Area Photos associated with Week: brand new Horizons Breaks a Record for Long-Distance Photography

This abstract glow is not merely a regular old area photo—it ended up being taken a record-breaking 3.79 billion miles away from Earth. NASA’s Pluto-grazing brand new Horizons spacecraft snapped this photo associated with Wishing Well available galactic star cluster coming toward its 2nd location, the Kuiper belt item 2014 MU69. For contrast, the runner-up for distance photography could be the famous Pale Blue Dot, taken by the Voyager spacecraft whilst it was 3.75 billion miles away.

This stunning photo of Jupiter was captured by NASA’s Juno spacecraft on its tenth orbit on December 16. The planet’s odd zigzagged storms are on complete display, plus a white cyclone. Jupiter appears huge within photo, however it’s nevertheless hard to get a feeling of scale—the white cyclone on left could be the size of a entire continent in the world.

This Hubble image looks like an artfully crafted watercolor painting, however it’s a genuine picture of galaxy NGC 7331, which will be located 45 million light years away. NGC 7331 shares a great deal in keeping with our own Milky Way Galaxy—it’s approximately the exact same size and hosts an identical quantity of stars, upwards of 100,000 million.

Hubble is at it once again! This wispy galaxy is officially NGC 7252, but its nickname is Atoms for Peace, after a message provided by President Eisenhower in 1953 because of the objective of a calm quality to nuclear energy. But 1 billion years ago this area ended up being the opposite of calm, whenever two galaxies violently merged together.

Martian avalanche! No body spilled paint on Mars; this is often a naturally occuring function due to dirt moving downhill. The contrast in color is because of there being less dust in darker areas than in the encompassing lighter areas. Therefore whilst the dust it self is not that much darker, the total amount of material changes its observed color.

Recently NASA’s Curiosity rover sent back this image of the stone. However it’s not just any Martian stone; geologists on Earth identified odd star-shaped and swallowtail-shaped crystals on the exterior of the stone. In the world such forms are observed in gypsum, a mineral formed in water. These sesame seed-sized features are characteristic of gypsum-crystals that may form whenever sodium water evaporates—but it’s thought Gale Crater had been home up to a non-salt water lake, making this rocky mystery an open investigation.

Can an Airplane remove for a going Runway?

This real question is probably as old because the airplane itself. It goes something such as this:

An airplane includes a takeoff speed of 100 mph (I just made that number up). What if it gets for a super giant treadmill machine that moves backwards at 100 mph. Could a plane with this giant treadmill machine remove or would it not simply sit there going at 0 miles per hour?

Initial question a reasonable individual would ask is “in which would you get yourself a giant plane-sized treadmill machine that goes 100 miles per hour?” Yes, which indeed a great question—but i will not answer it. Instead, i will offer this question top physics answer I am able to.

Before i actually do that, i ought to explain that others also have answered this question (not surprising as it’s super old anyway). First, there was the MythBusters episode from 2008. In fact, they didn’t answer the question—they did issue. The MythBusters made a giant conveyer belt having plane about it. It had been awesome. Next, there is the xkcd response to this concern (additionally from 2008).

Now you get my answer. I shall respond to with different examples.

A Car on a Conveyer Belt

This isn’t so difficult. Let’s say I put an automobile going 100 mph on a conveyer gear that is also going 100 mph? It could appear to be this (something like this):

Actually, there’s probably no real surprise right here. The vehicle’s tires would roll at 100 miles per hour as the treadmill machine (or conveyer gear) moves back at 100 mph so that the vehicle stays stationary. Really, here is a somewhat cooler example (with the same physics).

Let me reveal an test (also from MythBusters) which they shot a ball at 60 mph out of the back of a truck additionally going 60 miles per hour. You can view your ball stays fixed (with regards to the ground).

Super Brief Takeoff

Here is a airplane from Alaska that takes off in a really short distance.

How exactly does this work? We’ll provide you with a hint—there is definitely a strong wind blowing in to the front side for the plane. Without a headwind, this couldn’t happen. However if you consider it, this brief lose is certainly much such as the vehicle regarding treadmill machine. For the plane, it generally does not drive on the floor, it “drives” in the air. In the event that airplane possesses takeoff rate of 40 miles per hour and is in a 40 mph headwind, it doesn’t even have to go at all according to the ground.

Airplane for a Conveyer Belt

Now let us do it. This is a short clip from MythBusters launching a plane on a going treadmill machine.

Yes, it requires off. A plane takes faraway from a runway relocating the opposite direction? But why? It is because the tires for a plane never really do anything. The only function for the wheels would be to produce low friction between your aircraft together with ground. They do not also push the airplane forward—that is performed by the propeller. Truly the only distinction whenever releasing an airplane for a moving runway is the fact that wheels will spin at twice the standard speed—but that willn’t matter.

Therefore the airplane on a treadmill works, but how about a case where in fact the plane wouldn’t take off? Imagine if the plane ended up being similar to a glider with motorized tires? For a normal runway, these motorized tires would raise the rate for the glider until it reached takeoff speed. However, if you place this on a going runway, the tires would spin on right rate and cancel the motion regarding the treadmill so the airplane would remain motionless and not reach the proper rate for the launch.

okay, making sure that is the response to everybody’s favorite question. But never worry, this answer wont stop the endless discussion—that will go on forever.

Astronomers Trace Fast Radio Burst to Extreme Cosmic Neighborhood

On Christmas Eve 2016, Andrew Seymour, an astronomer at the Arecibo Observatory in Puerto Rico, kissed his 4-year-old daughter, Cora Lee, goodnight, telling her he was off to track Santa. He walked to the well-worn telescope, occasionally passing revelers riding horses through the empty streets—a common sight in Arecibo during the holidays. Sometimes a lonely firework would light up in the distance. Close to midnight, he nodded to a guard and entered the nearly empty complex.

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Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

The radio dish was on a break from its regular schedule, so Seymour decided to test out new hardware that he and his colleagues had been working on. Soon after he began recording his observations, an extremely powerful radio source, 3 billion light-years away, decided to say hello. Seymour didn’t find Santa that Christmas, but rather an unexpected twist in the tale of one of the most mysterious objects in the cosmos.

The object that Seymour caught that night was the only known repeating fast radio burst (FRB), an ultra-brief flash of energy that flickers on and off at uneven intervals. Astronomers had been debating what might be causing mysterious repeater, officially called FRB 121102 and unofficially the “Spitler burst,” after the astronomer who discovered it.

In the weeks following that Christmas detection, Arecibo registered 15 more bursts from this one source. These flashes were the highest frequency FRBs ever captured at the time, a measurement made possible by the hardware Seymour and his team had just installed. Based on the new information, the scientists have concluded in a study released this week in the journal Nature that whatever object is creating the bursts, it must be in a very odd and extreme cosmic neighborhood, something akin to the environment surrounding a black hole with a mass of more than 10,000 suns.

The new work helps to strengthen the theory that at least some FRBs might be produced by magnetars—highly magnetized, rotating neutron stars, which are the extremely dense remains of massive stars that have gone supernova, said Shami Chatterjee, an astrophysicist at Cornell University. In the case of the repeater, it could be a neutron star “that lives in the environment of a massive black hole,” he said. Or it might also be like nothing we’ve seen before—a different kind of magnetar ensconced in a very intense, magnetically dense birth nebula, unlike any known to exist in our galaxy—“quite extraordinary circumstances,” he said.

Too Extreme to Find

It wasn’t obvious at first that the repeating burst had to live in such an extreme environment. In October, 10 months after Seymour detected that initial burst at Arecibo, Jason Hessels, an astronomer at the University of Amsterdam, and his student Daniele Michilli were staring at the data on Michilli’s laptop screen. They had been trying to determine whether a magnetic field near the source might have twisted its radio waves, an effect known as Faraday rotation. There appeared to be nothing to see.

But then Hessels had an idea: “I wondered whether maybe we had missed this effect simply because it was very extreme.” They had been looking for just a little bit of a twist. What if they were to search for something exceptional? He asked Michilli to crank up the search parameters, “to try crazy numbers,” as Michilli put it. The student expanded the search by a factor of five—a rather “naive thing to do,” Chatterjee said, because such a high value would be completely unprecedented.

When Michilli’s laptop displayed the new data plot, Hessels immediately realized that the radio waves had gone through a hugely powerful magnetic field. “I was shocked to see how extreme the Faraday rotation effect is in this case,” he said. It was like nothing else ever seen in pulsars and magnetars. “I’m also embarrassed because we were sitting on the critical data for months” before attempting such an analysis, he added.

Jason Hessels led the team that identified the Faraday rotation coming from the burst.

Courtesy of Jason Hessels

The discovery sent ripples across the community. “I was shocked by the email announcing the result,” said Vicky Kaspi, an astrophysicist at McGill University. “I had to read it multiple times.”

Final confirmation came from a team searching for aliens. The Breakthrough Listen initiative ordinarily uses radio telescopes such as the Green Bank Telescope in West Virginia to scan the skies for signs of extraterrestrial life. Yet “since it’s not obvious in which direction they should point the telescope to search for E.T., they decided to spend some time looking at the repeating FRB, which clearly paid off,” said the astronomer Laura Spitler, namesake of the Spitler burst.

The Green Bank Telescope not only confirmed the Arecibo findings, it also observed several additional bursts from the repeater at even higher frequencies. These bursts also showed the same mad, highly twisted Faraday rotation.

What Powers Them

The extreme Faraday rotation is a signal that “the repeating FRB is in a very special, extreme environment,” Kaspi said. It takes a lot of energy to produce and maintain such highly magnetized conditions. In one hypothesis outlined by the researchers, the energy comes from a nebula around the neutron star itself. In another, it comes from a massive black hole.

In the nebula hypothesis, flares from a newly born neutron star create a nebula of hot electrons and strong magnetic fields. These magnetic fields twist the radio waves coming out of the neutron star. In the black hole model, a neutron star has its radio waves twisted by the enormous magnetic field generated by a nearby massive black hole.

Researchers haven’t come to an agreement about what’s going on here. Kaspi leans toward the black hole model, but Brian Metzger, an astrophysicist at Columbia University, feels that it’s somewhat contrived. “In our galaxy, only one out of dozens of magnetars resides so close to the central black hole. What makes such black hole-hugging magnetars so special that they would preferentially produce fast radio bursts? Did we just get really lucky with the first well-localized FRB?”

And the debate may get muddier before it gets cleared up. Chatterjee said theorists are certain to soon jump on the paper and start producing a multitude of new models and possibilities.

Burst Machines

The Spitler repeater is still the only FRB source that has been nailed down to a particular galaxy. No one knows quite where the other bursts are coming from. To say with any certainty that some—or all—of these energetic radio flashes come from highly magnetized environments, researchers need more data. And data are coming in. The Australian Square Kilometer Array Pathfinder (ASKAP), which is not yet officially complete, has already netted more FRBs than any other telescope in the world. With a tally of about 10 FRBs last year alone, it has proven to be “a remarkable FRB-finding machine,” said Matthew Bailes, an astrophysicist at Swinburne University of Technology—although none of them repeat.

Soon another telescope with a highly unusual design, called CHIME, will come online in Canada, and should spot many more FRBs—maybe 10 times more than ASKAP. Other next-generation telescopes, like the Square Kilometer Array (SKA), with dishes in South Africa and Australia, will surely contribute as well. As we register more of these flashes, chances are that some of them will repeat. Once scientists can sift through such data, the Faraday rotation effect may help them understand whether all FRBs are powered by a similar mechanism—or not.

Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

The Math Behind Gerrymandering and Wasted Votes

Imagine fighting a war on 10 battlefields. You and your opponent each have 200 soldiers, and your aim is to win as many battles as possible. How would you deploy your troops? If you spread them out evenly, sending 20 to each battlefield, your opponent could concentrate their own troops and easily win a majority of the fights. You could try to overwhelm several locations yourself, but there’s no guarantee you’ll win, and you’ll leave the remaining battlefields poorly defended. Devising a winning strategy isn’t easy, but as long as neither side knows the other’s plan in advance, it’s a fair fight.

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Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

Now imagine your opponent has the power to deploy your troops as well as their own. Even if you get more troops, you can’t win.

In the war of politics, this power to deploy forces comes from gerrymandering, the age-old practice of manipulating voting districts for partisan gain. By determining who votes where, politicians can tilt the odds in their favor and defeat their opponents before the battle even begins.

In 1986, the Supreme Court ruled extreme partisan gerrymanders unconstitutional. But without a reliable test for identifying unfair district maps, the court has yet to throw any out. Now, as the nation’s highest court hears arguments for and against a legal challenge to Wisconsin’s state assembly district map, mathematicians are on the front lines in the fight for electoral fairness.

Simple math can help scheming politicians draw up districts that give their party outsize influence, but mathematics can also help identify and remedy these situations. This past summer the Metric Geometry and Gerrymandering Group, led by the mathematician Moon Duchin, convened at Tufts University, in part to discuss new mathematical tools for analyzing and addressing gerrymandering. The “efficiency gap” is a simple idea at the heart of some of the tools being considered by the Supreme Court. Let’s explore this concept and some of its ramifications.

Start by imagining a state with 200 voters, of whom 100 are loyal to party A and 100 to party B. Let’s suppose the state needs to elect four representatives and so must create four districts of equal electoral size.

Imagine that you have the power to assign voters to any district you wish. If you favor party A, you might distribute the 100 A voters and 100 B voters into the four districts like this:

With districts constructed in this way, party A wins three of the four elections. Of course, if you prefer party B, you might distribute the voters this way:

Here, the results are reversed, and party B wins three of the four elections.

Notice that in both scenarios the same number of voters with the same preferences are voting in the same number of elections. Changing only the distribution of voters among the districts dramatically alters the results. The ability to determine voting districts confers a lot of power, and attending to some simple math is all that’s needed to create an electoral edge.

What if, instead of creating an advantage for one party over the other, you wished to use your power to create fair districts? First, you’d need to determine what “fair” means, and that can be tricky, as winners and losers often have different perspectives on fairness. But if we start with some assumptions about what “fair” means, we can try to quantify the fairness of different voter distributions. We may argue about those assumptions and their implications, but by adopting a mathematical model we can attempt to compare different scenarios. The efficiency gap is one approach to quantifying the fairness of a voter distribution.

To understand the efficiency gap, we can begin with the observation that, in a series of related elections, not all votes have the same impact. Some votes might make a big difference, and some votes might be considered “wasted.” The disparity in wasted votes is the efficiency gap: It measures how equally, or unequally, wasted votes are distributed among the competing parties.

So what counts as a wasted vote? Consider California’s role in presidential elections. Since 1992, California has always backed the Democratic nominee for president. Therefore, California Republicans know they are almost certainly backing a losing candidate. In some sense their vote is wasted: If they were allowed to vote in a toss-up state like Florida, their vote might make more of a difference. From a Republican perspective, that would be a more efficient use of their vote.

As it turns out, Democratic voters in California can make a similar argument about their vote being wasted. Since the Democratic candidate will likely win California in a landslide, many of their votes, in a sense, are wasted, too: Whether the candidate wins California with 51 percent of the vote or 67 percent of the vote, the outcome is the same. Those extra winning votes are meaningless.

Thus, in the context of the efficiency gap, there are two kinds of wasted votes: those for a losing candidate and those for a winning candidate that go beyond what is necessary for victory (for simplicity, we take the threshold for victory to be 50 percent, even though this could technically result in a tie; an actual tie is beyond unlikely with hundreds of thousands of voters in each congressional district). In a multi-district election, each party will likely have wasted votes of each kind. The efficiency gap is the difference in the totals of the wasted votes for each party, expressed as a percentage of total votes cast. (We subtract the smaller number from the larger when possible, to ensure a nonnegative efficiency gap. We could also take the absolute value of the difference.)

Let’s return to our four-district scenarios and examine their efficiency gaps. Our first distribution looked like this.

In this scenario, 75 of B’s votes are wasted: 60 in losing causes and 15 more than the 25 needed to win district 4. Only 25 of party A’s votes are wasted: 5 extra votes in each victory and 10 losing votes. The raw difference in wasted votes is 75 − 25 = 50, so the efficiency gap here is 50/200 = 25 percent. We say the 25 percent efficiency gap here favors party A, as party B had the larger number of wasted votes. In the second scenario, where the numbers are reversed, the 25 percent efficiency gap now favors party B.

Can the efficiency gap give us a sense of the fairness of a distribution? Well, if you had the power to create voting districts and you wanted to engineer victories for your party, your strategy would be to minimize the wasted votes for your party and maximize the wasted votes for your opponent. To this end, a technique colorfully known as packing and cracking is employed: Opposition votes are packed into a small number of conceded districts, and the remaining block of votes is cracked and spread out thinly over the rest of the districts to minimize their impact. This practice naturally creates large efficiency gaps, so we might expect fairer distributions to have smaller ones.

Let’s take a deeper look at efficiency gaps by imagining our 200-voter state now divided into 10 equal districts. Consider the following voter distribution, in which party A wins 9 of the 10 districts.

On the surface, this doesn’t seem like a fair distribution of voters. What does the efficiency gap say?

In this scenario, almost all of party B’s votes are wasted: nine losing votes in each of nine districts, plus nine excess votes in one victory, for a total of 90 wasted votes. Party A’s voters are much more efficient: only 10 total votes are wasted. There is a difference of 90 − 10 = 80 wasted votes and an efficiency gap of 80/200 = 40 percent, favoring party A.

Compare that with the following distribution, where party A wins 7 of the 10 districts.

Here, the wasted vote tally is 70 for party B and 30 for party A, producing an efficiency gap of 40/200 = 20 percent. A seemingly fairer distribution results in a smaller efficiency gap.

As a final exercise, consider this even split of district elections.

The symmetry alone suggests the answer, and the calculations confirm it: 50 wasted votes for each party means a 0 percent efficiency gap. Notice here that a 0 percent efficiency gap corresponds to an independent notion of fairness: Namely, with voters across the state evenly split between both parties, it seems reasonable that each party would win half of the elections.

These elementary examples demonstrate the utility of the efficiency gap as a measure of electoral fairness. It’s easy to understand and compute, it’s transparent, and its interpretations are consistent with other notions of fairness. It’s a simple idea, but one that is being used in a variety of complex ways to study gerrymandering. For example, mathematicians are now using simulations to consider millions of theoretical electoral maps for a given state and then examining the distribution of all possible efficiency gaps. Not only does this create a context for evaluating the fairness of a current map against other possibilities, it can also potentially be used to suggest fairer alternatives.

Though voters are not actually assigned to districts in the way we have imagined in our examples, the practice of gerrymandering achieves similar results. By strategically redrawing district boundaries, gerrymanderers can engineer voting distributions to create an uneven electoral playing field. These unfair fights affect how we are governed and help majority-party incumbents coast to re-election term after term. The case before the Supreme Court involves just one of many potentially unfair maps. Objective mathematical tools like the efficiency gap may be the only way to root out gerrymandering and keep our political battlefields in balance.

Download the “Doing the Political Math” PDF worksheet to practice these concepts or to share with students.

Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

What Protects Elephants from Cancer?

Elephants and other large animals have a lower incidence of cancer than would be expected statistically, suggesting that they have evolved ways to protect themselves against the disease. A new study reveals how elephants do it: An old gene that was no longer functional was recycled from the vast “genome junkyard” to increase the sensitivity of elephant cells to DNA damage, enabling them to cull potentially cancerous cells early.

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Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

In multicellular animals, cells go through many cycles of growth and division. At each division, cells copy their entire genome, and inevitably a few mistakes creep in. Some of those mutations can lead to cancer. One might think that animals with larger bodies and longer lives would therefore have a greater risk of developing cancer. But that’s not what researchers see when they compare species across a wide range of body sizes: The incidence of cancer does not appear to correlate with the number of cells in an organism or its lifespan. In fact, researchers find that larger, longer-lived mammals have fewer cases of cancer. In the 1970s, the cancer epidemiologist Richard Peto, now a professor of medical statistics and epidemiology at the University of Oxford, articulated this surprising phenomenon, which has come to be known as Peto’s paradox.

The fact that larger animals like elephants do not have high rates of cancer suggests that they have evolved special cancer suppression mechanisms. In 2015, Joshua Schiffman at the University of Utah School of Medicine and Carlo Maley at Arizona State University headed a team of researchers who showed that the elephant genome has about 20 extra duplicates of p53, a canonical tumor suppressor gene. They went on to suggest that these extra copies of p53 could account, at least in part, for the elephants’ enhanced cancer suppression capabilities. Currently, Lisa M. Abegglen, a cell biologist at the Utah School of Medicine who contributed to the study, is leading a project to find out whether the copies of p53 have different functions.

Vincent Lynch, a geneticist at the University of Chicago, has shown that part of what enabled elephants to grow so big was that one of their pseudogenes—a broken duplicate of an ancestral gene—suddenly acquired a new function.

Courtesy of Vincent J. Lynch

Yet extra copies of p53 are not the elephants’ only source of protection. New work led by Vincent Lynch, a geneticist at the University of Chicago, shows that elephants and their smaller-bodied relatives (such as hyraxes, armadillos and aardvarks) also have duplicate copies of the LIF gene, which encodes for leukemia inhibitory factor. This signaling protein is normally involved in fertility and reproduction and also stimulates the growth of embryonic stem cells. Lynch presented his work at the Pan-American Society for Evolutionary Developmental Biology meeting in Calgary in August 2017, and it is currently posted on

Lynch found that the 11 duplicates of LIF differ from one another but are all incomplete: At a minimum they all lack the initial block of protein-encoding information as well as a promoter sequence to regulate the activity of the gene. These deficiencies suggested to Lynch that none of the duplicates should be able to perform the normal functions of a LIF gene, or even be expressed by cells.

The eminent biologist Richard Peto, now at the University of Oxford, pointed out in the 1970s that elephants and other large-bodied animals ought to be at great statistical risk for cancer.

Cathy Harwood

But when Lynch looked in cells, he found RNA transcripts from at least one of the duplicates, LIF6, which indicated that it must have a promoter sequence somewhere to turn it on. Indeed, a few thousand bases upstream of LIF6 in the genome, Lynch and his collaborators discovered a sequence of DNA that looked like a binding site for p53 protein. It suggested to them that p53 (but not any of the p53 duplicates) might be regulating the expression of LIF6. Subsequent experiments on elephant cells confirmed this hunch.

To discover what LIF6 was doing, the researchers blocked the gene’s activity and subjected the cells to DNA-damaging conditions. The result was that the cells became less likely to destroy themselves through a process called apoptosis (programmed cell death), which organisms often use as a kind of quality control system for eliminating defective tissue. LIF6 therefore seems to help eradicate potentially malignant cells. Further experiments indicated that LIF6 triggers cell death by creating leaks in the membranes around mitochondria, the vital energy-producing organelles of cells.

To find out more about the evolutionary history of LIF and its duplicates, Lynch found their counterparts in the genomes of closely related species: manatees, hyraxes and extinct mammoths and mastodons. His analysis suggested that the LIF gene was duplicated 17 times and lost 14 times during the evolution of the elephant’s lineage. Hyraxes and manatees have LIF duplicates, but the p53 duplicates appear only in living and extinct elephants, which suggests that the LIF duplications happened earlier in evolution.

Elephants are closely related to large animals such as manatees (left), but also to smaller ones like hyraxes (right), aardvarks and armadillos. Elephants only began to develop their immense size about 30 million years ago.

Jim P. Reid, USFWS / Bjørn Christian Tørrissen

Lynch found that most duplicates of the LIF gene are pseudogenes—old, mutated, useless copies of genes that survive in the genome by chance. The exception, however, is the LIF6 gene sequence, which unlike the others has not accumulated random mutations, implying that natural selection is preserving it.

“We think that LIF6 is a refunctionalized pseudogene,” Lynch said. That is, the elephant LIF6 re-evolved into a functional gene from a pseudogene ancestor. Because it came back from the dead and plays a role in cell death, Lynch called it a “zombie gene.”

Although manatees and hyraxes also have extra copies of LIF, only modern and extinct elephants have LIF6, which suggests that it evolved only after the elephants branched away from those related species. And when Lynch’s group dated the origin of LIF6 by molecular clock methods, they found that the pseudogene regained a function about 30 million years ago, when the fossil record indicates that elephants were evolving large body sizes.

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“Refunctionalizing a pseudogene is not something that happens every day,” explained Stephen Stearns, an evolutionary biologist at Yale University, in an email to Quanta. Being able to show that it happened at roughly the same time that elephants evolved a large body, he wrote, “supports, but does not prove, that the refunctionalizing of the gene was a precondition for the evolution of large body size.”

Evolving protections against cancer would seem to be in the interest of all animals, so why don’t they all have a refunctionalized LIF6 gene? According to the researchers, it’s because this protection comes with risks. LIF6 suppresses cancer, but extra copies of LIF6 would kill the cell if they accidentally turned on. “There’s a bunch of toxic pseudogenes sitting there” in the genome, Lynch explained in an email. “If they get inappropriately expressed, it’s basically game over.”

There also appears to be a trade-off between cancer suppression mechanisms and fertility. A study published in 2009 suggested that LIF is critical for implantation of the embryo in the uterus. Because LIF activity is controlled by p53, LIF and p53 jointly regulate the efficiency of reproduction. When the same set of genes has two functions (such as reproduction and cancer suppression), it is possible that those functions will be in direct conflict—a phenomenon that geneticists call antagonistic pleiotropy.

The elephants may have solved the problem of antagonistic pleiotropy by duplicating p53 and LIF and splitting up those functions, according to Maley. “Some copies of p53 and LIF are doing what’s necessary for fertility, while other pairs of LIF and p53 are doing what’s necessary for cancer suppression,” he said. Maley speculated that the gene duplicates “allowed the elephants to get better at cancer suppression and still maintain their fertility, which would allow them to grow a larger body.” That hypothesis, however, still needs to be tested, he said.

Bats are not large animals, but some species live for decades. Scientists are investigating whether they have their own protective adaptations against cancer.

Ann Froschauer, USFWS

Evolving extra copies of p53 and LIF may have helped elephants overcome Peto’s paradox, but that can’t be the only solution: Other large animals like whales have only one copy of p53 and one version of LIF. Lynch and his team are currently exploring how whales and bats solve Peto’s paradox. Although not large-bodied, some bat species live up to 30 years, and the longer-lived ones might have evolved cancer suppression mechanisms that the shorter-lived ones lack.

Maley is also working on how whales solve Peto’s paradox. Even though whales don’t have extra copies of p53, he said, “we do think there has been a lot of selection and evolution on genes in the p53 pathway.” Maley believes that understanding how diverse large-bodied animals solve Peto’s paradox may have applications in human health. “That is the end goal,” he said. “The hope is that by seeing how evolution has found a way to prevent cancer, we could translate that into better cancer prevention in humans.”

“Every organism that evolved large body size probably has a different solution to Peto’s paradox,” Maley said. “There’s a bunch of discoveries that are just waiting for us out there in nature, where nature is showing us the way to prevent cancer.”

Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.