 Thank you for that introduction. So, yes, I'm going to enlighten you a little bit about modelling lung structure and function. This is going to be a very quick journey through some of my group's research, a journey from basic science discovery through applied through to clinical research, and back again. And it's also a multidisciplinary journey and a lot of international collaborations. So, first, the first thing in this title, Modelling Lung Structure. So, we start with a can-wee question. So, can we use mathematical algorithms to simulate the anatomical structure of the lungs? So, the airways, the blood vessels, the lung surface topology? The answer is yes, fortunately. So, what you see here is a mathematical model of one human conducting airway tree-generated using an individual's medical imaging, so computed tomography. We use these tree-creating algorithms, volume-filling branching algorithms to create the tree geometry. Now, why does that end up being important? Well, we know that there are significant differences between species in terms of this branching geometry. But if you are thinking about drug discovery, drug development, trials, initially animal trials, if you are testing your drug dispersion in a very different geometry to what you are hoping it's going to end up in, which is human, then you can end up with results that don't get translated well to human physiology. That's just one of the purposes. Once we have structure, we then want to think about function. Now, in the lung, as in any biological organ structure and function are intimately related to each other, when we have lung disease, we are typically getting a change to structure which affects function. So, we would like to understand how these things are related to each other and how we can exploit understanding of structure-function interactions to come up with better methods for diagnosis and for treatment of lung disease. So, we've developed methods to simulate how the lung tissue deforms under gravity and then linking that to simulations of ventilation distribution in the lung. So, when you breathe in, the air doesn't go uniformly everywhere in your lung. It depends on your posture. So, with your upright lying on your back, lying on your stomach, the air distribution is different and as you age, which I'll touch on later, there are further significant differences. So, we've developed models that go from the very complicated through to more simplistic methods that we can use sort of at the bedside, rapid methods to simulate ventilation distribution. Along with that, we also need to understand where the blood goes in the lungs. So, you don't get gas exchange if you don't bring air into close contact with blood. So, we have developed models. So, these are one-of-a-kind models that simulate from the right ventricle through the entire pulmonary circulation, including the recruitable capillary beds, and back again to the left atrium. So, these models include all of the significant mechanisms that affect the characteristic distribution of blood in the lung. So, again, affected by gravity, affected by structure, affected by the recruitment of these capillaries. You don't always have blood flowing through all of your capillaries. So, once we put these things together, ventilation distribution and perfusion distribution, we can then simulate gas exchange. So, this is occurring at approximately 32,000 little individual gas exchange units in your lung, and we simulate that at that level of detail. The variability that we predict and that we know is present, anatomically or physiologically, sorry, is really important. The variability that's present at baseline and then when we start to overlay additional ageing or pathology. So, let's look at just one way in which we've used this. So, this work, I should acknowledge Alice Clark, who was a post-doc with me on an HRC grant a few years ago. So, this is using our models, so now we have this ability to simulate the tissue deformation, ventilation distribution, blood distribution and gas exchange throughout the lung. This means we can then start to investigate clinically relevant problems. In this case, acute pulmonary embolism or blood clots in the lung. So, clots that are preventing blood from getting to parts of the lung tissue and therefore preventing gas exchange occurring in those bits of tissue. So, we can do computer simulations. So, we take imaging from individuals who've been diagnosed with acute pulmonary embolism. We then create a subject-specific model for that individual or group of individuals in this case. Why we were motivated to do this was to understand why you can get people with apparently the same clot load, so apparently the same amount of clot blocking off bits of lung, but they can have very different clinical symptoms. This is important for stratifying patients for what sort of treatment strategy should they get. We were from this work able to come up with a potential new model-based biomarker for stratifying patients into these different groups. A radiological scoring tool that radiologists can use to come up with a simple metric to stratify patients. And a surgical tool, so for being able to do virtual surgery to remove sort of fibrotic mass in patients who go on to develop a chronic form of this condition. So, this little journey I'm talking about. So, we start off with just some questions where there doesn't appear to be any real specific applied outcome. So, how can we model how the lung tissue deforms or can we model it? So, being in a sort of basic science question, this was supported by Marsden, which gave us the ability to develop the basic model framework. Then, we go on to validation in animals, validation in humans, applying this model in patients who are invasively or non-invasively ventilated. And then, through international connections, through to which we're looking at now, understanding how different types of ventilation strategies can be optimised to individuals to improve their clinical outcomes. Another question. What happens to the lung as it gets older? Lots of bad stuff, I can tell you. So, an NIH subcontract, first of all, just to develop a statistical model of the lung and then going on to re-examining hypotheses for lung function now in the framework of the older lung. Okay, thank you.