us to give an account, however tentative, of what life itself
is.
This
is an enormously ambitious project for a short paper. Luckily, Keller (ibid),
Strohman (1993, 2003) and many others have covered the scholarly part of the
project brilliantly. What this paper will focus on are four themes; first of all, computation and
its reference to epigenetic explanation; secondly, evolution, metabolism and
thermodynamics; thirdly, symbols, recursion and phenotypes; fourthly, boundary
conditions, emergence, and the putative biological uncertainty principle. Then,
having depicted a specifically social realm discontinuous from the biological,
we go on to examine consequences in terms of worldview and possible ethical
echoes.
2. Epigenetics and computation
Deoxyribonucleic
acid (DNA) is a polymer of four
molecular compounds with subunits called
nucleotides, each of which has a base, a
sugar, and one to three phosphates. It is
read 3 bases at a time, and an amino acid is specified through a complicated process involving RNA. Amino acids, in turn, are bound together by peptide bonds to form proteins.
Gene expression is the transfer of biological information from the gene
to the protein; an rna copy of the gene in mrna is made by a polymerase; the
mrna binds to the ribosome; and there the proteins are constructed from amino
acids. Three bases specify an amino acid. Each sequence of three nucleotides in
dna is called a codon. These code for proteins, which are assembled on the
ribosome. Regulatory genes control the operation of other genes.
A
gene's most common allele, or variant, is called the “wild” allele.
Transcription factors initiate the transcription of genes and are themselves
regulatory proteins Retroviruses perform reverse transcription into dna. This
seems a priori a counterexample to
Crick's deliberately portentous “central dogma” that dna generates rna
generates proteins.
Similarly,
the Beadle/Tatum dogma (1941) of one
gene, one protein/enzyme was found utterly impracticable; there must be a generative approach like
that for modern linguistics which we explore below. Molecular biology is
ultimately a synthesis of informational (including Gamow-like cryptographic)
and biochemical (“wet lab”) approaches. It attempts to use the processes of
physics and chemistry in genetics. It has been in many ways spectacularly
successful; yet, even after the HGP, we have straightforward monogenetic correlates
of only 2% of diseases. The analogy with Machine translation by computer, where brute-force methods are
currently being touted by researchers, after 50 years of other methods, seems
apt.
In
Paris in the early 1960's, Jacob (et al,
1962), Monod, and their colleagues produced evidence for genes that work at a
meta-level, by turning other genes on and off. In particular, genes can
initiate the activity of sets of other such in particular metabolic
environments. In the 1970's the work of Roberts, Sharp, and others indicates
that much dna is “silent”, and a consequence is that “alternative splicing”, a
phenomenon like prepositional phrase attachment in natural language processing
, occurs with genes (O Nualláin, 2007b).
At that time Watson (1977)
hastened to insist that it is possible that a number of proteins could
be generated from single “genes” (ibid.). This cautionary lesson was lost in
the hype about the HGP.
Since
the advent of multi-cellular organisms 600 million years ago, master genes have
had to determine what type of expression would take place in different
contexts. They in turn are governed by ?gSpindles?h in the chromatin. The chromatin is a set of
specialised molecules that protect and control DNA. In embryonic cells,
therefore, the master regulatory genes are simultaneously repressed and readied
for action through marks on the ?gspindles?h in the chromatin. The developmental programs
directing a cell to specialise into, for example, a neuron or liver cell, are
initiated by these master regulatory genes. These genes produce proteins called
transcription factors that bind to special sites on the dna and control the
activity of lower-level target genes.
Of
course, the issue of what regulates the master genes comes to mind. The answer
seems to be related to the spools of protein called histones around which the
DNA strand is looped 1.5 times. This hierarchical form is common to language
and music. These spools can make the DNA accessible to transcription or not, as
the occasion demands. For example, a complex known as the polycomb tags the
spools at a site called K27, which signals another set of proteins to make the
dna inaccessible Conversely, spools tagged on K4 allow the cell to activate the
local genes
Histone
proteins and the nucleosomes they form with dna are the fundamental building
blocks of chromatin. We are obviously referring to nucleated organisms. Histone
modifications may affect chromatin structure. Barbieri (1998, 2002)
hypothesises that a histone ?glanguage?h
may be present that is read by proteins
A
recent article (2006) by Bernstein, Lander , et al, in ?gCell' looked in detail at
the chromatin at the points where the master regulatory genes were themselves
in turn being regulated. They found that the chromatin contained both types of
tags, as if the genes were being simultaneously readied for action and
silenced. This makes sense, as most master regulatory genes will be
unnecessary, but one will eventually be required. Likewise, mature cells have
resolved into carrying just one or more of the K4 tags. So the ?gBivalent?h state in embryonic cells
is keeping them poised to go in a number of different directions. This has been
established for mouse, human, and dog cells. The specifics of control seem to
involve a network of oct4, sox2, and nanog, known to be associated with the
embryonic state
The
chromatin may give us our first non-human code not specifically related to the
genetic code, which links dna and amino acids. We will see several more such
below.
Epigenetics
is simultaneously in danger of becoming a catch-all term, and finding itself
chained in perpetuo to single lab observations like
methylated cytosine DNA markings
or acetylated histone markings. For
once, Scylla and Charybdis truly beckon. The sea-monster has been thrown up
with the idea that there exists another logical level of genetic explanation,
that of the epigenome, and that the epigenome manifests itself as the genome.
So the HGP – or, more correctly, the HEP - should be done again, but with a
broader jurisdiction and terms of reference. The contrasting danger is that of
identifying epigenetics solely with one observed phenomenon, be that related to
stress reaction or obesity.
Hidden
in the discussion of epigenetics is the issue of where is the program for the
phenotype. The answer from the boosters of the HGP was the disingenuous “in the
genes”. The reply from researchers like Atlan, Koppel, and Nijhout (Keller, op.
cit., 28-29) was vociferous; the DNA may be merely a data structure within the
overall computational architecture of the cell. In fact, inheritance may best
be regarded as an epigenetic phenomenon in their scenario. It behooves us to
unpick this latter lock first.
Conrad
Waddington (1966) was concerned, at least at one stage in his varied career,
with outlining a scenario in which effectively inheritance of acquired characteristics could be squared
with adherence to the “Central dogma” of molecular biology that dna makes rna
makes proteins make the phenotype, rather like the more famous Baldwin effect. His specific mechanisms of epigenetic assimilation and
canalization of development are of less interest to us here than the notion of
the epigenetic landscape itself.
The
above is the famous depiction of the “epigenetic landscape” and is currently
being more narrowly interpreted in terms of cell fate wrt organs, where the
ball “fell” into one or other chreod, or groove. In fact, Waddington's concept
affords a perspective in which organism and environment can coherently be
considered as a single unit over time (Maynard Smith, 1958, 1993). This
conceptual breakthrough admits of the possibility of a converse to “epigenetic
assimilation”, the process by which useful characteristics are incorporated in
to the genome; that is, “environmental assimilation”, a process whereby the
genome allows mechanisms to be inherited through the environment. The grooves,
and indeed the whole landscape, can
themselves change shape. It is likely indeed , given his later posthumous book
on chaoplexity, that Waddington (1977) would be sympathetic to an idea that saw
discontinuities arise in evolution as a result, for examples, of catastrophes
as one fold in the landscape touched another.
An
example of “environmental assimilation”
might perhaps be the Galapagos finch species scandens and fortis (Grant et al,
2006). The single species demarker is the song; yet this is learned from the
father, and has no genetic component. Evolutionary biologists will recognize
the sympatric/allopatric sequence. Similarly, monarch butterflies manage a
multi-generational migration which seems to depend on the disposition of
milkweed over an an enormous geographical space over eons. If the environment is stable, it may be more
computationally efficient to allow it rather than the genome to hold the
necessary information. Indeed, we might find the organism and its environment
perpetually together at the edge of chaos (Kauffmann, 2000), as we discuss in
the next section.
What
of computation? Here we might learn much from the programming language Lisp,
based as it is on lambda calculus with all the connotations that has for the
essence of computation itself; lambda calculus is a formally equivalent
alternative to the turing machine. The general format of Lisp is
(function
arguments); thus (+ 3 4) will return 7.
(Please note that the parenthesising form is ubiquitous in Lisp, leading
to the derogatory nickname “Lots Of Irritating Silly Parentheses”)Each form
gets handed over to an interpreter called “Eval” which evaluates it. (The
addition of a compiler would strain the
analogy beyond breaking-point). We may, however, wish to prevent this
evaluation and can do so by prefacing the structure with a quote; '(+ 3 4) will simply return (+ 3 4). This is
useful if we are dealing with text. We
can write procedures if, for example, we wish repeatedly to add 3 and 4 by
using defun;
(Defun
add34 ()
(+
3 4))
We
can invoke it as follows; (add34) which will simply return 7. And so we have a
correlate to the mapping from sequences of nucelotides to specific amino acids.
Let's call this level 1 computation.
In
common with most programming languages, Lisp allows creation of more complex
functions. These may be triggered by preconditions which we symbolise by
“cond”; in general, the syntax is
(Cond
(critical condition) (Action if critical condition is met)
(T
(Action if critical condition is not met).
Using
this schema, we can engage with the
Jacob/Monod apparatus of operators and operons. So we wish beta-galactoidase to
be made if lactose is present; otherwise, we wish nothing to be done (with a
report 'null)
(defun
lactose ()
(Cond
((sugar (setq beta-galactoidase 't)
(t
'null)))))
At
any point, then, we can all the function lactose to probe the environment to
see if a particular type of transcription should start. Let us call this level
two.
So
far, then, we have automatic generation of amino acids and conditional
initiation of transcription. The many brilliant minds behind Lisp, however, did
not leave matters there. While functions can easily be written, it may be the
case that we want them to be applied to one static piece of text and a variable
to be instantiated with a value that depends on the context. A technical
apparatus called defmacro allows this; briefly, the symbol ` requires that the
text be left inviolate while ~ (or in “Common”
Lisp dialect ,) requires instantiation. Now we have ways of nuancing
evaluation whereby the same list can be data, a function, and partially or
wholly evaluated as we wish. The point is that if we are to make use of the
computational analogy in DNA transcription, it helps if it is a more
sophisticated one that allows the same stretch of dna to be a transcription
unit, ignored, or part of an encompassing task.
It
is fair to say that we can encompass even the more radical suggestions of
Nijhout with a conception of the genome as now program, now data structure, now
a mixture of both; now catering only to context-dependent concerns, and now
working at a level of great abstraction. The ultimate controller is not to be
found in any Cartesian homunculus, Maxwellian demon, or Schroedingerian deity,
to cite three of Keller's (ibid) metaphors; rather, it is ordering principles
immanent in the relation of organism, species and population in situ over time.
This
writer predicts that it will take many of the greatest minds of the
twenty-first century much of its span to untangle the chain of control
involving the polycomb, operators, promoters, micrornas, sirnas, and so on wrt
the environment. (In the meantime, the
straw man of Darwin,
innocent of genetics, will confront that of YHWH, innocent of the whole of
modern science, and great will be the din.) Issues of control of gene
expression must be confronted in an evolutionary context; it may be the case,
for example, that sirnas prevent too much change to an evolutionarily stable
phenotype by one-off expression anomalies.
So
far, we have a computational metaphor for automatic and conditional
transcription. The latter can handle immune reaction, changes due to metabolic
factors, and so on. It is obviously of much greater interest to try develop an
analogy for generation of an entire
organism. We know (O Nualláin, 2007a) that Hox genes work at two levels, at
least. At the first level, genetic switches belonging to Hox itself specifies
expression in different longitudinal segments of the body; at another,
recognition by hox proteins varies gene expression. These are discussed in
greater detail in section 5. We need to be able to handle factors at a greater
level of abstraction using the technical apparatus supplied by macros. In
particular, we should have a generic macro that can specify how a generic body
part is made, and have this be instantiated into legs, arms, and so on which
then have functions to generate them. Lisp allows all of this;
(defmacro
make-body-part (part)
`
(defun ,part ,specification-of-part))
So
we can then set up the details for variable called “arm” which comprise the
information that Hox uses and then (make-body-part arm) will require that a
function be generated called “arm” that, in self-referential fashion, works on
its own definition of itself qua data structure..
I
wish to emphasise that all of the above is metaphorical; the cell is not a lisp
interpreter, and the functions, macros, etc do not provide anything like the
requisite complexity needed. However, Lisp is a much better computational tool
for thought than the various concepts Keller (1995) so ably exposes as the core
of late twentieth century thinking about the gene and then, equally ably, deconstructs; Maxwell's demon, Descartes's
homunculus, and so on.
In
this section, then, we looked at some basic mechanisms of gene expression, and
attempted to consider the computational environment in which such expression
occurs. Waddington's notion of the “epigenetic landscape” was returned to the
larger context in which it was devised; that of the co-evolution of organism
and environment over time.
3. Evolution, metabolism and
thermodynamics
Strohman
(2003) stressed several issues about thermodynamics and biology. First of all,
no gene expression can operate as a deus ex machina; it must conform to the
laws of thermodynamics and kinetics. Indeed, the theory of evolution must need
be incomplete without continual reference to such laws. Conversely, the
organism can handle great genetic insult if the ancient biochemical pathways
maintain their integrity. He lauds the emphasis by physician-researchers like
Walter Bortz(2005) on metabolism in maintaining health.
Remarkably,
the argument about metabolism can be extended to consideration of the origin of
life itself. (This is distinct from the
set of arguments about one versus two membranes ab initio; see Cavalier-Smith, 2006 )It is perhaps clear that the
chicken/egg quandary concerning the fact that replication requires a critical
number of nucleotide replicants which cannot get together without replication
already being in place is unresolvable from first principles. While Shapiro
(2007) successfully compiles a list of arguments against dna-first and rna-first
theories, Orgel's (2008) posthumous rebuttal argues that the perceived
inadequacy of these theories is insufficient to motivate adoption of
metabolism-first. In particular, he
stresses the current paucity of non-enzymatic thermodynamically stable chemical
pathways that are thus demonstrably abiotic; yet he leaves the door open that
some such may be discovered.
In
his Dublin
exile (for immersion in what he called “this remote and beautiful island” he and his wife regularly,
if quietly, thanked the Fuehrer)
Schroedinger chanced on the notion of negentropy as a defining factor of life.
While Keller (1995, 66-78) is rightly keen to invoke Maxwell's demon in her
exegesis of Schroedinger, we now have a superior vocabulary of dissipative
systems, and chaoplexity has gifted us, inter alia, with the realisation that
even abiotic systems like hurricanes can exist, negentropically, far from
thermodynamic equilibrium.
Several
other ordering principles are carried over from the physical realm. It will
never do simply to invoke the deity to explain life, or even gratuitously in a
scientific context a la Schroedinger.
However, it is as well to say that life could not have emerged without the
masses of the electron and proton at about 1836 (Barrow, 2002, P. 166).
Likewise, immanent ordering laws are present not just in Feigenbaum's constant
in chaoplexity, wherein the ratio between orbits at that rate seems to herald
the onset of behaviour driven by a strange attractor, but also in the simple
fact that a log scale of mass plotted against size in animals gives a nearly
straight line (Barrow, 2002, P. 47). Similarly, the fine structure constant
might be tweaked slightly without many
adverse result, but make it much bigger and there can be no atoms (op. Cit. 141-2). Finally, reduce nuclear forces
slightly and there can be no biochemistry (ibid.). The number of photons per
proton, the ratio of dark versus luminous matter, the specifics of the
expansion of the universe all bear similar witness (op cit. 182)
The
coincidences that proponents of the anthropic principle rely on continue
further. Fred Hoyle, the major opponent of the theory he derisively labelled
“big bang”, theorised and then
established that carbon exists only because the production of oxygen is
non-resonant (op. Cit 153-154).
Likewise, Kauffmann (2000, 157) cites theory from Horowitz that the
biosphere is at an energy per unit volume that permits the maximum expansion of
molecular diversity.
Shapiro (ibid) stresses the critical importance for metabolism-first
models of the prior existence of the following components; a boundary
(ie a primitive membrane), an energy source, a linking
mechanism(so that energy can be used),
and a chemical network . He adds that the network must grow and
reproduce and will at some point welcome a replicator., thus allowing death by
“wearing out” to enter nature. At this
point, we can perhaps dare to call the result “life”, while remaining attentive
to Orgel's caveats.
We should perhaps investigate the use of concepts from
complexity and dynamical systems theory in general. Obviously, many of these
terms are an expression of skepticism about the current state of our knowledge,
epitomised by the word “chaos” itself. In a
dynamical system, a fixed rule describes the time dependence of a point
in geometrical space. “Emergence” refers to complex pattern formation from
simple rules. A complex system is one with emergent properties. Chaotic motion
is bounded, sensitive to initial conditions, and has dense periodic orbits. We
can talk of basins of attraction like those that the brain settles into;
Fixed point ; dampened pendulum
Limit cycle; heartbeat when resting
Strange attractor; has non-integer dimensions and its
dynamics are chaotic
Kauffmann
(ibid.)argues that nature always drives the nexus of organism and environment
over time to the “edge of chaos”, maximum creativity. His is one of the most
serious recent attempts to create new foundations for biology continuous with
physics and chemistry, yet honouring the incredible complexity of life
Kauffmann states that life emerges from complex chemical
reactions. He then introduces the notion of “ autonomous agents” that can
replicate and do one work cycle, normally far from thermodynamic equilibrium.
They will be crucial, and he regards them as a new ontology of processes and
events. He argues that there is a current crisis of explanation; an explanatory
circle involving work, constraints, measurements, energy records, processes,
events and - particularly –
organization. We have adequate accounts of matter, energy, entropy, and
information. Kauffmann. is strongest when he draws consequences from
chaoplexity.
In similar vein to his invocation of Horowitz above, who argues that the biosphere
is at an energy per unit volume that permits the maximum expansion of molecular
diversity, he argues that networks in cells exist near a phase transition
between order and chaos. So the number of attractor states in the cell is the
root of the number of genes (about 158) and the cell can cycle around all these
states in a couple of days. He argues in this context that communities of
molecular autonomous agents may evolve to
apparently discrete phase transitions
like going to the edge of
chaos or a self-organized criticality.
The ordered and chaotic regimes and phase transitions between them are
characteristic of a class of non-linear parallel dynamical systems.
Ecology
is a fortiori a happy hunting-ground for proponents of emergentism (Williams et
al, 2000) and indeed power laws (Williams et al, 2001) wherein linearity is
left behind as a template for species distribution.There are many competing
paradigms in ecology, which will have the above apparatus of chaoplexity
repeatedly used on it.. For example, metabolic theory relates metabolism to
body mass and temperature and derives useful items like speciation. At a higher
logical level, spatial macroecology looks at how patterns in the distribution
and abundance of species vary across spatial scales. Thermodynamic considerations
include the fact that things never self-organise in a closed system Entropy
production is maximised in irreversible
processes; from this fact, as some argue, the other phenomena like species area
laws fall out naturally. For example, is the greenness of earth maximising
dissipative heat flow?
In
this section, then, we have been careful to consider emergent ordering
principles throughout all of nature, particularly when these are of a
non-linear nature.
4. Symbols, recursion, and phenotypes
The
new field of bioemiotics stresses that with the advent of life comes also the
existence of codes that are by definition
not informationally dependent on the appearance of their carrier. The
strong biosemiotics position is that biology is above all about communication.
Codes include the genetic code; codes for apoptosis, or programmed cell death;
histone codes; and so on.Witzany ( O Nualláin2007c and d) specifies
code-editing as the essence of life, and a process that links us humans to the
biosphere as a whole.
Let
us first look at some of the basic tenets of biosemiotics (see Barbieri 1998,
2002, 2007). (Bios=life; semion=sign). Sebeok pointed out that signs used by
animals are processed in the same way as humans' signs; his term, zoosemiotics,
was later extended to plants as well and thus “biosemiotics”, coined by
Rothschild in 1962, became common currency. Much of the theoretical
infrastructure comes from Peirce who asserted there is a trio of sign, object
(meaning), and interpretant in any act of signification. Signs must signify
something; conversely, meanings require signs for their completion. A semiotic
system connects meanings and signs through a code; all three elements are
necessary. This contradicts Saussure, for whom a semiotic system was “sign and
meaning”
The
biosemiotics credo a la Barbieri is that organic coding requires signs,
meaning, and an adaptor. This is a variation on Peirce. The physicalist notion
is that “biological information” is a metaphor. This is denied by most
biosemioticians; they say, for example, that genes and proteins are artifacts,
made by molecular machines, and this artifactual property is the essence of
life. Thus, it refutes this physicalist idea
Genes
and proteins are molecular artifacts because they are created by molecular
machines. Life is “artifact-making”. Artifacts require entities like sequences
and codes to be characterised. Nevertheless, organic information and organic
meaning are not metaphors, but as real as any “natural' process. We call their
results “nominable' entities which require an ordered listing of their elements
for identification. Shannon's concept of
information, based on Boltzmann's equation about the relationship between
entropy, microstate, and macrostate, does not specify sequence subunits.
However, biological information does, and is thus a nominable entity. Organic
meaning mediates between molecules
Any
organic code links two independent worlds (e.g. Genes and proteins) by a third
world (e.g. Rna). “Sign, meaning, and adaptor” is pertinent rather than “sign,
meaning, and interpretant”.According to Barbieri, therein lies a crucial
distinction between objective and subjective. Early in the history of the
biosphere, chemical “bondmakers” got created; some of them acquired the ability
to join nucleotides together wrt a template, and are “copymakers”. As proteins
require mrna, trna, and the ribosome, they are more complex than copymakers.
There is no necessity in the relationships between dna and amino acids, or
between proteins and their eventual destination in the cell; we therefore can
speak of codes.
A
code is a set of rules that establishes correspondence between elements of two
independent worlds. Barbieri (2007) has repeatedly argued that trna, with two
spatially and informationally distinct loci that represent codons and amino
acids is the beginning of the emergence of an arbitrary code. Organic
information, it bears repetition is, according to biosemioticians, objective
and irreducible. There are a plethora of codes in nature including;
The
genetic code; the mapping from dna nucleotide sequences to amino acids
Signal
transduction codes in cells: Cells continually respond to their environment;
yet, the hundreds of possible “first” messages are transformed into
combinations of only 4 “second” messages
The
spliceosome features recognition of either end of scores of introns for each
“gene”. So we can talk about “splicing” codes
The
cytoskeleton is anchored to the cellular structure in an arbitrary fashion
There
also are sugar codes, apoptosis codes, and so on.
So
we can produce some summary statements as follows:The cell is a semiotic system
with genotype, phenotype, and ribotype. The basic processes in life are coding
and copying. The basic processes in evolution are natural selection and natural
convention. Semiosis is defined by “coding”, not interpretation. Signs and
meanings are codemaker-dependent. They are nominable, that is they can be
specified by naming their components in their natural order. Rna and proteins
also are codemaker-dependent. The translation
apparatus is a semiotic system.
In
classical semiosis; A (the interpretant) interprets B (the object) as
representing C (the “meaning”)
This
is called the “interpreter” model. The “codemaker” model has A (the adaptor,
like tRNA), operating on B (the “sign”, like the genes), to produce C (the
“meaning', like amino acids). (The scenario to be outlined below reserves
meaning for function in the environment). Since codes are arbitrary, learning
their application is context-dependent. Genes are made by copymakers, proteins
by codemakers
Several
variations on what biosemioticians do exist. For Sebeok, life and sign science
imply each other. Communication is exactly what distinguishes living from
nonliving. An organism is a device which communicates its structure to its
offspring. For Emmeche, it is a branch
of general semiotics, and its place in nature has yet to be determined. For
Hoffmeyer, unification of biology depends on emphasising the semiotics nature
of life. Sharov, largely in agreement, contends that it should be viewed both as biology and
semiotics, not as a branch of the latter. Pollack introduces how our
understanding of the genetic code, which burgeoned between the 1950's and
1970's, has unified the notion of text and organism. Pattee added the notion
that communication is the essential characteristic of life, and Hoffmeyer the
notion that the organism itself is a message. Uexkuell, following Piaget, wrote
about organisms as interpreters of their environment.
Pattee
(2001) is one of the chief theorists in the area. He argues that “semantic
closure” is the crux for autonomy of systems.
Thus, they reproduce themselves in the future and define their identity
through the process of self-reproduction. “Self” is a semiotic term, but is
handled well in immunological theory.
He
emphasises the epistemic cut, the separation of rate-independent symbols from
the rate-dependent dynamics they control. The converse is measurement, the
coding of dynamic processes into symbols.
For
him, there is a general issue about bridging the gap between the observer and
the observed, the controller and the controlled, the knower and the known, mind
and brain; the epistemic cut
In perhaps an excessive move, he argues that the
process of measurement in QM falls under the same rubric as biological
processes
Pattee
extends the epistemic cut to a variety of distinctions; observer and observed,
knower and known, genotype and phenotype.
So the answer to the question about the distinction between living and
nonliving is complex. The “motion of inorganic corpuscles” is rejected; there
is no merely physical delimiter. There is an epistemic cut, with both
constraints and dynamics. In short, local and unique heteropolymer constraint
determined the origin of life.
The
perspective in this paper is that the biosemiotic position, as enunciated by
Barbieri, has merit wrt novelty in
evolution and the overall perspective afforded. In particular, the nexus of
histones, epigenesis, sirnas and metabolism described above can best be
approached using suitably sophisticated linguistics. Let us try and grapple
with this subject, using a generative approach.
We
should distinguish between Grammar, the totality of a person's linguistic
knowledge, and “grammar” (lower-case), which we'll restrict to syntax. A
grammar in the generative tradition is a set of re-write rules that generates
(ideally, all and only) the sentences of a
language (l). The vocabulary V = a,b,c....is the tokens forming the
elements of the l. A sentence S (e.g. bca) is a string of these tokens
L
is all sentences each of which is a string over V. We also have non-terminals
like NP and VP, etc, to complement the terminals a,b,c....
The
Chomsky hierarchy posits languages of different levels of formal complexity; we
can formulate general grammatical rules at each level. The top level, level
0, languages modelled by non recursively-enumerable sets
and the next level, level 1 recursively
enumerable such, are outside our scope here (O Nualláin (2007b, 253-254) . Type
2, context-sensitive grammars, have rules of the form S (Sentence, or protein
sequence) is rewritten as X if A precedes X and B follows it
S-X/AB
We
can also have Hox genes generating contexts or “fields” in this manner. Wrt our
language analogy,
“Sonic hedgehog” type genes allow
context-sensitive rules. Carroll (2005, 42) cites experimental work by Saunders
showing that transplantation of a chunk of tissue from a posterior to an
anterior part of developing chicken's wing-bud resulted in “fingers” being
developed in the reverse order to what they would have been. Thus if “a” and
“p: stand, respectively, for anterior and posterior contexts, we can write the
following rules; S- a/3,4
S-p/4,3
Hox
genes, then, allow for context-sensitive operations. It cannot be proven that
any randomly chosen level 2 language can be recognised in finite time;
likewise, computational problems at this level cannot have posited of them a
solution in finite time. These connections are reminiscent of the unexpected
connections between fractals and chaos; a priori, there is no reason to
anticipate this type of phenomenon. Daley et al (2003) provide further light on
this intriguing area. Natural languages in general seem susceptible to
formalisation by an indexed grammar, which caters to the context-sensitive
examples found by various linguists in
human language(O Nuallain, 2003, 101-128)
Phenomena
like alternative splicing (Ast, 2005) indicate that there is some degree of
ambiguity, and thus complexity in gene expression One hypothesis is that proteins are semantic
primitives, rather than “meaning”At the syntactic level, Bcl-x, which governs
cell death, can be alternatively spliced into Bcl-x (S), a promoter of
cell-death, and Bcl-x(L), a suppressor
thereof (O Nualláin (2007b, P. 251).
This is structural ambiguity; to be more specific, it is a problem of
prepositional phrase attachment, which needs access to the semantic or a deeper
level to be resolved. So “the man shot the girl
with the gun” leaves issues about his culpability. The nature of this layer has been approached
by Bentilola (2005) who stresses the fact that living organisms have immense,
dynamic memories; each act, reflects all previous acts.
Let
us introduce type 3 grammars with an
example; playing tennis and “plugging” one's opponent's backhand before playing
a cross court to the forehand. We do not want to generate bf; that is
over-generation, but all and only the winning rallies. We need at least two
backhands, so bbf, bbbf, bbbbf, etc are winning rallies. To write the grammar,
we need to introduce a non-terminal E (Upper-case for these). We can define E –
bf. We also write a recursive rule E – bE If we add S-bE, where S is a full
rally (or sentence)we now have the full grammar.
A
critical non-human code is the
starling's song, analysed by Tim Gentner et al (2006)., and found to conform to
a recursive grammar. It took 15,000 trials with differential reinforcement to
get this effect
Birds
were asked to pick out songs with inserted rattling or warbling phrases. 9 of
11 succeeded 90% of the time The same task was attempted, and failed by tamarin
monkeys used by Mark Hauser. He argues that the starlings do not have
semantics, even if the recursive phenomenon is correct
Type
4, regular grammars, look like keyword systems; this/that is/was alive/dead
which can generate just the sentences “this is alive”, “that was dead” and so
on. The HGP was implicitly based on type
4, or finite-state automaton, even at the HGP’s most enlightened moments. The
rest of the time, the HGP behaved as if the genome was similar to the parody of
language apparent in the pattern-matching programs of the 1960’s. Lisp programs
were programmed in these systems with preprogrammed scripts like “I have
problems with my x”, to which they would reply “Tell me more about x”. It is
likely that parsing the genome is infinitely more complex than this. O Nualláin
(2007b) explores this issue in detail
In
gene expression then, as in language, it
is suggested here that contexts, are idiosyncratic interactions between
linguistic and operational knowledge, which require knowing the precise
relationship between the words (the genes) and semantic formalism (the
metabolic context) in order for correct
processing to occur (in order to predict what proteins will be generated). It is likely indeed that all of this holds
for gene expression (O Nualláin 2007b)
Specifically,
context seems to deform the layers of language as it becomes restricted in much
the same way that gravity deforms space-time as one approaches the surface of a
planet. (ibid.). The HGP worked on the assumption that the context was always
going to be sufficiently restricted for
single words to work, and therein lies its failure. It is a valuable
lexicographic tool, and therein lies its success. However, we also need syntax,
semantics, discourse pragmatics, and enumeration of contexts if nl is anything
to go by. The HGP may be looked at alternatively as having elicited
context-independent semantic primitives, or discovering unambiguous
collocations, or as doing a lexicon. Time will tell which is the most fruitful
perspective.
We
must try and understand the metabolic
context for the particular cases that
Veech et al (for example, in their 2001 paper) examine or the “cytoplasmic
regulatory protein components” (Bentilola, 2005). Then comes issues of
“discourse structure”; how tasks like building and maintaining the integrity of
the organism act as high-level goals affecting the minutiae of protein
generation, which we outlined above
Wrt
gene expression research then, exemplified by the exaggerated claims being made
in HGP research, it looks like remaking
all the same mistakes made in AI. Indeed, the search for an “epigenome” where
all will be revealed corresponds precisely to the search for an interlingua in
machine translation, which was an almost complete failure (Ó Nualláin, 2003)
.Likewise, the attempt to introduce Bayesian nets between genotype and
phenotype resembles nothing so much as expert systems which have been revealed
to be either context-dependent or else of very little practical use
5. Boundary conditions, emergence, and a biological uncertainty principle
Following
Maynard smith, Barbieri (2007, P. 16) outlines a set of “major transitions”;
genes, proteins, first cells, eukaryotes, embryos, mind and language. There is
an emergentist ethos here that cannot be gainsaid. We can also discern a
hierarchy of natural law regimes from the level of the biosphere to that of
populations to single species to groups, individuals, organs and cells; and now
plasmon rulers, optical tweezers and so on allow investigation at scales
hitherto inconceivable. At the nanometer level, X-ray crystallography is
appropriate; above 200 nm, light-ray microscopy. It is possible that
characteristics of life itself will not emerge at these dimensions. As we
progress up the hierarchy from the genes to the biosphere, there are boundary
conditions at each level. For example, the genome can be considered as the set
of boundary conditions for the making of proteins.
For the moment, let's look at an intermediate
dimension, that studied by evolutionary developmental biology (evo-devo). Just
as CERN attempts to intuit aspects of
cosmogenesis by studying subatomic interactions, so evo-devo attempts to study
evolution by looking at laboratory incidents of gene expression. Hox genes,
which we've alluded to several times,
belong to the homeobox gene family, a gene sequence that determines how
the body develops from the first stages of embryogenesis. After the
anterior-posterior and dorsal-ventral axes of the body are established, hox
genes pattern the body into distinct segments, and within-segment patterns of
cell fate determination. Thus, hox genes determine where limbs and other body
segments grow during development. The homeobox is a 180-basepair sequence of
dna and the polypeptide domain it encodes is called the homeodoman, about 60
amino acids long. Homeobox genes encode transcription factors.
There
are four families of hox genes for different body areas in mice and all other
mammals as in fruit flies. The evolution of body form in both arthropods and
vertebrates has been achieved by shifting hox genes up and down the main axis.
"If the impossibility of formation of a complex organ through a series of
small changes was ever to be proven my theory would have certainly collapsed.
However I could not find such an organ..." (Darwin, 1964, page 189.) Along with alternative
splicing (short et al, 2008), hox provides a realm of plausibly non-small
changes.
We
have seen that Hox genes function with switches at two levels; one set belongs
to the hox genes themselves, and specify their expression in the different
segments of the animal, and the other involves recognition by hox proteins to
vary gene expression. The 1980's and 1990's saw the identification of Hox genes
in drosophila. For example, drosophila's front wings are large, flat, venated,
and powered for flight. The hind wings are balloon-shaped, smaller, and used
for balance The difference is due to a hox gene called Ultrabithorax (Ubx).
This is activated in the hind wing to ensure that venation does not occur. Ubx
switches off genes that encourage venation. Tool kits like these can be used
again and again.
In
fact, much recent evolution can be thought of in terms of the shifting of Hox
genes up and down the body axis. The bat's wing, horse's leg, whale's flipper
and human hand are homologously formed by homologous genes along homologous
developmental pathways. The pax-6 or eyeless gene regulates eye development
from our camera-type eyes to the fly's compound eyes. When the gene is
manipulated to turn it on in other parts of the fly, we get eye tissues in the
wings, legs, and so on. This also applies if the mouse eyeless gene is turned
on in the fly.
Returning
to Drosophila, bithorax mutations produced flies with an extra pair of wings.
Antennapdia mutation transformed antenna into legs. These confirmed that there
might be genes that controlled large-scale patterns of whole-body architecture,
including positional information on the body axis. A mutation in human hox d13
produces an extra finger. Homeosis describes modifications of the anatomical
themes and variations in body form. These genes have remained relatively
unchanged throughout evolutionary history, and the complex may have evolved
from a single ancestral hox gene.
In
flowers, we get the same theme of serially repeated structures arranged in a
systematic order, with repetition in linear-concentric symmetry rather than
linear-bilateral symmetry. The multifunctionality of tool kit genes provides
evidence for the notion of evolutionary descent from a few common ancestors. So
we find that the BCMP gene, expressed in different contexts, can govern
development of ribs, outer ear, and thyroid cartilage. Mc1r and agouti can both
cause melanism. Mc1r is known to cause melanism in a set of light and dark
pocket mice in Arizona.
475 miles away in New Mexico,
it is cause by an as yet unknown mechanism. Note what we have been saying; the
biological correlate to “meaning” in
language is not proteins generated, but function in the environment, and again
we emphasise context
While
the concept of the “biological uncertainty principle' has recently been misused
for “silent” DNA, it has a more venerable proponent;
“In
every experiment on living organisms there must remain an uncertainty as
regards the physical conditions to which they are subjected, and the idea
suggests itself that the minimum freedom we must allow the organism will be
just large enough to permit it, so as to say, to hide its secrets from us. On
this view, the very existence of life must in biology be.....(like the quantum
action) taken as a basic fact that cannot be derived from ordinary mechanical physics” (Bohr, 1933)
It
is possible that life needs an interlocked self-contained metabolic system
protected by some membrane that also includes the possibility of
self-replication and therefore some kind of, paradoxically vicarious, survival
after death. The resulting complex has emergent properties that several of the
tools available today are too tiny to detect; precisely Bohr's point.
Let
us leave this section with a brief foray into the ID/Darwin minefield. Fodor
(1975) successfully argued that all human knowledge must be innate on totally
logical grounds; a new concept is by definition discontinuous from the old (Ó
Nualláin, 2003 91-92). The Iders will continue to use this type of rhetorical
device successfully, particularly if their opponents insist on referring to Darwin, whose notion of
inheritance actually precluded evolution insofar as it was at all coherent.
Indeed, they will probably win arguments specifically about speciation, let
alone the major transitions referred to above. Evolution, with its multitude of
mechanisms including endosymbiosis and genetic drift, must be rescued from Darwin.
6. Mind and the
discontinuity of the social and biological
Witzany
(2006, 2007) has laudable goals in his Weltanschauung; they are to establish
the social as continuous with the biological, and inculcate a reverence for
life. The argument to be made in this short section is that this goal is
misguided. In the first place, it is a category error; the social is a different category to the biological. Ó
Nualláin (2003, 169) cites work by Dyer that testifies to the extremely
difficult path from biological process to symbolic behaviour. Yet that is still
within the realm of the biological; what is not is a notion of a norm.
This
author's work (Ó Nualláin, forthcoming)
attempts, inter alia, to provide a foundation in cognitive science for social
science concepts. It begins with the concept of selfhood, which is posited in
the writer's experimental work as being founded on data-compression in the
brain. In particular, our experience of selfhood qua identification derives
from exclusion of data regarded by the organism either as irrelevant or as
dangerous to its integrity. Our experience of ourselves as agents is largely a
fiction in that we narrate continually, ascribing to ourselves the origins of
actions that occurred automatically. However, there is a core of agency within
each of us, while manifest perhaps in a conscious “won't” rather than “will”.
The
social is a higher category to the cognitive, which refers to the processing of
information in the individual brain, and to the non-cognitive biological, yet
is rooted in both. Insofar as the individual can construe herself as being the
object of a norm or value, she is
immersed in the social. This can be mediated as intersubjective, and not
necessarily conscious, or fully conscious. Social pressures can be exerted on
the individual, with often devastating results. Some such are artifacts of
colonisation; yet that is getting ahead of the story.
The
expression of the social is primarily verbal, and that will be our first port
of call. It can be argued that all human institutions are created by speech
acts, whereby concepts previously abstract acquire rights and duties, and power
over the individual; deontic powers. The particular types of speech acts
involved are called performative utterances, which take the form “X institution
shall...”. And so it can be said, for example, that a certain limited company
shall exist within a certain legislative framework for a certain amount of
time, including for eternity.
Yet
the words alone will not unravel the web in which critical theory finds that
humans live. While it is perhaps
excessive to state that behind the structure of modernity lies the
mediaeval, there is undoubtedly ample room for projection, and indeed
scapegoating. The contemporary critic might indeed go further and point to the
access of torture and Christian crusade in the early years of the 21st century to suggest something altogether
darker. Admixed with freedom of conscience are themes a great deal lower in the
brain than the cortex.
Therefore,
the social realm can be expressed as laws, norms and values; it is a mark of
legislative failure that biological concerns intervene to destabilise a regime.
It is a symptom of maladaptation, whether cause by himself or the society, that an individual should have to focus on
the facts of his biological being, rather than objective conditions, in order to resolve a personal crisis.
Finally,
one can consistently follow Barbieri (2007) who, perhaps by oversight, omitted
consciousness from the major transitions. It can consistently be argued that
consciousness existed eternally, and that what is happening in the case of our
individual experience is that the intentional structure of the mind is “bathed”
by consciousness. This allows us to
create the largely fictitious selves that we have through narration to
ourselves; yet such narrations are the personal correlate of those inevitable
forces that we call “social”
7. The foundations of
biology and consequences
Let
us now recapitulate with some summary points. 21st century biology will possibly be as
consequential to its century as physics was to its predecessor:
1. Darwin must be sacrificed for the
sake of the stupendous theory of evolution which is emerging, which draws its
evidence from the subatomic as from Hox genes.
2. Some kind of anthropic principle will always be
invokable to explain the origin of life, of multicellularity and all the other
major transitions as it is for apparent coincidences like the value of the fine
structure constant
3. Recursive symbolic function is a fact of nature.
4. There does exist a biological uncertainty principle
at a scale much larger than the physical one
5. Some aspects of the emergence of novelty will remain
forever mysterious
6. A new, more elaborate version of computation must be
used for cellular function
7. In a post-dissipative systems world, it is helpful
to define life also in terms of replication after death.
The
interaction between metabolism and symbol-processing that is present at all
levels of life that makes biology so difficult, has enormous consequences. Gene-expression is subservient to ancient
metabolic pathways; GMOs may indeed be filtered out by pure thermodynamics (but
not before they have done much damage). Agriculture undoubtedly needs to focus
more on the integrity of the ecosystems that it undoubtedly disrupts. In
medicine, while prevention, including exercise, is undoubtedly currently more
efficient than cure, the advent of “prospective medicine”, which predicts
illnesses 50 years away, suggests a different argument. While an emphasis on
metabolism, with its integrity undamaged by insult to the phenotype is correct,
a return to socialized medicine a la Europe
will work even better. Corporate medicine will always find a way to exploit the
individual.
So
we end with the political infringing on the biological. In this context, it is
worth saying that even a cursory look reveals a stupendous epic of evolution
resulting in our current state. It is indeed just a story; yet so also the rest
our knowledge is subject to the restrictions of these evolved brains. It is as
ridiculous to impose metaphysical censorship on ourselves as we, with awe,
contemplate our origins as it is to accept as Gospel – well, the Bible. It is possible to develop a politics based on
the integrity of ecosystems as long as it is realised that our capacity for
symbol use, and our very selves are also part of nature. To assert a “green”
politics is also to assert the finest heights of human culture, and its
extraordinary perennial search for the absolute grounds of its own existence.
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