Okay. Good morning, everyone. It's very good to see so many of you here.
This is the second sort of theoretical physics morning that we've we've run.
I noticed a couple of people who were present at the first one, so they obviously weren't completely put off by it, which is great.
So so this, this, this is something slightly different. I mean, when I was a graduate student in theoretical physics, which was a while ago,
you know, it was particles, it was things going on in semiconductors.
Hall was still doing plasmas. And and then there was sort of hard, complicated astrophysics problems.
And what we're going to be talking about today is something which is new from that point of view.
And and the whole topic of biological physics is really emerged over about the last 20 years.
And it's now become something which is, you know, mainstream business for big physics departments.
So if you go to most big physics departments, you'll find that they have some kind of a biological physics.
But it's still relatively small because it's it's growing.
You know, there are many fewer people here doing biological physics than there are particle physics, for example.
But but as time goes on, you know, the relative proportions will change.
And it's an extremely light, like any neat, completely new area for theoretical physicists is sort of very exciting because,
you know, there are lots of easy things to do. There are lots of things nobody's ever thought about before.
There are lots of things which are actually amenable to the represent and so attacked by the methods of theoretical physics.
But, you know, nobody's ever tried before. So so you're you're in completely and completely new territory.
So I think this is a you know, I think this is a fascinating topic.
I think it's it's a topic which will become increasingly important in the you know, in in this in the century.
And I think we're probably only only just at the beginning of the applications of biological physics.
You know, to real world medical problems, for example. So I'm very glad to see see so many of you here today.
And so now I and welcome once again and I'll pass over to Roman, who's going to give the first talk.
Okay. So good morning, everyone. My story and I'm going to tell the whole thing as a story so you won't see much technicalities in my talk.
It will be basically trying to to to paint a picture about the kind of thing that well,
the three speakers today and many physicists these days are beginning to to be interested in seriously.
So the story starts from Erwin Schrödinger, who towards the end of his career became interested in biology, in fact.
It was. Basically he gave a series of talks when he was in Dublin, I think it probably was after he moved on, after his very brief tenure at Oxford.
And then he wrote this book based on those lectures.
And on the first page of the book, he basically poses this very simple, fundamental question,
which is how can we describe the events in space and time to take place within the boundary of a living organism?
And that seems a very simple question, but in fact, it's very fundamental.
And, you know, you can say, well, this is not really a helpful question because we can ask the same thing about, say, a.
Sort of a chamber which has an ideal guest in it.
Can we really track or chase individual atoms and molecules and is it really useful to do that kind of thing?
And we know that we have developed physics so that we can stop worrying about those details.
We can average over them and produce macroscopic quantitative information that we can test, we can probe and measure.
Just a brief note about the history because it was mentioned also.
So the book was written in 1944 and in fact, it was inspired by the work of another theoretical physicist,
Max Delbruck, who was advised by Niels Bohr to start looking into biology.
And he did. He worked on bacteria and the genetic mutations in bacteria, and basically he was very influential.
Having Schrödinger inspired by his work conjectured in this book that genetic information, basically DNA is something like an episodic crystal.
It has some sequence on it which carries the code of genetic information or the code of life, if you want.
And it was this book was published about a decade before the work of Crick and Watson.
So again, Francis Crick, who was a condensed matter physicist of the Cavendish, who basically put together the double helix structure of DNA.
So although this history of molecular biology only stands a chance in this building and in this audience,
I think it's based on a few factual statements.
And it's still worth remembering that physicists have had a very important role in what's so perhaps a more approachable way of rewarding.
This question is as follows Imagine you can.
You know, get over the chemistry beat and synthesise all the molecules that, you know, they should be in a living cell.
And then you put them together in the sack and make the sack of chemicals that is equivalent.
I mean, this is a hypothetical experiment is equivalent to what you expect a living cell to be made of.
Now, if you do that, then the question is, how can we go from this sack of chemicals,
which is basically just a collection of molecules to something which is a functioning living cell that does all the things that are living cell does.
And that's I mean, when you look at it this way,
I think it's clear that this is a question for condensed matter physicists to look into because it involves the interactions
of all these molecules together and then forming these organised structures that eventually will lead to function.
And we will talk more about that. But but I think it's clear that there is a very interesting story here for physicists to look into.
And we as we will sort of move forward in this story,
you will see even more how we can start to do sort of more practical things and not just a very hypothetical.
Imaginary sort of question. Okay.
So if there is a I mean, we are talking about a very fundamental thing here.
So like in physics, where we go back to our fundamental governing equations, you know,
shredding a question for quantum mechanics of Newton's equation for classical mechanics,
perhaps we should start from the most fundamental governing rule in biology, which is evolution, to try and answer these questions.
So, you know, can we basically start because evolution tells us the sort of dynamical rule, if we have something we can,
you know, take it one step further and see how it evolves with time in terms of complication.
Now, the problem with that approach is that you there's an arrow of time associated with evolution.
You cannot really run evolution backwards and say, okay, I will sort of go backwards in time until I reach the simplest possible form of life,
which is probably, you know, just made of one or two molecules.
And then I will work my way back over that.
There is this notion that evolution only propagates in the in the positive direction, and that's from the theory aspect, if you want.
So so this is thinking about evolution in a theoretical sense.
In terms of the evidence that actually exists.
The story is even more interesting because if you look at this map, you know, you can call this the cosmology of evolution.
Life apparently started somewhere around 3.8 billion years ago from a simple form of life, which is called the last universal common ancestor.
And then all forms of life have evolved from that through evolution and led into things,
you know, like simple bacteria all the way to very complicated mammals.
But the problem with, you know, trying to incorporate this way of thinking in terms of evolution with that's cosmological math is
that the first living cell is pretty much the same as any other living cell that you would find.
And that's the problem, because that means you cannot go backwards.
This is basically emphasising what I just mentioned in the previous slide.
You cannot simplify things by running evolution backwards and say, okay, now I'm getting to two very,
very, very simple forms of life which is made of one or two types of molecules.
In other words, we are forced by the evidence to think of life as an emergent collective behaviour which can only exist once, you know,
a large number of things put together their efforts and basically come up with this emergent behaviour which is,
you know, pretty much is going to be the same as any other form of life that you can find.
And this, incidentally, is something physicists might be able to help with,
because physicists have a lot of experience with basically this kind of emergent behaviour.
They have thought about phase transitions and macroscopic behaviours of materials and
found things that you could not really trace back into individual molecular details to.
Emphasise my point a little bit further. I will go back to the history of magnetism.
Just a very brief slide on the transition from power magnetism to Ferro magnetism should be familiar to most of you.
Basically, we say if we have a piece of magnets, a macroscopic piece of material,
you can find these small microscopic spins as the individual elements in a very simplified theoretical picture of the
individual elements that make the material in the most simple form of this model that is called the ising model.
You can think of this spin as only having two degrees of freedom spin off or spin down.
If the spins don't talk to each other at all, the system will behave in the paramagnetic sense,
in the sense that if you apply an external magnetic field, they will align normally without a magnetic field, there will be thermal fluctuations,
which means on average you would have equal number of spin offs as I spin downs and on average you will have no net magnetisation
if you apply an external magnetic field to this thermally fluctuating macroscopic collection of microscopic spins,
you will impose a bias. Things will become slightly biased towards spin up, let's say compared to spin down.
On average you will start seeing a magnetisation.
So the point I was talking about before was this point that the origin zero magnetisation zero external magnetic field, and now I'm running it.
I'm running along this blue line here, producing an magnetisation, which is linear in the external magnetic field that I'm imposing.
Ultimately, if the magnetic field is strong enough, I will align all of the spins and that means this will saturate somehow.
So I cannot go linear forever. This is what we know as power magnetism now is the spin start to talk to each other and this is something local.
This is an interaction between two neighbouring spins that maybe they will gain an energy of minus j.
If they align parallel to each other, then there is this possibility.
If J is stronger than a certain critical value,
that when you start from the Magnetised state in which you apply an external magnetic field and you reduce the magnetic field to zero,
there will be a residual so-called spontaneous magnetisation in the system.
So that's a decision made by all of these spins collectively to pick up an orientation and magnetise all in that direction,
despite the fact that there is no external magnetic field guiding that or imposing that,
and that's known as spontaneous symmetry breaking because they could basically pick spin off or spin down one of these two orientations.
So have. This is a very interesting phenomenon because basically it shows us how an emergent property in a macroscopic piece of material can come
to life just because of the local interaction between them and without anything exposing externally imposing this behaviour on the system.
Incidentally, this model was solved exactly by large Gonzaga on the same year that Schrodinger wrote that book.
Now, this is a very, very simple system.
I'll talk a little bit more about emergence on the next slide.
But before going to that slide, I would like to draw your attention to this sort of critical curve in between the red one,
which is which corresponds to when the coupling g is exactly equal to the critical value.
You can see that that's to sum something in intermediate between the paramagnetic and the magnetic behaviour.
It has a singular behaviour in the sense that when you apply the extent of magnetic field, you start seeing this very,
very rapid or very sensitive response to the external magnetic field, almost divergence response, because the slope here is these 90 degrees.
And so a little bit of magnetic field applied externally could excite a very sensitive and
large response in the system and that's the kind of behaviour which is going to basically.
So we will find other types of systems that behave like that.
And that's a very interesting, it has some fundamental implications on, on the,
on the behaviour of the system and that's something to to look into if you want to understand it.
Okay. So imagine the way I described it.
As I said, this was a very, very simple system.
If you look at more complicated examples, you will see that in fact in in an emergent behaviour,
it's not always the case that you can identify features in the behaviour that you see in the system, in the microscopic elements.
For example, think about the phase transition between gas and liquid and solid.
When you look at the solid made of the same molecule, it has a different kind of let's say a different kind of mechanical properties.
It can stand shear stresses, whereas a liquid cannot.
Yet both of them are made of the same molecule.
So you cannot say that if I choose that particular molecule, the macroscopic imagine behaviour is going to be affected by it.
Typically they will have these sharp onsets, very sensitive response and phase transition that will basically lead to macroscopic phases.
So you will, you will go from one macroscopic behaviour to another macroscopic behaviour and also something which is quite common is that we
cannot keep track of all the details in systems that want to study when we want to basically focus on the emergent properties.
We need to find ways of minimising the degrees of freedom we put into this
model and basically just keep the essence so that we can describe the system.
But that doesn't mean that the details are not important.
For example, when I built and ising model for a magnet, you know, I think I understand what the phase transition means.
That doesn't mean that I can answer the question, for example,
whether one type of atom can make a magnet a ferromagnetic or another type of, for example.
But if you if you look into those details, eventually you can make a connection.
For example, you can make a connection between those details and the value of that coupling constant j that I had in my previous case and say,
okay, if I have this particular type of material, J will be strong enough to give me the ferromagnetic transition that I need.
Or in more complicated examples, for example, superconductivity, you know, again, you will have some kind of macroscopic understanding of it,
but that doesn't mean that, you know, that the details about what compounds the superconductivity, etc., is unimportant.
So the question is, can we do something like that for biology?
And I emphasise this point about details because that's the first place that physicists hit the wall when they try to approach questions in biology,
you know, get overwhelmed with all these details and immediately we propose these really simplified models and the biologists say, you know,
you are too naive because in biology details matter and you cannot build in the model which is like an ising model and describe life.
You know, that's not going to happen and. So, you know, we need to educate ourselves in the details.
But as I said, it's going to to to be something like the question of self connectivity.
Ultimately, we need to be able to find a description which is generic enough that will overcome this barrier.
Okay. Let's go through the the features of a living cell that we want to describe physically.
And and let's actually not worry about the names because, you know,
that's something which is always a barrier for physicists, you know, remembering these names.
And it for our purposes, they don't really matter too much.
So let's just see what a living cell is made of and what kind of properties we we should expect to be able to describe.
So first of all, a cell needs to keep to shape.
It needs to have a structure because it's made of soft material, it's made of polymers and, you know, things that that bend easily.
And actually that's on purpose as well because living systems work basically based on units of cables.
So that's the thermal energy and they need to be able to deform and take advantage of energies in that level.
And that means they have to be soft if you make a living system out of iron or carbon sheets or graphene and so on,
you know something which is or I meant to say a diamond, it's not going to be able to function because it cannot deform easily at all.
It has available its units of cavity. So the way it does it is basically it forms these sort of set side the skeletal structures,
these filaments that form bundles and then these bundles basically make a backbone which holds the the overall shape of the cell.
There's also some element that's keeping the boundary in shape.
If it's and in fact, this is not a static structure.
There are little motors in place that can deform the cell if it's needed.
For example, if it if there's need for global motility or deformation in response to some environmental signals, then there's energy requirements.
And basically most cells live on universal currencies of energy.
And that's a very interesting notion as well. So ATP molecule, for example,
it's an energetic molecule which is made in these factories where sugar glucose is
broken down and are complicated chemical reactions basically eventually leading
to this molecule that has around 12 KB of energy and then the entire cytosol is
filled with this energetic molecule and then any anywhere that's basically a,
you know, a chemical reaction or something is going to take place, a mechanical activity that requires energy.
They will have access to this universal currency of of energy, and they will break down this molecule, ATP, into two components and take the energy.
And those two components will make their way back to the energy factory and will
be put together back into the universal currency and again released for use.
So somehow there's a notion of a cycle in the system because there's also economy in the in the form of material that it uses.
It's true that it has basically a lot of input and output of material with outside,
but it's not a very economical way of living if it wants to completely import its energy source and always just turns it into waste and and sort of
dispose of that in instead what it does is basically it circulates this form of energy inside by basically importing simpler forms of of energy,
let's say chemical energy or in the case of green lights and so on.
Then there's. A lot of function that is going to happen inside the cell.
And that function requires these agents. I will describe them later.
They are proteins and these proteins are synthesised on order.
So if a function is needed for some reason.
A protein needs to be synthesised for that function and the code for that is stored in the nucleus of the cell here in the DNA.
So that's just a a repository of or or sort of a storage place in which this code can be found.
And then very close to that, because you need to have access to that, there are these chambers that are where the proteins are made.
So the code is read and then turned into this disposable agent.
All of that requires raw material and then it will produce waste because it's chemical reaction.
And that means you need to have some kind of transport system, which is basically not left to diffusion.
It's guided by those sort of cytoskeleton structures.
So there is a track connecting the centre of the cell to the boundary.
And then there are molecular motors that walk along it in a very controlled way,
carrying these cargos that basically have the raw material on the way in and the waste material on the way out.
The materials factory needs to be in the form of these convoluted chambers because you
have a lot of reaction going on and you don't want them to interfere with each other.
So you need to make these chambers the separate things.
And also, if you have chambers in which chemical reactions take place, you can drive the system away from equilibrium.
And that's something I will explain a bit later more easily, because you can just remove and incorporate these politicians.
And that's the classic when we teach that.
I mean, it's the classic thing that we do is we talk about free expansion of gas and so on,
and that's the type of idea which is used in the design of these chambers, because they they basically evolve with time in a very dynamic way.
So this is the picture of a living cell that we will need to take away.
And the idea is to try and basically understand all of this using physics.
So just to summarise what we saw, we saw a hierarchical structure both in space and time,
time in the form of these cycles and in space in the form of these self-assembled structures, the sort of membrane chambers that I showed.
Etc. The whole thing is very precise, despite being, you know, fluctuating all the time.
This is room temperature, a lot of stochastic beauty, and yet there is precision down to the molecular detail of the sequence of the DNA,
which is rather than transformed into the sequence of the amino acid, which is turned into a protein which will go and function somehow.
If there is a mistake, it will be corrected. So there are even error correction mechanisms.
There's a high flux of material both in and out and also energy.
So this is a very non-equilibrium system, highly non-equilibrium.
And we will basically talk about that in more detail. And as I said, there's this element of economy because the cell needs to be able to use its.
You know what it has available economically.
So many of the building blocks will have multi multiple functions and these multiple functions will basically happen in different times.
So for example, the building block will be when the cell is dividing.
Everything is dedicated to the cell division, which is a very important stage for the cell.
And then when it's not dividing, the same building blocks are used in a in a different function.
And I also it's interesting, the cartoon that I actually showed doesn't reflect this, but cell is in fact,
not a sort of bubble in which one or two things are moving around in a in a random and very dispersed fashion.
It's a very crowded environment, and yet it's very agile.
And these two are not you know, it's not trivial that they can go together.
And we will talk about that. But again, the idea is to understand these physically.
So just to give you one example about the last point that I mentioned,
let's look at how DNA is stored inside a living cell and just putting a few numbers to to have an idea about the situation.
So. Human DNA is of about a metre in length and the radius of of DNA is about ten nanometres.
If you just multiply a metre and two factors of a nanometre to calculate the actual volume of DNA that you have in every single cell,
you get ten to the -18 cubic metres. And if you turn that into a sphere that volume, you get a micron for the radius.
And that in fact, is the radius of the nucleus of the cell, which is enclosing that DNA.
And that means basically DNA still pretty much at its close packed density inside the nucleus of the cell.
And that's quite surprising, because if you think about it, this is a storage device.
So how do we make storage devices?
We make typically two dimensional matrices, and then we use the third dimension to go and have access to that point.
Yet the cell has basically this close packed, three dimensional spherical structure,
and it has to have access to every single point of it as and when it needs.
And that's a very, very difficult process.
But yet it can achieve that. And the way it does it is by using, again, hierarchical structure and dynamics.
So this is not going to be a dead, you know, completely jammed, although it has the consistency of a chewing gum.
If you if you push it and press it, it's not completely dead on and on accessible.
It's actually quite easy because it's dynamically accessed.
So, you know, there's a lot of clever. Mechanisms that are ongoing.
Okay. Now, what do we know, you know, from physics that we can apply to these systems.
Basically, the thing we know best is equilibrium, statistical physics.
When we want to describe the behaviour of a few things that interact with each
other at room temperature and form these collective structures and equilibrium,
statistical physics tells us that if we know the interaction potential between these molecules that interact with each other,
we can basically predict their collective phase behaviour.
For example, if you think about the Linear Jones interaction potential that has basically three parts,
that's a typical interaction potential between, say, two molecules when they are very far from each other.
It's it's very, very small when they get close to each other.
There is an attractive element to Indiana Jones potential that comes from Panda,
both interaction, which is the fluctuating dipoles in the molecules and atoms.
And then when they get too close to each other, there is an excluded volume part and that's because of Fermi exclusion.
So the electrons cannot really penetrate each other and that keeps them apart.
So if on average the distance between two molecules in a system is in this range, we will end up having a gas dilute form of, of our, of our matter.
If on average the distance between them is around that minimum energy attractive, well,
we will get a liquid which is a very dense form of matter, but but very agile, very dynamic.
And then if they get too close to each other so that they will feel the excluded volume part, they will form a solid if they can.
If they have enough regularity, if they don't have enough regularity, they will end up forming a glass in a very jammed structure,
which is which is, you know, behaves like a solid, but it's not completely ordered in terms of the lattice structure.
We do have face separation and sensitive response of the type I just described in the ising model.
But there are problems. And the problem is basically it's very simple when you have a phase transition in equilibrium.
So this physics of the phase that you get is macroscopic, which means that, you know, if you have a, say, liquid gas coexistence,
you get a macroscopic phase of liquid coexisting with the macroscopic phase of gas you can never have in equilibrium a system with microstructures,
with the length scale, which is of the order of, let's say, a hundred nanometre micron,
and basically remains in that scale dynamically and maybe in a few places.
Same goes with temporal structure. If the phase transition is triggered,
it goes all the way and you get the macroscopic phase in the new phase when say you change a parameter and you cannot get a system which oscillates,
let's say, between two things or has a temporal structure in the form of, you know, changing between different states, let's say, as time goes on.
The sensitivity you can have is controlled by macroscopic size of the system.
So if you basically if you have a system which is small,
then the response you can get from it is not as sensitive as, let's say, a macroscopic system with with larger size.
So that degree of sensitivity is controlled by size and in living systems.
This is not the case. Also, I mentioned the last point about dense structure.
So basically if we put together everything we know about equilibrium, statistical physics,
we expect the interior of a cell to be a completely jammed completely that structure.
So in conclusion, equilibrium is is dead.
And if we want to have something which is, you know, not dead,
we need to bring in something else which is basically going to drive the system away from equilibrium, something you can call magic in quotation.
Or another way of putting it is living matter is is active in the sense that it
has a mechanism to go away from equilibrium in a continuous way all the time.
The system basically is driven away from equilibrium and in a controlled way, and it does that via these agents that are in fact proteins.
So these are the things that basically are synthesised in the system.
And remember, the code that tells the cell how to synthesise these is is kept in the nucleus of the cell.
They can have different kinds of function and drive the system away from equilibrium in different directions.
It could be mechanical by exerting forces. There are proteins that act as motors.
And I mentioned the sort of transport mechanism and also the cytoskeleton changing the shape of the cell.
And that's a part of the activity. But the biggest the majority of agents in the cell are these enzymes, the ones that catalyse chemical reactions.
And the main business of a living cell is basically.
You know, these catalytic chemical reactions happening as and when needed, the consequences will be,
you know, producing and maintaining gradients that will keep the system away from equilibrium.
Let's say if you go to a mitochondrion, that's where ATP molecule is made.
You will have proton gradients that are maintained and generated actively by using energy from the source of energy that you have from outside.
And there are other mechanisms that will clearly create a non-equilibrium situation.
I mentioned again this sort of close actions, nature of the cell.
Again, that is going to be kept dynamic by mechanical activity, by by these mechanical agents.
There will be instabilities and patterns and dynamical order. And and basically these are the things that will.
Make sure that the cell can respond in a sensitive way when there is a small molecular signal.
It cannot rely on sensitivity of the type that I describe in a second order, in a phase transition for the magnetic system.
And all of these things are basically the subject of of the relatively new field of active self matter,
which is you will hear a lot more about it in Julius Talk right after mine.
Okay. Let's have a look at one example. The case of mechanical activity.
So the most important mechanical activity of any cell is division.
And in many cells, it's done through a structure that's called mitotic spindle.
You will have these cytoskeleton filaments formed from proteins called tubulin.
But again, no names. So.
So these filaments are formed and somehow they are attached to the DNA and why they are pushing apart this sort of interior of the cell.
They are also pulling apart the two copies of DNA at the same time.
And these copies are complementary.
So that means each of them can acquire a complementary second strand, which will create basically two independent DNA copies of the original one.
And all of this happens when the cell divides into two and eventually reaches a point at which it can draw the curtain and say, okay, you know,
this is one cell and it's completely separate from the other one and they can go away, not basically worrying about association with each other.
Now,
it's interesting that when you take that materials to the microtubules and the molecular motors and you wait for clever enough to do the experiments,
this was done recently in the group of Van Dijk in Brandeis,
and you can say that's putting together the same elements that you you purify and basically
make in the lab will create that dead jammed those pack structure that I depicted for you.
If you don't provide fuel, that's ATP concentration written up there.
That's at zero ATP concentration.
As you increase the concentration of the the fuel molecule,
you can see that this the structure starts to become dynamic and at relatively high concentration.
So minimal concentrations of ATP,
you can see that the same structure is completely dynamic and you can even begin to see similarities to to mitotic spindle.
So in a sense that's a collection of proteins that will self-organize given
the right condition into something which can do a mechanical task like that.
It is made of something which is intrinsically unstable.
And that's a very interesting point because if you want to have something which, you know, carries on relatively easily,
which is the business of of of living systems, it's very clever to run them on unstable processes that you you basically control somehow.
So so this is something which is unstable.
If you have a macroscopic system with these proteins, it will it will give you a turbulent and completely out of control structure.
If you keep a small enough subset of it, you can have a cycle in which you can control things.
And that's exactly or seems to be exactly what is happening inside of a cell that is dividing.
So in other words, there seems to be a notion that things will be kept dynamic yet in control through the instability,
and also that will somehow select the length scale that's a fundamental ruler for the system because it knows what lengths,
again, to choose such that you will have the right balance or combination between instability and, you know,
and dynamic nature and the control that you want so that you can be sure where you end up with the process.
Chemical reactions are similar.
So you have these agents, so called enzymes, they basically catalyse chemical reactions where needed and this is how they work.
So basically you should think about a typical reaction in the cell being like going from this state,
which is a higher energy state to the lower energy state. So it's something which is ultimately designed to to happen,
but over a very long period of time because of this barrier which is basically put in between.
So it's something which is ready to to act, but it's waiting for the order if you want.
And what the enzyme does is when it comes along to the right location, it will lower that barrier.
So it's a mechanism, again, to have something which is it has the drive but is being kept away from what it wants to do unless the right time.
Basically the door is open and the system can make the transition going from one state, high energy state to the lower energy state.
Ultimately, this will be put back in in place in another place in the cell when the system is prepared for the next round as as we talked about it.
And that's very interesting because you can control this.
So remember the code that is used to synthesise an enzyme that will basically appear late where it's needed and do this task is stored in the DNA.
So that's a mechanism to program what is needed and what is not.
And things can change depending on basically the requirement of the signals it get from the environment, etc.
And another interesting aspect of this process is that it leads to a nonlinear process,
because when you need the the enzyme at that location for that particular chemical reaction, it means that in the sort of rate equation type level,
the rate at which this reaction will happen is proportional to the density of the enzyme and density of the
chemical or the probability of finding the enzyme at that location times the intensity of the chemical.
And that means you have a nonlinear process in in your system and nonlinear reactions.
Especially when they are. Complemented with the reverse reaction, which is the concept of economy that I mentioned earlier, can lead to cycles.
This is a very genetic phenomenon that when you have a cyclic and non-linear reaction,
they can they can create oscillations and self-sustained oscillations.
And in fact, cycles are ubiquitous in living systems.
For example, the Krebs cycle, which is quite complicated.
It has either of 17 elements involved and other cycles of.
It's it provides a mechanism to select an intrinsic frequency.
It's like a clock, because basically there is a natural selection of the function of the parameters in the system.
When coupled with diffusion, it can provide also spatial information.
It's known that reaction diffusion can create patterns like Turing patterns, and that will also give you a mechanism, for example, to find, you know,
the right place for the middle of the cell to divide and, you know,
things that are quite they need to be done quite accurately, that there are these natural nonlinear mechanisms for them to.
To to perform those activities.
And it's interesting that nonlinearity also brings in robustness,
because there is this concept of of a limit cycle in this sort of field of dynamical systems.
And that's, you know, if you have a dissipative process which has a, you know,
has an equilibrium end point, if you start from a number of initial points,
initial conditions, let's say in the configuration space, you will all always end up in that fixed point, which is where the equilibrium is.
In an oscillating system like that, you could have a a closed loop which undergoes oscillation for the system,
which is basically the end point of any starting. Initial point for the process.
So somehow you have this ability to create stability depending on the initial conditions of the system.
Okay. So just to sum up, it seems that from the point of view of condensed matter physics,
you can say that living matter is an emergent collective phase of active self matter.
It's controlled basically based on the information which is available to the
to the cell to perform these chemical and mechanical activities via proteins,
these agents that it synthesises. And it seems to be able to keep things in a robust way in this non-equilibrium condition.
So does that mean that we know everything about a living cell and we can go away and just do it?
The answer is no, because in fact, things are not obviously as easy as I described here.
There is a problem. And that problem, it has to do with the hierarchical structure of of living systems.
So what I described so far is that you have this information, which is almost like a sort of fixed set of rules that is embedded in the DNA.
And then we just go to the information and get instructions and come back and perform this activity, let's say.
But it's not quite as simple as that, because all of these things have influence on each other and in particular information itself
can get influence from the environment and from the mechanical and chemical activities,
which it basically is regulating. And it could change.
And this is not something we have experience with in physics because, for example,
when we when we make this course grained description of, let's say, a piece of magnets,
ultimately this is only useful when we know that the microscopic detail, which is going into some tiny element at the molecular level,
is going to be unimportant at the level of the sort of effective emergent theory that I'm describing.
That will just give me some kind of you know, it will affect one of the parameters that I use.
But in living systems, it's not like that because it's tiny molecular detail.
Say something which happens to a protein can actually change the entire genetic
code that is stored in the cell and is passed on to the next generation.
So there is a dynamic process and if you want,
this is equivalent to saying your imagined level description could change because of the molecular detail.
And if you cross grain over everything and get rid of all those molecular details, then there is no way you can keep track of this kind of change.
So this is quite a challenging problem for for us physicists and I think it will keep us busy for quite a while.
And I think it's a good place for me to stop. And thanks for your attention.