Transcript Aug 2008

Gareth Mitchell: This is the official podcast of Imperial College London. And I’m Gareth Mitchell, a lecturer in the Science Communication Group here at Imperial, and I present the BBC’s technology programme Digital Planet. Hello. And this month, with the Beijing Olympics finally upon us, let’s talk sport. In particular the prospect of genetically enhanced athletes. One of our professors here is an expert in gene doping and I’ll be shot-putting some questions to him on that contentious subject in just a moment. And also today, the antics of ants and group behaviour of panicking people; seemingly rather random phenomena. We’re at the meeting at Imperial seeking to create some mathematical order out of all that chaos.

Henrik Jensen: The idea is that you try to see what you get if you just assume random behaviour, if you like. So like just mindless copying. And then you make predictions. And you know that you can believe these predictions because they are mathematically sound. Of course, there is no proof of the assumptions. The assumptions you just make because you need some starting point. When you now see deviations from your predictions what you know is that there’s more in that specific social phenomenon you’re studying than just mindless copying.

GM: But away from the maths we’re anything but formulaic on this podcast. So to keep things varied did you know that Imperial has an Olympic Ambassador? Nor did I until I met this chap.

Steve Trapmore: The triathlon is going to be up in Hyde Park, which is obviously very, very close to the campus. The logistics within the campus itself are going to be supporting the Olympics as well in terms of accommodation. We’re also looking into all sorts of different ways to help teams that are coming over in terms of acclimatisation. Providing services of support for their build up to the Games itself across all sorts of different Olympic and Para-Olympic sports.

GM: Our Ambassador to the Olympics tells me what such a person actually does. And we’ll sprint through some of the headlines from around the campus. It’s all right here on the official podcast of Imperial College London.

Professor Dominic Wells on 'gene doping'

So it is Olympics month so all kinds of issues relating to sport and medicine are very high on the agenda. Not least of all gene doping. And that’s of particular interest to Professor Dominic Wells here in the Department of Cellular and Molecular Neuroscience at Imperial College’s Hammersmith campus. And Dominic, you’ve written a paper in the BMJ, it came out last month, entitled Genetic Engineering in Athletes. So, in a nutshell, what were you saying in the article.

Dominic Wells: What I was responding to was a series of pieces that have been written over the last two or three years by people predicting that gene doping is going to be the next big thing in athletics. And really what I was trying to point out was that at the moment our technology is not good enough in order to get effective gene doping. The risks are too high and the chance of detection in most cases is going to be fairly easy. Thus, I would predict there is not going to be a genetically engineered athlete at Beijing. But with the rate that technology is changing there is a possibility for London 2012. And therefore we need to be putting safeguards in place to be able to detect such cheating in the future.

GM: And when we talk about genetic doping. I know you’re saying that the technology is some way off, if could be here by 2012, what kind of things are we talking about here? I mean, literally introducing genes that boost the muscles in various ways?

DW: Yeah, there’s a number of things that athletes are currently doing which could be translated into a gene doping approach. So people are taking growth hormone. They’re taking erythropoietin. They’re taking a variety of substances. And, of course, one can avoid some of the detectable aspects of that doping by transferring the gene responsible for those particular proteins directly into the athlete so that the protein that’s produced appears more natural. Fortunately, for the people interested in detection, in most cases there’s still detectable differences. And, of course, if you’re doing a genetic doping approach it tends to be a relatively permanent one and so you’re not going to be able to do what many athletes apparently do which is to dose themselves prior to an event but to stop taking the drug in time to avoid the testing. However, there is a sub-set of genetic engineering that could be very effective for gene doping. And that’s where we modify the muscle itself rather than anything that’s circulating throughout the bloodstream.

GM: How might you modify the muscle itself using these gene doping techniques then?

DW: We now know that, for instance, there are genes such as insulin-like growth factor one which helps to grow muscle, helps to repair muscle more rapidly. And so if you could transfer the gene for that into the muscle it acts locally within the muscle itself. It doesn’t spread throughout the rest of the body. And that would allow the athletes to recover quicker from training. It would allow them to recover from any damage they incurred. And would allow them to put on bulk more quickly. And there are now increasingly over the last couple of years we’re seeing more and more genes that have a similar sort of effect.

GM: If those were introduced into the body would those particular ones be incredibly hard to detect then?

DW: The skill, if you want to refer to it that way, from the gene doping point of view will be to introduce genes at high efficiency specifically directly into the muscle. Control their expression through the use of muscle specific promoter sequences. And to make sure that you put in a gene that doesn’t produce a product that leaks out of the muscle. Because at the moment with testing for athletics you can test with blood, you can test with urine, but no athlete is going to be happy if you want to take a muscle biopsy. Okay, so now we come back to the technology aspect of this. So a number of us are working in this field mostly because what we’re trying to do is develop treatment for muscle diseases like Duchenne muscular dystrophy. And we’re interested in trying to get as efficient a possible gene transfer into muscle.

At the moment we’re not bad at doing it in mice. We’re not so efficient when we go up larger animals. And at the moment there is no human treatment available. And in many cases, athletes that are doping are taking products that are intended for human treatment and are applying them in an incorrect fashion. That’s not going to be available for a gene therapy approach for many, many years to come. The question is whether people could do it on a sort of illegal basis having developed their own gene therapy and agents. And, at the moment, I would fairly confidently predict that that’s not an option. Because at the moment we’re not efficient enough at delivering genetic material to humans.

GM: Also in your British Medical Journal article you speak about myostatin. Can you just walk us through that or maybe sprint us through that in this context.

DW: Myostatin is an exciting gene because it is a gene that negatively regulates muscle growth. In other words, the reason that I don’t look like Arnold Schwarzenegger, well one of the reasons anyway, is that my myostatin is busy controlling my muscle and only making sure that I have the muscle that I require for my everyday activities. You can block the action of that gene in a number of ways. And, at least in animal models, you can show massive increase in muscle growth. And that would be very important for athletes.

The reason that myostatin is attracting an awful lot of interest from the therapeutic point of view is, of course, as we age our muscles get weaker. If we’re in bed-rest our muscles get weaker. If you could block the action of myostatin you could prevent an awful lot of that weakness. So a drug that becomes available to block the action of myostatin would have huge use in the medical community but, of course, would be hugely tempting for athletes. The skill is going to be in confining the way of controlling the myostatin to the cell to muscle. And an obvious way of doing this is to introduce a silencing element using this inhibitory RNA approach which will prevent the myostatin being produced actually in the muscle as a local effect but will not be detectable through the rest of the body.

GM: And I know it’s so hard to predict how quickly technology is going to advance but you seem to be pretty confident that this is an issue we’re going to be facing by the time we get to the 2012 Olympics in four years’ time?

DW: This is an aspirational goal. Because if we’re getting that problem in athletics we’re hopefully also developing very effective therapies that we can use in people with muscle diseases. So I would like to be solving the problem of muscle diseases the by-product of which is likely to be illegal use of the substances. And that’s what we’ve got to guard against. And therefore it’s important that the anti doping agencies can develop suitable tests that will help to detect those sorts of problems.

GM: And that’s a good point to end on, isn’t it? Because a lot of this discussion of gene doping is a bit downbeat because we’re talking about the athletes cheating. But the upside is that the therapeutic aspect of this is incredible exciting, isn’t it?

DW: Absolutely. This is one of the most exciting times in the field that I work in, in terms of muscular dystrophy. There a huge number of clinical trials ongoing. They’re all at the moment sort of safety level trials really trying to make sure that we don’t do any harm. But that means that in the next two to three years we’ll be moving with a number of them into therapeutic trials. And at that point the real excitement happens. That there’s a possibility that for some of these diseases, for which there is no effective treatment, that a treatment will become available at least at the clinical experimental level within the next five years. And that is, of course, a wonderful prospect for those of us who deal with these absolutely crippling lethal diseases.

GM: Professor Dominic Wells at our Hammersmith campus. And there will be more about the Beijing Games in just a little while with our Olympic Ambassador. And also still to come, the mathematics of animal behaviour. We bring you some true numerical selection.

Headlines from around the College

But, before all that, let’s have some quick headlines from around the College.

Clinical trials of new breast cancer drugs should take greater account of ethnicity. So say researchers in Imperial’s division of Surgery, Oncology, Reproductive Biology and Anaesthetics writing in the medical journal the Lancet. In an opinion piece entitled Ethnicity and Breast Cancer Research the authors say that too many patients to trials are from white populations in Europe, North America and Austrialasia. But with the disease becoming increasingly prevalent amongst those in Asia and economically developing countries elsewhere recruitment to trials should further reflect these groups.

The scientists base their case partly on a drug called trastuzumab. Research shows that people of a particular genotype respond especially well to the drug and yet studies into it haven’t recorded the ethnicity of the participants. With better data doctors could more effectively prescribe breast cancer drugs based on an individual’s ethnic background.

To the Physics Department now. And if you have a state of the art laser device for photographing the ultra high speed movements of electrons within atoms just how do you convey the true scope of the speedy microscope to school children? That was the challenge for Imperial scientists who’ve just been showing off their wares at the annual Summer Science Exhibition at the Royal Society in London. To put high speed photography truly in context they took along a specialist video camera with one of the fastest frame rates available. The rapid shutter movement allows the camera to capture events like water filled balloons bursting in really detailed slow-motion. One of our team at the Royal Society bash was Sarah Baker.

Sarah Baker: We have a commercial camera running that’s about as fast as you can buy. So it runs at 750 frames a second and that means that you can have a kid with a water balloon in their hand and you can pop the balloon and you can see the balloon fall away. And then we can explain to the kids that actually as far as we’re concerned 750 frames a second is really, really slow. So our lasers run a million billion times quicker than that.

GM: So having introduced the concept of really high speed photography Sarah and her colleagues were then able to explain to visitors at the Royal Society just how their laser camera records electrons moving around at around 10 million kilometres per hour. In so doing the physicists can record how small molecules change shape during chemical reactions and how electrons hold matter itself together, even those that form balloons. At least until someone fills one with water and bursts it.

And that was the news, as they say. But you don’t need to wait for each new edition of this podcast to find out the latest from the College. Get all the Imperial news before it even finds its way into the rest of the press by staying across our Press Office website. The address for all your Imperial news and events is imperial.ac.uk/news.

Using maths to understand animal behaviour

Well, now then, if you happen to look at a load of ants moving around their behaviour looks pretty random. A closer look reveals that at an individual level the ants’ roles are surprisingly well defined. So enter the mathematicians who can express this individual behaviour in equations and formulae. And just at maths is very good at defining the relationships between numbers so it can model behavioural relationships between ants. So, why stop there? Similar analysis can be applied to other social creatures like fish and even human beings. That was one of the topics being discussed amongst the highly social individuals invited to Imperial for a recent meeting on complexity and networks. Recho Carabetta caught up with the hosts there, who included members of the College’s Institute for Mathematical Science, as well as visitors from all over the UK and Europe. Recho was keen to see just how the ways of nature had programmed into the numbers.

Claire: My name is Claire and I’m working at the University of Brussels. We are really interested in social systems and in complex systems such as insect societies. Because they show a wide spectrum of sizes of organisation. We are trying to understand what is the link between the behaviour of the individual, of the nest mates, and the collective structure that emerges at the level of the society.

Recho Carabetta: And understanding such complex and seemingly chaotic behaviour is no mean feat. Devising mathematical relationships that describe behaviour may also describe the ants’ relationships.

Claire: They can reach for a few individuals up to thousands of individuals. They are able to cooperate with each other and are able to influence the behaviour of the others. And all this multiple interaction leads to the emergence of wonderfully organised structures and patterns.

RC: Just as Pi describes the ratio of a circle’s circumference to its diameter, so mathematics can predict other phenomena in nature. The formula for Pi is simple. Every school student knows it and yet it yields a number that unlocks so much in the natural and engineering worlds. At the University of Leeds in the North of England, Professor Jens Krause is bringing engineering and nature together too. He’s gone beyond using maths merely to observe how groups of creatures behave. Here he’s using the principles to control behaviour. In this case, not in ants but in fish. He’s even built a robotic fish, the aquatic equivalent of a sheepdog, and programmed it with mathematical instructions of how to herd a group of real fish in a tank.

Professor Jens Krause: This is a new project that we developed over the last year. That we built this robotic fish which can be controlled from a computer. It’s capable with interacting with live fish and this gives us control over certain social situations. And we wanted to see how we can build a very strong leader fish into which this robot will be capable of guiding us in different situations. For instance, we let the robo-fish swim past a predator and we see whether other fish are willing to follow that and copy this, despite the fact that it’s actually not advantageous for them. And so with insects, these robot animal interactions have been done in the past. And I think partly because it’s a bit simpler. So we’re trying to do this for vertebrate animals now where the cognitive abilities of the individuals are higher and you need to have more sophisticated mechanisms for tricking them, if you like.

RC: All this talk of tricking fish and herding them the way sheepdogs herd sheep is strange enough. Wherever next for this technology? Herding kittens perhaps? Okay, well maybe not yet. But going beyond fish, researchers do have higher vertebrates in mind. Humans. You might think that the large intelligent and not to mention free spirited creatures like us are a little above being herded. But Jens Krause says that our group behaviour has more in common with that of fish than we might at first of thought. And the clue, as ever, seems to be in the numbers.

JK: We have a very active research programme on looking at human crowd behaviour. So we look at large and human crowds and processes of self organisation and we try to understand to which degree large crowds are capable of swarm intelligence. And we found that the proportion of individuals that it takes to guide a shoal of fish or a group of humans is actually very similar. It’s a similar proportion of about 8 to 10 per cent of informed individuals that are necessary to guide a crows of, say, 200 people or 200 fish. These are the kind of things that we are looking at. Evacuation scenarios of crowds from buildings and we look at what role informed individuals might play in guiding these people.

Henrik Jensen: I’m Henrik Jensen. I’m Professor of Mathematics and I’m leader of the Programme for Complexity and Networks in the Institute of Mathematical Sciences. And one of the problems with complexity science is that the term itself is ill defined. They are by nature difficult to take out of context and therefore important to study in real settings as real life phenomenon.

RC: So what can something as abstract as mathematics or computer modelling actually say about real human interaction?

HJ: Well, that’s a very good question. At today’s meeting there were these people trying to make models. The idea there is that you try to see what you get if you just assume random behaviour, if you like, without any mental processing, so to say. So like just mindless copying. And then you make predictions. And you know that you can believe these predictions because they are mathematically sound. Of course, there is no proof of the assumptions. The assumptions you just make because you need some starting point. When you now see deviations from your predictions what you know is that there’s more on that specific social phenomenon you’re studying than just mindless copying. But you can identify exactly in what way human behaviour, in this case, deviates from the assumptions and therefore you can start to analyse and localise what kind of human behaviour is important.

RC: So whether you can recite Pi to hundreds or thousands of decimal places or whether, like me, you’re hopeless at arithmetic it seems that mathematical equations underlie our daily lives and those of other social animals.

HJ: One of the liberating things of doing computer models is that you don’t need to limit your modelling to what you can do analytically, what you can do by hand with pencil and paper. You can go far beyond that using computer models and actually put in the phenomena in your modelling that you think are most relevant. When you do applied mathematics, where you focus on the ability to do the maths, you’re often limited by what is mathematically doable. Whereas when you have a computer you can crunch through anything.

GM: Henrik Jensen, Professor of Mathematics at Imperial College, ending that report from Recho Carabetta currently studying on our Science Communication MSc here at Imperial.