Muscles in microgravity, and probing the placebo effect
On the Naked Scientists news podcast, 'muscles on chips' provide microgravity researchers new opportunities to study ageing. Also in the show, the machine learning models overhauling weather forecasting, and scientists unpick how the placebo effect reduces pain by discovering the brain network responsible. Then, we speak to a doctor on how to protect yourself from skin cancer in the summer, and we find out what it is we can smell when it rains and where you are most likely to smell it.
In this episode
00:58 - Growing muscles in space for microgravity research
Growing muscles in space for microgravity research
Ngan Huang, Stanford University
As we get older, we gradually lose muscle mass and strength because of an ageing condition called sarcopenia. Here on Earth it tends to progress slowly - but for people who experience microgravity - or weightlessness - in space, this happens at a much accelerated rate. A team at Stanford University has been trying to find out why this happens and what - if anything - can be done about it, by developing a way to grow muscles in dishes that can be flown in space, studied to see how they respond, and used to test drugs that might be able to block the process, making space flight and old age safer. Here’s the study’s author, Ngan Huang…
Ngan - Civilian space travel has really become a reality. As we think about space tourism becoming more common in the next few decades, it's important to understand how microgravity, the gravity that's experienced near the International Space Station, how that affects the ability for muscle to be able to heal itself since muscle is one of the most prevalent tissues in the body. In addition to that, understanding how drugs could potentially be used to counteract the effects of microgravity. Basically we asked whether or not we could develop an engineering platform to study and identify drugs that could counteract the effects of microgravity.
Chris - What are those effects, Ngan? How does space and microgravity as an environment affect our muscles?
Ngan - It causes the muscle to lose some of their function. They're weaker and sometimes much smaller owing to the fact that they don't always get enough stimulation in space despite, for example, exercise that's done by the astronauts. When animals like mice are sent to space and exposed to microgravity, they have also been shown to have basically impaired muscle regeneration compared to how they would repair their muscles on earth, which is what we call normal gravity. Even in the cases when just cells on a Petri dish are sent into space, those cells also show reduced ability to form new muscle fibres. A lot of this data in the literature suggests that microgravity has really profound and oftentimes negative effects on our ability for muscle to function normally as well as to heal itself.
Chris - How did you do this, then? Because obviously the aim is not just to test astronauts, it's to be able to do this at a massive scale and test drugs and things that might not be ethical to give to astronauts in space. So what did you develop to make this doable?
Ngan - Right, and exactly: we don't want to rely on astronauts alone to teach us about microgravity effects. So we develop what we call a muscle on a chip in microgravity platform. These muscles on a chip are essentially what we call engineered muscle. They are engineered with what we call progenitor cells that are grown on patterned three dimensional scaffolds that allow these cells to form early stages of muscle fibres that are actually oriented similarly to how muscles normally organise. So generally we can think of a basic muscle group as being muscle fibres that are organised in parallel, almost like a bundle of sticks, and using these oriented scaffolds we can coax these cells to orient and form these premature muscle fibres, similarly in line like a bundle of sticks.
Chris - How do you use them then? What are you actually measuring when you do the experiments?
Ngan - That's a very good question. So we send these muscle progenitor cells onto the international Space Station and in this platform, which can be expanded and scaled up in the presence of microgravity, we can then study how these muscle progenitor cells are able to form muscle fibres and be able to be subjected to different kinds of drug stimulation.
Chris - And have you started doing this yet? Have you got some drugs that you can put on them and show that they really do seem to affect how these cells respond?
Ngan - Some of the work that we've done has been to try to test the feasibility of this platform for drug screening in space and, in doing so, we tested just two drugs because we wanted to base it on drugs that have known therapeutic benefit on Earth. So we used two drugs in this initial space study to see if those drugs had a benefit in improving muscle regeneration and found that these drugs were able to have benefit in preventing some of the negative effects that are associated with microgravity.
Chris - So it looks like your space holiday might be on the cards then!
Ngan - Exactly.
06:12 - Quiet AI revolution taking weather forecasting by storm
Quiet AI revolution taking weather forecasting by storm
Richard Turner, University of Cambridge
In recent weeks, we’ve had some exciting announcements about the benefits of AI in weather forecasting. Some of the world’s leading tech firms - such as Microsoft, Google and China’s Huawei - are all getting in on the act. So, what do we need to know about it and how it works? And - crucially - will it lead to more accurate forecasts? Richard Turner is a professor of machine learning at the University of Cambridge. He’s also a visiting researcher at Microsoft and busy working on developing what he says are far more energy efficient and more accurate AI systems for telling us when it’s finally not going to rain all over the UK…
Richard - The traditional approach to weather forecasting involves two steps. First, observational measurements from satellites and weather stations, and you combine them all together and get an estimate for what the current state of the atmosphere is. In the second step, having figured out what the atmosphere looks like at the moment, you run a big simulation on a supercomputer that evolves the atmosphere and tells you what it's going to be doing, say, a day ahead or a week ahead, or two weeks ahead. To date, AI has revolutionised that second step, the forecasting step, and it replaces that with a machine learning system. The great advantage of the machine learning system is firstly it's about 10,000 times cheaper, computationally. You can literally run these things on a big desktop computer. Secondly, you can, in certain circumstances, actually get a more accurate, as well as a much cheaper system.
Chris - And how much better is it?
Richard - That's a really hard question to answer, but the improvements are of the order of maybe 5%. Just to put that into context, when you take a national weather forecasting agency's predictions, it might take them a year and a large team and a big supercomputer to get an equivalent improvement. Those improvements are really tangible to farmers in agriculture, or if you are using these things to predict renewables for energy production, it's a big deal with these sorts of numbers.
Chris - Where's the bottleneck now then?
Richard - One of the current bottlenecks is actually you still need to run a conventional weather forecasting system in order to get that initial estimate for the state of the atmosphere. One of the things I'm really excited about in my group, we have a project called Project Aardvark, where we're looking to replace the entire system with a machine learned variant. The system ingests data from weather balloons and satellites, weather station measurements, and then directly outputs a forecast for the next 10 days. It's about as good as the best systems from the US and a little bit behind the best systems in Europe.
Chris - And how do you train something like that? Was it literally you took enormous amounts of climate data, or initially not climate data, just data, and then honed in on climate data and then said, this is the outcome, this was the rainfall, this was the wind direction, this was the temperature. Is that how you trained it?
Richard - Yeah, so in the Aardvark system, that is pretty much how we trained it. We trained it over about 10 years of data.
Chris - One of the constraints of the present system is that it's down to how good the data are in your particular geography. So in the UK people are saying we are predicting weather with some accuracy down to sort of the square kilometre, aren't they? Whereas, you go to the middle of nowhere, there's much less data, much less accuracy. Now you can't improve on that presumably?
Richard - No, that's right. You're fundamentally limited by the accuracy and so I think there are real challenges here. For instance, underdeveloped nations, the weather forecasting is much poorer and more limited, partly because of the lack of observational measurements. But one of the great advantages of the Aardvark Project is it's easy for developing nations to develop personalised weather forecasting systems, which previously would require huge teams to operate, deploy, and maintain. So we're trying to figure out a way to get Aardvark to those nations and already seeing it can lead to quite big benefits over the traditional approaches.
Chris - Would that be almost like an open source system, and they just have a big desktop and they can just run this at home, program it with local data and they've got their own bespoke local weather forecast?
Richard - That's right. They would need a bit of computational resource to train it, but once it's been trained - and it isn't terribly expensive to train compared to having a supercomputer - they literally could run it on a desktop or a laptop computer and take ownership of that model.
Chris - It sounds pretty revolutionary. Why have I not heard people shouting from the rooftops about this for much longer until I met you?
Richard - Well, I think if you've looked for the signs of it, you'd have seen it. But it's been called the quiet AI revolution by the chief scientist at the Met office. It's absolutely ripping up and transforming the field and the big meteorological agencies are now hiring big machine learning teams. It's not clear what the future is going to be and exactly where AI will be embedded into the current processes, but it's clear it's going to make a massive difference.
Chris - One of the things that's emerged from a lot of these large language models that's got people spooked is - it's more accurately termed confabulation but the wider public refer to hallucination - it just makes stuff up. So is it going to do a sort of reverse Michael Fish and say, 'there's going to be a hurricane!' In fact, there isn't.
Richard - I think that is a great question. One of the things that we need to do is rigorous evaluation of these models and one of the great fears is when you need it most in severe weather, these things will confabulate. That of course would be really, really bad. We know machine learning systems do worse in the extremes where they don't have much training data. I think that's the particular challenge in the climate case as well because obviously we don't have much data about how the climate's going to change. So there has to be a few years I think of assessment of these models and looking at how well they hold up in extreme events. The early indications are that they hold up much better than people expected and I think even the meteorologists have been surprised that they still seem on par with the best numerical systems in these extreme events.
12:44 - Brain pathway behind the placebo effect
Brain pathway behind the placebo effect
Gregory Scherrer, University of North Carolina
But first, scientists in the United States have discovered the brain circuit that underpins the placebo effect. Although we’ve known about the power of thought to suppress pain for many years, brain scans in humans could only provide vague evidence for what might be behind the phenomenon. Now, Gregory Scherrer, at the University of North Carolina, has been able to trace connections from the front - decision-making - part of the brain to a region at the very back called the cerebellum, which is mostly concerned with controlling and learning movements. So the finding that it’s responding to - and controlling - how much pain we feel argues that it might also be responsible for setting our pain thresholds, and opens the door to developing a raft of new drugs that target this pathway.
Gregory - In the pain field, so far, in terms of pathways by which we perceive pain, we and others have mostly focused on sensory systems. That's bottom up, organisational pain secretory: so how our nerves detect painful stimuli on our body and how this information is then transmitted to the spinal cord and then to the brain. Here, what we wanted to do is something different. To better understand the top down control of pain, to find the secret mechanisms by which cognitive factors such as expectations or feelings, things that are present in our brain, can control how we perceive pain.
Chris - In other words, the placebo effect, the idea that if I think something is going to give me some degree of comfort or pain relief, then it does.
Gregory - Right, exactly. The placebo effect is probably one of the most striking demonstrations by which our thoughts, our feelings, can change how we feel about pain. Developing a model of the placebo effect, so how a positive expectation of pain is sufficient to change a pain threshold, was a good entry to try to tackle this problem.
Chris - How powerful is the placebo effect? If we do experiments on people, for example, where we can measure things objectively, how much pain relief can a person get from just the placebo effect, do we think?
Gregory - It is a very potent effect. In fact, it's so potent that, as you might know, many clinical trials fail because in the control group the patients that receive the placebo, so no drug essentially, show a response that is comparable to the novel drug that is tested. It's a profound effect in our studies, the placebo pain relief that we get in our rodent assay is comparable to a low dose of morphine.
Chris - That says a lot, doesn't it? What's surprising though is that we've been studying the pathways in the nervous system that convey pain signals for decades, and we've known about the placebo effect for as long, even longer in fact because of historical documentation and so on. So why didn't we understand the neurological underpinnings of it? Why had that escaped scrutiny?
Gregory - Several reasons. I think it sort of made sense, if you're trying to understand pain, to first understand pain at its source. So, much of the effort has been dedicated to understanding how our sensory neurons detect painful stimuli in the first place. Then, there's a lot of work that's been done also in humans to understand how our thoughts and cognition can change pain, but this is much more difficult to do in animal studies as you can imagine. In animal studies, we can stimulate animals with a stimulus and measure their response to pain, but to understand how the animal's feeling or expectations can change is much more difficult to model. It takes more work essentially to develop assays to model this aspect of pain experience.
Chris - We had a sort of broad idea as to what might be going on, but we couldn't unpick the neuroanatomical, the connection level, what's talking to what to make this happen. Is that what you are probing with this study?
Gregory - That's exactly right. If you do these studies in humans using, for example, functional magnetic resonance imaging, so techniques where we can see by putting people in a scanner what parts of the brain are active, for example, during pain you can see that certain areas of the brain, the front of the brain or the back of the brain, are active during pain, but you don't have the resolution, the precision to see exactly what cells in the brain are connected to be active during the placebo effect. This is where animal models are useful because we can do very precise manipulation with which we found this novel pathway that links the front of the brain, a part of the brain that's important for cognition, decision making, to the back of the brain, the cerebellum, that's a region that's been mostly studied for movement so far and where we think something important is happening during pain perception that's been overlooked so far.
Chris - And presumably if you can track down what these circuits are, once you know them on a cellular level, you can do things like ask, do we have any drugs or can we invent drugs that will specifically target that pathway? You could almost put the placebo effect on steroids and get really powerful pain relief?
Gregory - Exactly. So this is one of the most exciting aspects of the study. We show that in the absence of conditioning, without producing a placebo response, if we just artificially recruit this pathway as we could do, for example, with drugs or with neurostimulation methods, this is sufficient to produce an analgesic effect. So this could lead to the development of a completely novel class of pain drugs.
18:38 - Sun protection factor, and how to spot skin cancer
Sun protection factor, and how to spot skin cancer
Animesh Patel, Addenbrooke's Hospital
School’s out for summer in the northern hemisphere and that means many of us are heading for the beach and a dose of sunshine (hopefully!) So here’s Animesh Patel - a leading skin cancer surgeon at Addenbrooke’s hospital in Cambridge - to offer us some tips on staying safe in the sun, starting with where specifically on the body cancers tend to crop up…
Animesh - They do arise on exposed parts of the body. That is typically the face, but also the hands, forearms and the legs as well is where we often see skin cancers. Things like melanomas, especially in men, are quite common on the trunk often because men over the years have probably been outside without t-shirts on.
Chris - Why does the sun do this? Do we know the mechanism by which sun exposure causes these cancers to happen?
Animesh - So the sun obviously emits ultraviolet radiation and there are various types of it. We categorise them as UVA, B and C. C is not so important as most of that is filtered out in the upper echelons of the atmosphere. However, UVA and UVB do penetrate to the earth's surface and typically UVB is the one that we worry about in terms of causing skin cancers. At a cellular level, there is damage to DNA and if this occurs repeatedly then that can result in changes in the cells that make them behave abnormally and can result in tumours forming.
Chris - And what does sunscreen do?
Animesh - There are different types of sunscreens and they work in different ways. They can either block the UV radiation or they absorb. So essentially you can divide them into two broad categories, those that are physical blockers and those that are almost chemical blockers.
Chris - And when they say sun protection factor, what does that actually mean?
Animesh - The sun protection factor is a number, the number represents the extra time that somebody can stay in the sun before they get burned. So, for example, if you are of the skin type who might burn after 10 minutes of sitting in the sun, if you applied SPF 30 to your skin, theoretically, you'd be allowed to stay in the sun for up to 30 times 10 = 300 minutes before you were to get the same effects from that UV. Obviously these are theoretical numbers and there are various factors that will influence actually how often you'd need to reapply sunscreen.
Chris - And when does a person end up coming to see you?
Animesh - We often see patients at various stages of their diagnosis. Often some patients might present very early and have a very small lesion on the skin or a small changing lesion on the skin. But we also see the other spectrum unfortunately, where patients have neglected skin lesions and they present to us sometimes with quite advanced disease.
Chris - What should they look out for then? When you say people have neglected things, what have they missed or what should we be more vigilant to look out for?
Animesh - So there are different types of skin cancers and their presentation is different as well. One of the most common skin cancers is something called basal cell carcinoma, which in the old days used to be called rodent ulcers. Patients present with a raw patch that often bleeds recurrently, forms a scab, the scab might fall off and then the whole cycle starts again. That's typical behaviour of a basal cell carcinoma. At the other end of the spectrum and more sinister are melanomas. Now, melanomas can present in a variety of ways, but typically it's a pigmented lesion, so a coloured lesion that might be brown or black and often evolve. It may arise in a preexisting benign mole, or it may just appear out of nowhere. Typically these lesions are asymmetrical, they may have an irregular border. I mentioned the dark colour and the colour may be variable within it and as it starts growing to a larger diameter, that's when we start worrying.
Chris - What do you do when you see someone with that? Do you just whip them off and then look at them down the microscope or do you say, let's take a piece of it out? How do you investigate?
Animesh - Typically, patients present when these things are quite small, so it's relatively easy to perform what we call an excision biopsy. So the whole mole is removed and we send that to our colleagues in the histopathology department who analyse it under a microscope. We then have a diagnosis. Subsequent management then depends on what that diagnosis is. For example, with a melanoma, if we have a new diagnosis of a melanoma, the various things that we look at from the histopathology, typically, we want to know how thick the melanoma is because we know that thin melanomas, ones that are caught early, have a better prognosis compared to thicker melanomas which may have invaded deeper into the skin. If we do come across a patient who has a very thick melanoma, then we often have to perform other investigations such as CT scans just to make sure that there hasn't been any spread anywhere else.
Chris - But if it is a thin one, is there a good chance, if caught early, you can cure that person?
Animesh - A thin melanoma is associated with an excellent prognosis. So once a thin melanoma has been removed, and we often do perform subsequent surgery called a wide local excision procedure which takes a little bit more skin away - and that's just to ensure that there aren't any rogue cells around the scar from the original biopsy that might lead to the tumour recurring - but in answer to your question, a thin melanoma is typically associated with an excellent prognosis.
Chris - And some general tips as people consider going and sunning themselves on the beach. What can we do to minimise the risk of having to come and see you? I mean that in the nicest possible way, Animesh, I don't really want to see you professionally. How do I minimise the chance of that happening?
Animesh - The NHS website has excellent guidance on sun safety and a lot of it is common sense: stay in the shade, especially in the middle of the day when the sun is at its peak. Use sunscreen in an intelligent way. There's a lot of research out there which shows that even adults don't apply it properly and miss what otherwise might be obvious areas. Often people don't reapply it at regular intervals, especially if you're in a hot climate where you might sweat a lot if you're swimming. These kinds of things require regular reapplication of sunscreen. There are obviously other things that people can do: wear a broad brimmed hat, cover the ears. The ears are often missed with things like baseball caps and things, so a broad brimmed hat is really useful and there's clothing available as well which also has a high sun protection factor. That's something to look at as well, especially if you're somebody with fair skin that's more prone to these kinds of problems.
25:29 - What is it I can smell when it rains?
What is it I can smell when it rains?
Elizabeth wants to know what that smell is when it rains, and whether there are any geographic differences which might influence our ability to pick up on it. Anne Jungblut from the Natural History Museum helped James Tytko with the answer...
Anne - 'Petri' comes from 'petra,' which is ancient Greek for rock and stone, and 'chor' means the the liquids flowing through the veins of ancient gods and immortals.
James - Very poetic.
Anne - Yeah. And so petrichor is a mixture of plant oils that are around seeds that stops them from germinating when plants are dry. It also contains a compound called geosmin that's produced by two groups of bacteria called cyanobacteria and actinomycetes. So when it's dry these compounds are accumulating on the surface of soil, and then when it starts raining the rain will form bubbles in the pores of the soils and then these bubbles will burst and then that releases little aerosoles which then come in the air and then can be detected by humans.
James - So that explains what the smell is. Why is it that perhaps in the UK we are able to smell this less frequently maybe than they can in America? Is there any truth in that?
Anne - Yes. So it's produced everywhere on the whole world, this compound, but it will be more likely smelled somewhere where it's more dry beause it's produced and accumulating when the salts are dry and then released and then we can smell it. Whereas, in the UK, it's also present, but I guess the seasons, the winter, the autumn spring, nearly any time, there can be quite a bit of rain, and so it's not accumulating and maybe released that much. People from the UK will know that probably they would've smell it most during the summer when it's been quite dry and then suddenly there's this enormous downpour and then all the smell appears. So it's related to the conditions like dryness.
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