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What Matters in Bioengineering*

by Patrick J Prendergast

B.A., B.A.I., PH.D., F.T.C.D. (1998), M.R.I.A. (2008)

Professor of Bioengineering (2007) Provost, Dean, colleagues, family and friends; bioengineering, why it matters to me, and why it should matter to all of us, is the subject of my lecture to you this evening. I am pleased to be able to address such a large audience – I didn’t expect such a crowd; for many of you it will be your first lecture in engineering, for many of you it will also be your last, so I know that a lot rests on what I am going to say to you this evening. And it’s with some trepidation that I begin knowing that what I say could have such a permanent effect on your views of engineering. * Edited transcript of an inaugural lecture

delivered at 6 p.m. on the 30th of September 2008 in the MacNeill lecture theatre, Trinity College Dublin

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I very much appreciate the effort my family has made to be here; my mother here somewhere, ah there, my sister Anna from Luxembourg, my brother Damien and his wife Yvonne, my brother John who has come from all the way from Melbourne, Australia, [clapping] so that’s really something – he was in Europe anyway on business but made arrangements to stay an extra day to hear this lecture and I appreciate that very much. Brendan and Ger are also here and my youngest brother Peter, so it’s very good to see so many people here. And I see some of my Aunts and Uncles – you’re very welcome. I don’t know what you’re going to get out of this but you’re very welcome. It’s very good to see you here and I look forward to talking to you afterwards. Most importantly of course, my wife Petra is here, and bought a new dress for the occasion; I haven’t even seen it yet, only the top of it from here, but it looks great. And her parents Annie and Sake from the Netherlands; it’s really great to have so many family and friends, quite apart from all the engineers and people from Trinity College and from other

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universities in Ireland and abroad. Now I want to give you a little bit of a premonition of what you’re in for. This will really not be a show-and-tell lecture. It’s going to be rather academic. I’ve given show-and-tell lectures before and I wanted to talk now about my own research in this lecture. So I’ll talk about my own research interests, carried out mainly in the last few years with our research team in the Trinity Centre for Bioengineering. So after a few general slides in the beginning, I fear I’m going to lose some people. But I hope I’ll get you back by the end of the lecture. I’ll begin with an old story often told about engineers. A priest, a lawyer and a mechanical engineer are about to be guillotined. The priest puts his head on the block, and they pull the rope: nothing happens. He declares that he has been saved by divine intervention and he’s let go. The lawyer’s head is put on the block and the rope is pulled. Again, nothing happens. He claims he can’t be executed twice for the same crime and he’s let go (lawyers

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are always very clever like that). Then they grab the mechanical engineer and they stick his head under the guillotine and they pull the rope and again nothing happens. He looks up and he says ‘Aha! Now I see what your problem is.’ And I tell this little joke because if you tell a joke it’s good to tell it about yourself for a start, but also it’s because it really says what engineering is about; engineering is about problem solving and engineers are problem solvers, sometimes no matter what the cost. Engineering, then, is about problem solving. To use the lofty language of the professional engineering codes “engineers use the principles of engineering to harness the great forces in nature for the use and convenience of mankind”. That’s quite grandiose in a way, and it’s true; one might generalise to say that engineering is the art of using knowledge to achieve objectives. It’s really not about obtaining knowledge in the disinterested way that science perhaps

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claims to search for knowledge. Even if such a claim of disinterested searching for knowledge could stand philosophically, you wouldn’t find any engineer in the audience here, and there are many, that would want to make that the reason for their research work. However, as I will show later (and as I believe others will show too in this series of engineering inaugural lectures), engineers do science when they need to develop a model to create a design or when they need new information to complete a project. Now because, in the academic environment, engineers are not always involved in engineering practice it can look to an untrained eye very much as if they are scientists, and at least I sometimes feel like this. In fact, and I wouldn’t like to speak for all my colleagues, I feel that in the academic environment, engineers lead double lives as both engineer and scientist. But it must be remembered that engineers are about meeting techno-logical objectives and, in meeting these objectives, the knowledge we need is rarely just scientific or even mainly

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scientific but it understands, or it involves an understanding of, problem solving in the widest and in the broadest sense. I say this because it is important not to think of engineering as practical or applied science. It is a mistake too easily made, one I’ve heard made unfortunately in this university and, if it gained any ground, really it would provide society with bad engineers which would be bad enough in itself, and it would probably also provide society with quite bad scientists. So engineering is about using the principles of engineering to achieve technological objectives. It doesn’t exclude science, but it involves much more. What, then, are these principles of engineering that Engineers use? I want to say something about this here because it is a unique opportunity for those of you who are not engineers to get an appreciation of what we do. Engineering involves solving to completion technical projects, usually sophisticated technical projects, occasionally huge undertakings like construction of power plant or

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airplanes and this cannot be done in an ad hoc manner. It cannot be done in an ad hoc way by following your nose or whatever takes your interest or fancy. In engineering, problem solving must be systematic and creativity is focussed on a purpose, and a plan is followed. Now, there are various methods – there are people standing in the back, that’s amazing, I don’t think I ever had as many students in this lecture theatre; please feel free to come away on down, you won’t be getting in the way if you want to come down. In engineering, as I say, the problem solving approach must be systematic and my colleague engineers will be very surprised that I’ve put up this boring slide to start my lecture because it is about the engineering design process [over]. What engineers do in a systematic design process begins with identification of a need. Now we won’t get into the complicated psychology of this but this is often the most creative part of designing an engineering artefact; in my case here, medical

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devices. Next, we define the problem to be solved, and a long time can be spent on this part obtaining specifications for the device to be designed, such as its performance characteristics. Next we move on to synthesis, sometimes called concept design, where various designs are proposed and evaluated. Concepts that do not survive analysis are revised and evaluated again and there are many feedback loops in this process, and again I say this is the simplest version from a junior fresh undergraduate textbook. There are many more complicated ways to go about

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engineering design. Then we have analysis and optimisation, selection of solutions best meeting the problem specification, evaluation of solutions next in this phase that I’ve ringed, and this is a particularly difficult thing for medical devices because the devices are evaluated for use in humans. Yet how do you evaluate it? You have to take a risk if you put it into a human. You evaluate the device perhaps then by putting it into an animal. There are ethical issues with animal experimentation but also animals are not like humans; their body structure is obviously different, so it’s very difficult to evaluate some medical devices and this is a key issue. Really they can only be evaluated when they’re released into the human population in multi-centre hospital trials, and the risk to patients must be minimised there. And then the final part is presentation and demonstration. So this is what engineers do – a systematic problem-solving approach, well coordinated, with good commun-ications and teamwork being essential,

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and I make these few points as utterly basic preliminaries before I begin to talk about bioengineering proper and why it matters to us.

* * * Now, my next slide is talking about the human body as a machine. This fellow is Giovanni Alfonso Borelli. He was an Italian from the 17th century and he is regarded by many as the founder, the first real analyst, in biomechanics and bioengineering. And here is what Borelli did. He analysed the musculo-skeletal structure of animals – this is a diagram of a forelimb, say a human

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arm. If we carry a weight in the hand, what Borelli found out was that a much larger force acts at the joints. Now even anyone that’s got Leaving Cert physics can understand this. Take that black dot on the diagram on the left (that’s an attachment point for that muscle) and take moments about that point. The blue line is the joint reaction force and the red line is the weight in the hand. By the law of the lever, because the distance between the red line and the black dot is much greater than the distance between the blue line and the black dot, we’ve a very much larger force at the joint than we have in the hand. So you can easily carry 10 kilograms in the hand; that would mean that you would have many times 10 kilograms acting at your joint. As a matter of fact when you work out the distances you’ll find that the ratio is about 1:20. So you could have 20 times 10 kilograms, that’s 200 kilograms, that’s almost 3 times the weight of a person acting at your elbow joint. So our joints really are magnificent

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structures because they can function throughout your lifetime under these usually very large loads - and this is what Borelli found out. And it was the first real attempt to persuade people that the human body was a machine , or could be analysed as a machine. Borelli was a student of Galileo’s actually, and that’s where he started to apply this method. People will be more familiar with his contemporary, William Harvey, who also studied in Italy. William Harvey was the person who proposed the idea of the human circulatory system from which came the realisation that the heart is a mechanical pump. So here we have a system of levers and a mechanical pump. This was revolutionary for people in the 17th century, that they could view their bodies as machines. So I’ll finish this part of the lecture with that idea; the human body as a machine.

* * * But the human body is not a machine that lasts forever. The machine

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degrades and most of us want to do something about this. Terrible processes set in as we age, as we know, not just getting grey hair or anything like that, but serious degeneration of the human machine, we might call it. The circulatory system degrades and the heart no longer pumps the blood at the same pressure; the bones begin to become brittle and break, and we want to do something about this. And this is where the engineering of medical devices comes in. You might well ask what these things (medical devices) are. I’m going to talk now, briefly, about some projects I was involved in this last year gone by regarding the design of these devices. The first are aneurysm repair devices, as the diagram [over] shows. An aneurysm occurs when your blood vessel expands like a balloon so you might have a local dilation and this is very bad because the blood flow no longer goes along the artery. The diagram shows what’s done to repair it. Here’s the dilation – you can see an aortic aneurysm and this just balloons

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out and we want to bypass this. And the way we bypass it is to insert a catheter through the blood vessel; you’re going to see a white line come up along here and then we will expand that bypass graft like this one. And then along the other leg we put a catheter and expand another bypass graft into that. Now when the blood flows, it will not flow into the aneurysm, it will flow rather through the white tubular structure, through this bypass graft. So you may well ask the question: how do you design these things? Firstly how do you get them in? This is

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no simple matter; look how big the graft device is. In fact you get it in by designing it so as it can be compressed onto this small catheter and a catheter is pushed in; in fact, the graft is enclosed in a very small diameter sleeve and the sleeve is held together longitudinally with slip knots and these slip knots open to allow the graft (in white in the picture) to expand out – such a mechanism has only recently been perfected. A big issue with these is that the blood flow will cause them to slip and they have to be therefore expanded tight out enough against the vessel wall so as they stay where they’re supposed to be. So that’s one example of a repair of something gone wrong in the circulatory system. Another medical device that’s quite common is knee replacement prostheses. Now orthopaedic joint replacement prostheses are very common – I bet you there are several people in the audience with artificial hips or artificial knees, and indeed knee replacement has now become more common than hip replacement. But in the beginning knee replacement

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was a disaster. Early designs were hinges – a hinge has a fixed axis, so a hinge on a door, for example, has a fixed axis. These early hinge designs loosened in a few years almost always. I couldn’t even get a nice picture of one they’re so old. Then these hinge designs were replaced by much more interesting designs. If you were to get a knee replacement now, you’d probably get a design like the one to the right on the picture – I’m going to set a video clip running here, at least I hope it’ll run – this is me playing with a knee prosthesis in my office; look how much

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better this design is – it isn’t a hinge. In fact it’s a so-called ‘mobile bearing prosthesis’ where this polyethylene part can rotate over the tibial part. And this is absolutely essential actually because the reason the hinge designs failed is that they didn’t allow for this motion. The next time you are at home you can flex your knee like that [speaker flexing his knee] – you’ll see if you look that it’s not a hinge. In fact close to the full flexion the tibia rotates relative to the femur and there’s a so-called ‘screw home mechanism’. This ‘screw home mechanism’ is essential because it allows human beings to stand upright with minimum energy. If you think of other primates, chimpanzees, they don’t fully flex their knee. As a matter of fact their knee is always somewhat bent. Humans can straighten their knee and that has to be provided for also in the design knee replacement prostheses. So these newest designs – and they are only 5 to 10 years old – are so-called ‘rotating platform’ designs; they are much more successful than hinges. As a matter of fact, one of the people who was involved in inventing these, I’m almost

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embarrassed if I’ve got it all wrong here, David FitzPatrick, is in the audience. If I’ve got it wrong, David, you’ll just have to tell me later! So these are ‘repair kits’, if you like, for the human body.

* * * So far I’ve talked about engineering design, design of aneurysm devices, and design of knee replacement prostheses. But in fact we animals – we organic forms – have not been designed by engineers. In fact organic forms haven’t been designed at all. They’ve come about by a process of trial-and-error. Well they haven’t been designed at all if you don’t believe in intelligent design and I’m assuming that most people in this audience are persuaded by the arguments in favour of the alternative, which is evolution, and that organic forms have come about by this process of trial-and-error in evolution and that animals have become fit for their environment by competition with each other.

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I have here a bone! I’m going to ask you what has this bone, a tibia, a human tibia actually, got in common with my next slide which is a KLM Boeing 747. The Dutch people are laughing; but anyway, this bone and this aircraft have something in common and I want to talk to you about it a little bit.

Evolution has not designed this bone. Actually, evolution has not created, I should say, a bone that will never break. In fact these bones do break; about 10% of the people in any group will break a bone – a long bone like this – in their lifetime.

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So evolution has not resulted in bones that never break. As a matter of fact bones do break and why is that? Well, perhaps because to create a very large bone would actually be somewhat of a disadvantage to an animal. It’s metabolically costly to maintain it, and it’s metabolically costly to move it around. As a matter of fact bones are continuously breaking. As you walk around, your bones are continuously accumulating micro-damage. And colleagues of ours in RCSI, Clive Lee and Fergal O’Brien, and David Taylor here in Trinity, have been among the world’s leaders in identifying this microdamage occurring in bone. It’s a bit like this aircraft. The parts of this aircraft have not been designed so as they would never fail. The turbine blades and various components of this aircraft have been designed to last for a particular time; then they’re brought in and repaired and then the aeroplane goes out again. It’s a bit like this with your bones. They are not designed through evolution – evolution has not created bones that do not fail. It has, in fact,

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evolved ‘self-repairing’ bones, bones a bit like this aircraft that are continuously brought in for servicing and repair of microcracks. So this self-repairing mechanism may extend the functional life, but sadly not enough; our musculoskeletal machine cannot perform forever. As I have said, it decays. I’m going to talk to you about one aspect of how it decays and this is osteoporosis which is one of the things we have been working on in the last number of years. I was at a conference last week, one section of it was on osteoporosis and three of the presenters out of five had this slide, and I can see why – because if you type ‘osteoporosis’ into Google the first thing that comes out is these Chinese women. You can see the issue with osteoporosis. With osteoporosis, particularly with certain genetic groups, you get bone loss and continual fracturing of, in this case, the trabecular bone in the vertebral

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column. So if we look at a cross section of a vertebrae in your spine, take it out, cut it with a band saw and look at it, that’s what you’ll see [over]. You’ll see this trabecular network, but over time it degenerates in fact, and the vertebral column gets shorter and that is how you get the bending over and shortening of people during life. And what’s more, you also lose trabeculae. Why do you lose these bone trabeculae – that’s the question that many people are asking.

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And if we focus in a little bit and I can show you an animation of the cellular prcesses. In this little animation, those red dots are cells that are going to resorb bone and so you have this continual process ongoing in bone where some cells resorb bone and others deposit new bone. And this continual turnover process is what repairs the microcracks when they eventually appear. So this process is ongoing all the time, turning over the bone and putting down new bone where there were older bone packets.

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And so if we set the animation going here, we’ll see the osteoclasts in red resorb a piece of bone on the trabecular strut, followed along by the osteoblasts in blue which deposit new bone and this process keeps on going all the time in your bone. Remodelling is ongoing there as you sit there – you have these little cells doing their work. Now when the animation completes, you’ll see that actually not as much bone was deposited as was resorbed. There’s a deficit – we’ve lost some bone in this remodelling cycle and that is what causes osteoporosis. Now you might say, and certainly if you’re a mechanical engineer, we should be able to solve this; we should be able to get it so that the osteoblasts deposit as much bone as the osteoclasts resorb. This is proving impossible and it’s why we can’t resolve the problem of osteoporosis. Some years ago we began to look at this using our bioengineering theories. Here’s an experimental study that we did as part of this work together with some European partners led by

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Erasmus University of Rotterdam. This was an EU project that myself and Dr Kevin O’Kelly had a couple of years ago, and this animation is one of the best things that came out of it; it’s a really good video clip of osteoporotic bone loss ongoing. Prof. Harrie Weinans and his group work in the University in Rotterdam. This is the cross section of a tibia; you can see even the growth plate in this and over time (this is an in-vivo microCT scan) you see loss of bone. This is in a rat that’s been overectomized which is a way of inducing osteoporosis. We loose the trabeculae, the de-densification of trabeculae occurs. Trabecular perfor-

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ation and trabecular loss occurs. This is it happening in an animal monitored using this in-vivo microCT scanner. Now can we model this? Can we analyse it? I’m going to propose to you two hypotheses. As the people who work with me know, I’m quite keen that we actually craft hypotheses that we can test. And so we believe that there are some biomechanical reasons for osteoporosis that are not yet being sufficiently accounted for in studies of osteoporosis because osteoporosis research is mostly done by drug design people. Firstly we hypothesise there’s a stiffness change in trabecular tissue causing trabecular perforation and osteoporosis. So we’re saying that increasing in the stiffness of these trabeculae, which happens over time for a particular reason, causes osteoporosis. And what is more it’s possible that, as you get older, the cells in your body are less sensitive to mechanical stimulation. This leads to

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our second hypothesis concerning osteoporosis: that reduced cell mechanosensitivity leads to trabeculae being perforated during the remodel-ling cycle. I want to test this out in a model – now this is where I might lose some people. Looking to the algorithm and the graph [below], on the x-axis here is strain (epsilon stands for strain in mechanical engineering), and on the y-axis is the rate of change of density. So on the positive y-axis is bone formation and on the negative y-axis is bone resorption. For a low ‘strain min.’ we lose bone because we have strained

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bone below a threshold. The cells respond to that by net resorption. Between ‘strain min.’ and ‘strain max.’ we have a so-called dead zone where the bone is, if you like, happy. It’s adapted, it’s not changing. Above that, we have bone formation where the strain is so high, that new bone gets laid down, like the tennis players who are very active, their tennis playing arm gets more bone than their non-tennis playing arm. That’s what’s happening. Now at very high strain, bone begins to accumulate micro-damage. And micro-damage, as I’ve said earlier, is a stimulus for this resorption process – and that’s what the red dashed line on the graph [above] is about. So we create that into an algorithm and this is the general procedure that we follow. We create an algorithm and we run it using a computer simulation of a piece of bone. We initialise the material properties, set up the so-called finite element model (I’m sorry if I lose some people here but if I’m going to get into the detail, I have to do this) to compute the biophysical stimuli which are

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stresses and strains. Coming to the first decision box in the remodelling algorithm [below], is the damage, which is given the symbol ω, above a critical level? If so, then resorb, if not then enter the strain adaptive remodelling phase. Is strain above a particular level? If so, then add new bone: if it’s not then remove bone. If it gets to the bottom of the flow chart, then it’s in the adapted zone, or dead zone, and there is no change. And you go round in this iterative cycle. So we set up a very simple model of a trabecular strut, and this was work

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that began with Laoise McNamara and was carried on by Brianne Mulvihill in her PhD thesis. The yellow here is the simplest possible example of a trabecular strut. In engineering modelling we tend to keep things simple, and the model should be as simple as it can possibly be. As Einstein said, ‘as simple as possible, but no simpler’, and this is as simple as it gets from the structural point of view. And the little red region is a piece of damaged bone that you see here. We won’t get into the details except to say that this is a linear elastic model of a trabecular strut. We have replicated the existence of cells as integration points in the finite element model and we effectively remove elements in this model to simulate the remodelling process, to simulate the remodelling cycle. Now we’ll do some simulations. If we run simulations, we’ll see that our algorithm can indeed simulate the remodelling cycle successfully. Then can we can use the model to test the

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hypothesis. If we have the normal (low) stiffness, this is what I just showed you, you’ll see it again here now, yellow is the trabecular bone, not much happens in this simulation so I have to do it again, yellow is the trabecula and blue is the bone marrow, if we run it we see that bone is resorbed – the yellow (bone) turns into blue (marrow) and then it’s filled back up again, not totally filled, so we are getting this remodelling deficit. Actually, this is the first time that anyone has created a simulation that can simulate this remodelling cycle of resorption and deposition with the remodelling deficit.

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Now if we have a higher stiffness, what we get actually is that trabeculum perforates. So if bone tissue stiffness becomes high, we actually lose the trabeculum altogether during the remodelling cycle [pointing to right panel on slide above]. And we think that this is one of the mechanisms whereby you get osteoporosis and bone loss. We think it’s because the tissue itself gets somewhat stiffer, more highly mineralised, causing perforation in the remodelling cycle. So we are happy to say that we corroborate our first hypothesis about the effect of stiffness (Young’s

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modulus) on trabecular perforation and osteoporosis. Now the second hypothesis about cell mechano-sensitivity can also be tested. A little aside here, it’s actually well known that individuals are variable in their genetic susceptibility to bone loss, and genetic loci have been identified in experiments. Inter-individual variation in bone degredation rate with age may be partly explained by a variation in how sensitive our cells are to mechanical stimulation. In modelling terms, that means that some people will have a narrow ‘dead-zone’ whereas others will have a broader ‘dead-zone’. So I’ve changed something in that, you can’t probably see it but I’ll change back and forth [pointing to diagram overleaf]. A wider dead zone means less mechanosensitivity. If you have a wider dead zone, you have less mechano-sensitivity. I’m going to decrease the mechano-sensitivity now and run the simulation again. What do I get if I run the simulation with cells that are

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decreased in their mechano-sensitivity? Well, it looks like it’s going to fill but eventually it will perforate. So this actually fits what we know about osteoporosis because as you get older your cells may become less mechano-sensitive and, if that’s the case, that could be the reason for osteoporosis. So I like to say that we have corroborated our second hypothesis that decreased cell mechano-sensitivity decreases the degree of refilling in the remodelling cycle and therefore predisposes to osteoporosis.

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To finish this part of the lecture, we can prevent osteoporosis by preventing over-mineralization or maintaining bone cell mechanosensitivity with age. I’m very glad to say that together with Professor Veronica Campbell and a new PhD student we’re going to look at cell mechanosensitivity as a function of age funded by a new Science Foundation Ireland Research Frontiers Programme grant.

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Now, what’s been covered so far in this lecture? And how close are we to the end? Well, unfortunately we’ve only got as far as the first three topics, namely, • Principles of Engineering, • Bioengineering of the human

machine, and • Osteoporosis. I want to talk to you now a little bit more generally about repair and regeneration processes. I promised my brothers there would be one slide worth looking at in this lecture, and here it is [over]. I won’t name everybody in this picture here but this

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is the female part of the bioengineering group – the men aren’t worth showing you (I’m only joking). The picture was at a ‘James Bond night’ at a conference – I have their permission to use it, (I hope). I’m showing you this because research on some of the stuff I’m going to say to you now has been done by Louise McMahon, Emma Kearney, and Niamh Nowlan, and they’re all in this picture. Brianne Mulvihill, who did the osteoporosis simulations is there as well. Actually the human skeleton is remarkable in another way. I said it could be viewed as a machine as, you

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know, it has the levers and the heart is a pump, but there’s more going on machine-wise in the body than that. Inside in the bone there are repair processes going on, as I just said. But break a bone, like if you fracture your femur, and you can see it repairs to almost perfect, almost indistinguish-able from before. So we can fracture a bone, here’s this tibia, and if we were to fracture it, and it was still in the body obviously, it would repair so as it would almost be perfect. And this is really remarkable. We don’t think about this enough, how remarkable it is. And this process is mainly carried out by the cells that I’ve identified here. The cells in question are stem cells. Stem cells are existing in our bone marrow. These are the adult stem cells, not the controversial embryonic stem cells. But we have adult stem cell populations in our bone marrow. They will invade the fracture callus or the broken part of the bone and regenerate new tissue. And it is that capacity for regeneration that many people in regenerative medicine are trying to capture, including work we are doing

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ourselves. Now, my particular interest is computational simulation of these regeneration processes. But what precisely do we have to simulate? Well first we have to simulate cells moving into the regeneration region. We have to simulate the proliferation of cells and the death of cells. If you put cells onto a plate and leave them there, they’ll actually proliferate, they’ll divide and spread all over and we want to model this process. Second we may also have the formation of capillaries. Bone will not regenerate unless blood vessels grow into it. Third, at some stage during migration of these stem cells into the regenerating region their fate will be determined. I’ve been collaborating recently with Dr Paula Murphy and her group in developmental biology and for the first time it became clear to me that I had the wrong concept about this – previously the stem cells we had in our models differentiated as soon as they were hit with a particular stimulus, but actually a more general, a more

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valid, approach is that cells be programmed to differentiate some time later after they’ve got the stimulus. So this is what matters in the process: stem cell fate, stem cell differentiation, and matrix synthesis. All this has to be added together to create a simulation of the regenerative processes, and I’ve put it all into a diagram [below]. And I’ve just put the ‘Bond girls’ picture into the diagram because they’ve been involved in doing experiments in every part of the process. Because I don’t believe we can validate or corroborate the total simulation – that’s very difficult to do

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because of the variability in clinical outcomes. But what we can corroborate, or validate, are the internal algorithms that form part of the simulation. Now here is a simple thing, we can model cells moving around in a lattice. We could simulate motion in many ways but what we’re going to do is create this lattice of points that are equally distant from each other and the cells move around in a random walk process. Many people here who have done science or engineering will be familiar with random walks. So we’re assuming that cells move randomly in this lattice.

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What’s more, we can simulate the process of cell proliferation and cell death. Because if you have a cell, and take that top/left one there [below], there’s a cell in the middle, it splits and it can leave two cells occupying the first position and a new position, in that case above it. As a matter of fact, when you work all this out you find that there are 21 possible states for cells to end up in after they divide. Therefore, with our model that uses a lattice for simulating cell positions, we can simulate cell proliferation as well.

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We have to do some experiments on this and these are interesting experiments. As part of Emma Kearney’s PhD we built this device. I don’t have a pointer but maybe I’ll use this – in here we can put a piece of silicone and in fact the device stretches it back and forward, using a little cam mechanism.

So we can put the stem cells onto this surface here [pointing to diagram above], and stretch them back and forward. And we can see what happens for different amounts of stretch. Emma got many interesting results but

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essentially we find that, if you compare the black bar with the white bar, increasing the extent of the stretch, and also with the number of days after starting the experiment, the amount of proliferation decreases. So we can get a relationship between the degree of stretch and the amount of cell proliferation. The upper and lower graphs are 2.5% strain and 10% strain. So the degree of strain and the time determines the amount of cell proliferation. Emma also looked at cell death (apoptosis) and in this next picture [left side], you won’t really notice it, but stem cells are dying. If we look on the graph, on the x-axis, we have strain and on the y-axis percentage of DNA defragmentation which is a measure of cell apoptosis or cell death and as the strain increases, we reach a threshold of about 7.5% strain where we get significant greater amounts of cell death. So this is the kind of empirical information we need to run our models.

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So what we have here is a cubic model of a piece of tissue [see over] – this is our computational model of tissue – seeded initially with four cells. These cells migrate and proliferate and take over the regenerating domain. But as they do so, they’re subject to a biophysical stimulus and they differentiate, and we want to model this next. If they differentiate they do so dependant on the oxygen they receive. And oxygen gets into your tissues through your blood vessels. We all know this – we breathe, air goes into the lungs, and the blood is pumped through the lungs, gets

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oxygenated, so you have to simulate the growth of capillaries. Sara Checa, a posdoc working with us, has been attempting to model this for some time. Imagine the top there is a parent vessel [see over]. We can simulate in this lattice model rather easily; we can simulate the random growth of a blood vessel in the regenerating domain. This is just one little picture of it. The blood vessel grows towards a region where there are angiogenic factors, VEGF in this case, indicated by the green box [see over]. I’m not going to get into the details of this but we can simulate anyway the growth of

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blood vessels which is very important because bone will only form near a blood vessel, near a capillary. As a matter of fact, a hundred microns or thereabouts is considered the threshold. So we incorporate that in our models. Next is a famous picture about stem cell fate [overleaf]. This is coming on to the last part of the model. At the top there are these mesenchymal stem cells. How do they choose which lineage they go into? This is the question. Many people are trying to answer this. For example

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leftmost in the diagram [below], those stem cells enter the osteoblast lineage and differentiate to form bone. They could differentiate in the chondrogenic lineage to form cartilage also, and so on. People are particularly interested in getting them to form neural tissue for nerve regeneration but that’s not a particular focus of our work. We want to know how the mechanical stimulation can determine the differentiation pathway of these cells.

Now, James McGarry when he was working with us, he has since gone on to be an undergraduate medical student, did some interesting

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experiments putting cells under different degrees of stimulation: putting them on a glass plate and flexing the plate, or putting them on a glass plate and having fluid flow over Them, and then measuring various things. Leftmost in these graphs is measuring NO, it’s not ‘no’ it’s nitric oxide, and PGE2 is prosteoglandin E2. Here we find that fluid flow and substrate strain create different degrees of reaction in the cells. But what’s important here actually is that, in the graph to the right, the increase in collagen type 1 is much greater for substrate strain than it is for fluid

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flow, whereas fluid flow dominates for the production of those other two factors (NO and PGE2) So in fact we can conclude from this that there’s an independent role for fluid flow and strain in cell mechano-regulation. And we’ll put that into a model – this is what I personally like to do. This is my diagram that was first thought of when I myself was a postdoc with Professor Rik Huiskes in Nijmegen – I ask all my graduate students put into every presentation whether they want to or not! On these mesenchymal stem cells, on these precursor cells, shear strain and fluid flow act. Depending on the magnitude of that, shear strain and fluid flow, you get differentiation to form fibroblasts and fibrous-connective tissue, chondrocytes and cartilage connective tissue or osteoblasts to form bone tissue. So the important point is, then, that the degree of mechanical stimulation determines the stem cell differentiation pathway, in this case a pathway to form a fibrous

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connective tissue [solid line], in this case a pathway to form bone [dashed line]. And Louise McMahon did some experiments on this in a bioreactor. This is a bioreactor [pointing to the metallic box, over]; as a mechanical engineer I have to show some machine like this; this [pointing to bar] moves back and forward continuously, stretching the samples. I see there are five wells there. Only two of them are filled with sample in this picture. The sample pulls back and forward applying a cyclic stretch. But this time

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we don’t stretch just a piece of silicone, we stretch a little piece of scaffold that has depth and thickness to it as is depicted here [in yellow]. So we seed the cells into this scaffold, stretch it and see if that affects their differentiation pathway. Thankfully it did: the images to the right show the cells actually in the scaffold. The green is the cell and the red is the scaffold. So the cells attach, in 3-dimensional terms when they’re put inside in the scaffold. But here’s the main result [picture below]: 35S sulphide incorporation on the y-axis is the measure of the

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amount of GAG synthesis, so it’s a measure of cartilage. And on the x-axis are different experimental groups. If we look at the first one, it’s uncons-trained with no chondrogenic factors. If we add the chondrogenic factors in the unconstrained we get much more cartilage, many more chondro-cytes. But if we constrain it and thus prevent the scaffold from contracting – because as soon as you put this scaffold in water it contracts – we reduce the amount of stem cells differentiating into chondrocytes and forming cartilage. So this shows clearly what some people will still debate, but

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it shows clearly that there is a mechano-regulatory effect on stem cell differentiation. If we stretch it, it becomes again different from the constrained case, becoming more like the unconstrained case actually. So mechanical forces definitely affect stem cell differentiation. That’s the ‘take home’ message. Now, we can put all this together into a simulation. And as the cells move in our simulation, they will differentiate forming fibrous tissue, cartilage bone. I realise that time is moving on here now. Referring to the diagram [overleaf], we initialise a lattice, we do a finite element analysis, we simulate blood vessel growth, we simulate stem cell migration, and we only allow the cells to proliferate if they have passed a sufficient age at which time we apply our mechano-regulation rule, including the fact that biophysical stimuli determine stem cell fate, plus the fact that you have to be nearby a blood vessel to get bone differentiation.

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Then we run our simulation and we can simulate various processes. So this is our big theory, and I’ve no illusions about how making a lasting contrib-ution but I hope that the work we’re doing on this is quite novel, and I think people are interested in it because of the value it could bring to research in functional tissue engineering. The most famous picture in tissue engineering is an ear on the back of a mouse, it’s terrible isn’t it. We don’t do anything like that …… What we’re interested in is looking at human cells and how we can use them

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to create human tissues. So I’m going to apply the model that I just described to you to a real problem. Here is a printed-type scaffold [below]. This is collaborative research we did on an EU project with Damien Lacroix in the Polytechnic of Catalonia. We want to see kind of porosity, Young’s modulus and other material properties should this scaffold have to regenerate bone. So we develop a finite element model of the scaffold – this shows a simple version of it in green. In fact we’re only interested in the

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regenerating tissue part of it which is in red here in the yellow box. So every finite element model in this is full of lattice points which will later become occupied by cells in the simulation. The final part of the figure here [part (c)] is only necessary because this scaffold actually dissolves. Most tissue engineering scaffolds used for regenerative medicine dissolve and, as they dissolve, there’s more space for cells and we have to account for that by creating more lattice points, and that’s what we do here (they’re in blue). So that’s the hypothesis: The porosity of the scaffold, the dissolution rate of the scaffold and the Young’s modulus can be optimised for maximum bone regeneration in a printed-type scaffold. This is a slide I got from Danny Kelly, who holds a President of Ireland Young Investigator Award (PIYRA) in this subject in the School of Engineering. If I ran that bioreactor [pointing to the slide overleaf], what I’m saying is we want to put a scaffold into this and apply a mechanical pressure on it and

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ask: what are the design qualities of the scaffold that would best give bone regeneration? In fact you can see here there’s a little piston running back and forward there and this piston will stress the scaffold and the cells seeded within it and the question is what sort of loading do we want to put on the scaffold, and what design of porosity, to give maximum bone regeneration. So we do some simulations under a high load and a low load. Now it might be hard to understand these but in fact we are looking at one quarter of

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that scaffold. Actually we’re looking at the face that has the yellow box around it, and what you’re going to see here now is in the beginning the simulation has stem cells appearing and cartilage cells appear and then bone cells appearing. A low load actually gets quite a lot of bone. Eventually all the stem cells will disappear in the simulation and we’ll have mostly cartilage and bone. But if we do it under a higher load, we’ll find actually the simulation produces very little bone at the outcome. Mostly it produces cartilage. And this, by and large, fits in with what’s found in experiment – that too much loading

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predisposes towards soft tissue formation with less bone. As you can imagine we can use this model for many parametric studies and we do that to find optimal scaffold design for bone regeneration. We vary the porosity, the Young’s modulus and the dissolution rate and we keep the load low and we find the porosity, Young’s modulus and dissolution rate that gives maximum bone regen-eration. So this is the advantage of doing the kind of computer simulations we talk about, and I think it’s essential for regenerative medicine and tissue engineering to use computer simulations like engineers so commonly do for many other applications. You’d never think of designing a thing in mechanical engineering without doing a model of it or some sort of prototype, particularly in the automotive or aerospace industry. But it hasn’t caught on yet in regenerative medicine and we’re one of the world’s proselytizers for changing this situation.

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So I’m getting near the end now. But I can’t stop without showing you this. These are results for fracture healing of a long bone; I’ve put in Mr. Damien Byrne because he should have submitted his PhD a month ago and this is a hint (I hope you don’t mind, Damien!) but he will submit it very soon and it’s great work that he’s done. This is a tibia [below] of your lower leg, and on the tibia is a fixator, and what Damien’s been able to do is develop a simulation process. The fracture callus is shown differentiating and resorbing around a piece of bone. The bone is cut

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in half just so as you can view it, and you’re looking in at the fracture callus. Talking you through this animation now, in the beginning we have bone formation in green, cartilage in pink, but eventually we simulate the complete repair process and resorption process in three dimensions in a human femur under realistic loading – we have collaborators in Germany that gave us the realistic loading for this human femur bone. So we believe we can take this sort of thing forward to provide predictions of what the optimal loading environments are for healing in the human case. We’ve also done work like this in, not me personally, but collaborating with Danny Kelly, on the human mandible for example, and many other applications of tissue regeneration in a clinical environment. Right, that’s four topics of this lecture done. I’m about to finish with • mechano-regulation, and • bioengineering and why it matters.

* * *

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You might not know this but we do live in a very high gravitational field and as a matter of fact we’re like ‘Sponge Bob Square Pants’ and all his friends, we live at the bottom of a sea and we’re pressurised by a fluid – air. We’re pressurised by it because the gravitational field pulls on us and pulls the air on top of us. And we have, over evolutionary time, become attuned to living in this mechanical environment and the cells within our bodies are tuned to make our bodies grow and survive and prosper and pass on our genes in this high mechanical environment. So I want to finish by saying that mechano-regulation algorithms are created in biological tissues during evolution. I call them algorithms at least because they encode an automatic sequence of events in response to biomechanical stimuli acting within the tissues. And the algorithms act to continuously grow and attune our skeleton, our musculo-skeletal frame, to living in this gravitational field. So there’s a

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connection here between evolution (biology) and gravity (physics) that many people are working on the interface of. I actually wrote a very good paper on this once and nobody cites it. I can’t get over it. But it’s a curious thing, I think it’s one of the best things I’ve written because it goes into this idea that you have mechano-regulation algorithms and not only is the skeleton itself evolving, but the algorithms designing and repairing the skeleton are also evolving, encoded in the genes: mechanosensitive genes.

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And I think that this is an important issue, and part of work on this is being done now in collaboration with Paula Murphy and Niamh Nowlan. This is one of their interesting images of the forelimb of an animal [see above] trying to identify what the mechano-sensitive genes may be, and where they are expressed. What are the mechano-sensitive genes that are responding to these biophysical stimuli? Some very interesting work is being done on this with embryonic chick and mouse. This is a limb in the embryonic chick actually. These pictures can be used to create finite element models to calculate the stimuli acting within actual growing bones and, along with other techniques, can identify what genes are being expressed. And the idea is to correlate, and this has already been done, there’s no time for me to explain it and I wouldn’t want to take the wind out of Niamh’s sails on this kind of results anyway, but the important thing is that we can identify what genes are being expressed in response to which biophysical stimuli in growing bones. And this work is ongoing, and will, I hope, produce

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results that will help us to understand how “mechano-regulation algorithms” are being continuously executed with our load-bearing skeletal elements.

* * * This is a slide of where I’m from; a place called Oulart in County Wexford – where our family is from. It’s well known, as some of you who are historians will know, for its role in the 1798 rebellion. Oulart is well represented on the internet as I found out when I went searching for these pictures. In fact there is a book about one of the most famous things that

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ever happened in Oulart, the Battle of Oulart Hill in 1798. It’s a famous event – well famous enough for a book to have been written about it – and the cover is shown here on the slide; it’s about the struggle, I suppose you might call it, that the local insurgent army had against a militia that was sent out to defeat them. And this battle happened on the top of Oulart Hill, and has made it a very interesting place historically. In 1898 a monument was built for the centenary [middle picture]. More recently in fact we’ve built a more conceptually challenging monument which I recommend that you should see. I think it’s a magnificent structure. This is it here on the top of Oulart Hill; you can see it in the distance. And in fact close up it looks like this [pointing to pictures above] – it’s a mound, a ‘tulach’ in Irish, split down the middle by these concrete walls and inside in the concrete walls, you can just about see it there, well maybe it doesn’t come out in slide, but inside the mound there’s a room, a space, so you can walk through into the mound and into a room, and there’s a particular time of the year

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that the sun shines straight through it. Obviously it’s mirroring what happens in Newgrange. I’m going to quote here from the builders and architects: “The memorial is split down the middle, just as the old feudal world of the 18th century is separated from our own democratic age, kept apart by the flood of ideas we call the enlightenment which elevated us all from subject to citizen”. So this monument on the top of Oulart Hill is a monument to an idea and all of us here, ladies and gentleman of the university, all of us have our own, admittedly much smaller, contrib-utions to make to the world of ideas. In this way bioengineering matters, I’m going to say, because it matters to me, and to the students who come here to study it. And the free pursuit of ideas should matter to all of us. That’s why I think that what we do in the university is so important. I wish to make a few acknowledge-ments; particularly I’d like to acknowledge the graduate students

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and the postdoctoral Research Fellows I have worked with. I would like them to know I have appreciated, and enjoyed, working with them. I’d also like to acknowledge the Principal Investigators in the Trinity Centre for Bioengineering and colleagues in Mechanical Engineering, also too numerous to mention individually, but the kind of engineering research that we do really is ‘team science’ and it wouldn’t get anywhere without the team effort. It is a pleasure also to thank Sheena Brown for her administrative support for our bioengineering research: it’s an honour

• Graduate students and post-doctoral researchers

• Colleagues in bioengineering and in mechanical engineering

Acknowledgements

Brendan McCormackDamien LacroixPeter FerrisSuzanne MaherPaul ConnollyBruce MurphyDanny KellyMatteo MorettiLinda MurphyAlexander LennonAdriele Prina-MelloPatrick KennyCaitriona Lally

Laoise McNamaraJohn BrittonMary WallerJohn VardLaura WalshJames McGarryPaul ScannellLouise McMahonEmma KearneyOlivia FlanneryNiamh NowlanRuairi MacNiocaillRuth McLoughlin

Brianne MulvihillPatrick WulliamozDamien ByrneKaren RoddyGeraldine KellyPavel GalibarovParnell KeelingColin BoyleColm LowerySara ChecaHanifeh KhayyeriKatey McKayedFeng Xue

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for me to be part of this winning team in bioengineering. I’d like to finish with that. Finally there’s a great Dutch phrase that all professors in the Netherlands use conclude their professorial lectures, and it is ‘Ik heb gezegd’. Thank you very much.