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NS 31 aug 02
Pig cell transplant hope for diabetics
STEPHEN LEAHY AND MICHAEI LE PAGE
A 17-YEAR-OLD girl with diabetes has not needed to take insulin or any other drugs for more than a year after being given cells from newborn pigs, claims the Mexican team that performed the transplant. If confirmed, it represents a rare success for animal-to-human xenotransplantation. However, five other teenagers given the cells have only had their insulin requirements reduced by half, and another six didn't benefit at all. Sceptical researchers have pointed out that young people with diabetes sometimes start producing insulin again, and that the Mexican team has yet to prove that the insulin is coming from the pig cells. "I am not convinced," says Camillo Ricordi of the University of Miami, former president of the Intemational Pancreas and Islet Cell Transplantation Association. Hundreds of millions of people worldwide have insulin-dependent or type I diabetes, caused by the death of the insulin-producing islet cells in the pancreas. There have been many attempts to cure it by transplanting pancreases or islet cells. In the past three years, up to 8o per cent of people given human islet cells taken from corpses have still been making enough insulin in their own bodies a year later. But there is a severe shortage of human islet cans suitable for transplantation. Worse, all those who have received transplants will have to take immunosuppressive drugs, with all their nasty side effects, for the rest of their lives. To get around the need for immunosuppressive drugs, Rafael Valdes of the Children's Hospital of Mexico transplanted Sertoli cells from the testes of newbom pigs along with pig islet cells. Previous studies have shown that Sertoli cells have a special marker on their surface that makes attacking immune cells commit suicide. First, Valdes implanted two 3,-centimetre-long stainless steel tubes just below the skin. Two months later, when tissue had grown around and into the tubes to provide an ample blood supply to the area, the Sertoli cells and around a million islet cells from week-old piglets were inserted. No immune- suppressing drugs were used. The patients lost a large number of the cells early on due to rejection, but the immune response lessened over time, says David White of the Robarts Research Institute in Canada, who collaborated with Valdes. The findings were presented this week at a meeting of the Transplantation Society in Miami. The trial did spark concem about rogue" transplanters operating in unregulated" countries, says transplant surgeon David Cooper of Harvard Medical School. But Cooper says he inspected the facilities of Diatranz, the New Zealand company that supplied the pig islet cells, and found them to be excellent. Although the Food and Drug Administration has no jurisdiction in Mexico, Cooper would like Vaides to apply for FDA approval for the new trials he plans. "if he did that, everyone would be happy," he says. There are also worries that xenotransplantation could allow porcine endogenous retroviruses (PERVs), which lurk in the pig genome, to leap to humans. But Ricordi says there's no evidence of this in the hundreds of patients worldwide who have been (unsuccessfully) treated with pig islet cells so far. One of the major hurdles with xenotransplantation is that the immune system attacks animal cells even more vigorously than cells from non-compatible people. But PPL Therapeutics of Edinburgh announced last week that it had removed both copies of the gene responsible for provoking the most severe immune attack from pigs (see New Scientist, 12 January, P 7). Transplants from these pigs should have a better chance of surviving.
In the mane, darker is more desirable
FAKE lions have helped unravel the long-standing mystery of the signiflcance of the lion's mane. it turns out that the darker a male's mane, the better he'll be as a mate. The origin of the mane has long puzzled biologists. Some believe the tough, shaggy hair acts as protection in fights with other lions. Yet scrapping lions don't particularly target their opponent's head and shoulders. And other cat species also fight, but don't have manes. "No one really knew what the mane was for," says Peyton West at the University of Minnesota's LionResearchCenter. To investigate, West and her colleague Craig Packer planted life- size dummy lions near males and females in the Serengeti National Park in Tanzania. Male lions were less intimidated by dummies with lighter, less shaggy manes. Females preferred the opposite, suggesting that they saw males with darker manes as better prospective mates (Science, VOI 297, P 1339). The pair also found that males with dark manes have more testosterone and are better able to defend their families. One-year-old cubs are more likely to survive until they are two if they are bom to darker-maned males. But a darker mane comes at a cost - it makes lions hotter. West says it is likely that only the toughest can put up with this burden. "It's a very exciting contribution to the study of sexual selection," says zoologist Tim Birkhead at the University of Sheffield. James Randerson
What do galaxies, stockbrokers and style gurus have in common?
A set of numbers describing everything they do. Does nature's hidden program mean we're all deeply predictable, asks John Casti
WHEN was the last time you bucked a trend? Really swam against the tide? Chances are, you never really have - at least, not for long. But it's not your fault. You may not have as much free will as you think.
Most of us are aware of our tendency to go with the herd. We tag along with fashions: our hemlines rise and fall, our trouser legs widen and narrow, or we buy technology stocks when others are doing the same. We accept that, much of the time, we're not being "individual". What we're not aware of is why. There are evolutionary arguments, of course: if you haven't enough information on which to base a judgement, the next best thing is to assume that the herd knows where it's going. But a mathematical analysis of our activities indicates that there may be something deeper going on. We seem to be fated to act in a way that mimics patterns found elsewhere in nature.
We already know that some actions of society appear to follow laws that often apply to otherwise completely unrelated phenomena in the Universe. The numbers behind the fractal shape of a snowflake can also describe our society's financial activities, for instance. Financial data is one thing, but why should the maths that describes a seashell's spiral also underlie our technological progress? Why can our shopping habits be described by the same rules that dictate how galaxies are spread through the cosmos? It's as though we are somehow programmed by mathematics. Seashell, galaxy, snowflake or human: we're all bound by the same order. Mathematical laws are already used to describe human activity, of course. There are various tools such as Bayesian theorems, power laws, hidden Markov processes and cellular automata, just for starters. All of these have been used in modelling financial markets, with varying degrees of success - and popularity. But now an old mathematical idea, first dreamed up in the 193os, has come to the fore again and is proving itself more powerful than anyone ever thought possible. It has enabled people to make specific predictions about the financial markets, forecasts that are now unfolding with uncanny accuracy. The fact that this technique also has something to say about what it is to be human makes it all the more remarkable. To begin at the beginning, you have to go back to California during the Great Depression. Ralph N. Elliott, a Los Angeles accountant, is in frail health and unable to find work. While recuperating, he has plenty of free time to investigate the stock market and try to work out why it has just lost go per cent of its value over a three-year period. He becomes convinced that there are repetitive pattems within market indices such as the Dow Jones index. Of course, Elliott knows it's not really saying much to point out that the Dow Jones moves in cycles. What he needs to understand is how to characterise the kinds of cycles, and then to look for patterns within them. He realises that such an understanding would enable alert investors to predict the rising prices of a bull market, foresee the decline of a bear market and even anticipate great crashes such as those of October 1929. Elliot, a hands-on specialist in corporate financial rescue, was no stranger to market analysis or the ebbs and flows of business and eventually managed to fit together the pieces of a fascinating puzzle. Elliott's great leap forward was the reatisation that the cycles don't originate within the financial markets, but are a product of the humans that drive them.
"The connection between Elliott waves and the Fibonacci series linksthe stock marl(etwith other natural patterns and processes found in livingforms"
"Human emotions are rhythmical; they move in waves of a definite number and direction," Elliott observed. "The phenomenon occurs in all human activities, be it business, politics, or the pursuit of pleasure." And so, by analysing stock market data, he picked out certain fundamental rhythms. Today they are known as Elliott waves. The theory of Elliott waves is based on patterns of ups and downs, underpinned by a few basic principles. First of all, action is always followed by reaction: up is eventually followed by down. At this level, an Elliott wave cycle is composed of two waves, where a "wave" is simply a change - either an upward "impulse" wave, or a downward "corrective" wave.
However, Elliott found that each wave isn't necessarily just a straight line. Instead, it can be subdivided into five smaller waves, so an impulse wave might actually consist of up- down-up-down-up. Likewise, the data revealed that waves were sometimes subdivided into just three waves: down-up-down for a corrective wave, for example. So, on closer inspection, an up-down Elliott wave cycle is actually composed of eight waves. One slight complication is that the number of sub-waves within a given wave actually depends on whether that wave is with the overall trend or against it. So if the overall trend is downward, for example, then corrective waves in that trend have five sub-waves, and impulse waves have three (see Diagram, opposite). However, just as "zooming in" on an up-down pattern reveals eight smaller waves, zooming out shows that it can also be considered as a 2-wave component of a larger 8-wave cycle. So the wave principle is hierarchical in the sense that the same basic shape appears at all scales: each wave has component waves and is itself a component of a larger wave. This self-similarity at different scales is the hallmark of fractal pattems, which are seen everywhere in nature in things like fern fronds, coastlines and blood vessels. So how many scales, or "degrees", of waves, sub-waves, and sub-sub-waves are there-how far can you zoom in or out? Elliott named nine degrees, from those lasting centuries to those lasting just hours. But the actual number of degrees may be limitless, since the same patterns show up even on one-minute graphs of stock prices, and are likewise presumed to operate over indefinitely large timescales. As you might expect, the area in which Elliott waves have been most extensively applied is in finance. For instance, the value of the Dow Jones between 1932 and the present can be broken down in terms of Elliott waves. If you can identify the waves and sub-waves and if know where you are on a wave, you know exactly where you're going next (see "Riding the wave"). For example, Elliott used his wave theory to announce, in the middle of the worst of the Second World War, that a multi-decade stock market rise was about to begin. And financial guru Robert Prechter did the same in the midst of recession in September 1982 by announcing that a "super bull market" had begun and forecasting a fivefold increase in stock values. In both cases, the Elliott waves enabled them to get it right. But Elliott waves are something more profound than just a money-making tool. They la-a,ve a very close connection with the series of numbers known as the Fibonacci sequence, where each number is the sum of the two previous ones. This produces an infinite series of numbers: 1, 1, 2, 3, 5, 8,13, 21 The number of waves that comprise the Elliott patterns at each successive level of detail are precisely the numbers of the Fibonacci sequence.
"Is our behaviour somehow dictated bythese numbers? Is whatwe dojusta natural process, I i ke the way a snowflake ora seashell forms?"
It's easy to see why when you consider how the pattern builds up. The simplest expression of a corrective wave is a downward straight line, while that of an impulse wave is a straight line upwards. So a complete up-down cycle is just two waves. At the next level the corresponding number of corrective and impulse waves are 3 and 5, respectively: Elliott's theory says the downward line has 3 sub-waves, and the upward one has 5. The total cycle then consists of 8 waves, and we have the first six numbers of the Fibonacci sequence (see Diagram, P 32). This process continues indefinitely. The connection between Elliott waves and the Fibonacci sequence is intriguing, because it links the wave principle that underlies the stock market with other natural patterns and processes found in living forms. The Fibonacci sequence appears all over the scientific landscape: it describes the spiral patterns found in seashells and the DNA helix, as well as the number of spirals on pine cones and sunflower seed heads, to give just a few natural examples. It also crops up in fractals. According to Prechter, who produces a monthly publication called The Elliott Wave Theorist, these patterns reveal a direct connection between nature's numbers and all of human behaviour. Prechter believes the wave patterns are an organising principle for myriad social behaviours, ranging from newspaper sales figures to the fortunes of national leaders.
The reason Elliott waves can tell us all this is simply because they are a direct reflection of human psychology - the rhythms of human emotion, as Elliott put it. It doesn't matter what the exact mechanism is; the point is that they're a result of human behaviour. Their success at predicting stock movements stems directly from the fact that price movements in financial markets mirror the collective beliefs of investors about the future. If the majority are optimistic, prices rise; if not, they fall. But the stock market is just one way to take society's emotional temperature. If you look at the average length of hemline as fashions change and plot it against the Dow Jones, there is a striking correlation: the stock market faithfully rises and falls with hemline length. The obvious explanation is that when people are feeling bold and adventurous, they buy stocks and wear more revealing clothes. When they feel threatened and conservative, they do the reverse. The mood is pervasive, and almost everyone gets swept along with it. Prechter's theory, which he calls socionomics, is that the units in a social system, whether they are investors, voters, music fans or shoppers, tend to base their decisions on what they see others doing. In other words, they herd. These decisions are then translated into a social mood, which shows up in indicators such as the Dow Jones, hemlines, lyrics in songs, and so on. Armed with Elliott waves, you can start forecasting all sorts of things. Indeed, Prechter has had astonishing successes with the method in areas where no one else is even trying. Take Major League Baseball, for example. In iggi, the sport enjoyed what some commentators felt was its most exciting season ever. Fans got so enthusiastic that a record 76o,ooo of them turned out to welcome the two teams returning to Atlanta and Minneapolis from the World Series, despite the fact that it was sleeting in Minneapolis. Players, owners and leagues predicted ever-increasing popularity for the sport, and cities began building new stadiums. But socionomics predicted exactly the opposite. Prechter plotted the go-year annual ticket sales for Major League Baseball and identified an unmistakable Elliott wave. Immediately following the 1992 season, he wrote: "if you're an investor, take profits on baseball cards. If you're a player, sign a long- term contract. If you're an owner, sell your club." In the ensuing months, the speculative bubble in baseball-card prices burst, the stock price of card maker Topps collapsed, a players' strike cancelled the 1994 World Series and the TV ratings for the World Series began a steady, fall to an all-time low. And he says the retrenchment is not over yet.
Prechter has also used these principles to anticipate the peak and subsequent fall in the popularity of a financial guru - himself. Using the number of subscribers to The Elliott Wave Theorist as a measure of popularity, he saw that the subscription levels obeyed an EHiott wave pattern of their own. As wave 5 of his overall upward surge began to slow in late 1987, he knew that the end of his ride as a guru was near. And sure enough, despite the fact that i988 was one of his best forecasting years ever, various members of the media had had enough of Prechter and began to attack the persona that they and their colleagues had overpromoted. He's now written about far less, and far less lionised. Socionomics completely tums on its head the idea that events shape social mood. Since trends in social mood produce Elliott-wave patterns, the mood itself must follow a definite pattern. And if that's true, it certainly cannot be the result of external events, which are random and don't follow set trends. The only possible conclusion, Prechter argues, is that the direction of causation goes the other way: social mood actually shapes events. Work out the social mood by looking at stock market data, Prechter says, and you can then predict future social events
The Enron scandal in the US illustrates that socionomic viewpoint very well. For weeks, newspapers and magazines trumpeted the conventional direction of cause and effect: the scandal deeply unsettled investors, they said, triggering the collapse. But socionomic thinkers argue just the opposite: worried investors precipitated the scandalous behaviour (see "Who collapsed Enron?"). The conclusion of Elliott wave theory is that the herding instinct in society governs events in economics, politics, and even war and peace - and all these events follow exactly the same kinds of cycle. This idea has deep implications. If Elliott waves can describe all of human activity - economic trends, wars, shopping habits and political ideas - and a sequence of numbers that is ubiquitous in nature can describe Elliott waves, is our behaviour somehow dictated by those numbers? Is what we do just a natural process, like the way a snowflake or a seashell forms? Conspiracy theorists and fans of science fiction would love to take it as indication that we're helping to carry out some cosmic computation. But, whatever the real answer, we may well not like it. Somehow, for all our cleverness and cherished free will, it seems we might simply be living by numbers.
Natural GM becomes a field day
Species have been happily swapping genes for millennia.
What happens when the transgenesjoin in? Bob Holmes finds out
IN THE long-running debate over the safety of genetically modified organisms, one fear stands head and shoulders above the rest: what if the genes we insert don't stay where we put them, but instead escape into other species? One of the panicky subtexts behind the tabloid references to Frankenfoods is the possibility that engineered genes, like Mary Shelley's monster, might escape their master's control and turn nasty. Is this a legitimate concern or empty scaremongering that can only muddy the waters over the future of genetic engineering? The answer is an unsettling one. In the real world, organisms of different species toss genes back and forth all the time. They always have, and they always will. Occasionally, even before the advent of transgenics, this genetic shuffling created a weedier weed, or drove a wild species toward extinction. The real question, then, is not whether transgenes might move: they will. But is this any more dangerous than the high links ordinary genes get up to? So far, at least, the answer is clear. The latest evidence, including results of the first-ever experimental tests, suggests that today's GM organisms aren't worth losing sleep over. But that doesn't mean we can sit back with a sigh of relief: new transgenes that may hit the market within the next lo years could carry a much greater potential for harm. Even though gene transfer is common in nature, little of it involves genes taking great evolutionary leaps between unrelated species. Sure, bacteria are experts at "horizontal gene transfer", in which one species picks up fragments of DNA shed by another. We've seen it in the explosion of antibiotic resistance over the past 50 years as a wide range of species swap resistance genes like business cards. But horizontal transfer between plants and animals, or between these organisms and bdcteria, is very rare. The draft sequence of the human genome, for example, contains no genes unequivocally acquired from bacteria in the past few hundred million years. instead, the overwhelming majority of "escaped" transgenes, especially among plants and animals, will spread through good, old-fashioned sex. Almost every major crop hybridises with wild relatives somewhere in the world, and so do many animals. Often the amount of hybridisation can be staggering, especially when crop plants vastly outnumber their weedy relatives. For example, Neal Stewart, a plant molecular geneticist at the University of Tennessee in Knoxville, tracked the spread of a jellyfish fluorescence gene from rapeseed (canola) to its wild relative, wild turnip. Around the periphery of a rapeseed field, he found that more than lo per cent of wild turnip plants gave off a telltale glow. "Genes are transferred back and forth all the time, I am convinced," says Stewart. Other researchers have found uP tO 42 per cent of the seed produced by wild sunflowers growing at the margin of a commercial sunflower field were hybrid. Some rapeseed hybrids have been found uP tO 3 kilometres from the nearest transgenic crop, and hybrids of beets and their wild relatives have been a problem for years. Hybrids are common among animals, too, most notoriously among fish such as trout and minnows. Genes will wander, then, and there's no reason to suspect that transgenes are any more or less footloose than the rest. But a little gene flow is not necessarily a problem. After all, it's been happening for hundreds of millions of years. "Some environmental groups have convinced the public or politicians that as soon as a transgene appears, it's a hazard. And I think that is not right," says Detlef Bartsch, a plant ecologist at Aachen University of Technology in Germany. Instead, the real issue is what effect the gene will have on its new owner. For the most part, that boils down to the question of whether a transgene will make hybrids more likely to survive than their wild kin. If it does, the gene will spread throughout the wild population. If not, then the hybrids are an ecological and genetic dead end, a minor sideline we can safely ignore. "Traits that are not going to persist are not worth worrying about," says Allison Snow, a plant ecologist at Ohio State University. If she's right, and most experts think she is, we can strike several sorts of GM organism off our escaped-transgene worry list straight away. Engineered genes that boost the nutritional value of a crop, such as "golden rice" enriched with vitamin A, probably wouldn't give a weed any extra edge. In fact, they'd most likely make it less fit by diverting the plant's energy into producing molecules irrelevant to life in the wild. The same would apply to microbes modified to break down toxic waste: once the waste is gone, the specialised enzymes become an unnecessary burden, and the engineered microbes should fade away. "There should be no risk," says lames Tiedje, a leading microbial ecologist at Michigan State University in East Lansing. Of course, developers would have to check that the transgenes didn't help the microbes use some other, natural foodstuff, but that should be relatively easy to do. For similar reasons, transgenes that turn crop plants such as maize into factories for churning out vaccines, drugs or industrial molecules are unlikely to spread widely. But if these GM crops cross-pollinate with nearby food crops, regulators will need to keep checking on them to ensure they don't become contaminated with unhealthy levels of the foreign molecule. "Who wants a pharmaceutical in their cornflakes?" says Rebecca Goldburg, a senior scientist at Environmental Defense, an advocacy group in New York. Nor do herbicide-resistance genes pose much of a threat of spreading into natural ecosystems. "As an ecologist, I'm not very concerned," says Bartsch. "Very often, resistance is achieved at some physiological cost. A person can protect himself against rain with a big plastic raincoat, but it makes him less able to run." That means herbicide- resistance genes aren't likely to spread much beyond the edges of cultivated, sprayed fields. The biggest threat is to the agrochemicals company that makes the herbicide. In the end if too many resistant weeds appear, no one will buy the firm's product. Weedy relatives might have more to gain from genes that confer resistance to insects or diseases. Snow's team studied sunflowers engineered to express a gene for the insecticidal toxin, Bt. When the experimental GM crop hybridised with wild sunflowers, the hybrids produced 5o per cent more seeds than ordinary wild sunflowers (New Scientist, 17 August, p 11). The Bt gene helped the wild sunflowers oust unwanted invaders, leaving them with more energy for making seed. "We didn't even know it, but there were insects feeding inside the stems," says Snow. "In a case like that, the gene would spread and have a huge advantage." The sudden increase in fitness could make wild sunflowers much more abundant, upsetting the ecosystem's normal balance. It could also drive insects toward extinction if their larvae feed exclusively on the sunflowers.
Nothing to worry about In contrast, wild squash plants bearing a transgene that makes them resistant to mosaic viruses show little or no advantage over their kin without the gene, probably because the virus only rarely causes significant damage except in the crowded conditions of cultivated fields. "So far, we've not seen anything that leads us to worry about the escape of these particular transgenes," says Hector Quemada, a plant pathologist at Westem Michigan University in Kalamazoo, who led the work. No one knows which of these two scenarios will be more common, but most experts agree that the riskiest transgenic traits are still to come. "The genes that catch my attention as an ecologist are anything that makes the plants bigger and healthier, or anything that would allow them to expand their range, like cold tolerance or drought tolerance or salt tolerance," says Snow. "These are all genes that people are working on now, and they're going to be available in five or ten years. Those could have some major eccdogical effects if they get into wild relatives and suddenly those plants could grow where they never grew before." Such shifts could create noxious new invaders - the transgenic equivalents of .vnurp.es such as kudzu and strawberry guava, which crowd out native species and drive them towards extinction. Not everyone is comfortable with such sweeping generalisations. "It's too problematic and too complicated to make a blanket statement that a trait like drought tolerance in any crop would be more risky," says Tom Nickson, who heads Monsanto's ecological technology centre in St Louis. "It's too superficial an evaluation. one reason for the uncertainty is that very few experiments have addressed this issue. "It's very frustrating that there's so little research," says Snow. That's especially true for microbes. "We are pretty ignorant about organisms we cannot see, including bacteria," says Kaare Nielsen, a microbial geneticist at the University of Tromso, Norway. "When the current state of knowledge is at that level, it's very difficult to start predicting how transgenes will affect the community." Genes which came from bacteria in the first place, such as Bt, probably don't confer much of an advantage. if they did, horizontal transfers among bacteria would already have spread them widely. "But at the point where you start to engineer your own genes and make things which deviate substantially from natural counterparts, it will become increasingly difficult to predict what the outcome would be," says Nielsen. One especially risky area might be engineering pathogenic microbes for biocontrol, where an escaped virulence gene could create new diseases in other organisms. Similar considerations apply to the fledgling field of GM animals. Livestock rarely interbreed with wild relatives, so there's little chance of gene leakage. But plying fish with growth-enhancing genes is more worrying, because fish hybridise so readily. Bigger, faster-growing fish could certainly upset the competitive balance in lakes, rivers and oceans. or take the Australian government's plan to control alien carp by releasing GM fish that produce only male offspring (New Scientist, 11 May, p 6). Such a gene would make females scarcer and scarcer with each generation until the carp pest vanished altogether. Australia has no native species in the carp family, so the gene poses no risk of escape there. "But if that fish were to be brought to China, oh man says Eric Hallerman, a population geneticist at Virginia Tech in Blacksburg. China is the centre of diversity for carp. The biotech industry, and government regulators, may find ways to reduce the likelihood of troublesome transgenes making their bid for freedom (see "Curbing wanderlust", opposite). However, it seems clear that in the end, there will be no substitute for a case-by-case assessment of the risks. Some transgenes clearly pose negligible risk, while others may well prove far too dangerous to play with. But so far, scientists just don't know enough about the consequences of wandering transgenes to sort out any but the easiest cases with any confidence. "The science of putting genes in is far ahead of the risk assessment research," says Marjorie Hoy, an insect geneticist at the University of Florida. Governments, not biotech companies with their obvious conflicts of interest, must ramp up research if they expect the public to trust their safety calls in the future. But one more twist bedevils those who fear the spread of transgenes into natural populations: any risks apply just as much to traits acquired through conventional breeding. For example, both conventional breeders and genetic engineers have now created salt- tolerant tomato plants (New Scientist, 18 May, p 47). Either one could spread to wild relatives, potentially creating a new weedy invader of saline habitats. Yet while governments and NGOs tightly regulate the planting of GM varieties, they put no restrictions on the products of conventional breeding. "Should we regulate the other methods more, or transgenics less?" asks Stewart.