Nerve interfaces and infrared fossil finding

Plus, assessing animal welfare and building infrastructure on areas of biodiversity...
24 March 2023
Presented by James Tytko

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In the news, scientists seeking to make measuring animal welfare a top priority on farms. Machines seeing the original chemicals in the bodies of fossilised animals. And why superglue might be the key to superior plastic recycling. 

In this episode

Pigs on a farm

00:56 - Assessing animal welfare on farms

Putting numbers on how well looked after the animals that end up on our plate are...

Assessing animal welfare on farms
Harriet Bartlett, University of Oxford

When we go to the supermarket and pick up a meat product, there are all sorts of badges and logos relating to food standards. While the current labelling system can give us a pretty good idea of the environmental cost of producing the sausages we buy, it’s not so good at informing us about the welfare of the animals as they were being reared. Researchers at the University of Cambridge have sought to close this information gap by coming up with a reliable way to measure animal welfare across the different types of farm. This means that animal welfare can now, for the first time, be properly considered alongside other impacts of farming to help identify which farming systems are best. I spoke to Harriet Bartlett to find out how they did it…

Harriet - There were two main things we did with this particular study. Firstly, we made metrics - ways of measuring animal welfare that are compatible with these established ways that we measure other things. So for example, if we talk about carbon footprints, we have very established ways of measuring a carbon footprint that's very strict and it's called a life cycle assessment. And they're being used quite widely, but we don't have an equivalent for welfare. And so what we did is we created an animal welfare metric using the rules from carbon footprinting. So we've got a kind of standardised and rigorous way of quantifying animal welfare. And then the second thing we did was we then collected this data from a broad range of UK pig farms from those that had no certification or labelling all the way through to organic and woodland farms. So we could actually see the outcomes for animal welfare.

James - Practically, how do you assess animal welfare on a farm? What are those key considerations?

Harriet - I used what's called welfare quality method, and they're one of the most rigorous sets of welfare assessments. So I'll be looking for everything from specific health problems and recording how common they are through to looking and observing the behaviour. And so that gave me the measure of quality of life. But we developed them in a couple of ways. We added time - because if you have two farms, for example, that had equally poor levels of quality of life, but one had twice as many animal life years experiencing that quality of life to produce your sausage, then that should be accounted for in a metric.

James - And of those which came out on top for animal welfare and which performed not so well?

Harriet - We did find within a type there was sometimes quite a lot of range. So they varied, but in general the best were woodland farms and then organic, then free range, then RSPCA assured, then red tractor, then those with no certification or labelling. But a big caveat there is that this is just looking at welfare and when we're choosing the best products and promoting the best ways of farming, we can't just think about welfare, we need to think about this broad range of things including environmental impacts. And really the aim of our study is firstly to provide some of this data for welfare but to also provide those metrics. So in the future we can explicitly include things like carbon and animal welfare when we're choosing the kinds of products that we want to eat or choosing the ways that we're farming.

James - Your goal here is not to make it more complicated, it's to synthesise the various labelings we've got now into a couple of scores, basically, of some of the key factors that ethical consumers might want to weigh up when purchasing a meat product.

Harriet - Exactly. And I think it's also a step back from that. So not just thinking about the consumers and specific labels, it's thinking about the types of farms that we want to be promoting. Because we've actually measured the consequences for carbon biodiversity, animal welfare, all these different things and they've come out on top. We're pretty good now at measuring environmental impacts, but we're really not very good at measuring welfare. So often welfare is assumed or sometimes it's even ignored. Whereas now we've got the metrics in place so that it can be incorporated into these broad sustainability assessments, so consumers can make the choice about the products they want, but also retailers and farmers can choose about how they're farming and ways that they're farming.

James - And I'm assuming that often farms that score quite highly on animal welfare might on the other hand be the most resource intensive when it comes to rearing. So is that just an unfortunate state of affairs or is that not the story that you were seeing when you went to visit those farms?

Harriet - A couple of weeks ago, another paper came out where we looked at land use and antibiotic use and we found there was this trade off: in general, the more intensive farms had lower land use requirements, they needed less land to produce a kilo of pork but they had higher antibiotic use. But we actually found that there were lots of farms that were exceptional and really quite well performing in both. So, I think sometimes there's this story of these tradeoffs and inevitable compromises, but it hasn't really been tested. And actually we've done the same study on welfare, land use, greenhouse gas emissions and animal welfare. And so I'll be able to answer that question for you hopefully in a few months time.

James - I think everyone probably agrees that we need to eat less meat and is this research facilitating a way we can reduce how much meat we're consuming, but the stuff we are consuming, we know that it's as sustainable as it can be.

Harriet - Yeah, exactly. I think sometimes there's a bit of a forced dichotomy between changing consumption, eating less, and improving farming practices when the evidence shows that we need to be doing both and we need to be doing both pretty quickly. And you're right, we can't ignore the consumption issue. Globally, we're reproducing four times the amount of meat we produced in the 1960s. And we know without a change, our food system on its own will mean that we can't meat the 1.5 degree targets that we need to to keep away the worst effects of climate change. So even if we stopped all fossil fuel use, our food system on its own would mean we can't meet that target. But there's also evidence that we don't all need to go vegan and that dietary change is slow. So it's still important to figure out how to produce meat as sustainably as we can.

Chert

07:05 - Using machine learning to analyse fossils

This new AI oriented approach to fossil identification will improve accuracy...

Using machine learning to analyse fossils
Corentin Loron, University of Edinburgh

The advent of machine learning and AI is reaching back 400 million years to re-evaluate our fossil record. In the past, we were resigned to cracking open a fossil and looking at it under a microscope. But since then, scientists have realised that also present in the fossil are some of the original chemicals that were in the entity when it was alive millions of years ago. A technique called ‘infrared spectroscopy’ can use infrared light to see and quantify these substances. So researchers have now gone a step further and developed a system that can use the relative compositions of these chemicals to confirm what the biological sample might have been. The machine learning algorithm had a test run on the Rhynie Chert, an almost perfectly preserved set of fossils from Scotland, and identified them with remarkable accuracy. So what are the advantages of using machine learning , and where next for the project? Will Tingle spoke to the University of Edinburgh’s Corentin Loron…

Corentin - Using machine learning, computer algorithm statistics, all those kind of tools, you are able to go behind what you can see with your own eyes and access very tiny details that you would've missed if you were just qualitatively analyzing your data. I mean, infrared spectroscopy is not new. What is new is to use machine learning with the data from a infrared spectroscopy. But what is very interesting with this particular technique compared to all the other types that could be used is we have only a bare minimum of preparation for the sample. We're going to slice the rock into sections and those are usually made to look at the fossils under the microscope and there are thousands of those in museums. So now we can take those out of museums and just apply the technique directly on those. We're not going to do any new destruction. So in that way, and this is exactly what we've done in this study, we were able to go in to this precious collection from the National Museum Scotland and look at them without destroying all the rocks. And this is a precious collection. You don't want to destroy those to do studies.

Will - Now that you've had a test run with these well preserved, well-documented fossils and you've seen that it works, is the plan to go out and find some more ambiguous samples?

Corentin - Obviously, the idea behind looking at this very famous site was that we can recognise with our eyes what the fossils are. And so when we look at the signature, we can do a positive matching. You have a positive control over your data. So now we know machine learning approaches worked on fossils because we can actually see that it was a match between what the fossil is and what the signature was. So now we can go back in time in fossil assemblages that are 1 billion - 1 and a half billion years old, which contain a lot of fossils, but with very, very simple shapes, very, very simple forms for which we have no idea what they might have been. They might have been algae, they might have been fungi, they might have been protists, some sort of microorganism. And now we have a new type of approach to look at what their affinities, biological affinities, would be.

Will - So this might give us an idea of the biological makeup of billion year old organisms?

Corentin - Exactly, exactly, yes.

Will - What does this method reveal about the molecular preservation of samples? Because with a 400 million year old sample, I'd personally assume there's not much left?

Corentin - So this site is known for its incredible preservation. It didn't undergo a lot of geological transformations. That's why we can see so many fossils with our eyes on a microscope. But what it revealed on the molecular level is that not only the preservation, the morphological preservation, is amazing, but the molecular preservation is also amazing. And for instance, we were able to see very tiny details of what those fossils were composed of, what type of sugars were composed, what types of fossils, for example.

Will - Does this allow us to look at harder to reach samples? If we find a perfectly preserved 500 million year old sample, that's great, but that's also very rare. Could this machine learning help us identify more partial fossil remains?

Corentin - I would say, theoretically, yes. Now it will depend of course on what kind of condition your fossils were preserved. Because if they were preserved in a very, very harsh environment, if you undergo very high temperatures, then maybe you will see that a fossil was there. But the molecular signature will be not very good. But we're lucky because we have a lot of very ancient fossil sites where the fossil are very well preserved. Some of them in the UK, the billion years old Torridon group in the North of Scotland, for instance. So definitely they're a good target for this kind of technique.

Will - Is there potential to shake up what we already know? You might go back to something that everyone has assumed is one thing and your method says otherwise.

Corentin - Exactly. I think this is the whole point of this whole approach, and we do it in a certain way in this paper when we looked at those curious organisms that were assessed to be part of plants, maybe they were part of a fungi, maybe they were bacteria. And with our study, we were able to show that actually they have a molecular composition that is closer to plants than to fungi. So we definitely could go to those cryptic fossils that we have and try to know where they could fit in the tree of life.

 

A tube of superglue

12:56 - Can superglue help fight the plastic crisis?

Superglue could be used to recycle plastic into more useful products

Can superglue help fight the plastic crisis?
Scott Phillips, Boise State University

The world makes about half a billion tonnes of plastic every year and throws away nearly all of it. It ends up in the oceans, landfill and in incinerators. And for various reasons, recycling plastic is not simple. But Scott Phillips, from Boise State University, has come up with a way to turn an everyday substance that is much easier to recycle back to the starting material - into useful plastics. He can turn cyanoacrylate - otherwise known as superglue - into long polymer chains that can be made, with a mould, into any shape you want. Admittedly the mould itself needs to be made of plastic to stop the glue sticking but they're working on that one, and recycling it just involves adding some heat…

Scott - Plastics are great materials, but the issue is that they've been designed to last forever and we don't need most of them to last forever. So what we're trying to do is create ones that would have good properties as plastics, but that we could ultimately convert back to starting materials to recycle the plastics. In this case, we looked at super glue as a starting material for making that kind of plastic that we could easily recycle.

Chris - Before we talk about super glue, why are plastics hard to recycle? We do have a plastics recycling bin and you're urged to put your waste plastic in it, so someone must be doing something with it.

Scott - It's a separation problem. And that we have a really large mixture of plastics labels that are on the plastics, glues that are with them, paper, aluminum. There's a variety of things mixed in with that plastic waste. And then the plastic itself has additives, dyes to make color, other kinds of additives to give certain properties to the plastic. At the end of the day, what we really need to be able to do is separate out the individual materials within those plastics from everything else that's in that mix. And with the polymer that we've just published on. We've designed a way that helps to circumvent some of that separations problem,

Chris - Tell us what it is and what it's got to do with super glue then.

Scott - When you glue something together with super glue, you're actually making a polymer. So super glue itself is not a polymer, it's just a starting material that reacts with surfaces. And when it reacts, it forms polymers. What we wanted to do is ask the question of could we take that same starting material that's in super glue and be able to make really long polymers and convert it into a useful plastic? People haven't really looked at that because super glue sticks to everything, so you wouldn't necessarily look at making it into a plastic.

Chris - And how did you solve the problem?

Scott - There's multiple components there. One is figuring out what container we could use, which seems like a silly problem to have to solve, but it's super glue and it sticks to everything. And ultimately what my student, Alison Christie, found and discovered is that superglue doesn't stick well to certain kinds of plastics like polyethylene polypropylene Tupperware, as an example. She could do her reactions and make long polymers in Tupperware, which makes it really, really easy to make plastics. And then the cool part about it is you can make Tupperware like plastic in any shape. So we're, we're not only making the polymer and the plastic, but we're also shaping it into a desired shape during the polymerization.

Chris - What about when you want to do the magic thing we were talking about, which is to recycle this? How do you get the plastic to fall apart again?

Scott - Well, one of the interesting things about the polymer that's formed from superglue is if you heat it past a certain temperature, it will reverse, meaning the reaction goes in the opposite direction to starting materials. So we knew that happened. The question was, could we take really bulk plastics, so large plastic items, rather than something like a glue or take a large plastic item and be able to heat it up and have those polymers still break down back to starting material? And then could we collect the starting material cleanly? And then the even harder question is, could we do that in the presence of a really contaminated, dirty mixture of other plastic waste, which is what you would normally encounter in a real life scenario.

Chris - And can you do that? So if you were handed a mixed bag of recycling and it had some of your polymers in it, as well as what normally ends up in the recycle bin, you would be able to get out back to the starting point, what you had made?

Scott - We can, and so we demonstrated that. We actually took basically household waste and it had paper and aluminum and food residue and shampoo and toothpaste residue and all the things you would expect to be in there. And then we combined it with some of Alison's plastic, heated it up, and then ultimately at the temperature that we're using, the starting material becomes a gas. And so we can then collect that gas and separate it from everything else that's in that mixture, including the dirt and the ketchup and everything that's there. The yield there for that experiment was about 75% of the polymer converted back to starting material that we were able to recover. So it's not a hundred percent in that dirty context. If we remove the paper and a bunch of food residue and all those other components, then the yield goes up, into the low 90% range.

Chris - Presumably the irony hasn't escaped you that you do need some non-environmentally friendly plastic, you call it Tupperware, to make your new plastic <laugh>. Can you get around that?

Scott - Oh, I think we probably could. We have other research where we're taking existing plastics, ones that you can't easily recycle, and we're combining them all together and making some new materials out of that existing plastic. Now, whether we could completely get around it, that remains to be seen. That's a good question and something that we'll have to explore.

Close-up of the top of a wind turbine.

19:01 - Infrastructure's impact on biodiversity

Collecting data to study how things we build can harm certain species...

Infrastructure's impact on biodiversity
Ash Simkins, University of Cambridge

In the battle to preserve biodiversity, humans almost inevitably have a hand to play in habitat loss and environmental destruction. And a study this week has found that 80% of the world’s most important sites for biodiversity on land currently already contain human developments. Here with us to explain the implications is Ash Simkins from the University of Cambridge.

Ash - Yeah, I think it's a good question. Biodiversity seems quite a complicated topic. What does it mean. Does it mean the number of species? Does it mean functions or services? Do they provide pollination? So what we did was we looked at KBAs, which are key biodiversity areas, which are aiming to capture different elements of biodiversity, whether it be things like threatened biodiversity, so is a species threatened with extinction in the wild, or are species found only in small parts of the world? Or it could be similar for ecosystems or key ecological processes or biological processes. So things you would call wilderness areas or key life stages, or migratory sites for birds as they're passing over, for example. So this is an approach to try and combine a lot of different measures of biodiversity to create a systematic network and it's the most comprehensive network we have to date.

James - And you were looking particularly at the impacts of human infrastructure on these particularly important areas, is that right?

Ash - Yeah so we were using data from WWF sites, which is a geospatial tool that they compile to look at near real time changes in conservation, things of conservation values. It could be species, habitats or ranges. It could be these protected areas or these key biodiversity areas. So they have a lot of data compiled from various places on things like road networks across the world, oil and gas, extraction sites, pipelines and then plans for future development, particularly around oil and gas and mining. So we obviously leveraged this stuff for the first time because, in most sites, unfortunately, because a lot of them are hard to reach and there's over 15,000 sites on land across the world. So it's hard to monitor all of them regularly. But this satellite world we're in now enables us to get information in much more real time.

James - And what were the main conclusions you drew about how human infrastructure is having an impact on these biodiverse, important areas?

Ash - I think it's important to say what we looked at was where infrastructure is in relation to these areas of biodiversity. So we can't necessarily get at impact. We were finding that around 80% of these 15,000 sites or so have at least some sort of human development in them, and given what we know from the literature around things like how roads impact biodiversity, or how things like wind turbines, things like that, how they might impact biodiversity, it's likely that them being there is an indicator that there might be a threat happening. So it's the first step in that. But we are calling on people to do more research to fully understand the impacts.

James - Could you speculate as to whether human infrastructure is always going to have a negative impact on the wildlife in these areas? Or could there be examples where some species will benefit?

Ash - Yeah, I think it depends how it's done. Most species are not likely to benefit overall. So there might be some species that are more generalist, which means that they can exploit a greater variety of habitats or environments. So things you might see typically in gardens or urban areas may be more adapted to living alongside humans, for example. So things like pigeons or grey squirrels you tend to see much more around in urban areas. Whereas a lot of species tend to be more sensitive, especially ones that are more threatened. So it depends what species you're concerned with as to how vulnerable it would be. And it depends on the type of infrastructure that you're impacting. If it's a road, maybe if something's flying at high enough altitude, it won't be in the line of traffic. Likewise, if birds are flying at a lower level or if something can't fly, it will be at risk of being hit by cars. So it sort of depends on the context about how much it'll impact it, but there are things we can do to try and minimise that impact.

James - Sure. And we'll get onto that in a second, but a lot of the things you mentioned earlier, the infrastructure projects, strike me as ones that, as we transition to a more green economy, more sustainable modes of getting our energy, are only going to become more prevalent. Are you worried therefore about how this is going to impact on the biodiversity of these areas?

Ash - Yeah, I think it is a cause for concern. As I say, I think there are things we can do in terms of more smart planning. There's this thing called the mitigation hierarchy, which suggests you want to avoid these areas. So these things like key biodiversity areas, using things like species that we know are particularly vulnerable to things like roads for example. You might say, okay, we should avoid roads going through those networks and try and maybe route the roads around them. Whatever kind of infrastructure it is, whether it's wind turbines, maybe put them in area of high wind where there's a low chance of birds flying through that area. So there's things you can do in terms of placement of these infrastructures to try and minimise their impact by ideally avoiding or putting them as much out of harm's way as you can get them, or even putting mitigation measures in to adapt the environment such that species are less likely to encounter direct impacts from this infrastructure.

James - And are there any more ways we can reconcile this need for more infrastructure against their effects on biodiversity?

Ash - You can look at restoring an area after impacts that you've had or restoring completely different areas to compensate called offsetting, which is an approach and sometimes is necessary because the infrastructure has to go in a certain area and it's unavoidable. But I think ideally we need to be first looking at the planning stage and looking at how we can ideally avoid those areas most at risk.

A single cell neuron

24:53 - New neural implant prevents scar tissue

Researchers have used stem cells to make neural implants more refined and with less scar tissue

New neural implant prevents scar tissue
Damiano Barone, University of Cambridge

A better way to couple up computers and prosthetic devices to the nervous system has been unveiled this week. Researchers have turned stem cells into muscle cells, and linked those muscle cells with tiny electrodes. When they’re implanted into a nerve, the nerves wire themselves up to the muscles and can activate them. The electrodes detect the muscle responses and send the signals to a computer or a prosthetic device such as an artificial arm. This technique has allowed the team to get around the existing problem that, normally, when you implant electrodes alongside nerves, a build-up of scar tissue subsequently introduces interference and blocks the detection of the signals. Damiano Barone is a neurosurgeon at the University of Cambridge and one of the brains behind the new approach…

Damiano - The nerve is not just one single structure, the nerve is a collection of wires - the axons. At the moment, most devices get what is called a compound signal. So they get all the information of all these axons together rather than the single axon that will go to a single muscle cell, for example. So what we want it to do is how do we get information rather than from a group of axons to a single axon.

Chris - So you're saying when you look at a nerve, there's a whole bunch of different wires in there, and present devices are listening to all the wires and mixing all the signals together and calling what they detect. You want to listen specifically to individual signals going down individual wires and do it in a way that won't scar up?

Damiano - Absolutely. And that's exactly what we've been trying to do. So what we did, we used stem cells that we pushed to become muscle cells, and what the nerve likes to do is to connect to muscle and muscle cells because that's what they're meant to do. They're meant to go to the muscle, make a junction, and then tell the muscle, please do contract. And the nerve was connected to our muscle cells, which were connected to our electrodes, and every time one of these wires was sending the signal, one of these muscle cells was contracting and it was telling one of the electrodes what was happening.

Chris - How do you get the muscle cells to talk to the electrodes without forming a scar? Because it seems like you are kicking the can down the road a bit where you put the electrodes into a nerve and it scars and that hampers performance. You've put muscle cells between the electrodes and the nerves, and you are saying that it doesn't scar. Well, why not?

Damiano - It's an interesting part because the muscle cells don't come from the body. So the muscle cell is a biological tissue but it's no biological tissue that was part of the body before. So all the, what we call the immunological reaction that caused that scarring, does not happen.

Chris - So how much better is this then, when you do these sorts of studies? And I presume that what you're doing with this is your model would be a person who, for instance, has lost an arm and you want to put a prosthesis on and control it with the same resolution as one could have moved their own fingers and you're putting these devices in into the severed nerve in order to pick up the signals. How much better is this than if you just took existing electrodes that you would couple up to that nerve stump?

Damiano - There is not really an electrode that is currently using clinical practice to power a neuro prosthetic arm. The best way in clinical practice is to take the nerves, implant it to the big muscle of the chest and the shoulder, and then they put cutaneous electrodes to pick up the signal. And that gives, to give an idea, six to eight signals to basically close and open the arm, move the wrist into a direction, same for the elbow. What we've done, we went up to 32 channels already. So we increase by at least one or two orders of magnitudes the number of signals we can get from a standard state of the art.

Chris - And how big is your device? Is it something that's relatively miniature and therefore could comfortably be implanted into a patient?

Damiano - Absolutely. I mean, at the moment the device we used was one to two millimeters squared.

Chris - And what about the duration of action? How long have you looked for to see how long this effect lasts for, of the superior performance and the failure of any scar tissue to form?

Damiano - In this project, we went up to four weeks. And the reason why we chose four weeks is because that is the time that the nerve takes to make those junctions muscles. And in four weeks we demonstrated that the cells do survive, but also that they kept functioning normally. What we need to do now is extend this time and connect the signals they were getting to an artificial limb.

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