Theoretical Molecular Biology

What is life?

Koichi Itoh M.D.,Ph.D.

The Institute for Theoretical Molecular Biology

21-13, Rokurokuso-cho, Ashiya, Hyogo, JAPAN 659-0011

http://www.i-tmb.com/

e-mail: itoh@i-tmb.com


Table of contents

Preface

Chapter 1. What is Molecular Biology?

Chapter 2. What is theoretical molecular biology?

Chapter 3. Theoretical analysis indicates human genome

is not a blueprint and human oocytes have the instructions.

Chapter 4. Theoretical analysis indicates ‘the principle of
fluctuations’ fundamentally control life phenomena.

Chapter 5. The future images of medicine.

Chapter 6. What is life?


Preface

　This book is an introductory textbook and philosophy book. I think that
academic fields need philosophy. Around 1900, physicists discussed about
the quantum theory and physics divided into experimental physics and
theoretical physics. In the case of biology, especially molecular biology,
each scientist has been played a role as an experimental biologist and
theoretical biologist for about 60 years. One of the reasons, I think, is that
fundamental principles have not been discovered. However, scientists who
have the techniques and the knowledge of molecular biology have been
produced enormous data and those data are stored in official databases. I
think that the time is coming to build up the new academic field to analyze
those enormous data. The storage of data will continue. That is why I have
been waiting the timing to build up the new academic filed as theoretical
molecular biology. There exists theoretical biology, but the new academic
field of theoretical molecular biology has not been existed. I venture to
build up theoretical molecular biology, because materials are made of
molecules and living bodies are also made of molecules. In addition, I am a
molecular biologist and medical doctor. Hence, my theoretical molecular
biology is for health of human beings and medicine. Firstly, what
theoretical molecular biologists must do is to decide propositions or
hypotheses. If these propositions or hypotheses are not correct, it must be
impossible to get logical theories. Hence, theoretical molecular biologists
must pay careful attention to decide the propositions or the hypotheses
which really have the solutions. If propositions or hypotheses do not have
the solutions, theoretical molecular biologists will not be able to get the
solutions from the survey of enormous databases. Therefore, theoretical
molecular biologists rely on what they have been experienced and
meditated. In other words, theoretical molecular biologist must have their
own perspectives on nature. Theoretical scientists should concentrate and
think logically to give the solutions to the propositions which they judge to
be able to solve, in terms of their own perspectives on nature. What
theoretical molecular biologists should do is to search for the fundamental
principles which control life phenomena, and logically to prove them.
There are two great books which are .Molecular Biology of the Cell and
.Molecular Biology of the Gene. as the bibles for molecular biologists.
However, textbooks are constructed from figures and tables and
explanation of those. Hence, the most part of the textbooks explain results
which were investigated by the past experiments, and short comments or
discussions are written about unknown things. The theoretical molecular
biologists must meditate and think about already known things, things
which are thought to be matters of course and unknown things, and once
again try to elucidate the fundamental principles of life phenomena. The
theoretical molecular biologists must prove the fundamental principles
which control life phenomena to the utmost. To do these things, it is
necessary to be familiar with other academic fields such as mathematics,
physics, and chemistry in addition to molecular biology. This book is
constructed from chapter 1. What is molecular biology? chapter 2. What is
theoretical molecular biology? chapter 3. Is Genome the blueprint of life?
chapter 4. The principle of .fluctuations. fundamentally control life
phenomena, chapter 5. Images of future medicine. Chapter 6. What is life?
I wrote this book compactly to be able to read it from cover to cover. I was
strongly impressed by Watson-Click’s double helix. I came to have a dream
to determine human genome sequences and to cure every disease to correct
incorrect sequence to correct sequence and to get the Nobel Prize in
Physiology or Medicine. I was born in 30th September 1964. I graduated
Osaka University Medical School and Osaka University Graduate School
of Medicine. After graduation, I studied in Howard Hughes Medical
Institute, Harvard Medical School. After coming back to Japan, I have been
thinking about founding a new academic field as theoretical molecular
biology. The concept is 1) to meditate and determine propositions or
hypotheses, 2) to prove logically those propositions or hypotheses without
doing experiments, 3) to get the solutions.

Chapter 1. What is Molecular Biology?

　Before 1953, researches about molecules in living bodies had been doing,
but Watson-Click’s double helix hypothesis in 1953 was the beginning of
molecular biology. Molecular biology was different from mathematics or
physics which were described by mathematical formulas. This must be
profoundly recognized as special characteristics in molecular biology.
There was the fundamental thought that molecular biologists elucidated life
phenomena to investigate action and function of molecules. Therefore,
materials of researches were mainly bacteria, yeasts, worms and mice as
models for researches. However, final aim of we life scientists and medical
scientists must be elucidations of the fundamental principles of life
phenomena in human beings. The missions for life scientists and medical
scientists must contribute for the health of human beings. Richard Feynman
who is the Nobel Prize winner in Physics said that if, in some cataclysm, all
of scientific knowledge were to be destroyed, and only one sentence passed
on to the next generations of creatures, he believe it is the atomic
hypothesis that all things are made of atoms. Molecular biology is also the
academic field to investigate the action and the function of molecules in
living bodies. The aim of molecular biology is to elucidate the fundamental
principles in life phenomena. Molecular biology has been enormously
contributing life science. Taking a long look at the indexes of .Molecular
Biology of the Cell. and .Molecular Biology of the Gene., the progress of
molecular biology is easily recognized in these 60 years. The mechanism of
duplication of DNA, the sequences of genomes in many living bodies, the
mechanism of gene expression, apoptosis, polymerase chain reaction, three
dimensional structures of proteins, RNA interference, expression profiles
from microarrays. These discoveries and inventions have been enormously
contributing to life science and medicine. I think that the time is coming to
elucidate fundamental principles in life science and medicine utilizing
enormous data which were stored by experiments without doing
experiments. Molecular biology must be divided into experimental
molecular biology and theoretical molecular biology.


Chapter 2. What is theoretical molecular biology?

　I define theoretical molecular biology as the molecular biology getting
solutions to prove logically propositions which are significant in medicine
without doing experiments. Firstly, the most important step is to meditate
and determine appropriate propositions. If appropriate propositions were
not determined, it is impossible to get solutions. Therefore, the most
important step is to meditate and determine propositions which really have
solutions. If the propositions were fundamental and significant in life
science and medicine, it is possible to contribute to health of human beings.
Theoretical molecular biologists must get solutions to prove them,
meditating and thinking logically without doing any experiments. The data
are already stored in National Center for Biotechnology Information
(NCBI: http://www.ncbi.nlm.nih.gov/) and other official databases. These
data are the precious property which many life scientists and medical
scientists have been making efforts to investigate life phenomena. The
databases in NCBI and other official databases have been improved to easy
to be used and surveyed. From now on, user interface may be improved and
data may be piled up. After determine propositions, theoretical molecular
biologists must meditate, think and analyze logically and profoundly data
to get solutions using and surveying any materials such as databases, past
experimental results, textbooks without doing experiments. Any materials
are fine. This is theoretical molecular biology. There are many exceptions
in biology different from mathematics and physics. Is it possible to describe
life phenomena with mathematical formulas? In my opinion, it is
impossible to describe life phenomena with mathematical formulas even if
the analyzing ability in computers were improved and even if a lot of data
were stored in the future. That is why living bodies are not machines. If
machines go out of order, is it possible to repair them by themselves? Is it
possible to describe human minds and emotions as mathematical formulas?
Is it possible that machines accomplish evolution automatically? For these
propositions, solutions are NO right now. Hence, the present aims of
theoretical molecular biology are get solutions to propositions logically, not
to try to describe life phenomena by mathematical formulas. Because it is
unknown which life phenomena will be able to be described by
mathematical formulas? Therefore, for the proposition which life
phenomena are described by mathematical formulas, the solution is NO
right now. Scientists must not have illusions. Scientists must meditate,
think and analyze propositions realistically. Hence, the aims of theoretical
molecular biology are to give the solutions to propositions by logical
thinking for the fundamental principles of life phenomena, not to make
mathematical formulas.


Chapter 3. Theoretical analysis indicates human genome is not a
blueprint and human oocytes have the instructions.

Abstract

　Is Human Genome really a blueprint? If it is not a blueprint, how are
human bodies constructed? This paper solves this hypothetical proposition.
Firstly, I indicate 8 examples of important biological pathways and factors
among house-keeping genes and proved that human genome is not a
blueprint. Human Genome is storage of genes. Secondly, I proved that
human oocytes have the instructions for development and differentiation. In
this case, I used opened public database for expression profile of human
oocytes. I selected 12700 genes which expressed in human oocytes. Among
12700 genes, more than 800 genes which are related to development and
differentiation are expressed. Here I show that human genome is not a
blueprint and human oocytes have the instructions.

Introduction

　Human genome has been thought to be a blueprint, but what type of the
blueprint has been a mystery. Human genome project was over in 2003, and
seven years are already passed, but the number of human genes still
unknown. Analysis of human genomes has been continuously done, but the
discussion which a human genome is a blueprint has not been done. Far
from that, any traces of a blueprint are not found in human genomes. This
may be evidence that a human genome is not a blueprint. The
Watson-Click’s DNA double helix is very beautiful. Hence, we
life-scientists have been imprinted that a human genome is a blueprint. If
we hypothesize that a human genome is a blueprint, what types of absurdity
do emerge? And if a human genome is not a blueprint, what must be
needed to construct human bodies? To solve these hypothetical
propositions are the aim of this document. In the case of unicellular
organisms such as E.coli, their genomes may play a role for blueprints.
However, biological mechanisms of multicellular organisms such as Homo
Sapiens, are much complex and it is difficult to contain all information as a
blueprint in their genomes. Therefore, a human genome plays a role for
storage of genes, and I think that human oocytes have the instructions and a
fertilized egg selects necessary genes from that storage, and expresses
genes for development and differentiation.

Materials and Methods

　Table I was made from NCBI database (http://www.ncbi.nlm.nih.gov/)
and KEGG (http://www.kegg.jp/ja/). One hundred ninety six key words in
Supplemental Table I were selected from reference3-7. Supplemental Table
II was made from Supplementary Data 1, 2, 3 which were originally
located in
http://www.canr.msu.edu/dept/ans/community/people/cibelli_jose.html
(Kocabas 2006). I re-locate Supplementary Data 1, 2, 3, in
http://www.i-tmb.com/text.html. Supplementary Data 1 contains
up-regulated genes in human oocytes, Supplementary Data 2 contains
down-regulated genes in human oocytes, and Supplementary Data 3
contains uniquely expressed genes in human oocytes. I combined
Supplementary Data 1, 2, 3, and eliminated duplicated genes. Finally, I got
12764 genes which expressed in human oocytes (Supplemental Table II). I
surveyed 12764 genes with 196 key words and I selected 823 genes which
are thought to be important in development and differentiation in GenBank
release 175.0 (Supplemental Table III). Table II shows the number of important genes for development and differentiation. Supplemental Table
I, II and III are located in http://www.i-tmb.com/.

Results and Discussion

　Human genome is not a blueprint. At first the definition of a blueprint must
be determined. According to a dictionary, a blueprint for something is a
plan or set of proposals that shows how it is expected to work. I scrutinized
loci of genes for 8 important biological pathways and factors, and their loci
are scattered all over the human genome at random (Table I). I think that a
blueprint must have regularity, periodism, harmony, some types of patterns,
consistency or beauty which a blueprint itself has. But there were not
existed such things. On the contrary, more than half of human genome
sequence consists of Lines, Sines, retroviral-like elements, DNA-only
transposon fossils, Alu sequences and pseudogenes (Alberts 2008). The loci
of genes for 8 pathways and factors are scattered all over the human
genome, and there do not exist any operons such as in bacterial genomes.
Some reports exist that genes that make a cluster in one-dimensional,
construct a cluster in three-dimensional, but there are no report that
scattered genes in one-dimensional construct a cluster in three-dimensional
(Schneider 2007). In mathematics, one opposite example is enough for
proof. But biology has some exceptions. However, genes in Table I are
biologically important genes, and if a human genome is a blueprint, 8
exceptions must not be permitted. Here, I logically show that a human
genome is not a blueprint. Hence, how are human bodies constructed from
a human genome which is storage of genes?
Human oocytes have the instructions. Before fertilization, human oocytes
express genes. If a human genome is storage of genes, mRNAs which are
important for development and differentiation must be expressed in human
oocytes and translated into proteins as soon as fertilization begins.
Therefore, I surveyed public databases and I found an expression profile in
human oocytes. In that profile, there are 12700 genes, and among 12700
genes, I found more than 800 genes which are related to development and
differentiation. In general, many sample data must be necessary for
comparison of gene expression levels for statistical analysis. But in my
case, I do not need statistical analysis. Because the importance is only in
which certain types of genes are expressed in human oocytes. I think that
human oocytes play a major role because of the amount of genes related to
development and differentiation. Essential genes for human development
and differentiation such as Oct3, Oct4 are not existed in Table II. But I do
not think that it is critical. I just think that mRNAs of Oct3, Oct4 did not
hybridize on the microarray chips. Because the genes which must be
expressed must be expressed in human oocytes. And because of RNA
interference, some mRNA might be broken. However, the amount of genes
in human oocytes related in development and differentiation indicates that
human oocytes have the instructions. Definition of instruction must be done.
Instructions are clear and detailed information on how to do something. In
this point, I think that human oocytes have the simple instructions. If
human oocytes do not have the simple instructions, where is the blueprint
or the instructions? I already indicate that a human genome is not a
blueprint. Hence, it is logical that human oocytes have the simple
instructions because a human body begins to be built from only one cell, a
fertilized egg. If other cells except for human oocytes give proteins or
mRNAs from outside of human oocytes, nurse cells or stromal cells might
be candidates for the simple instructions. But it is not realistic that those
cells give most of biologically important proteins or mRNAs into fertilized
eggs. Therefore, I logically proved that human oocytes have the simple
instructions.
Important genes for the instruction in human oocytes (Gilbert 2006, Moody
2007, Schoenwolf 2009, Slack 2006, Wolpert 2007). The homeodomain is
an approximately 60 amino acid sequence containing many basic residues,
and forms a helix-turn-helix structure that binds specific sites in DNA. The
homeodomain sequence itself is coded by a corresponding homeobox
(HOX) in the gene. The homeobox was given its name because it was
initially discovered in homeotic genes. However, there are many
transcription factors that contain a homeodomain as their DNA-binding
domain and although they are often involved in development, possession of
a homeodomain does not guarantee a role in development, nor are mutants
of homeobox genes necessarily homeotic. A very large number of
homeodomain proteins have important functions, e.g. Engrailed in
Drosophila segmentation, Goosecoid in the vertebrate organizer, Cdx
proteins in anteroposterior patterning. An important subset are the HOX
proteins which have a special role in the control of anteroposterior pattern
in animals. Homeobox genes are found in animals, plants, and fungi, but
the Hox subset are only found in animals. The LIM domain is a
cysteine-rich zinc-binding region responsible for protein-protein
interactions, but is not itself a DNA-binding domain. LIM-homeoproteins
possess two LIM domains together with the DNA-binding homeodomain.
Examples are Lim-1 in the organizer, Islet-1 in motorneurons, Lhx factors
in the limb bud, and Apterous in the Drosophila wing. PAXs are
characterized by a DNA-binding region called a paired domain with 6
alpha-helical segments. The name is derived from the paired protein in
Drosophila. Many of pax proteins also contain a homeodomain. Examples
are Pax6 in the eye and Pax3 in the developing somite. Zinc-finger protein
is a large and diverse group of proteins in which the DNA-binding region
contains projections (“fingers”) with Cys and/or His residues folding
around a zinc atom. Some examples are the GATA factors important of the
blood and the gut, Krupple in the early Drosophila embryo, WT-1 in the
kidney. Basic helix-loop-helix (bHLH) protein transcription factors are
active as heterodimers. They contain a basic DNA-binding region and a
hydrophobic helix-loop-helix region responsible for protein dimerization.
One member of the dimer is found in all tissues of the organism and the
other member is tissue specific. There are also proteins containing the HLH
but not the basic part of the sequence. These form inactive dimmers with
other bHLH proteins and so inhibit their activity. Examples of bHLH
proteins include E12, E47 which are ubiquitous in vertebrates, the
myogenic factor MyoD, and Drosophila pair-rule protein hairy. An
inhibitor with no basic region is Id, which is an inhibitor of myogenesis.
FOX have a 100 amino acid winged helix domain which forms another
type of DNA-binding region and known as “FOX” proteins. Examples are
Forkhead in Drosophila embryonic termini and Fox2A in the vertebrate
main axis and gut. T-box factors have a DNA-binding domain similar to the
prototype gene product known as “T” in the mouse and as brachyury in
other animals. They include the endodermal VegT and the limb identity
factors Tbx4 and Tbx5. High mobility group (HGM)-box factors differ
from most others because they do not have a specific activation or
repression domain. Instead they work by bending the DNA to bring other
regulatory sites into contact with the transcription complex. Examples are
SRY, the testis-determining factor, Sox9, a “master switch” for cartilage
differentiation, and the TCF and LEF factors whose activity is regulated by
the Wnt pathway. Trnasforming growth factor (TGF) beta was originally
discovered as a mitogen secreted by “transformed” (cancer-like) cells. It
has turned out to be the prototype for a large and diverse superfamily of
signaling molecules, all of which share a number of basic structural
characteristics. The mature factors are disulfide-bonded dimmers of
approximately 25 kDa. They are synthesized as longer pro-forms which
need to be protrolytically cleaved to the mature form in order for biological
activity to be shown. The TGF-beta themselves are in fact often inhibitory
to cell division and promote the secretion of extracellular matrix materials.
They are involved mainly in the organogenesis stages of development. The
activin-like factors include the nodal-related family, which are all involved
in induction and patterning of the mesoderm in vertebrate embryos. The
bone morphogenetic proteins (BMPs) were discovered as factors promoting
ectopic formation of cartilage and bone in rodents. They are involved in
skeletal development, and also in the specification of the early body plan.
There are a number of receptors for the TGF-beta superfamily. Their
specificity for different factors is complex and overlapping, but in general
different subsets of receptors bind to the TGF-beta themselves, the
activin-like factors, and the BMPs. In all cases the ligand binds first to a
type II receptor and enables it form a complex with a type
I receptor. The type I receptor is a Ser-Thr kinase and
becomes activated in the ternary complex. Activation causes
phosphorylation of smad proteins in the cytoplasm. Smads 1, 5, and 8 are
targets for BMP receptors; smad 2 and 3 for activin receptors. Smad 4 is
required by both pathways, and smad 6 is inhibitory to both by displacing
the binding of smad 4. Phosphorylation causes the smads to migrate to the
nucleus where they function as for transcription factors, regulating target
genes. The hedgehogs were first identified because mutations of the gene in
Drosophila disrupted the segmentation pattern and made the larvae look
like hedgehogs. Sonic hedgehog is very important for the dorsoventral
patterning of the neural tube and for anteroposterior patterning of the limbs.
Indian hedgehog is important in skeletal development. The full-length
hedgehog polypeptide is an autoprotease, cleaving itself into an active
N-terminal and an inactive C-terminal part. The N-terminal fragment is
normally modified by covalent addition of a fatty acyl chain and of
cholesterol, which are needed for full activity. The hedgehog receptor is
called patched, again named after the phenotype of the gene mutation in
Drosophila. This is of the G-protein-linked class. It is constitutively active
and is repressed by ligand binding. When active it represses the activity of
another cell membrane protein, smoothened, which in turn represses the
proteolytic cleavage of Gli-type transcription factors. Full-length Gli
factors are transcriptional activators that can move to the nucleus and turn
on target genes, but the constitutive removal of the C-terminal region
makes them into repressors. In the absence of hedgehog, patched is active,
smoothened inactive, and Gli inactive. In the presence of hedgehog,
patched is inhibited, smoothened is active, and Gli is active. Activation of
protein kinase A also represses Gli and hence antagonizes hedgehog
signaling. The founder member of the Wnt family was discovered through
two routes, as an oncogene in mice and as the wingless mutation in
Drosophila. Wnt factors are single-chain polypeptides containing a
covalently linked fatty acyl group which is essential for activity and renders
them insoluble in water. The Wnt receptors are called frizzled after
another Drosophila mutation. There are several classes of
receptor for different ligand types and they do not
necessarily cross-react. Wnt 1, 3A, or 8 will activate
frizzleds that cause the repression of a kinase, glycogen
synthase kinase 3 (gsk3) via multifunctional protein called
dishevelled. When active, gsk3 phosphorylates beta-catenin, an
important molecule involved both in cell adhesion and gene
regulation. When gsk3 is repressed, beta-catenin remains
unphosphorylated and in this state can combine with a
transcription factor, Tcf-1, and convey it into the nucleus.
This pathway is important in numerous developmental contexts,
including early dorsoventral patterning in Xenopus, segmentation
in a Drosophila, and kidney development. Other Wnts,
including Wnts 4, 5, and 11, bind to a different subset of
frizzled that activate two other signal transduction pathways.
In the planar cell polarity pathway a domain of the dishevelled
protein interacts with small GTPases and the cytoskeleton to bring about a
polarization of the cell. In the Wnt-Ca pathway phospholipase C becomes
activated by a frizzled. This then acts to generate diacylglycerol and
inositol 1,4,5 triphosphate, with consequent elevation of cytoplasmic
calcium, as described above under G-protein-coupled receptors. For the
Delta-Notch system both the ligand (Delta, Jagged) and receptor (Notch)
are integral membrane proteins. Their interaction can therefore only take
place if the cells making them are in contact, as for the ephrin-Eph system.
Binding of ligand to Notch causes cleavage of the cytoplasmic portion of
Notch by an intramembranous protease, gamma-secretase, and this causes
release into the cytoplasm of transcription factor, CSL-kappa. This migrates
to the nucleus and activates target genes. The gamma-secretase is the same
protease that generates the peptide whose accumulation in the brain leads to
Alzheimer’s disease. Notch can carry O-linked tetrasaccharides and
presence of this carbohydrate chain can affect its specificity, increasing
sensitivity to Delta and reducing sensitivity to Jagged. Control is often
exercised through the activity of the glycosyl transferase Fringe, which
adds GlcNAc to the O-linked fucose. The Delta-Notch system is important
in numerous developmental situations, including neurogenesis,
somitogenesis, and imaginal disc development. Cadherins are families of
single-pass transmembrane glycoproteins which can adhere tightly to
similar molecules on other cells in the presence of calcium. Cadherins are
the main factors attaching embryonic cells together, which is why
embryonic tissues can often be caused to disaggregate simply by removal
of calcium. The cytoplasmic tail of cadherins is anchored to actin bundles
in the cytoskeleton by a complex including proteins called catenins. One of
these, beta-catenin, is also a component of the Wnt signalimg pathway,
providing a potential link named for the tissues in which they were
originally found, so E-cadherin occurs mainly in epithelia and N-cadherin
occurs mainly in neural tissue. The integrins are cell-surface glycoproteins
that interact mainly with components of the extracellular matrix. They are
heterodimers of alpha- and beta- subunits, and require either magnesium or
calcium for binding. There are numerous different alpha and beta chain
types and so there is a very large number of potential heterodimers.
Integrins are attached by cytoplasmic domains to microfilament bundles, so,
like cadherins, they provide a link between the outside world and the
cytoskeleton. They are also thought on occasion to be responsible for the
activation of signal transduction pathways and new gene transcription
following exposure to particular extra cellular components.
After the birth of molecular biology, we life-scientists proved only two
things, in my opinion. Firstly, there is high possibility that genes or proteins
which have similar nucleic acid or amino acid sequences have similar
3-demensional structures and functions. Secondly, Genes or proteins have
many functions because of the timing of working, permutation and
combination. The number of human genes might be 40000 at most. In the
first place, only 40000 genes cannot control complex biological
mechanisms. Therefore, I think that limited number of genes and proteins
change the timing of working, permutation and combination, and control
the diverse biological mechanisms in human bodies. Genomes of viruses or
bacteria might have the possibility that those genomes play a role for
blueprints. But it will become impossible that human genome play a role
for a blueprint. Hence, I think that human genome begins to exist as storage
of genes. And human oocytes express essential genes for development and
differentiation as the simple instructions. After fertilization, a fertilized egg
differentiates according to micro-environment surround the fertilized egg.
Therefore, human oocytes expresses genes for adhesion molecules such as
integrins, cadherins and so on. From now on, a lot of evidence will be piled
up to support my hypothesis. Finally, I foresee that once organogenesis
begins, tissue differentiation proceeds autonomously and human bodies are
built. This is, I think, theoretical molecular biology and .Itoh hypothesis..


References

　Alberts B, Johnson A, Walter P, Lewis J, Raff M, Roberts K (2008).
Molecular Biology of the Cell, 5th edition, Garland Science, Mortimer
Street, London. 1-1601
Gilbert SF (2006). Developmental Biology, 8th edition, Sinauer
Association Inc. Sunderland, MA. 3-751
Kocabas AM, Crosby J, Ross PJ et al, (2006). The transcriptome of
human oocytes, Proc. Natl Acad. Sci. USA. 103:14027-14032.
Moody SA (2007). Principles of Developmental Genetics. Academic
Press, New York. 2-1022

Schneider R, Grosschedl R (2007). Dynamics and interplay of nuclear
architecture, genome organization, and gene expression. Genes Dev.
21:3027-3043.

Schoenwolf GC, Bleyl SB, Brauer PR, et,al, (2009). Larsen’s Human
Embryology, 4th edition, Churchill Livingstone, New York. 1-644
Slack JMW (2006). Essential Developmental Biology 2nd edition,
Blackwell Publishing, West Sussex, UK. 3-336
Wolpert L (2007). Principles of Development, 3rd edition. Oxford
University Press. 1-522

Table I. Loci of genes for major biological pathway　　

TableII. Genes for development and differentiation in human oocytes


Chapter 4. Theoretical analysis indicates ‘the principle of fluctuations’
fundamentally control life phenomena.

Abstract

　The proposition of the existence of fundamental systems which control
or manage life phenomena has not given the solution. The profiles of gene
expression or the pathways for the protein interactions have been
elucidated. However, those are the results of the gene expression patterns
and the pathways only under steady states and have not been elucidated the
fundamental systems or principles of complex life phenomena. Hence, do
really the systems or principles exist which fundamentally control or
manage the complex life phenomena? I logically proved that .the
principle of fluctuations. control or manage the fundamental life
phenomena. In other words, life phenomena exist on the basis of .the
principle of fluctuations.. Hence, living bodies can cope with the change of
diverse conditions. Replication of DNA, DNA mismatch repair, gene
expression, translation into amino acids, production of proteins, the process
of energy productions and the process of signal transductions are not be
firmly operated in 100%. Notwithstanding, living bodies operate life
phenomena without hindrance. This means the existence of .fluctuations.
fundamentally. Life phenomena are operated harmoniously. Since living
bodies are constructed by molecules, living bodies must be accepted the
uncertainty principle in the field of physics. It is impossible to make
mathematical formulas, because life phenomena are too complex and too
flexible to make such formulas. Living bodies are not machines. Therefore,
I suppose that life is the states of operation of life phenomena on the basis
of .fluctuations., because the boundary line between living conditions and
dead conditions is not be able to be defined.

Introduction

　Since physicist Dr.Schrodinger published the book .What is life?. in
1944, the proposition “What is life?” has been one of the most important
propositions in the field of life science1. But still now, the solution of the
proposition has not been elucidated. The fields of systems biology and
bioinformatics emerged to solve to the proposition which the systems
control or manage life phenomena. However, these fields have not been
given the solution to the existence of the fundamental systems which
control or manage life phenomena so far. I think that the way of trials to
elucidate life phenomena in terms of systems biology or bioinformatics are
correct. However, even if gene expression profiles by microarrays and
protein interaction pathways were elucidated, or analysis of biological
information were performed, those trials have not been given the solution
to the proposition of the existence of the systems which control or manage
fundamental life phenomena. Living bodies maintain homeostasis under the
steady state, but if once those conditions are damaged by some kinds of
stresses, the homeostasis brake and other life phenomena set in motion2, 3.
Do really replication of DNA, gene expression, translation into amino acids,
protein production, pathways of energy production of glycolysis or TCA
cycle and pathways of signal transductions which are essential for life,
support life phenomena all together harmoniously? The solution to this
proposition is NO! Many systems and pathways have been elucidated, but
even one of them has not been the fundamental systems which control or
manage life phenomena. In the fields of systems biology and
bioinformatics, the concept of robustness advocated and those scientists
emphasize that systems cope with diverse life phenomena by the existence
of robustness4, 5. And in the fields of chemical biology, biophysics, physical
biology, those scientists emphasized the existence of the system on the
assumption of mechanism or physicalism6-20. Trials to elucidate life
phenomena have also been performed by complex system and
self-organization, these trials have not been successful so far 21-25. Are life
phenomena systematic such as machines which can be designed by
mathematical formulas? When living bodies fall into danger and certain
systems do not operate fully, living bodies operate the other systems to
compensate for the danger to survive. It is redundancy. Hence, how does
make an interpretation of the existence of redundancy? How is the
uncertain principle of physics adapted for life phenomena26, 27? It is very
significant to elucidate life phenomena. Hence, the propositions which
theoretical biologists try to elucidate, are .what is the fundamental principle
to control and manage life phenomena?. and “What is life?” I emphasize
that the system does not exist to control or manage life phenomena
fundamentally, but .fluctuations. exist on the basis of life phenomena. The
uncertainty principle of physics is the basis of the existence of
.fluctuations.. Because living bodies are constructed by molecules, life
phenomena are operated by the uncertainty principle of physics. Finally,
the solution of the proposition “What is life?” is supposed to be the
condition which life phenomena are controlled or managed by
.fluctuations..

The definition of words and phrases.

　Before the discussion, the definition of words or phrases is significantly
important. Because scientists must use appropriate words or phrases. In the
fields of systems biology and bioinformatics, the word “robustness” is used
to express flexible strength of the systems of life phenomena. But the real
meaning of robustness is to withstand or overcome adverse conditions by
dictionaries28-38. If life phenomena are not based on the systems,
flexibilities, randomness and vagueness, .fluctuations. is thought to be
appropriate to express the principle of control the system of life
phenomena.

Systematic or nonsystematic?

　Are life phenomena systematic or nonsystematic? There must be only
two choices. In the fields of systems biology and bioinformatics, scientists
emphasize that life phenomena are the aggregation of individual systems,
and life phenomena are smoothly controlled or managed by robustness on
the basis of the aggregation of those systems. Forthermore, some scientists
in those fields try to make mathematical formulas on the basis of
mechanism or physicalism. On the contrary, I emphasize that systems are
controlled or managed by .the principle of fluctuations. which are
constructed which is existed on the basis of unstable life phenomena.
Because of the existence of .the principle of fluctuations., the values of
blood examinations from one healthy human have the unevenness (data not
shown). However, human beings can act life phenomena harmoniously.
This means that life phenomena are controlled or managed fundamentally
on the basis of .fluctuations.. In other words, life phenomena are controlled
or managed on the basis of .the principle of fluctuations. fundamentally.
Endosymbioses have dramatically altered eukaryotic life, but were thought
to have negligibly affected prokaryotic evolution. By analyzing the flows
of protein families, the evidence that the double-membrane, Gram-negative
prokaryotes were formed as the result of a symbiosis between an ancient
actinobacterium and an ancient clostridium. The resulting taxon had been
extraordinarily successful, and had profoundly altered the evolution of life
by providing endosymbionts necessary for the emergence of eukaryotes
and by generating Earth's oxygen atmosphere. Their double-membrane
architecture and the observed genome flows into them suggest a common
evolutionary mechanism for their origin: an endosymbiosis between a
clostridium and actinobacterium39. Why sex evolved and persists is a
problem for evolutionary biology, because sex disrupts favorable gene
combinations and requires an expenditure of time and energy. Further, in
organisms with unequal-sized gametes, the female transmits her genes at
only half the rate of an asexual equivalent. Many modern theories that
provide an explanation for the advantage of sex incorporate an idea
originally proposed by Weismann more than 100 years ago: sex allows
natural selection to proceed more effectively because it increases genetic
variation. Dr. Goggard and colleagues tested this hypothesis, which still
lacked robust empirical support, with the use of experiments on yeast
populations. Capitalizing on recent advances in the molecular biology of
recombination in yeast, they produced by genetic manipulation strains that
differed only in their capacity for sexual reproduction. They show that, as
predicted by the theory, sex increases the rate of adaptation to a new harsh
environment but has no measurable effect on fitness in a new benign
environment where there is little selection40. If the systems are robust in
human cells, tissues and organs, life phenomena may not cope with flexibly
the dangerous conditions which menace the homeostasis. Further, if
systems exist on the basis of life phenomena, living bodies could not
acquire these flexibilities, in other word, .the principle of fluctuations..
Hence, any living bodies such as bacteria, yeast, human beings may be
disturbed evolution. In that case, the systems must not have the space to
acquire other systems, because the systems must be constructed completely.
I deductively and logically proved that life phenomena do not exist on the
basis of systems. It is very difficult to prove logically that life phenomena
are not fundamentally controlled or managed by the systems. Even if only
5000 molecules control or manage all biological activities in a certain
living body, the systems maintain homeostasis. If the systems are damaged,
the living body copes with redundancy. But if the systems were not able to
maintain homeostasis, the living body will die. Is it possible to predict
which and how the pathways or the systems cope with those crises? It
depends on the size and type of crises. Therefore, as a result, it is
impossible to predict how to cope with those crises. Because, life
phenomena are controlled or managed by the principle of uncertainty in the
field of physics. In other words, I deductively and logically proved life
phenomena are unstably fluctuated under those crises. If .fluctuations. do
not exist under the crises for life, living bodies may be accepted the crises
and stop biological activities. Notwithstanding, living bodies manage to
survive. This is for the sake of existence of .fluctuations.. But it is
impossible to predict how to manage to survive. I proved by abduction as
stated an above-mentioned. If the systems exist fundamentally control or
manage life phenomena, life phenomena may be controlled or managed by
the gene products of house-keeping genes. However, these genes products
must be classified into the several essential pathways such as DNA
replication, DNA mismatch repair, gene expression, translation into amino
acids, production of proteins, the process of energy productions, and the
process of signal transductions and so on. And the existence of upper
systems or the link to totally control or manage to these pathways is not
identified still now. In addition, it is undeniable to predict how much
amount or genes and proteins must be different from individual living
bodies, and how to respond.


Mechanism, physicalism, probability theory and the uncertainty
principle

　Systems biology, bioinformatics, chemical biology, biophysics and
physiological biology ultimately exist on the basis of mechanism or
physicalism. But because of the uncertainty principle in the field of physics,
life phenomena are not able to be predictable. In case of DNA replication
or DNA mismatch repair, there exist mistakes in certain probabilities. And
the timing of gene expression and gene expression pattern are also
considered by probability theory. The timing of working, permutation,
combination and the efficiency of working of proteins are also considered
by probability theory. Hence, how much amount of proteins is secreted?
How fast are the proteins degraded? Do pathways of energy productions
usually produce the same amount of energy? How are those pathways exact
and fast under stress? How fast does the concentration in blood of
antibiotics increase, in case of giving antibiotics? It is impossible to solute
these propositions. Because life phenomena are exceedingly complex and
unpredictable. It is further more impossible to design mathematical
formulas. Because all of life phenomena must be considered by probability
theory. There manifestly exist the differences of biological activities among
individual living bodies from the results of research and treatment. This is
the way Heisenberg stated the uncertainty principle originally: If the
measurements on any objects are made, and the x-component of its
momentum with an uncertainty p can be determined at the same time, it
is impossible to know its x-position more accurately than x = h/　p, where
his a definite fixed number given by nature. It is called “Plank’s constant”.
Hence, it means that life phenomena have the uncertainty and are not
predictable even in an instant future. This means that the positions and
momentums of molecules are not predictable.

Living bodies are not machines.

　The academic discipline which I advocate theoretical molecular biology,
is a science to elucidate life phenomena logically and theoretically. Life
phenomena must be considered by probability theory, and exist on the basis
of .the principle of fluctuations.. According to .fluctuations., life
phenomena which are not machinelike, flexibly cope with the changes of
environments and crises of homeostasis. I inductively proved as a stated
above. I will elucidate the proposition which living bodies are machines.
Firstly, if living bodies were machines, living bodies could not accomplish
evolution. Furthermore, DNA replication, DNA mismatch repair, gene
expression, translation into amino acids and productions of proteins might
have mistakes. If living bodies were machines, living bodies must not
accomplish evolution and not make mistakes in case of DNA replication,
DNA mismatch repair, gene expression, translation into amino acids,
productions of proteins and so on, because living bodies must be created in
100% machinelike. Hence, the solution is that living bodies are not
machines. Firstly, if there do not exist .fluctuations., individual cells cope
with crises of homeostasis in 100% uniformly. And tissues or organs which
are the aggregate of cells also cope with in 100% uniformly. But living
bodies operate biological activities harmoniously without hindrance and
cope with crises of homeostasis. To sum up, life is on the basis of
.fluctuations.. Blood examinations were performed from only one male
(Data not shown). The results show that there were certain different
measured values of two blood samples which were took at interval of only
one hour. Even at the same time, the measured values of two blood samples
have difference. These were measurement errors. However, instead of the
existence of unevenness of blood examinations, human beings can perform
life phenomena without any obstructions. This means that life phenomena
fundamentally have unevenness. Hence, life phenomena are based on the
uncertainty principle in the field of physics, and the measured values of
blood examinations must not be able to predictable only in one hour.
Because, the systems which control or manage life phenomena are based
on .fluctuations.. I proved the existence of .fluctuations. inductively.
Secondly, I will prove life phenomena are controlled or managed by the
uncertainty principle. Can we predict our life phenomena or body
conditions in one hour, one week or one year? This is impossible. We will
be able to interpret the events such as life phenomena or body conditions
by the analysis of gene expression profiles or the pathways of protein
interactions. Hence, life phenomena must not be predictable according to
the uncertainty principle in the field of physics. This means that there exist
uncertainties of life phenomena on the basis of .fluctuations.. I proved an
above-mentioned deductively. Thirdly, why living bodies can perform
evolution? If the systems which control or manage are robust, evolution
might not be performed. Hence, the systems which control or manage life
phenomena must have flexibilities to acquire new characters or traits. This
means that there do not exist the robust systems, but must namely exist
flexible .fluctuations.. I proved an above-mentioned deductively.

It is impossible to make mathematical formulas.

　It is also impossible to make mathematical formulas. That is not why
analytical capabilities of the present time computers are not sufficient to
analyze more than billions of interactions of molecules in living bodies. If
it will be possible to analyze more than billions of interactions of molecules
in living bodies, will it be possible to make mathematical formulas in the
future? And if all systems of life phenomena were elucidated in the future,
will it be declared to elucidate life phenomena completely? The solution of
these prepositions is NO! It is impossible to make mathematical formulas
to elucidate the systems or the principles of life phenomena, because life
phenomena are too complex, and biology is different from mathematics or
physics. And many systems operate together and are connected with other
systems on the same time in life phenomena. Hence, it is impossible to
make mathematical formulas and elucidate the systems or the principles of
life phenomena fundamentally. I inductively proved that the systems do not
exist on the basis of life phenomena. Some theoretical biologists try to
make mathematical formulas, but living bodies do not live and cope with
crises of homeostasis in 100% uniformly. That is why that it is impossible
to make mathematical formulas.

What is life?

　Can the boundary line between living conditions and dead conditions be
defined in terms of biological and philosophical point of views? Is it
possible to define when living bodies die? The solutions for these
propositions may be that living conditions and dead conditions are
continuous sequentially. Because living bodies are not machines, it will not
be impossible to define the boundary line between living conditions and
dead conditions. The important fact is that life phenomena are not
predictable, not be able to make mathematical formulas to elucidate the
systems, and exist on the basis of .fluctuations.. That is why living bodies
are able to operate diverse biological activities and cope with crises of
homeostasis harmoniously.


Conclusion

　Here, I logically and theoretically proved that the solutions for the
propositions of the systems or principles which control and manage life
phenomena fundamentally are .the principle of fluctuations.. I name this
thought as Itoh’s .the principle of fluctuations.. And the proposition of
“What is life?” may be supposed to operate or perform biological activities
on the basis of .fluctuations..

Methods summary

　Blood examinations were performed from only one male at interval of
only one hour. And blood examinations were performed from the same
person on the same time as a negative control.


References

1. Schrodinger, E. What Is Life?: with "Mind and Matter" and
"Autobiographical Sketches" (Cambridge University Press, 1992).

2. Alberts, B. et al. Molecular Biology of the Cell: Reference Edition 5th
edition (Garland Science, 2007)

3. Fauci, S. A. et al. Harrison's Principles of Internal Medicine, 17th
Edition (McGraw-Hill, 2008)

4. Kitano. H, Systems biology: a brief overview. Science 295, 1662-4
(2002).

5. Kitano. H, Computational systems biology. Nature 420, 206-10 (2002).

6. Creighton. E. T, The Physical and Chemical Basis of Molecular Biology
(Helvetian Press, 2010).

7. Meyer B. Jackson. B, M, Molecular and Cellular Biophysics
(Cambridge University Press, 2006).

8. Beard. A, B, & Qian. H, Chemical Biophysics: Quantitative Analysis of
Cellular Systems (Cambridge University Press, 2010).

9. Sener. B, Innovations in Chemical Biology (Springer Netherlands,
2010).


10. Waldmann. H, & Petra. J, Chemical Biology (Wiley-VCH, 2009).

11. Mayer. G, The Chemical Biology of Nucleic Acids (Wiley, 2010).

12. Miller. D, A, & Tanner. J, Essentials Of Chemical Biology: Structure
　　and Dynamics of Biological Macromolecules (Wiley, 2008).

13. Al-Rubeai. M, & Fussenegger. M, Systems Biology (Springer
　　Netherlands, 2010).

14. Nagasaki. M, Saito, A, Doi. A, Matsuno. H, & Miyano. S, Foundations
　　of Systems Biology: Using Cell Illustrator and Pathway Databases
　　(Springer-Verlag New York Inc, 2009).

15. Iglesias. A, P, & Ingalls. P, B, Control Theory and Systems Biology (The
　　MIT Press, 2009).

16. Choi. S, Introduction to Systems Biology (Springer, 2010).

17. Glaser. R, Biophysics: An Introduction (Springer, 2010).

18. Claycomb. J, & Tran. J, Introductory Biophysics: Perspectives on the
　　　Living State (Jones & Bartlett Publishers, 2010).

19. Nelson. P, Biological Physics (W. H. Freeman, 2007).

20. Scherer. O. J, P, & Fischer. F, S, Theoretical Molecular Biophysics
　　(Springer, 2010).

21. John H. Miller. H, J, & Scott E. Page. E, S, Complex Adaptive Systems
　　(Princeton University Press, 2007).

22. Page. E, S, Diversity and Complexity (Princeton University Press,
　　2010).

23. Kauffman. S, At Home in the Universe: The Search for the Laws of
　　Self-Organization and Complexity (Oxford University Press, 1996).

24. Kauffman. S, The Origins of Order: Self-Organization and Selection in
　　Evolution (Oxford University Press, 1993).

25. Camazine. S, et al. Self-Organization in Biological Systems (Princeton
　　University Press, 2003).

26. Feynman. R, Leighton. R, B, & Sands. M, L, The Feynman Lectures on
　　Physics (Addison-Wesley Publishing Co, Inc., 1963).

27. Dirac. M, A, P, The principles of quantum mechanics 4th edition
　　(Oxford University Press, USA, 1982).

28. Trumble. R, W, Shorter Oxford English Dictionary 6th edition (Oxford
　　University Press, USA, 2007).

29. Hornby. S, A, Turnbull. J, Lea. D, & Parkinson. D, Oxford Advanced
　　Learner's Dictionary 8th edition (Oxford University Press, USA; (April
　　26, 2010).

30. Title. B, Cambridge Advanced Learner's Dictionary 3th edition
　　(Cambridge University Press, 2008).

31. Collins English Dictionary 30th anniversary edition of 10th revised
　　edition (Collins, 2010).

32. House. R, Random House Webster's Unabridged Dictionary (Random
　　House Reference, 2006).

33. Soanes. C, & Stevenson. A, Concise Oxford English Dictionary (Oxford
　　University Press, 2008).

34. Cambridge Academic Content Dictionary (Cambridge University Press,
　　2008).

35. Oxford Dictionary of English 3rd Revised edition (Oxford University
　　Press, 2010).

36. Webster's 3rd New International Dictionary (Merriam Webster, 2000).

37. Longman Dictionary of Contemporary English (Pearson Longman,
　　2009).

38. Anderson. S, Katharine Coates. K, & Hands. P, Collins Cobuild
　　Advanced Dictionary (Heinle, 2008).

39. Lake. A, J, Evidence for an early prokaryotic endosymbiosis. Nature
　　460, 967-971 (2009).

40. Goddard. M, R, Godfray. H, C, & Burt. A, Sex increases the efficacy of
　　natural selection in experimental yeast populations. Nature 434, 636-40
　　(2005).


Chapter 5. The future images of medicine.

1) Gene therapy

　Recently, we do not hear about the phrase .gene therapy.. Because it is
impossible to do gene therapy right now. Original definition of gene
therapy is that to correct incorrect genome sequences into correct
sequences. Before profound discussion about the possibility of
accomplishment of the technique of genome alteration, development of the
technique of gene transfer began. Hence, viral vectors were developed
because of high efficiency of gene transfer into cells. Adenoviral vectors
transfer genes the most efficiently. However, adenoviral vectors are not
inserted in to genomes and were not used gradually. Using retroviral
vectors, DNA fragments are able to be inserted in genomes. However,
because of carcinogenesis, retroviral vectors are not able to be used in gene
therapy. The helpes vectors are used to transfer DNA fragment into brain
cells. Howsoever, it is impossible to do gene therapy because the
techniques to correct incorrect genome sequences into correct sequences
were not accomplished. Human cells have many barriers to protect
mutations. That is why it is impossible to correct incorrect genome
sequences into correct sequences. If it is easily DNA fragments inserted in
human genomes, it means that carcinogenesis occur very easily. And
human genome in mucosal cells in intestines must be inserted DNA
fragment easily. Hence, the concept of gene therapy is going to disappear.
There are a lot of unknown things to get solutions without doing
experiments. But before doing experiments, life scientists and medical
scientists must meditate and think profoundly if propositions really have
solutions. Compared with human somatic cells, human germ cells have the
ability to DNA recombination. However, is that techniques really efficient
to cure diseases? In case of human somatic cells, it is almost impossible to
correct incorrect genome sequences into correct sequences. If it becomes
possible to correct incorrect genome sequences into correct sequences,
germ cells must be used. However, there are big obstacles ethically and
technically. If it were permitted ethically, do really correct only incorrect
sequences in 100%? If mutations occur other portions of human genomes,
what will happen? It is impossible to predict what happen if these problems
were not solved. In my opinion, if germ cells were not used, there will not
be any chance to accomplish gene therapy in the future. However, if germ
cells were used, it is almost impossible to find out new techniques to
correct incorrect genome sequences into correct sequences. Therefore,
doing gene therapy is impossible right now.

2) Genomic diagnostics and gene diagnostics

　Medical treatment in 5-10 years from now will be totally different from
present medical treatment. Because China government officially
announces that they will sequence of a whole human genome of one
person by about $100 in 2-3 years. Actually, Stanford University
sequences a whole human genome of one person by about $200. Hence,
we will be able to know our own genome sequences in about $100 in
2-3 years. If human genomes among 10 million people were compared,
analyzed those sequences statistically and found the positions of
insertion, deletions, mutations and small nucleotide polymorphisms
(SNPs), it will be possible to predict when patients become diseases,
which types of diseases patients suffer from and which types of drug
combination are efficient for patients. In other words, in 5-10 years,
hospital will become the place to go to check if patients do not suffer
from predicted disease yet, but will not become the place to go after
suffering from diseases. There actually exist the pedigrees of cancers. If
we predict about when they suffer from cancers, preventive medicine
will be important. And it will be much easier to find cancers in early
stage and to cure cancers early. However, it is unsafe to expect too much
expectation. Because the causal genomic insertions, deletions, mutations
and SNPs or causal genes for hypertension, hyperlipidemia, diabetes
mellitus, autoimmune disorder, connective tissue diseases and other
diseases will be found, but those findings will not be able directory to
contribute to treatment of those diseases. However, if patients know
when and which types of diseases they will suffer from, it will be
possible to delay the timing of suffering from those diseases. Therefore,
as the results, it will be possible to find the new treatment to cure those
diseases.


3) Drug delivery system (DDS)

　The concept of drug delivery system (DDS) emerges instead of gene
therapy. DDS is the method to deliver chemical materials to target cells
or tissues. The best examples are the molecular target drugs. In other
words, DDS means cell-targeting or tissue-targeting. These methods are
already used clinically and the efficiency is quite good. That is why
DDS will be developed more and more. However, it is impossible to
accomplish DDS without using antibodies right now. Will it be possible
to find chemical materials instead of antibodies in the future? I think
there are possibilities to find such chemical materials. However, it is
very difficult to find such chemical materials because antibodies bind
very efficiently the target molecules and affinity of between antibodies
and target molecules are quite high. Therefore, antibodies are the best
DDS tools right now.


4) Molecular target drugs

　In case of cancer therapy, molecular target drugs are attracted a great
deal of attention. This is a matter of course. I have been put forward to
this method is highly efficient to cure cancers. In case of treating
cancers, there are only two approaches which utilize the difference of
inside of cancer cells or outside of cancer cells. Many oncologists have
been doing researches about epigenetics such as signal transduction by
phosphorylations or methylation of genomes and so on, mainly inside of
cancer cells. However, even if we know epigenetics in detail inside of
cancer cells, it is useless to be utilized efficient DDS. In my opinion, if
the proposition is to cure cancers, the solution is to utilize the difference
of outside of cancer cells. In case of treatment of cancers, it is not
significant what happen inside of cancer cells. If the aim is to cure
cancers, DDS is the most important tool. Even if what happens inside of
cancer cells is a black box, it does not matter to cure cancers. When it
comes to cure cancers by DDS, antibodies are thought to be the best tool.
The target of those antibodies must be the portion of membrane proteins
which are outside of cancer cells. In human genomes, there do not exist
cancer specific genes. Therefore, certain amount of normal cells must be
destroyed. However, for advanced and end stages of cancer patients,
such kind of side effect will be permitted, because the aim is to save
patient’s life. Even if we know all epigenetics inside of cancer cells, will
it contribute to cure cancers? I do not think that doing researches about
epigenetics inside cancer cells are not significant. However, in case of
treatment of cancers, doing researches about inside of cancer cells are
not significant to cure cancers. Compared with cancer cells and normal
cells, we will be able to find highly expressed membrane genes in
cancer cells using results of microarray in NCBI or other official
databases. In this case, the products of those highly expressed
membrane genes are suitable targets of molecular target therapy using
antibodies. It is possible to produce hybridomas against the portion of
outside of those membrane proteins in cancers. It is possible to produce
single chain antibodies (ScFvs) from hybridomas which express those
portions. I determined the amino acid sequences in variable region of
ScFvs against Prostate Specific Membrane Antigen (PSMA). ScFv is
monovalent. However, making divalent human type antibodies, these
antibodies must be used as molecular target drugs. The important points
are to select the appropriate portions of membrane proteins in cancer
cells. Furthermore, several types of hybridomas must be produced. In
addition, it is possible to predict three dimensional structures of proteins.
Therefore, preparing several types or peptide antibodies on the same
time is safe. I experienced that more than 30 types of cDNA were
emerged to determine cDNA sequences from 4 types of hybridomas by
using RT-PCR. I translated those cDNA sequences into amino acid
sequences, but still there were more than 20 types of amino acid
sequences in ScFvs. I made my mind to select 5 amino acid sequences
and tried to make ScFvs. It was very difficult to prepare 5 types of
ScFvs on the same time, because ScFvs making from bacteria were very
fragile. I spent one and half year to produce 5 ScFvs on the same time
because I needed to determine the best condition to produce ScFvs. To
my surprise, 5 types of ScFvs had the same affinities against target
proteins. In my opinion, if there exist several types of amino acid
sequences in variable regions of ScFvs, all ScFvs will bind efficiently
the target portions of proteins. I experienced any difficult steps to
produce ScFvs and I have know-how to produce ScFvs. I try to
collaborate with many pharmaceutical companies, but I have not been
gotten good responses from them. However, it is easily possible to
select suitable membrane proteins as targets of molecular therapy drugs,
surveying NCBI and other official databases. The molecular target drugs
using my thought will be efficient to early stage to end stage cancer
patients. Therefore, for those patients, molecular target drugs using this
method will be the good news. In addition, I think that these molecular
therapy drugs will be also efficient to auto-immune diseases.

5) Regenerative medicine

　The most significant problem in regenerative medicine is
carcinogenesis. If regenerative medicine were enforced, results of
carcinogenesis will be known in 20-30 years from now. If patients want to
accept regenerative medicine to improve their quality of life (QOL), it will
be difficult to stop them regardless of carcinogenesis. In my opinion, if
regenerative medicine were enforced, I do not think that stem cells go to
only target tissues. As a result of this condition, a whole body will be
suffered from carcinogenesis. However, if patients want to accept
regenerative medicine to improve their QOLs regardless of carcinogenesis
and other clinical risks, regenerative medicine will be performed with
thorough informed consent. In my opinion, the most suitable cells for
regenerative medicine are germ cells. Because germ cells keep intact
genome sequences. However, it will be difficult to produce a whole tissue.
Even if intact cells were used, mutations are unavoidable in the step of
DNA duplication. Therefore, it is logically difficult to produce a whole
tissue without DNA mutations. That is why it is not realistic to produce a
whole tissue. However, even if it were impossible to produce a complete
whole tissue, it is useful to improve function of tissue. It will be possible to
improve cardiac function to transplant stem cells into a heart which were
suffered from myocardial infarction. It will be possible to improve brain
function to transplant stem cells into brain which were suffered from
cerebral infarction or cerebral palsy. Hence, according to diseases,
treatment must be changed. For cancers, DDS will be mainly used and for
dysfunction of tissues, regenerative medicine will be mainly used. In my
opinion, in case of regenerative medicine, the goal is to improve
dysfunction of tissues. I have a great interest to improve brain function in
Down syndrome patients. However, it is unclear if regenerative medicine
were really useful to improve dysfunction of brain in those patients.


Chapter 6. What is life?

(Proposition 1) What is life?

(Proposition 2) Is it possible to make mathematical formulas to describe
life phenomena?

Do there exist solutions for these two propositions? Systems biology,
nonlinear science, phase transition, the quantum theory, complex systems,
self-assembly, chaos, bioinformatics, biophysics, biological physics,
chemical biology. Among these academic fields, the point in common is to
try to make mathematical formulas to describe life phenomena. Making
mathematical formulas is the thought based on mechanism or physicalism.
Let us assume that life phenomena were able to be described by
mathematical formulas. I explain some counterexamples. 1) In that case,
life phenomena in the future must be able to be predicted. However, it is
impossible to predict life phenomena in the future. It is unknown when
human beings become ill and what human beings think in the future. 2) If
life phenomena were able to be described by mathematical formulas, life
phenomena must be mechanical. Do machines repair their troubles by
themselves? If machines break down, machines continue to be out of order.
However, if human beings catch cold, it is cured in few days by themselves.
This is a proof that human beings are not machines. 3) If life phenomena
were mechanical, evolution must not happen. However, human beings have
been evolved. Hence, human beings are not machines. These
counterexamples are enough to prove that human beings are not machines
and it is impossible to describe life phenomena by mathematical formulas.
Even if it were possible to make mathematical formulas, it is limited in
only a small portion of life phenomena. It is impossible to describe the
whole life phenomena by mathematical formulas. Because life is not a
machine. Let’s go back proposition 1. What is life? I list up what are not
alive. Machines, computers, books, air, water. These are not alive. On the
contrary, I list up what are alive. Bacteria, yeasts, plants, insects, animals.
These are alive. What are common factors? 1) These are made of cells. 2)
These have the ability to survive and leave offspring. Hence, the solution of
proposition 1 is things which are made of cells and have the ability to
survive and leave offspring. The uninterrupted process to survive and leave
offspring and die. This is life!