As. So start, Jim, by thanking you for coming here.
And so I've asked the my colleagues and the students in the department to ask some questions, so they give me a list here.
But before we get into this, this, too, just wanted to ask you, what attracted you to the academic world?
Was it sort of a family history or when did you decide this is what you wanted to do?
Well, it certainly wasn't family history, because if I hadn't had polio, I would have had to be a plumber and leave school at 14.
Like all my family. And I went on to school, decided I wanted to go on to university.
I never actually thought of academia to begin with.
And at the end of the third year, I got a summer job, but an aircraft company called Fairy Aviation.
And that was actually a major influence because I found out of a research group of I think it was about seven, six of them were unbelievable.
I wouldn't have accepted them at university, never mind have them design aeroplanes.
And one of them was I just thought I would never want to spend my life doing this sort of thing.
So I went back and I just found academic life kind of attractive.
And it was in St Andrew's, which is such a lovely place.
This certainly was then. And so after doing this in mathematics with a kind of ordinary degree in physics or natural philosophy,
in those days I decided to do a PhD, and that was it.
When I finished the Ph.D., I managed to do this the work in a year.
They let me go off and take a job for a year.
So I got a lectureship in Durham University and King's College, Newcastle,
and then I had always wanted to go off to America and that really took off from there.
Okay. And you've sort of come back and forth between the UK and America.
So why has that been? Well, I think one year I don't know how many times,
but I went to Harvard for and then I saw my family pressure, I suppose, really brought us back in 1959.
And I went to University College London, which was very nice.
And then I applied for a job in Oxford and got a fellowship at Hertford.
And the excessive teaching was just too much.
I couldn't do any research, so I handed in my resignation after a year to the gross irritation of the of the principal,
and then went back to America in 63 and was back there for University of Michigan and then at New York University.
And then I decided one really missed Oxford and the job came up in one of the colleges I liked,
namely Corpus Christi, and I applied for it and got it.
It was very nice, very informal interviewing board, and they offered me the job before I could get to the lodge, which was nice.
Yeah. And then of course, in those days you were working in fluid mechanics and then you went into mathematical biology.
So what prompted that? Well, actually, I switched into biology in the early sixties, in effect.
It's just that there's a fluid dynamics test I just found, you know,
working out the third or fourth fashioned topic term and in flow past a semi infinite flat plate was just not very exciting.
In fact, I didn't know the point of it. It was just mathematical. And when at the University of Michigan,
a professor of biology came to see if I could help to make a model of how oxygen diffused into entropy nodules.
And so I got involved in that. And but he I was in an engineer engineering department and as a professor of engineering mechanics.
And he thought he thought I was a student.
So he offered me five. And no, it was anyway, we, we started it.
We worked together and. And that was really, I think, the start of it.
And Michigan, then a professor of anatomy, was working on, uh, pilot ejection seats and back injuries.
And he wondered if I could make a model of how the injuries occurred and what they could do about it.
And so, along with a colleague, King Liu, we produced a model of really, if you have an accelerating seat, then it sends a wave up the spine.
And because the spine is curved, we modelled it as a wave that kind of broke like a wave and uh,
on the shore and that sort of took the vertebrae and just put them aside.
But it was the sequel to that when he, he said they'll do some experiments.
And I wondered how they could do an experiment with somebody being pushed up in the sphere on a chair and maybe have their back broken.
And they said, well, they did it with they did it with cadavers from the down and out in Detroit and strapped them to
the elevator chair and dropped them down the elevator shaft with strange gauges down the back.
And he found that indeed it was some kind of wave.
I mean, the work we did, it wasn't that quantitative.
It was more qualitative. And then I had been involved before and fluid ization and the theory developing a theory of fluid ization,
which was the last thing that I found interested in fluids.
And then by the roughly I suppose in the sixties I decided I didn't want to do fluids
anymore and then started to get more and more involved in biological problems like oxygen,
diffusion and muscles and why we didn't get cramps more often and why sea snakes didn't get the bends, just a variety of things.
And when you moved into that area, you were already well known in Fluid Dynamics World.
So what did those people think of you? Move. I'm not sure how well known I was, but certainly my first post-doc took me aside to lecture me on that.
I was wasting my time and all this rubbish in any way.
Biology is for girls, he says, which is so the know then.
It did take a while before people started to think that mathematical biology or ecology
or whatever one wants to call it was something worth doing for an applied mathematician,
you know. And so one of the questions that actually her, Ms.
Goodall, you asked was concerning that.
And he he wondered, did you expect mathematical biology to grow in the way that it has done?
Oh, yes. So I just thought the biology just was the subject in the general sense, including medicine and ecology and evolutionary biology.
I mean, it just seemed to me there were so many problems.
How could anyone not want to work in it if they are, you know, or stay with this queasy sort of non relative,
uh, in the world point of view, mathematics to just produce mathematics just didn't appeal to me.
Uh huh. And, and so one, one just, just being in Oxford at that time and certainly being in the universities I was at in America,
there was no pressure to do anything.
There was no necessity to. I mean, one applied for grants, but you didn't have to get them to.
And the bureaucrats, the bureaucrats were there to help.
Yeah. Unlike what seems to be the case now, and you mentioned that there was that scepticism when you moved into the area.
And so her Mrs. asking you, do you think that there's still that scepticism or.
Yeah, I, I think it's more it's more submerged.
I don't think that they're quite as open about it, but there's a lot of people who still think so, particularly in biology.
But the numbers, I think it's almost a question of age.
The biologists who. Brought up in an era where they didn't have to do any mathematics, they didn't have to do any modelling.
They did their experiments and that was it. Whereas now I find biologists, the really bright ones.
I mean, they want it all to be interdisciplinary because they think one can help.
Other people can help. And the evidence now, of course, is just overwhelming.
But at the time, there were quite,
quite a few biologists who were and I got lots of invitations to give talks to biological groups and the questions at the end,
a lot of them were very really they really wanted to know they weren't aggressive, but they wanted to know why.
Why should they bother? Yeah, in a sense, spending time with people like me.
And so one of the senior postdocs and research group Alex Fletcher was wanting is hoping to continue in academia.
And he asked the question of what sort of department do you see?
So somebody from a mathematical background who was working in math biology, where will they be sitting in, say, 30 years time, would you think?
Oh, I wish it would be me sitting there in 50 years time.
But if that's not possible, let's I think I think I'd rather sit in the mathematics department and because although it's not so,
it's not so crucial now with specialisation, but I would like to be able to work on whatever it was that I find exciting.
So if I was in the biology department, one might be, in a sense at least more constrained to work on problems associated with that department.
Yes.
Whereas I've been able to work with people and work on problems that cover a whole spectrum of the biological sciences and then the medical sciences.
So I am, I think the problem probably still in mathematics departments,
but I think biology departments will certainly want people to be in that group.
But I suspect they may be considered more a kind of there to help them rather than to for them to help
the mathematicians to work on original research that might not be related to the work in the department.
Yeah. Yeah. So I'm not sure what it will be, but certainly if I, if I was around at that time, I'd want to be in a mathematics department,
but one that had real applied mathematicians and not which is a place like Oxford.
Yeah. And there are not that many of them. Yeah.
And so moving on then to Professor Helen Byrne asked a number of questions here.
So from your start, your career, which piece of work you most proud of?
I think that they're not quite sure. I I've enjoyed a lot.
I mean, I liked working on animal patterns or how the leopard gets its spots.
Which one? Uh, the early on, I found it interesting working on why we don't get camp.
And this was with the biologist Jeffrey's women.
Um, maybe. Maybe because of Alan Turing and this reaction diffusion theory that was purported to really explain biological development.
And since it's been 60 years since his paper came out, it was only two years ago that someone actually found a chemical.
Yeah. And I just think of that as deferred gratification.
So it was it was good to sort of, in a sense, play games, to get patterns.
And so when George Foster came to spend six months in the Centre for Mathematical Biology, um,
we thought we'd try and develop a practical, experimentally verifiable theory of, uh, biological development.
And so we produced the, we proposed the mechanical theory of, um, development of morphogenesis,
and it was based entirely on quantifiable, experimentally determined, uh,
quantities like cells having traction, being able to deform the matrix within it, and then how to,
how they formed aggregations which eventually became bones and the developing limb.
And then we were able to do hypothetical experiments and we had a colleague, uh, Peer Albert,
who did experiments and they confirmed some of the predictions such that you could have a condensation,
it could move out and you could have something long.
It would be like that. We actually considered limbs like the humerus, and then it would bifurcate.
And what we show is that you can't get a tri fixation on the which was the reason for the title of the lecture.
You know, why are there No. Three headed monsters? Then it was applied to a large number of problems by you fill up of course with uh,
as the major figure in the, in the eighties and some of, uh, some of my other graduate students.
And we just were able to show that it really had a relevance in biology.
So I think it's a long way around to say. I think that's one of the things that, uh, I think, I really think has survived, I think will increase.
And I suppose when I wrote the book on mathematical biology in the late eighties, which is now into its third edition.
Yes. And still seems to be accepted as a as a textbook.
And and it covers a lot of the problems that I worked on, like sex determination and alligators,
marital interaction and divorce prediction, but a host of different things.
Yes. And certainly anytime I go anywhere, that that book is always on the shelf.
Oh, that's nice to know that. Yes. And so then the another question repellant, which you may not want to answer, is the other flip side of the coin.
Is there any work that you're not particularly bright? Oh, yes.
Yeah. Yes, it was when I at Michigan, I wanted to be back in the mathematics department.
So I got a I got a job at a New York University and New York University.
Uh, I, as you know, has the current institute where a lot of the people from Germany came and set it up for Quant, for example.
And there was a colleague there, Don Ludvig, who became a close friend, and he was on the pure side of applied mathematics.
And at lunch one day I said, You know, Don, you've never done anything practical in your life.
And he said, You've never. Prove the theorem in your life.
And so I thought, I'm going to show you. So I worked on a problem and wrote a paper.
And in it, there is a theorem. And I proved the theorem.
And it really had the papers.
I mean, I forgotten even the title, and I hope everybody else has a.
But the effect on Don Ludwig was he thought about it actually seriously.
And within a year, he had resigned from New York University, gone off to the University of British Columbia.
And he became the major one of the major world figures in marine ecology.
And so that paper. Maybe maybe I shouldn't be ashamed of it,
because it had the effect of really making Don move into a field that he found exciting for the rest of his career.
Yeah, there's other things, probably. But I've probably forgotten.
Yeah, I actually think this actually relates to one of the other questions that Helen asked, which says,
Do you think it's important to be able to prove existence and uniqueness in mathematical biology?
So I guess which also means like how important or sort of underpinning theory of mathematical of mathematics and mathematical biology.
Well, I mean, maybe I'm out of it.
I think it's got no relevance whatsoever. I mean, I I've never needed it.
Maybe the models should have had it.
But I found the models that I've worked on are based on intuition of what's going on and the process that I'm trying to model.
And so if the equations can capture that, then I think there's probably something there.
But whether or not the solution is unique. I mean, one would like it to be unique, but certainly in the case of digit development, for example,
or the growth of the humerus radius and owners and so on, small variations are there all the time.
Yeah. And so the solution is very difficult for the solution might be able to be proved, proved to be unique.
But if you start solving it numerically, there's always a there's always some minor variation.
And the initial conditions could be in whatever it is, a fifth place or whatever.
And that is going to change the solution.
So I think uniqueness well, existence is, is certainly a thing, but the proof of it has never really got me involved or got me interested.
I'd rather work on simpler models, which is what I've tried to do, that it be as simple as possible enough to capture the phenomena.
Yeah. And then view that. How do you view the presently?
There seems to be emphasis being put on very complicated multi-scale models, obviously comprehensive models.
Oh well no. I think they're I think they're important.
And I think it's probably what leads to much more specialisation within the people working in biology and medicine.
And I was just fortunate to get in kind of early on and where the models could be quite simple.
But Multiscale models, I think are incredibly important, but much more complicated mathematically, numerically, and they are certainly needed.
But I think in the case of some of the stuff I did,
like the diffusion of oxygen into muscles that combined with haemoglobin or myoglobin, the, the modelling was really very, very,
very simple and one could use some of the, the analytical work that I had worked on for quite a while,
mainly asymptotic theory and really getting approximations to the solutions where there is a small parameter.
Yes. And so I think I think that actually is a natural development that is important.
Yeah. Yeah. And did you have a role model when you were young, academic, academically or in biology?
Well, I guess it doesn't. She just doesn't specify that as a role model.
Role model, academic or non-academic. I mean, also.
Well, first, when I went to Harvard, George Carey at Harvard, uh, was one of the cleverest people I've known.
And he was interested in anything.
And he, he applied mathematical modelling to a huge variety of problems, not biological or medical.
And he believed in real simplicity as well as simple as you could possibly make it.
And I suppose that, George, I never thought of him as a role model.
He was a good friend. Yes. Yes. But certainly in as a student, I didn't really have a role model.
And that I mean, I liked my PhD supervisor, who was also a professional football player.
You know, in the syllabus, Mitchell said.
But he wanted me to be a numerical analyst, and I managed to figure out by getting an analytical so we could.
Yes. And I bet a lot of people have influenced me and I've been fortunate and meeting a lot of people who were very bright and.
But I think George Carey as is the one that kind of stands out.
Yes. And it's a rather gerben who's Royal Society Research fellow in the department
asked a question which also actually links in with one of Helen's questions,
which said, as you know, in mathematics of Fermat's Last Theorem, you have the Hilbert problems, etc., etc.
These are sort of holy grails of people. Yes, yes, sure.
Yes. Lives trying to solve. Do you think there's any equivalent in in biology, mathematical biology?
Oh, I think there's a lot like that.
I mean, I think we have I mean, the the whole business of genes, for example, I mean, unbelievably important.
But remember that my friend Lewis Wolpert, a developmental biologist who you knew.
Of course. Yeah. He said that when genetics is a subject finished, we won't know how to build a chicken.
And in a sense, in a sense, he's right.
The genes control the processes, but they don't actually do through the actual mechanisms, don't they?
Don't put the cells together and form cartilage.
Yes. And and so I, I really am not sure that's a kind of controversial sort of thing.
But it said that in 1900, David Hilbert presented his famous list of 23 unsolved problems in mathematics.
Would it be possible to formulate a similar list of inferential, unsolved problems in mathematical biology,
which is very mention one which is the the the mechanisms that lead to patterns within those.
There are a number of that type of questions.
Yes, I think I think there's almost fundamental questions that, like, could we create life without in some artificial way?
Yes. That really I mean, even if it was just an amoeba that we could actually make based on some modelling process, we haven't got there yet.
No, that's just right. And maybe eventually.
I mean, there is there's so many exciting new things going on in biology that we might we might stumble on it.
Yes.
But I think a lot of the research people are just because it's becoming so complex, all we can do is focus down the narrow tube to see their problem.
And I think the the fact that getting grant support is becoming so, frankly, irrational, I think that is detrimental to science in a major way.
Mm hmm. And when the Centre for Math Biology was started, I applied for again.
It was quite it wasn't a large application.
There were none of these ridiculous questions that one has now got to answer.
And they gave me the money and that was it. Yeah, I could do whatever I wanted with it.
I would meet somebody at a conference who I thought was doing interesting thing and I could see.
Why don't you come and spend a month or two months in the centre and we can cover all expenses
and they would come covered all the expenses and all I had to do was at the end of three years,
send in a report of what one had done with the grant.
And that that to me was I mean, the effect was unbelievably productive.
Yeah. All these visitors or masses of them,
brilliant people from around the world who just felt all that was essential was to do research and interact with other people.
And they didn't have to worry about this this ridiculous situation that the administrators have now introduced.
Yeah. And the government, of course. So I, I just feel that it's got to go back to that.
I think one's going to lose brilliant academics who will feel that it's not free in the universities anymore.
And the they will go into the outside world, which it's not necessarily been easy either.
But academia is not. Nothing like as attractive as it was when I started.
Yeah.
And I think that where, like, the Hilbert's problems are a sign of where a field is, well, mature, and you know what the fundamental problems are.
One of the exciting things about mathematical biology is that we still haven't
reached that level of knowing precisely what the problems are in a new way.
Oh, absolutely. That's what makes it very exciting to work in. But it's also, as you mentioned, one gets hamstrung by the grant system.
That is it. I think. I think an indication of the system is in, in America.
Many of the committees, uh,
the chairman of the committee or the chair of the committee quite often tend to be people who didn't make it research wise.
And this is a way that they feel that somehow that they're somehow moving in the big leagues.
Yeah. Yeah. And I found some of the people I met in that thing they one wouldn't want, wouldn't give them a job in the department.
Yes. And so I think their effect has actually been quite negative,
whereas certainly certainly in the earlier the people who ran these committees, uh, such as in the,
the National Science Foundation really where world class scientists applied
mathematicians who agreed to do it for three years because they felt it was important.
Yes. About the research giving. Yeah.
Whereas I think it just changed dramatically now and I think it's had a negative very negative effect in academia of academic research.
Yes. And in fact, your discussion about the early funding of the centre leads nicely into some questions that Peter Grindrod, whom I asked.
So his first question was what were the biggest hurdles in establishing a centre for mathematical biology,
research, funding, fellow mathematicians, outreach?
I guess you've really answered the funding question that you were able to get this funding that allowed you a freedom to do what you wanted to do.
Yeah, but I think getting there, getting the Centre for Mathematical Biology started in Oxford,
that it had the support of one or two people in, in, in the Mathematical Institute.
But a major figure was Dick Southwood or Sir Richard Southwood.
And at that time he was a Vice-Chancellor and he was incredibly supportive and helped to push it through.
Yeah. And then it was formally recognised or set up by the university and with the expectation that one would be able to get funding.
But that wasn't the condition.
It was genuinely wanting to help to set up a centre that was interdisciplinary and Dick Southwood thought this was very important.
And being, being a biologist himself, he, he approved that it was with both biology and the Royal Society.
Well. Few people in the Royal Society were supportive, but the society is still a touch focussed on discipline rather than interdisciplinary work.
And so it got started and it attracted then got some of the major people in the world
well who wanted to come and draw more people than the centre could accommodate.
Oh yes, yes. Yeah. And the students of course flocked to the course in maths biology because if you took mathematical biology they,
they saw how their mathematics could be used in the real world as and so the average class specialised.
Finally, if class size was around 9100 compared with some of the pure topics which had the size maybe ten in the class.
Yeah. And because these students they weren't all going to be academics.
Yes. They became they became really very interested in it and they remember saying, well,
we're in a we're going to develop a model for the spread of sexual disease in one country or another.
You've at that age, you've got their attention so vicious.
And so you mentioned about lots of visitors coming to the centre and this actually, John,
to Peter's next question, which was what do you think makes a good visiting scientist?
Oh, yes, I think it's somebody who well, if they're nice and friendly and not arrogant, of which they were during my time,
there were none like that in this in the centre but who are really genuinely interested in interdisciplinary work.
And it was one of the nice things about the centre,
the original building in the centre that you remember of course was that you went down into the comment room to have coffee with it.
There was always somebody there and there were the board,
the tables to write on and every time you went down they were talking about something and the
biologists then got known in the university and biologists would get in touch with me and say,
I'd like to come and talk about a problem, because I think it might be one might be able to model, model it.
And so a lot of them came and gave informal seminars to the group.
And then anybody in the group, visitors, students, post whatever, would then say, no, that's interesting.
And they would get together and then they would work. They produce a model and they'd produce papers.
And sometimes they were a little complicated.
I mean, one came about how if you mean they said if you were a medic, he said,
if you break your arm and your elbow, you know, how do you make a model how it all goes together?
Again, we weren't quite at that level. And I remember one pure mathematician came who I mustn't see who it is because he's changed dramatically.
He came. He wanted to said to me, Could he come and talk to the group in the centre?
I don't know if you were at that meeting.
Anyway, he came and he was a pure, relatively relative, pure mathematician and he wanted to hear about problems because then he'd be able to help him.
And it just happened that there were a bunch of experimental biologists visiting at the time and I've never seen anyone get such a hard time.
They they said to him, So, so if I describe what I'm working on, which is, you know,
animals see animals near the shore who can jump, what can you do about it?
And there was a humming and hawing and say, well, of course, that's very complicated.
And so he went off effectively with his tail between his legs and but interesting, he's now a significant figure in America.
Encouraging real mathematical biology was just another convert.
Yes. Yes. And and that actually leads onto the question that Peter had to some extent was that, um, nowadays, math, biology,
in those days you mentioned that this was one of the very few places it did mathematical biology,
but now it's sort of established in quite a few departments and quite a few universities are doing it.
You. Still think that it needs something like a special treatment or nurturing.
Or should we just say, well, it's actually no mainstream mathematics, let's just get on with it?
I think there's still a lot of prejudice right around.
I mean, like international prizes for mathematical sciences that is translated into pure mathematics.
Yeah. And so I still think there's always been, I think,
a feeling among pure mathematicians that applied mathematics and mathematical biology
is just grouped with it is somehow inferior because they don't prove theorems.
Yeah. And I think in development the, the conditions for rigorous theorems, they just don't exist in biology.
Yeah. I mean we if you weigh less than me or whatever, you know,
I mean there's just so many variations in everything biological that one just can't, one can't relate it in the same way to pure mathematics.
Yeah, I don't mean it's, it can't be useful, but I know very little that is which is.
But then that's probably an old fashioned view.
Other fields in math biology that you think should have happened sooner or, you know, or.
Well, I think medicine would have been the.
And the medical world just never, ever thought about it.
Yeah. And but that's why I got involved in the medical side from the medical people approaching me, which I thought were very forward looking.
And then in Oxford, because of the high table.
Yeah. System here, which to me is one of the most invaluable things in Oxford for promoting interdisciplinary things.
It's how I got involved in things like quantifying medication for obese patients based on body weight,
which you couldn't take, the obese weight you had to take.
Really. How do you how do you determine what the the kind of the real body is inside an obese person or things like prostate specific antigen?
Uh, food. Lots of people never heard about it, but it is a, it can be an incredibly good indicator of prostate cancer and the,
the number of medical problems, like many that you've been involved in, really benefit enormously from mathematical modelling.
Yes. And I just feel, you know, mathematics should recognise I don't necessarily mean mathematical biology,
but that this is an incredibly important area in the field of mathematics and that
I think its usefulness along with lots of other areas in applied mathematics.
Um, I think it would help if it was ranking, if it were recognised,
I think it would help to attract bright people into the field rather than just having them leave academia.
Yeah. Yeah. And so what advice would you have for a graduate student who's wishing to have a career in mathematical biology?
Well, I suppose I am a little prejudiced.
I think that you'd come to Oxford and be associated with the associated with the Centre for Mathematical Biology.
Um, but I think there is still more freedom in America.
There are just few places that you can actually do math,
biology and but certainly I still think it should be a mathematics department
because that could end up being like higher technician in biology department.
Yeah. And. And they would have less freedom.
Yeah. And I still think it's mathematics. Mathematics department, but forward looking ones.
And I think Oxford has always had applied and it's still got quite a ways to go, but.
So talking to a graduate students of Fred Hoffmann, who's a mathematical biology graduate student,
asked what you thought were the most exciting advances and experimentation from
the point of view of mathematical biology that might impact mathematical biology?
Well, I don't know. I think I think pattern formation and development is one, uh, the, I think in ecology and evolutionary biology,
it's a huge field and that there is very exciting work going on there.
And there's a lot going on in Princeton, where I am now,
where the graduate students are incredibly enthusiastic and they do their modelling and then in the summer they go off to Kenya, I mean Panama,
South America, they do their own experimentation, they gather data,
and the work that they produce is in the department is genuinely interdisciplinary except it's all done in the department.
Yes, the and they just have a very, very bright group of people.
And what's interesting is people who want to be graduate students in the department have to come to the department
for a week and they interact with the faculty and the graduate students and the postdocs and everybody has to see,
which is amazing. Yeah.
And if the student said, you know, this guy, you know, I'm not sure he would fit in, his chances of being accepted are extremely small.
Yeah. And which is why the atmosphere is so, so cohesive.
Everybody talks to each other and that's quite difficult to achieve in a in a department,
a mathematics department, such as in Oxford, because it's large.
And, uh, some people in the mathematics department, what they work on is more foreign than most biologists to me.
So I think it's, I think that is a problem.
And I guess with the things that you mentioned about data that you've been able to like get data on,
on tracking things or imaging which are spatial temporal data.
Yes, what these mathematical models are designed to try and predict.
So that's yes, I think that is incredibly important in the case of the work on obesity that I did here.
I mean, we talked about it as we tucked into high table food that drank this great line.
But the very simple model and the professor of clinical medicine at the time,
I said, well, it'd be good if we could have some data from real patients.
So he got ten, uh, obese patients who had a thing called hyper lactate tibia where which is quite dangerous,
and they wanted to quantify the level of medication, and so we had to determine the weight.
And so we came up with the idea of injecting lactate here for 10 minutes and measuring it out of this item.
And so and then the model really required only two parameters for the differential equations.
And from that data we could evaluate the parameters. And then we saw the effect of obesity or hyper lac,
the tibia and the curves that came out and ten patients where I said that, that's the real inner body doing this.
And so to really confirm that, um, we came up with the idea that how could we get people to lose weight quickly?
And so ten patients, obese patients, agreed to take diuretics and they lost on average ten kilos in five days.
We re did the experiment and the parameters were the same.
And then he wanted to get normal people and he went into the lab and, you know, old graduates, pre-med students, etc., the medical students there.
And he said, I need 20 volunteers. So I looked around all the students kind of raising their head and, you know, again.
And so they came and did the tests.
And we found that people with obese people with hyper lactate tibia had totally different parameters.
And we answered the key question that. They don't metabolise lactate as well as normal people rather than produce more.
Oh, and there were other problems that came from dinner conversations.
Yeah, and it did. It's just a fabulous system to effect interdisciplinary research.
Yeah, it is sort of funny that like the funding bodies and everybody else is trying to find ways of promoting interdisciplinary research.
And yet Oxford has had it there all the time.
So they should give and they should give money for kidneys. And why should you?
It is it should be. And so David Gavigan from.
Yeah. Yes, of course. Asks, What is the biggest challenge that we face in developing a quantitative and predictive biology?
Well, other than other than money to help to get poor, I, I think that's I think that's quite difficult.
I think biologists of biomedical scientists in the general sense who feel that the research interdisciplinary search has been effective,
has been successful, and that that can result in exciting results that they wouldn't have thought about had they not worked with other people.
And on the the sort of model side, it's that they have to be interested in a whole new world that they know nothing about.
Yes. Yeah. And that the biologist has to be sufficiently, uh, interested of patient to in effect teach him enough about it.
So one has to go to labs and all one has people like Lewis Wolpert who distinguished uh,
uh, by all the developmental biologist who I, we never, ever wrote a paper together,
but we spent an incredible amount of time, days over,
over many years where he patiently would talk about these experiments and tell me about this theory that I never quite believed.
And when we when we produced that, you remember the mechanical theory of pattern formation.
Lewis wanted to do experiments to show it was wrong and didn't exist.
He didn't. But as a result he discovered other things in the development of the limb.
Yeah. And so that sort of interaction it I thought was invaluable.
But of course it needed to have someone who was as clever as Lewis has such a warm personality.
Um, and so that has to be, I think, really to work.
I think there has to be this feeling that you really like the person you know.
Yes. Rather than somebody who is using you like a like some neutral computer or something.
Yeah. And I think you stressed also there the idea that you really need to go into the lab and learn a new subject,
or the biologist really need to have the patience to teach the the mathematicians.
And then this is a real issue in the present state of academia where it's one size fits all.
So if you're doing a doctorate, it doesn't matter what subject you do in the doctor, then you have to complete within four years.
If you get a grant as opposed to a three year grant, it doesn't allow for the flexibility of the.
I think that that is a problem. And I mean, in America, five years is a typical time for a PhD and that's where the grant money goes for five years.
And they feel certainly students feel much more relaxed.
I know. Yeah. And when I talked to them, they said, well, this is just my third year or something.
He was here, you know, almost a minutes of thinking by.
Yes, yeah. There. And, uh, and I think with postdocs it's the same their limited time and uh,
but certainly more and more universities around the world are looking for postdocs.
Mm. Yes. And I, I get emails perhaps once every two weeks saying, do I know anybody who would be interested in a postdoc?
Depends where. Yes. Yes. And so last question.
And if if you were a graduate student at the moment, would you work in academia to.
If I knew all that I know now and I've seen in the past few years, I would think very carefully about it.
Postdocs aren't able to see usually don't see the bigger picture, but with all the bureaucratic interference,
the difficulty of getting grants based on real science, the the system in universities, that is different.
Uh, I should have serious second thoughts.
Yeah, I suspect. I mean, I suspect I would go still go into academia, but one should be aware.
But it's not all just teaching bright students.
So being enthusiastic about research, it's dealing with the main ridiculous menu tie, such as a foreign postdoc,
somebody who's not part of the EU has to see where they're going almost every minute of the day.
Yes. And if they go off to London for a day and they don't tell you, you know, you and they are breaking the rules.
Yeah. And it could have serious consequences. Jim, thank you for taking time to feel a bit about this.
Thank you.