In this edition of The Naked Scientists, we look back at another brilliant year of science and select some of our favourite stories to come out of it...
In this episode
00:57 - Best of 2024: Plague pit DNA
Best of 2024: Plague pit DNA
Christiana Scheib, University of Cambridge & Fiona Gilsenan, Corpus Christi College
We begin our look back at 2024 in January, when we reported on the ancient DNA of almost 300 people who lived in Cambridgeshire before and after the Black Death - the plague that repeatedly rampaged across mediaeval England, and killed as much as a third of Europe’s population. For a long time, it was thought that such a shocking drop in numbers would have changed the genetics of the continent, as survivors passed on their resistant genes. Well, perhaps not. But one way to be sure is to sample one of Cambridge’s mass graves, to see what the ancient DNA has to say on the matter. Chris Smith ventured there - on an extremely cold day - to meet researcher Christiana Scheib, and Corpus Christi College’s Fiona Gilsenan…
Fiona - We're standing at what was the original entrance to Corpus Christi College. The college was founded in 1352 in the wake of the Black Death, the Plague, and the original entrance to the college ran across this passageway here from Bene't Street, past St. Bene’t's Church and into what's now called Old Court.
Chris - Indeed, this does look a bit like the tradesman's entrance. I can see why you moved it. It's much more prestigious now. But what's special about this entrance?
Fiona - Well, some years ago, we had to do some work on the building of what is now the Taylor Library. So we excavated part of this pathway and when we did that, the archaeologists found that there were some skeletons down there that were buried in an unusual way.
Chris - Is it relevant that right next door to where we're standing there is also a church.
Fiona - It's very relevant and this in fact is the oldest church in Cambridge and there are lots of burials here, but they were standard burials. The ones that we're talking about today were found stacked and not properly buried as individuals. And so that's an indication that they were probably buried quickly. The thinking by archaeologists who've worked on them was that they were probably victims of the Plague. And I think that there's some evidence that came out to indicate that that was the case.
Chris - Standing next to me is one of those researchers who worked on this. Tell us who you are and why you've come along today.
Christiana - I'm Dr. Christiana Scheib, I'm a fellow at St. John's College and a group leader at the Department of Zoology here in Cambridge.
Chris - You had access to some of the material that came out from under our feet. What were you looking for?
Christiana - I had access to four individuals, plus a fragment of cranium, so five individuals probably. And what I was looking for was, one, the human genome - we wanted to know more about mediaeval Cambridge, but also I was looking for evidence of plague.
Chris - There's been this question about the Plague which is, people say that because it killed so many people, it had an effect on the genetics of the people that are around today. It killed off a vulnerable group, left a survivor group. Were you able to get at any of those sorts of questions with this?
Christiana - That has been a longstanding question in the area, in the field. You would expect that anytime you have a pandemic, you will have a pressure on the population that's affected to adapt. And with the Plague, we know that the mortality rate was 30 to 50/60%. It was very high. So you would expect there would be a huge impact on the genetics of the people who survived. And that was what this project was about.
Chris - Was it just here you looked at or did you have material from other burials around the town?
Christiana - So the project itself comprised more than 10 sites across Cambridge. We were going all the way back to the Neolithic, so the earliest individuals are from an early Neolithic monumental burial in Trumpington. And the most recent are from the mid 19th century, from Holy Trinity Church just a few doors down. We wanted to get an idea of the overall population structure of Cambridge through time and how this might have affected them.
Chris - And the benefit of that huge time window is of course that straddles the time when the Plague circulated in Europe, doesn't it? Because it had gone by the 1800s and you predated it a bit. So I guess you can then ask, is there a before and after effect in terms of any impact on genetics?
Christiana - Exactly. What we were primarily looking at initially was the potential genetic impact of the Black Death or the second pandemic. That started in 1347 and came in recurring waves up until the 18th century.
Chris - How did you actually do it?
Christiana - So we screened a lot of dead people for both human genome, what their immune systems looked like, as well as what diseases they had and whether or not they did have plague. We had two sets, people who had plague and then people who did not have plague. And really for this study, we ended up not looking so much at the people who had plague because we know that those people actually died from plague. What we're interested in are the people who were living before the general population, before the second pandemic or the Black Death, and then the people who were definitely born afterwards, so therefore they were children of survivors.
Chris - And I guess you can then ask the question, are there any genes different between those two groups? Because if there was some effect of the plague killing off vulnerable people or preserving people who were more immune, I suppose you'd expect to see them more or less represented in those populations?
Christiana - That's exactly what we were looking for. Is there a difference in the genetics of the population before the Black Death and the people who were born, presumably of survivors?
Chris - And what did you find?
Christiana - We actually found that there was no difference. I mean there were minor differences, but nothing that you would call statistically significant.
Chris - So that sort of blows out of the water this idea that plague did have a big moulding effect on the genetics of Europe?
Christiana - The social impact was huge and the impact on the individual's lives would've been huge. But from a population standpoint, probably because we had so much mobility afterwards, we don't see a strong genetic impact, at least in Cambridgeshire. And it could also be because of the way that the plague kills. It's not maybe targeting a specific gene or something like that, it's maybe a more complicated route to death, if you will. And so therefore there's a lot of things being worked on and therefore there's not one particular target. It sort of muddies the waters.
Chris - What about the social question as in, because you were looking at a range of individuals from a range of different backgrounds, did you see that any particular groups were more susceptible? Because one of the things we see with disease, we often say people who are in poor conditions or poor health, generally, they don't have good food, don't have good living conditions, are more vulnerable. People who were better fed, et cetera, less so. Was the plague taking no prisoners or did it follow that pattern?
Christiana - People have long said plague is an indiscriminate killer and that seems to be reflected in our data. It doesn't matter how rich you are or how poor you are, you are still susceptible to the Plague. Now, whether you survived, if you had good resources that might have helped you survive. And unfortunately with this kind of study, we're only looking at the dead people that we can see. So we're seeing people who we know died of plague or people who we don't know whether they were ever exposed. We can assume they were exposed, but perhaps they never were. Maybe they moved to the country and they managed to avoid it, which did happen amongst people who could afford it.
Chris - Can you answer a question that's outside the scope of your present paper, but one which has baffled people for a long time, which is why plague just disappeared?
Christiana - Yes. This is a really interesting question and lots of people are working on it. It could have to do with the vectors. So we believe that it's carried in fleas on rats and perhaps something changed in the environment or the way that the bacterium was infecting the vectors and maybe improvements in sanitation helped eventually for it to die out, but it seems unlikely that it went away simply because everybody became immune.
Chris - And are there any more plague pits that you can dip into in Cambridge? Or have you run out of resources now?
Christiana - I think there are plague pits everywhere. In fact, my other work is on the first pandemic, the earlier plague, which came to England, that I've worked on as part of the 'After the Plague' project, but it's also known as the Plague of Justinian. So during the early Anglo-Saxon period, we also had a pandemic that came to England and affected people in very much the same way.
Best of 2024: How humans lost their tails
Itai Yanai, NYU Grossman School of Medicine
Into February now, and it may not have escaped your notice but us humans, alongside chimpanzees, gorillas and orangutans, do not have tails. It sets us apart from other primates, but suggests that, at some point, an evolutionary split occurred that left some primates with a tail, and some without. So why did we lose them, and how? In February, Itai Yanai - a geneticist and systems biologist at NYU Grossman School of Medicine - explained all…
Itai - The story starts with a student in my lab, his name is Bo Xia. Bo got injured while sitting in a car. So he moved over and he sat unfortunately on a belt buckle and he injured his tailbone. It all sort of culminated in a very simple question, how did we lose our tail? The chimpanzee, they don't have a tail, the gorilla doesn't have a tail. But if you go to something more distantly related like the macaque monkey, the macaque monkey of course still has a tail.
Chris - Is one way to try and find out why we even had a tail historically and how these other animals have a tail. Is it, you go and look at them and ask, well, what genes have they got that might make them have a tail? Because then you can, you can ask, well, are they different in us?
Itai - Right. So what Bo did is he studied the genome using a genome browser that allows him to see very conveniently, what does our genome look like? And particularly what does it look like when you compare it to the genomes of other animals like the macaque, like the gorilla and the chimpanzee. And what he saw is that there is a particular element that's in a region that doesn't look like it would be important. It doesn't look like it would be very disruptive. However, it had three interesting things about it. One, it was in this gene that was known for a very long time that it's responsible for the tail. Two, it's an element that we could see at the right time. Why is it at the right time? Because all the animals that have this change don't have a tail. And all the animals that do still have a tail lack this element. So it was the right pattern. And three, knowing molecular biology, Bo could see that that actually would be highly disruptive. So now Bo had a hypothesis, this change is how we lost our tail.
Chris - So in summary then you home in on this region of the DNA, which we know is linked to animals having tails or tail function. And that in animals that appear not to have a tail, there is a region of that gene which has a change in it, and it's in all the animals that don't have a tail. And it appears in such a way that it would disrupt or affect how that gene would work, which does look like a smoking gun genetically then.
Itai - Exactly. So now the question is what do you do with this? Bo and I sat down together and we designed this experiment where we would generate mice that have exactly the same kind of mutation that we saw that we have. And the prediction would be that if you make mice like that, they would also lose their own tails.
Chris - And do they? If you introduce this same change into a mouse, do you end up with mice with truncated or absent tails?
Itai - You know, they do and I still get goosebumps every time I think about it. They do. They're born without a tail. And although it took years of work, four years of generating mice and studying them, what we saw was that there's a correspondence between how much disruption we put in and the length of the tail.
Chris - Now most things that get fixed in evolution confer some kind of advantage. So on the one hand we lose a tail and gain 'taillessness'. So what would've been the advantage that would've meant this was so strongly selected for in the group of animals that were our ancestors back in history?
Itai - It was 25 million years ago, so we'll never know for sure. The way we speculated is that actually it could very well be that this mutation was the fundamental mutation that led to us sitting down here and talking on The Naked Scientists podcast that facilitated us to come down from the trees and have a life on the ground where we now stand on our two feet.
Chris - One issue though is that that part of the body, how we form the backbone and the spinal cord that overlays it, there is a small group of unfortunate people in the population who suffer neural tube defects. The condition spina bifida where the tube that forms the spinal column doesn't close up properly at one end, the tail end. Now does this link up with, or is that associated with, this particular gene and is there therefore a risk if you disrupt it that you're going to get more of that happening?
Itai - Yeah, you know, this was a completely unexpected aspect of this project that when we made the mice with those mutations, some of them were born with a condition that looked remarkably similar to the human condition that you mentioned with neural tube defects. And I think now it could lead to a series of new studies that promise to make some kind of advancements on how we treat this disease. And yet that's the magic of science, that if you let people follow their curiosity, it will lead to interesting places that are just unpredictable.
15:06 - Best of 2024: The largest sea reptile ever found?
Best of 2024: The largest sea reptile ever found?
Dean Lomax, University of Manchester
We continue our retrospective in April, as we heard how a father and daughter discovered what could be a remnant of the largest known marine reptile. Justin and Ruby Reynolds found a piece of jaw belonging to an ichthyosaur, dubbed Ichthyotitan severnensis, on a beach at Blue Anchor in Somerset. It was then sent to Dean Lomax - a palaeontologist at the University of Manchester, and this is what he had to tell me about the extraordinary finding…
Dean - To go back in time a little bit, not quite to the Jurassic of the Triassic millions of years ago. But I received an email initially way back in May, 2016 about a jawbone that was found in Somerset. And then after studying that specimen, which was found by Paul de la Salle, we described it in 2018 and we determined that it was a really unusual jawbone from a type of ancient marine reptile called an ichthyosaur. And because the age of which this comes from is about 202 million years old, right at the end of the Triassic, we knew then that it was something unusual and very likely came from a really big ichthyosaur. But we were kind of hesitant about giving it a name or working out exactly what type of species of ichthyosaur it was, and so entered this new discovery. Justin and Ruby managed to find my scientific study from 2018, reached out and were like, 'Hey Dr. Lomax, we think we found another one of these giant ichthyosaur jaw bones.' And of course you can imagine my huge grin on my face because I was like, 'absolutely, yes you have.'
Will - How do you then go from these two fairly abstract samples to being able to scale it up to make assumptions or predictions about the entirety of the organism involved?
Dean - Being completely honest, with just two giant jaw bones, it is impossible to say with absolute certainty just how large our new species of ichthyosaur was. However, there are other ichthyosaurs that have been found that are on the kind of size range lengthwise between like 15 to 21 metres. The biggest one was in the region of maybe 40 to 50, maybe a little bit more percent complete. And this ichthyosaur, which has a name called Shonisaurus sikanniensis, has an estimated skeleton length of 21 metres. Now by comparing Paul's original 2016 discovery and Justin and Ruby's discovery with the same bone, which is called a surangular, which is a bone right at the back of the lower jaw, we can work out that the specimens are about 25% larger. So by doing a little bit of kind of like quick maths and using a simple scaling factor, we can estimate that our ichthyosaur is upwards of about 26 metres. And then comparing it further with other ichthyosaurs, smaller species and those kind of bridging the gap between the very small ones and the really big ones, we can basically work out that our ichthyosaur would've been around about the 20 to 26 metre mark with most of the averages coming out at 25 metres.
Will - It's a very exciting finding, but I still do need some reassurances because growing up my hero was of course Liopleurodon, another marine reptile which, originally, thought to be 20 plus metres. And in the years since has been revised down to six, which is a remarkable shrinkage. It should probably be about three feet by next year. How can you assure me that this isn't going to happen to this as well?
Dean - <Laugh> I kind of anticipated this question would come at some point that makes me laugh. At the time, if I remember rightly, it was based on some really fragmentary vertebrae and then there's been a few other kinds of scalings up of Liopleurodon based on their teeth. To be honest, teeth and vertebrae are not the best bones to try and scale up an animal in size. Because just for example, I studied a whole bunch of different ichthyosaurs, thousands of them now over the years. And by looking at, say, some vertebrae of an individual that's 10 metres long. Those vertebrae may only be say, 12 centimetres across, versus you might find another iau that's like eight metres long and those vertebrae may be 15 centimetres across. So vertebrae aren't ideal. That's why we have much more confidence in our scaling of that kind of 20 to 26 metre mark because we know that we have an ichthyosaur from British Columbia that was definitely at the 21 metre range. So looking at our new specimens, Paul's and Justin and Ruby's, we have something that we definitely can compare to, and we have the same bone that's preserved in that animal as well. So it gives us a much, much, much more reliable estimate and scaling factor.
Will - Okay, well I'm ready to love again. But it does make you think, given that the fossil record is a fraction of a fraction of a fraction of what was actually alive at the time, what could be out there still ready to be discovered and something really could perhaps have the potential to knock the blue whale off its giant perch?
Dean - That's quite right. And I said for a little while, especially off the back of Paul's discovery in 2016 and our research in 2018, that we think that in time potentially maybe we'll have a skeleton or at least a big skull of one of these giants found. As part of our research in this new study and the 2018 study, we also looked at some bones that were found here in the UK. And these bones were originally over 150 years ago. They were very similar. They're big cylindrical chunks of bone. But back over 150 years ago, the scientists then, and even right up to this day, almost to a point about 10 years ago, people were still considering them to be the upper arm bone, say a humerus or upper leg bone or a femur of a terrestrial animal, like a dinosaur. But in actual fact, they are also bones from the lower jaws of giant ichthyosaurs. And one of them is about 30 to 40% larger than the bone from the one in Canada. So that's when you start to get to the realms of are we dealing with something that was even maybe 30 plus metres? And then are we dealing with a thing that could take the blue whale off that very top of the largest animals ever? Maybe, maybe not. This is the thing, as you say, this is the fossil record and that's why it always reveals its kind of secrets and things. And this is just a little bit more of that kind of tantalising evidence of one of these mysterious giants that lived at the very end of the Triassic period 202 million years ago.
21:02 - Best of 2024: Geoff Hinton explains how AI works
Best of 2024: Geoff Hinton explains how AI works
Geoff Hinton
In June, our summer series of Titans of Science returned. We heard from the ‘Godfather of AI’ Geoff Hinton who would go on to win the Nobel prize in physics later in the year, and I can only assume we played no small part in that win. Whilst AI is not so slowly creeping into every facet of our technological lives, the way in which AI actually makes its so-called decisions is still not clear to a lot of people. AI was built to function as a neural network, a model heavily influenced by the structure and makeup of our own brains. And so by simulating neural networks, you can learn a lot about how brains learn, and how AI learns too. This is what he told Chris...
Geoff - So we now have computer models of neural networks, things that run on a computer but pretend their networks are brain cells that work really well. You see that in these large language models and in the fact that your cell phone can recognise objects now it can also recognise speech. So we understand how to make things like that work and we understand that the brains quite like many of those things. We are not quite sure exactly how the brain learns, but we have a much better idea of what it is that it learns. It learns to behave like one of these big neural networks.
Chris - If it's down to the fact that we've got brain cells talking to brain cells and they're just big populations of connections, is that not relatively easy to model with a computer? What's the holdup? Why is it hard to do this? Well,
Geoff - The tricky thing is coming up with the rule about how the strength of a connection should change as a result of the experience the network gets. So for example, very early on in the 1940s or maybe early 1950s, a psychologist called Hebb had the idea that if two neurons, two brain cells fire at the same time, then the connection between them will get stronger. If you try and simulate that on a computer, you discover that all the connections get much too strong and the whole thing blows up, you have to have some way of making them weaker too.
Chris - I love that line, 'What fires together, wires together.' It's never left me. Because I remember reading Hebb's book when I was at University College London. So how did you try and address that then? Was it sort of just a damping problem? You make it so that the nerve cells get bored more easily as it were so that doesn't overheat in the way that the computer would otherwise have them do?
Geoff - Well that's kind of the first thing you think of and you try that and it still doesn't work very well. So the problem is can you get it to work well enough so that it can do complicated things like recognise an object in an image or in the old days recognise something like a handwritten digit. So you take lots of examples of twos and threes and so on and you see if you can make it recognise which is a two and which is a three. And it turns out that's quite tricky. And you try various different learning rules to discover which ones work and then you learn a lot more about what works and what doesn't work.
Chris - What does and doesn't work and why?
Geoff - Okay, I'll tell you something that does work because that's obviously more interesting. You have a layer of neurons that pretend to be the pic cells. So an image consists of a whole bunch of pixels and the pixels have different brightnesses and that's what an image is. It's just numbers that say how bright each pixel is. And so that's the input neurons. They're telling you the brightness of pixels and then you have output neurons. If you're recognising digits, you might have 10 output neurons and they're telling you which digit it is. And typically the network to at least to begin with wouldn't be sure. So it hedges its bets and it'd say it's probably a two, it might just be a three, it's certainly not a four. And it would represent that the output unit for a two would be fairly active. The output unit for a three would be a little bit active and the output unit for a four would be completely silent. And now the question is how do you get those pixels as inputs to cause those activities in the outputs? And here's a way to do it that all the big neural networks now use. So this is the same algorithm that is used to train big chatbots like GPT-4. It's used to train the things that recognise objects and images and it's called back propagation. And it works like this. You have some layers of neurons between the inputs and the outputs. So the neurons that represent the pixel intensities have connections to the first hidden layer and then the second hidden layer and then the third hidden layer and finally to the outputs. So they're called hidden layers because you don't know to begin with what they should be doing. And you start off with just random connections in these networks. So the network obviously doesn't do anything sensible. And when you put in an image of a digit, it will typically hedge its bets across all the possible 10 digits and say they're all more or less equally lightly because it hasn't got a clue what's going on. And then you ask the following question, how could I change one of the strengths of the connections between a neuron in one layer and a neuron in another layer so that it gets a little bit better at getting the right answer? So suppose you're just trying to tell the difference between twos and threes. To begin with, you give it a two and it says 'with a probability 0.5, it's a two with a probability 0.5, it's a three.' It's hedging its bets. And you ask, well how could I change connection strength so that it would say 51% two and 49% three. And you can imagine doing that by just tinkering with the connections. You could choose one of the connection strengths in the network and you can make it a little bit stronger and see if that makes the network work better or work worse. If it makes it work worse. Obviously you make that connection a little bit weaker and that's sort of a bit like evolution. You're taking one of these underlying variables, a connection strength, and you're saying if I change it a little bit, how can I change it to make things work better and save those changes? And you could do that and it's obvious that in the end that will work, but it would take huge amounts of time. So in the early days we would use networks that had thousands of connections. Now these big chatbots have trillions of connections and it would just take forever to train it that way. But you can achieve pretty much the same thing by this algorithm called back propagation. So what you do is you put in an image, let's say it's a two. The weights are initially random, the weights on the connections. So information will flow forward through the network and it'll say 50% is a two and 50% is a three. And now you send a message back through the network and the message you send back is really saying, 'I'd like you to make it more likely to be a two and less likely to be a three. So I'd like you to raise the percentages on two and lower the percentages on three.' And if you send the message back in the right way, you can figure out for all the connections at the same time how to change them a little bit so the answer is a little bit more correct. That's called back propagation. It uses calculus, but it's essentially doing this tinkering with connection strengths that evolution would do by just changing one at a time. But the back propagation algorithm can figure out for all of them at the same time how to change each one a tiny bit to make things work better. And so if you have a trillion connections, that's a trillion times more efficient than just changing one and seeing what happens.
Chris - But how does the layer at the bottom know what's going to be changed above it to make sure that the input that it then gets is the right one so that the change it's just made to it, and its probability, ends up being even better so that you don't end up changing yourself. Then that feeds forward, back up, the network changes something else, but then it becomes less optimal for you if you get what I'm saying.
Geoff - I get just what you're saying. It's a very good question. And essentially what's happening is, if you take a connection early in the network, it's kind of making an assumption. It's saying suppose all the other connections stayed the same, how would changing my connection strength make things better? So it's assuming all the other ones stayed the same. And then it's saying if I change my connection strength, how would it make things better? And they're all doing that. So if you change the connection strengths by a lot, things could actually get worse. because you could choose a way to change each connection strength that if you did that change alone would make things better. But when you do all the changes at the same time, it makes things worse. But it turns out if you make the changes very small, that problem goes away. If you make the changes very small, then I figure out how to change one connection strength. And because the changes in all the other connection strengths are very small, it's very unlikely they'll turn, for example, a change that helps into a change that hurts.
30:03 - Best of 2024: Cervical cancer self-test success
Best of 2024: Cervical cancer self-test success
Anita Lim, King's College London
In July, researchers at King’s College London told us about life-saving do it yourself cervical-cancer checks. The team said the results of their trial - which used swabs for lab analysis - was a “fantastic” success. Chris Smith spoke to the study’s author, Anita Lim, and she had this to say about it…
Anita - We know that cervical cancer is caused almost entirely by something called the human papillomavirus. And this is a virus that is very, very common. Most people in their lifetimes will have it, but in a really small proportion of people who have it, the infection will stick around and it will start to make changes on the cells of their cervix, which is the neck of the womb that can develop into a precancerous lesion. And it's really easy to remove and treat those and prevent cervical cancer from even developing. And that's what we use screening for.
Chris - And so the argument would be that if you remove as many barriers as possible to a person getting screened, so you maximise the uptake, you're going to maximise the detection early and therefore get more pickup, more early intervention, more cure.
Anita - Exactly. The numbers of people who've been coming for cervical screening has been falling and they've been falling for the last 20 years. And we know that a lot of the reason why people don't come for their cervical screening is because it's a really intimate test. So people quite often might find it painful or they might be worried about developing cancer or they might just be feeling really embarrassed to have it. Some people are just busy, they plan on going to get their screening and they just don't get round to it. And then there's also simple things like people just not even realising that they need to get screened. If you're not getting screened regularly, you're not getting that chance to go and pick up what is such a preventable cancer. And allowing people, giving people the choice and the convenience of being able to take a sample themselves and the privacy of their own homes. It's just completely game changing for cervical screening as we currently know it.
Chris - What was the overriding question that you were hoping to probe with the study?
Anita - We wanted to see if self sampling, if we did offer it to those people who weren't coming, how many more women could we actually get screened by offering them the opportunity to do that. We offered over 27,000 kits to people with a cervix. And we did this in two different ways. We offered it at GP practices, so we got GPs and nurses and healthcare practitioners to offer kits to women who were overdue for screening when they went into the GP practice for any reason. The other way that we got kits out to people is we mailed kits to people's homes directly. And what we found was that if you offer the kits at the GP practice, we found that 56% of people who hadn't come to their screening before would actually return a sample. And when you mail them to people's homes, 13% of people would return a kit. And based on this data, what we estimate is that you could get over a million extra additional women screened if this was to be rolled out over England more widely over one screening round.
Chris - And based on what we know about the prevalence of human papillomavirus, HPV that causes cervical cancer, and the number of cases of cervical cancer that are occurring, how many cancers do you think you can prevent with an intervention like this each year?
Anita - It's very difficult to actually estimate that number based on the type of study that we did. And one of the reasons for that is because this is a sort of cancer that develops over, over a 10 year period or so. So it's quite difficult to estimate based on the study that we did. But what we do know is that because screening is so protective against cervical cancer, we do know that by introducing something like this, it's very, very promising. It's very likely that we will be saving many lives.
Chris - One of the criticisms of self sampling that doctors have raised in the past is whether or not you get adequate samples, whether people do it as well as a healthcare professional to get meaningful data. So were you finding that the samples that were coming back to you were good enough quality for you to give a negative or a positive that really meant something?
Anita - 99 out of a hundred women can take that cell sample correctly and that will take it accurately and that you can rely on the result. And then the other way to think about accuracy, and I think this is probably what you are trying to get at here, is around whenever you do a test, you're trying to pick up something and the evidence for self sampling is very, very robust. So the important thing to know about this is that if you take a self sample and your result is HPV negative, you can be just as reassured because that is just as accurate as the same result on a sample that would have been taken by your doctor or nurse. But if you take a self sample and you test HPV positive, this is just a preliminary indicator and you would need to have a follow-up test with your GP or nurse, which would be the conventional screening test. And this is just because you don't collect cells from the cervix as part of the self sample test. And so you just need an additional step in order to tell you if you need to go and have additional tests with a gynaecologist.
Chris - Does this suggest, based on what you are finding, that in fact our gold standard for initial screening should be to just invite women to self screen and only escalate their cases when you pick up a positive along the lines that we've been discussing?
Anita - My personal view on this at the moment is that we aren't ready for that yet. Self sampling isn't going to be for everyone. And what I would see for now or the next few years is certainly that we are going to see both tests alongside each other and having the choice will allow us to really increase the uptake of screening participation.
36:02 - Best of 2024: Testing out a -120 degree cryochamber
Best of 2024: Testing out a -120 degree cryochamber
Gosia Bieniek, Light Blue Clinic
2024 was an Olympic year, with athletes around the world converging in Paris to duke it out at the pinnacle of sporting competition. And so we delved into the science of keeping athletes in tip top condition. One aspect is cold therapy, taking a dunk in a cold body of water or ice bath, with some proponents claiming increased mood, faster muscle recovery time, and even stronger immune systems.
To find out more, but also to avoid taking a dip into an icy lake, James Tytko took a trip to the Light Blue Clinic in Cambridge, which contains a cryochamber capable of cooling participants to -120 degrees Celsius, and met up with Gosia Bieniek who took him through the treatment...
James - While my cold therapy experience was to be facilitated by modern means in a high tech cryochamber, the healing benefits of exposing your body to extremely low temperatures has been posited for centuries. That's not to say it's for everyone, though. When I booked myself in at the clinic, I was asked to fill out a medical questionnaire online, making sure I had no underlying health conditions that might make me unsuitable for the treatment. On arrival, my blood pressure was taken, I was given protective clothing to shield my extremities, including thick socks, hat and gloves, and then it was time.
The lovely people here at the Light Blue Clinic have made sure I'm fit and firing, healthy, ready to take on the cryochamber. I'm faced with this enormous fridge. I'm being told there's a prechamber, which is going to go down to, what was it again? -60 Celcius. That sounds quite cold enough if you ask me. But then I'll move on to the main chamber, which is looking at -120 degrees Celsius. I'd be lying if I said I wasn't a little nervous, but I've got a friend. Gary's here with me.
Gary - I am indeed. I've been into the cryochamber before. You're in safe hands. We're going to enjoy this experience and you're going to benefit from all the things that you get out of the cryochamber today.
James - Brilliant. Well, I can't take the recorder in with me. It'll explode probably, but here goes. I'll see you on the other side.
Setting foot inside the atmospheric main chamber, it took a while for the coldness to really make its mark, distracted as I was by the liquid nitrogen fog dancing over my body. A combination of nervous energy and the shiveringly low temperature caused me to turn into a bit of a chatterbox, which I was assured by cryo enthusiast Gary was a normal reaction. Thanks for putting up with me in there, Gary. It also meant that, before I knew it, my three minutes was up.
Gosia, I've just about come back round from my cryochamber experience. My breathing is back to normal. That was quite something. I'm no elite athlete, but athletes are using this technique to aid with their recovery. How does it work?
Gosia - So, cryotherapy puts your body into shock, which means we pretty much induce the fight or flight response. With the cardiovascular system, what happens is that the blood goes back essentially to the heart to protect internal organs and there isn't really much circulation to the peripheries.
James - So the idea is to reduce inflammation, am I right in saying?
Gosia - Yes, you're absolutely correct. When you come out, you get vasodilation, you get redistribution of the blood, so you get more nutrients in, more oxygen in. The pain threshold shifts as well because the inflammation goes down. If there is any muscular pain, for the next 24 hours, it shouldn't be that noticeable. From the endocrine system point of view, what happens is that we get endorphins in as well. It helps with regulating your mood in the most natural way that you can actually imagine. The only thing is that it only lasts up to 24 hours, so you have to reset your system on a more regular basis. But we have clients using it twice a week, we have clients using it once a week. With the athletes, we really want to get the timing right. Provided they do the right nutrition and sleeping and all of the basic recovery, then this can really elevate their recovery.
James - So improved muscle soreness, improved mood, better sleep. Is longer, better? You're talking about the athletes there and you wanting to get the time specifically right.
Gosia - With the gold standard, we're talking about 3 minutes 30 seconds, but we also check the skin temperature before you go in. That's one of the indicators, well, the major indicator for us to know if that actually worked. You're going to get all of the acute responses and benefits that we talked about, so we check the skin temperature on the knee and then we check it on your trapezius as well before you go in. We expect the drop to be around 10 celcius when you come out. But the skin temperature is the indicator for us that tells us if the 3 minutes worked or if we have to try and encourage them to go in for another minute.
James - That huge chamber I was in was very high tech, very cool. What's the advantage of a cryochamber over an ice bath, say?
Gosia - It's optimising the time under which you have to be uncomfortable in order to get the full benefit.
41:49 - Best of 2024: Why E.T. could be AI
Best of 2024: Why E.T. could be AI
Martin Rees
The Astronomer Royal, Martin Rees, delivered a wonderful virtual lecturer to the Starmus science conference in Bratislava. It was about whether we are alone in the Universe, and whether our hunt for extraterrestrial life should focus on searching for organic matter at all. We enjoyed it so much, we asked him to record it for us in September, and so here is Lord Rees himself…
We’re all aware that our natural world is the outcome of about 4 billion years of Darwinian evolution. Most people think of humans as the culmination—the top of the tree, but no astronomer can believe that. The Sun’s not even halfway through its life; the cosmos will go on for far longer, maybe forever. Humans may not even be the half-way stage in the emergence of ever more wonderful complexity in the cosmos..
There are chemical and metabolic limits to the size and processing power of flesh and blood brains. Maybe we’re close to these already. But no such limits constrain electronic computers. We are perhaps near the end of Darwinian evolution, but technological evolution of intelligent beings is only just beginning.
Their evolution will be ultra-rapid compared to the timescales of the Darwinian selection that led to humanity’s emergence – but even more billions of years lie ahead. So the outcomes of future technological evolution could surpass humans by as much as we (intellectually) surpass slime mould.
We humans thrive on a planetary surface; but if posthumans make the transition to fully inorganic intelligences, they won’t need an atmosphere. And they may prefer zero-g, especially for constructing massive artifacts. So it’s in deep space – not on Earth, nor even on Mars -- that non-biological ‘brains’ may develop powers that humans can’t even imagine.
Thanks to Prof Mayor and his successors, we know that there are millions of earth-like planets spread through the Galaxy.
Does this aggravate the Fermi paradox? Not necessarily. Some who address this imagine that alien civilsations will be expansionist and aggressive. But even though Darwinian selection has favoured intelligence and aggression, post-human evolution, occurring via ‘secular intelligent design’, need not be aggressive or expansionist. Needing neither gravity nor an atmosphere they would not be on planets. A ‘flesh and blood’ civilization may be detectable for a few thousand years, but its electronic progeny and artifacts could survive for far longer.
The history of human technological civilization is measured in millennia (at most) – and it may be only one or two more centuries before humans are overtaken or transcended by inorganic intelligence, which will then persist, continuing to evolve on a faster-than-Darwinian
timescale, for billions of years. ‘Organic’ human-level intelligence is, generically, just a brief interlude before the machines take over.
Were we to detect ET, it would be far more likely to be electronic where the dominant creatures aren’t flesh and blood -- and aren’t on planets.
Conjectures about advanced intelligence are far more shaky than those about simple life. If it’s evolved on other worlds, with a head-start, I’d conjecture three things about the entities that SETI searches could reveal.
They will not be ‘organic’ or biological.
They won't remain on the planet where their biological precursors lived.
But we won’t be able to fathom their intentions. Maybe it’s the science fiction writers who can teach us most.
Best of 2024: Building robotic fish legs
Michael Ishida, University of Cambridge
to round off 2024, we head back around 375 million years. At that time, early fish species are thought to have taken one small step onto the land. We’ve learned a lot about the skeletal structure of fish during this time, including the famous specimen Tiktaalik, but the process of fossilisation does not preserve the soft tissues that could shed light on how the first fins acted as feet. So what to do? Well, a solution came from Cambridge’s bio-inspired robotics lab: why not create robotic fish to test out different muscle and tendon con-fin-gurations? I took a trip down to Cambridge University’s Bio-Inspired Robotics Lab to see Michael Ishida, and hear how robots could provide answers to some of life’s earliest mysteries…
Michael - It sounds a little ridiculous sometimes when I say it out loud, but obviously with a fossil, you can't observe it moving around. It's just a static piece on display. And so palaeontologists have all this expertise in kind of putting together these pieces, making strong inferences about how it may have moved, how things might have fit together, but there's no real way to loop that back and kind of prove this is for sure how things happened.
Will - What's missing from current fossils that you need in order to get that data?
Michael - There's a lot of things missing, we're very lucky to get partial fossils. And as I'm sure you know, there are many, many species that we think exist that we just haven't found fossils of yet. Not only are these fossils incomplete, but we're probably missing some in this evolutionary chain. And so with robotics, we can design a new robot that kind of fits into the gaps. And so all of these ways of building something to give us more information, more data is something that we're very interested in.
Will - So how'd you go about doing that? How'd you go from a fossil of what you think is a fish to a robot in front of us right now that can move and can provide some insight?
Michael - Obviously, there's no actual model that replicates the exact animal. You can't build a robot that replicates every muscle, every tendon, every piece of soft material. So the first job is to kind of simplify and say, what is the research question we're actually asking? Is it about the fin? So then maybe if our research question is about how this fin of the fish is able to support its body weight, maybe then we build a very detailed fin with the exact bones and the soft material we think it had, and then we can take more simplifications with the rest of the body. We can put the motor on the middle of the body so that it doesn't affect how this fin moves, because the fin is what's most important. We have a long history of what's called bio-inspired robotics, that's just robots inspired by animals that we can see today. And so there are some species of fish today that are able to swim and walk. So there's things like Polypterus, which is native to Africa, that kind of lives in a swampy area. It can swim in the water and kind of move from puddle to puddle. You have mudskippers that are native to places like Japan that I'm sure you've seen all the, the BBC videos of this thing kind of scooting across the sand. But the point is there's many species today that we can look at and get a first kind of understanding about how a fish might be able to walk. The physics of fish haven't really changed from now to 500 million years ago. If you understand something about walking fish today, you can then kind of apply that knowledge to ancient walking fish. Understanding as many species as we can today will give us some insight into this ancient animal. And we can see this strategy for walking on land in sand, let's apply it to this robot fish fossil. Maybe it doesn't work very well in sand. How about in mud? Maybe this also doesn't work very well. Well, maybe rock. Oh, okay. Maybe this is kind of the environment we're thinking of.
Will - So it's almost as important to understand the environment that they lived in hundreds of millions years ago, as it is to understand their physiology as well.
Michael - Exactly. So all of evolution is driven by the environment, whether the environment is water, whether it's, additional oxygen in the air, whether it's different predators that live in your environment. Everything in evolution is kind of driven by this interaction with your surroundings and the population around you. Building a robot also helps us understand the environment very simply. Instead of building a computer model where you're simulating the water around it and the mud at the bottom, we can just build a robot, put it into a water environment or a muddy environment, and then we don't have to make this additional guarantee that our simulated mud is accurate.
Will - This is a very promising and burgeoning field. Should this come to come and you work out how Tiktaalik and its friends all got out of water 400 million years ago. Where would you like to go next?
Michael - That's a great question. I think the power of robotics really is to help us explore what we call counterfactuals, things that didn't happen. We can see the fossil record is filled with animals that did exist. They did happen. And so using a robot to try other morphologies or other sizes or other designs that nature did not come up with or that we haven't observed is something that we're really interested in because then we can see why did nature not come up with this idea? Why did certain species die out faster than another species? We think there's a great untapped potential in paleo-inspired robotics. We have so many questions about the ancient history of our world that we can only get a partial tiny picture of fossils and things that are preserved today. So collaboration between roboticists, palaeontologists and biologists is going to be super important to understand these ancient creatures.
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