The surprisingly complicated physics of why cats always land on their feet

Ars chats with physicist Greg Gbur about his book, Falling Felines and Fundamental Physics

JENNIFER OUELLETTE - 12/25/2019, arstechnica.com

Enlarge / A cat being dropped upside down to demonstrate a cat's
 movements while falling Ralph Crane/The LIFE Picture Collection 
via Getty Images

There's rarely time to write about every cool science-y story that comes our way. So this year, we're once again running a special Twelve Days of Christmas series of posts, highlighting one story that fell through the cracks each day, from December 25 through January 5. Today: an intriguing recent book on the science of why cats always land on their feet.

Scientists are not immune to the alluringly aloof charms of the domestic cat. Sure, Erwin Schrödinger could be accused of animal cruelty for his famous thought experiment, but Edwin Hubble had a cat named Copernicus, who sprawled across the papers on the astronomer's desk as he worked, purring contentedly. A Siamese cat named Chester was even listed as co-author (F.D.C. Willard) with physicist Jack H. Hetherington on a low-temperature physics paper in 1975, published in Physical Review Letters. So perhaps it's not surprising that there is a long, rich history, spanning some 300 years, of scientists pondering the mystery of how a falling cat somehow always manages to land on their feet, a phenomenon known as "cat-turning."

"The falling cat is often sort of a sideline area in research," physicist and cat lover Greg Gbur told Ars. "Cats have a reputation for being mischievous and well-represented in the history. The cats just sort of pop in where you least expect them. They manage to cause a lot of trouble in the history of science, as well as in my personal science. I often say that cats are cleverer than we think, but less clever than they think." A professor at the University of North Carolina, Chapel Hill, Gbur gives a lively, entertaining account of that history in his recent book, Falling Felines and Fundamental Physics.

Over the centuries, scientists offered four distinct hypotheses to explain the phenomenon. There is the original "tuck and turn" model, in which the cat pulls in one set of paws so it can rotate different sections of its body. Nineteenth century physicist James Clerk Maxwell offered a "falling figure skater" explanation, whereby the cat tweaks its angular momentum by pulling in or extending its paws as needed. Then there is the "bend and twist" (not to be confused with the "bend and snap" maneuver immortalized in the 2001 comedy Legally Blonde), in which the cat bends at the waist to counter-rotate the two segments of its body. Finally, there is the "propeller tail," in which the cat can reverse its body's rotation by rotating its tail in one direction like a propeller. A cat most likely employs some aspects of all these as it falls, according to Gbur.

Gbur is quick to offer a cautionary word of advice to anyone considering their own feline experiments: "Please don't drop your cats!"—even in the name of science. Ars sat down with Gbur to learn more about this surprisingly prolific area of research.

Enlarge / Cats are cautiously fond of physics, as Ariel can attest.

Jennifer Ouellette

Ars Technica: What led you to write an entire book about the physics of falling cats?

Greg Gbur: It really started with my love of the history of science and writing about it on my blog. One day, I was browsing old science journals, and I came across an 1894 paper about photographs of a falling cat landing on his feet. I wrote a blog post about it. But I wasn't completely satisfied with the explanation, and I realized there were more papers on the subject. Every time I did a search, I found another paper offering another angle on the problem. Even in the last few weeks of writing the book, I still kept coming across minor little papers that gave me a little bit of a different take on the history. It was surprising just how many papers there were about the falling cat problem. The more you look, the more you find people intrigued by how a cat lands on his feet. It seems like a problem that would be readily solvable.

Ars: Surely one of the issues was that photography hadn't been invented yet, particularly high-speed photography. 

Gbur: Yes. Maxwell did his own preliminary investigations of the subject, but he pointed out that when you drop a cat from roughly two feet, it can still land on its feet, even if you're dropping it upside down. That's a really short period of time. The human eye simply can't resolve that. So it was a problem that was largely not solvable until the technology was there to do high speed photography.

Étienne-Jules Marey did the first high speed photographs of falling down. It was almost an afterthought for him. He was doing all these different high-speed photographs of different animals, because that was his research, studying living creatures in motion. He presented the images of a falling cat, and it genuinely shocked the scientific community. One of the members at the meeting where the photographs were presented, said (and I paraphrase), “This young Marey has presented us with a problem that seems to go against the known laws of physics."

The motions that are depicted in the photographs are quite complicated. The explanation given is part of the truth, but it seemed incomplete. It was good enough to convince physicists that a cat wasn't violating the laws of physics, but it wasn't good enough to convince everyone that it was the right explanation, or the complete explanation.

Ars: You summarize four distinct hypotheses offered at various times to explain the phenomenon of cat turning. So what is the best explanation we have so far for how a cat can turn and fall and land on its feet?

Gbur: This is part of why it was such a challenge: all these different motions play a role. If you're looking at a series of photographs or a video of a falling cat, it becomes almost a psychological problem. Different people, their attention is going to be drawn by different aspects of a motion. But the most important is a bend and twist motion. The cat bends at the waist and counter rotates the upper and lower halves of its body in order to cancel those motions out. When one goes through the math, that seems to be the most fundamental aspect of how a cat turns over. But there are all these little corrections on top of that: using the tail, or using the paws for additional leverage, also play a role. So the fundamental explanation comes down to essentially bend and twist, but then there's all these extra little corrections to it.

Enlarge / Chronophotograph (circa 1893) made on moving film consisting
of twelve frames showing a cat falling, taken by Etienne-Jules Marey (1830-1904).

SSPL/Getty Images

Ars: After all these studies, do we now know know exactly what's going on with a falling cat, or is this still an area of active research?

Gbur: I don't know that there's anybody actively studying the cat model to try and get the finer details. It's reached a point where understanding how a cat does it has reached, as a 19th century physicist once said, “hunting for higher decimal places.” Part of the catch is that every cat may do things just a little bit differently, because they are living creatures. You have heavier cats and lighter cats. I've got varieties of both at home. Longer cats and shorter cats. Each of them may twist and bend and tuck and turn just a little bit differently.

If you watch videos of falling cats, you will see that a lot of them use their tails to turn over. But we also know that cats without tails can turn over just fine. So from a physics point of view, the problem has reached a level where the details depend on the specific cat. People will still argue about it. I think a lot of physicists don't realize how complicated the problem is, and they're often just looking for a single simple solution. Physicists have an instinct to look for simple solutions, but nature's always looking for the most effective solution. And those two approaches are not always the same.

"From a physics point of view, the problem has reached a level where the details depend on the specific cat."

The emphasis these days is in that robotics area. Can we actually make a robot that can flip over like this, in as effective a way as a cat can. You can design a robot that, if you drop it upside down, can land right side up, but a cat can flip over and land right side up regardless of how it started— whether it's upside down, whether it's spinning, whether it's on its side. There's a video clip of a cat leaping up to grab a toy and it ends up flipping partially end over end as it leaps. And it does multiple twists and nevertheless manages to still land on its feet. That's the sort of thing that I don't think anybody has managed to get a robot to do yet. "Hey, I'm just gonna throw this robot up in the air with any sort of spinning motion I want, and nevertheless, have it still land perfectly on its feet."

Two different approaches to the falling cat problem intersect in robotics. You can use mechanical models to try and understand what a cat is doing, and then you can also use robotics to try and replicate the cat's motion properly. One is an analysis problem, where you're saying, "I want to understand what's going on." The second part is a synthesis problem where you say, "I'm going to try and make a machine that can accurately reproduce it."

Enlarge / Photographs of a Tumbling Cat, 1894.

Étienne-Jules Marey

Ars: You also discuss a 2003 paper by physics philosopher Robert Batterman, in which he examines falling cats in terms of geometric phases, which in turn connects to a Foucault pendulum. Can you elaborate a bit on this particular connection?

Gbur: The basic idea is that there are a lot of physics problems where you can cycle the system. You start with the system and one condition, and you bring it through some change of behavior back to its original condition. But nevertheless it ends with a different behavior than it started. The falling cat is a good example. The cat starts upside down with his back straight, ends up right side up with his back straight. Even though it's twisted and turned along the way, it ends up with a straight back again, but it's now rotated 180 degrees.

Foucault's pendulum is where you have this pendulum oscillating on the earth, a full day goes by, and the earth has done a full revolution. So the pendulum is spatially back where it started at the beginning of the previous day, but it is swinging in a different direction. The really remarkable thing is that the mathematics is structurally similar for all these different problems. So if you understand the falling cat problem, you understand a little bit about Foucault's pendulum and how it works. Batterman also ties falling cats to polarized light and parallel parking as manifestations of the geometric phase in physics.

Ars: It sometimes seems like physicists don't always appreciate how important their own history is to understanding current research.

Gbur: One reason I always emphasize learning a lot of science history is that it gives us a better understanding of how science is done. In basic physics classes, we're often taught a very abbreviated and abridged version of the history, where you're given the straight line path that leads to the end. I think of science history as sort of a maze. You've got a bunch of people wandering through this maze and a lot of people hit dead ends. That's very natural, because nobody knows what they're looking for. When we're taught the history of science in class, we're often only taught about the person who made it to the end of the maze without making any mistakes.

For students, that can give a very false impression that science is always about, "Yes, I know exactly what I'm doing and I know exactly where I'm going." That isn't the case. For the general public, it's often useful to realize that, yes, science is always moving forward, but there are these dead ends, there are these mistakes along the way. It's not perfect. That is not a condemnation of science, but the natural way things work.

---30---

Finding stars that vanished—by scouring old photos

Comparing images taken nearly a century apart.

12/24/2019, arstechnica.com 

First you see it (top left) then you don't.

Before the advent of digital imaging, astronomy was done using photographic plates. The results look a bit like biology experiments gone bad (of which I've perpetrated more than a few), with a sea of dark speckles of different intensities scattered randomly about. To separate the real stars from any noise, astronomers would take multiple images, often at different colors, and analyze the results by eye before labeling anything an actual star. Sounds tough, but by 50 years ago, astronomers had already managed to catalog hundreds of millions of stars in all areas of the sky.

These days, automated telescopes, digital imaging, and software pipelines mean that we can do equivalent surveys with greater sensitivity in a fraction of the time. But that doesn't mean the old surveys have lost their value. The original photographs provide data on how the sky looked before the relative motion of objects (and their occasional explosions) rearranged the sky. To get a better sense of just how much the sky has changed, a group of researchers has been comparing the old photographs and the modern survey data to figure out what stars went missing.

After whittling down a large list of candidates, the team came up with 100 things that looked like stars a century ago but no longer seem to be with us.

In the Navy (and not elsewhere)

There have been several large-scale, all-sky surveys done, and it's possible to compare the results to find objects that have changed between them. There are also dedicated efforts to find short-term "transient" events—objects that brighten or dim on the scale of weeks to months. But these may miss changes that take place gradually over longer time periods or events that happened before modern digital surveys.

To get a better sense of these events, some astronomers have formed a project called VASCO, for "Vanishing and Appearing Sources during a Century of Observations." Their goal is to compare data from the first surveys done on photographic plates to what we've been getting from modern surveys, and then to identify objects that have changed. The hope is that, among other things, having a longer time window will increase the odds of finding an extremely rare event, one that might not occur in the handful of years that separate the digital surveys.

To go back far enough in time, the VASCO team relied on the US Naval Observatory's catalog of objects, which combines the results of several surveys done on photographic plates. All told, this catalog contains over a billion objects. For modern data, the team used the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) database, which contains even more objects.

Conceptually, the study was simple: it worked by identifying the objects of the earlier catalog and checked whether they were still present in the later one. But there are a number of complications. First, you need to know that the object in the earlier catalog was actually there, not a bit of noise or something misidentified (like an asteroid mislabeled as a star). Then, you must be certain that the modern observations are at the right location to see the object if it's still there.

Finally, you have to make sure the object hasn't moved too much in the intervening time. While that's not an issue for distant stars or even for farther galaxies, stars closer to Earth will have a larger relative motion over the sorts of time involved here. You need to choose a search window large enough to make sure local stars are identified, but not so large that it becomes easy to pick the wrong star as "matching" the missing one.

Finding what's not there

For a first pass, computing time limited the team to examining a bit over half the sky, or about 600 million objects. From that, they come up with about 150,000 potential mismatches, a rate within the known range of data processing errors in sky surveys. So, figuring out what's real in that 150,000 is a substantial challenge, one limited by bringing in data from the Sloan Digital Sky Survey. This immediately found matches for about 65,000 objects, while allowing for relative motion cut the list of potential vanishing acts down to only 23,667 objects. At this point, the researchers examined them all visually.

This allowed the team to identify stuck pixels in the modern digital data or to see imaging artifacts from nearby bright stars. Further elimination eventually produced a final list of 1,691 candidates for vanishing stars.

At this point, the authors analyzed the average properties of the vanishers, finding that they were a bit redder, they varied more between images when multiple images were available, and they had a higher relative motion, suggesting that many were relatively close to Earth.

Those properties suggest one possible explanation for the vanishing act. Red dwarfs in the area of Earth would be dim, have high relative motion, and have light biased toward the red end of the spectrum. They're also prone to extended outbursts, which could have made them detectable at some time points but not others.

In any case, the authors continued to whittle their list down, eliminating 200 objects because of dead pixels in some telescope hardware and a large number where the star is actually present in both old and new images but is slightly offset. This nudged the list down to about 1,000 candidates that seem worth following up on.

What might these be? Aside from red dwarfs, we have a number of possible explanations. It has been proposed (though not verified) that some large stars, rather than exploding in a supernova, may directly collapse into a black hole, swallowing the remains of the star and avoiding the messy (and bright) debris fields that supernovae create. This could cause a star to essentially vanish. Supermassive black holes can disrupt stars or increase or decrease their intake of matter on years-to-decades scales, potentially causing them to brighten and dim dramatically. A bright star eclipsed by a dim companion could also cause stars to briefly vanish.

Then there are known variable types of stars, including Cephids and RR Lyrae stars, both of which brighten and dim regularly. There's also the extremely rare variable R Coronae Borealis stars, of which only 150 are estimated to exist in the Milky Way.

All of these make viable candidates for stars that appear to vanish, as they can simply drop below the detection limits of various telescopes. And, since they're interesting stars, it's worth doing follow-up observations of their former locations to see whether there might be anything dim now residing there.

But the team behind the new paper indicates that the project started with a far more exotic inspiration: Dyson spheres, structures that alien civilizations might build to enclose an entire star and harvest all of its energy. These would obviously cause a star to vanish, though the timescale of its dimming and eventual disappearance would be anyone's guess.

Regardless of the inspiration, the team has identified a large number of objects that might be interesting to astronomers. And that's only with surveying a bit more than half the sky. There also remains the follow-on work of doing the converse analysis—looking for objects that are in present surveys but weren't detected decades ago.

The Astronomical Journal, 2019. DOI: 10.3847/1538-3881/ab570f (About DOIs).

BACK IN ONE PIECE —

Starliner makes a safe landing—now NASA faces some big decisions

Contract says a docking demonstration is needed. Will NASA waive this requirement?

ERIC BERGER - 12/22/2019, arstechnica.com

The Boeing CST-100 Starliner spacecraft is seen after it landed in White Sands, 

New Mexico, Sunday, Dec. 22, 2019.

NASA/Bill Ingalls

The main parachutes begin to deploy as the Boeing CST-100 Starliner spacecraft lands.

NASA/Bill Ingalls

The Boeing CST-100 Starliner spacecraft jettisons the heat shield before it lands.

NASA/Aubrey Gemignani

The Boeing CST-100 Starliner spacecraft is seen landing in this 30 sec. exposure.

NASA/Aubrey Gemignani

Starliner touches down.

NASA/Aubrey Gemignani

Boeing, NASA, and U.S. Army personnel work around the Boeing 

CST-100 Starliner spacecraft shortly after it landed.

NASA/Bill Ingalls

Boeing, NASA, and U.S. Army personnel collect parachutes.

NASA/Bill Ingalls

Boeing, NASA, and U.S. Army personnel work around the 

Boeing CST-100 Starliner.

NASA/Bill Ingalls

A protective tent is placed over the vehicle.

NASA/Bill Ingalls

Boeing’s Starliner spacecraft safely returned from orbit on Sunday morning, landing at White Sands Space Harbor in New Mexico before sunrise. The capsule very nearly hit its bullseye, and initial reports from astronauts on the scene say the vehicle came through in "pristine" condition.

The company will now spend several days preparing Starliner for transit, before shipping it from New Mexico back to Boeing's processing facility at Kennedy Space Center in Florida. Then, engineers will spend most of January reviewing data captured by on-board sensors. What happens after that is the big question.

Mission Elapsed Time anomaly

After the spacecraft launched on board its Atlas V rocket, but before it separated from the booster, the capsule needed to figure out what time it was. According to Jim Chilton, Boeing's senior vice president of the Space and Launch division, the way this is done is by "reaching down into" the rocket and pulling timing data out. However, during this process, the spacecraft grabbed the wrong coefficient. "We started the clock at the wrong time," Chilton said. "The spacecraft thought she was later in the mission and started to behave that way."

The net effect of this is that Starliner's service module thrusters began consuming a lot of propellant to keep the vehicle in a very precise attitude with respect to the ground. When flight controllers realized the error, it took time to establish a communications link because the spacecraft was not where they thought it was.

FURTHER READING Starliner’s timer was off—capsule thought engines were firing when they weren’t

With the on-board propellant remaining, Starliner did not have sufficient reserves to approach the International Space Station and perform a rendezvous and docking with the orbiting laboratory—a key objective of this flight test before NASA allows its astronauts to fly on the capsule into space.

Much of the rest of the flight went very well, however, once flight controllers diagnosed and corrected the mission elapsed time error. (The clock was off by 11 hours.) The vehicle flew smoothly in orbit, its life support systems kept the spacecraft at good temperatures, and it made a safe and controlled landing on Sunday morning. Chilton said he believes the vehicle will meet 85 to 90 percent of the test flight's objectives.

Good enough?

The question is whether this will be good enough for NASA to proceed with a human test flight of Starliner without a second uncrewed test to determine the capsule's capability to dock to the space station. Part of that decision will depend on the root cause of the problem, and whether it represents a systemic error in Starliner's flight software.

"Make no mistake, this did not go according to plan in every way that we hoped," NASA Administrator Jim Bridenstine said Sunday. Even so, Bridenstine said he fully expects NASA to work with Boeing to get humans flying on Starliner in 2020. Of the software timing error, he said, “It’s not something that is going to prevent us from moving forward quickly.”

However, NASA's "commercial crew" contract with Boeing stipulates several requirements that must be completed by the orbital flight test. "The Contractor’s flight test program shall include an uncrewed orbital flight test to the ISS," the document states. And this test should include, "Automated rendezvous and proximity operations, and docking with the ISS, assuming ISS approval."

FURTHER READING Starliner flies for the first time, but one of its parachutes failed to deploy

After a news briefing on Sunday morning at Johnson Space Center, the deputy director of the commercial crew program, Steve Stich, said NASA will review the contract. "We’ll have to look at that afterwards and try to understand it," he said. "We’ll have to go take a look at what we achieved with what’s in the contract."

Boeing—which presumably would have to pay for a second test flight as part of its fixed-price contract with NASA—certainly would like to be able to convince NASA that it does not need to make a second uncrewed test flight. On the day Starliner landed, it sure sounded like some key NASA officials would like to talk themselves into that as well.

Listing image by NASA/Bill Ingalls

Forecasting El Niño with entropy—a year in advance

This would beat 6-month limit of current forecasts.

SCOTT K. JOHNSON - 12/28/2019, arstechnica.com 

Enlarge / A strong El Niño developed in 2015, visible here from temperature departures from average.

NASA EO

We generally think of weather as something that changes by the day, or the week at the most. But there are also slower patterns that exist in the background, nudging your daily weather in one direction or another. One of the most consequential is the El Niño Southern Oscillation—a pattern of sea surface temperatures along the equatorial Pacific that affects temperature and precipitation averages in many places around the world.

In the El Niño phase of this oscillation, warm water from the western side of the Pacific leaks eastward toward South America, creating a broad belt of warm water at the surface. The opposite phase, known as La Niña, sees strong trade winds blow that warm water back to the west, pulling up cold water from the deeps along South America. The Pacific randomly wobbles between these phases from one year to the next, peaking late in the calendar.

Since this oscillation has such a meaningful impact on weather patterns—from heavy precipitation in California to drought in Australia—forecasting the wobble can provide useful seasonal outlooks. And because it changes fairly slowly, current forecasts are actually quite good out to about six months. It would be nice to extend that out further, but scientists have repeatedly run into what they've termed a “spring predictability barrier.” Until they see how the spring season plays out, the models have a hard time forecasting the rest of the year.

A new study led by Jun Meng, Jingfang Fan, and Josef Ludescher at the Potsdam Institute for Climate Impact Research showcases a creative new method that might hop that barrier.

This method doesn’t involve a better simulation model or some new source of data. Instead, it analyzes sea surface temperature data in a new way, generating a prediction of the strength of El Niño events a full year in advance. That analysis, borrowed from medical science, measures the degree of order or disorder (that is, entropy) in the data. It turns out that years with high disorder tend to precede strong El Niño events that peak a year later.

What does it mean for the data to be disorderly? Essentially, the analysis looks for signs that temperatures in different locations across the relevant portion of the Pacific are changing in sync with each other. The researchers broke the area into 22 grid boxes, comparing temperature in each box to the others for consistent patterns.

Enlarge / An example of temperature data from different grid boxes within the region used to measure the El Niño Southern Oscillation.

Meng et al/PNA

For a very simple example of how this works, they first tested the method on similar pairs of grid boxes—but using some pairs of neighboring boxes and some pairs that were in different parts of the world. Locations right next to each other tend to behave similarly, while distant locations experienced completely unrelated ups and downs.

When they set this method loose on past Pacific temperature data going back to 1985, it worked surprisingly well. For the ten El Niño years in the dataset, their method indicated high disorder in the year previous nine times, missing only one of them. And for the rest of the years in the dataset, it only had three false positives, where it indicated a coming El Niño that never materialized.

Enlarge / Forecasts of El Niño strength (blue bars) based on data in the year preceding actual El Niños (red).

Meng et al/PNAS

What’s more, the degree of disorder correlated with the strength of the El Niño, allowing them to forecast the Pacific temperature within a couple tenths of a degree C. Most recently, the researchers calculated a 2018 forecast using the 2017 temperature data. El Niño/La Niña is measured by the average temperature across that region of the Pacific, with anything at least 0.5°C above normal qualifying as an El Niño. The 2018 forecast, calculated about 12 months ahead, comes in at +1.11°C (±0.23). The data show that 2018 actually hit about +0.9°C.

Statistics-based forecasts can be problematic, falling for meaningless correlations that have no physical basis and don’t hold up in the future. But in this case, the statistics don’t come from searching for correlations or fitting to existing data. It’s simply a real measurement that seems to pass the test pretty well. And there’s a plausible mechanism behind it, the researchers say.

FURTHER READING Current El Niño’s strength due partly to an earlier fizzle

Orderly temperature patterns could result from turbulent mixing of the ocean that helps temperature diffuse across the area. That is a common pattern during El Niño years, and it tends to see-saw. If temperatures are very orderly one year, they’re likely to become very disorderly the next, and vice versa. That sort of behavior has been noticed before, and this new method may be picking up on it.

If nothing else, efforts like this show the spring predictability barrier probably won’t stand forever. Seasonal weather outlooks might someday be a part of annual outlooks, though the task of forecasting next Tuesday’s weather will remain a separate endeavor.

PNAS, 2019. DOI: 10.1073/pnas.1917007117 (About DOIs).

Team that made gene-edited babies sentenced to prison, fined

China cracks down on researchers who edited genes in fertilized human eggs.

JOHN TIMMER - 12/30/2019, arstechnica.com

Enlarge / Chinese geneticist He Jiankui speaks during the Second International Summit on Human Genome Editing at the University of Hong Kong days after he claimed to have altered the genes of the embryo of a pair of twin girls before birth, prompting outcry from scientists of the field.

S.C. Leung/SOPA Images/LightRocket via Getty Images

On Monday, China's Xinhua News Agency reported that the researchers who produced the first gene-edited children have been fined, sanctioned, and sentenced to prison. According to the Associated Press, three researchers were targeted by the court in Shenzhen, the most prominent of them being He Jiankui. He, a relatively obscure researcher, shocked the world by announcing that he had edited the genomes of two children who had already been born by the time of his public disclosure.

He Jiankui studied for a number of years in the United States before returning to China and starting some biotech companies. His interest in gene editing was only disclosed to a small number of advisers, and his work involved a very small team. Some of them were apparently at his companies, while others were at the hospital that provided him with the ability to work with human subjects. After his work was disclosed, questions were raised about whether the hospital fully understood what He was doing with those patients. The court determined that He deliberately violated Chinese research regulations and fabricated ethical review documents, which may indicate that the hospital was not fully aware.

FURTHER READINGScientists, ethicists slam decisions behind gene-edited twins

He's decision to perform the gene editing created an ethical firestorm. There had been a general consensus that the CRISPR technology he used for the editing was too error-prone for use on humans. And, as expected, the editing produced a number of different mutations, leaving us with little idea of the biological consequences. His target was also questionable: He eliminated the CCR5 gene, which is used by HIV to enter cells but has additional, not fully understood immune functions. The editing was done in a way that these mutations and their unknown consequences would be passed on to future generations.

His goal was to provide protection against HIV infection, modeling it on known human mutations in CCR5; the embryos chosen for editing were from couples in which the father was HIV positive. There are, however, many ways to limit the possibility of HIV infection being transmitted from parents to children. And, if infected, there are many therapies that limit the impact of an HIV infection.

Ethicists and most researchers had suggested that gene editing be limited to cases where the edited genes would not be inherited. The only potential exceptions that were considered were lethal mutations for which there were no treatments. He's targets and methods violated all of these principles.

But until now, it wasn't clear whether those violations would have consequences. It had been rumored that He was placed under arrest even as a third gene-edited child was born. The legal action suggests that both of these were accurate.

He received a three-year prison sentence, a ¥3 million ($430,000) fine, and has had limits placed on any further research activities. Zhang Renli and Qin Jinzhou, who reportedly worked at the medical institutions where the work took place, were given shorter sentences and lesser fines.

Watch this video on The Scene.

Teach the Conspiracy: GMOs

Recent studies show the general public and the scientific community are deeply divided on the perceived safety of GMOs. Ars Technica's John Timmer explains why this rift exists and why GMOs are much safer than most people realize.

http://www.pewinternet.org/interactives/public-scientists-opinion

Transcript

00:00

[dramatic, scary music]

00:04

A little while back, two polls were done.

00:06

One sampled the US public, while the second sampled members

00:09

of an organization that include scientists

00:12

and people interested in the science.

00:14

The pollsters used the results to determine

00:16

where scientists and the public kept

00:18

the biggest differences in opinion.

00:20

You might expect it to be something political,

00:22

like evolution or climate change, but it wasn't.

00:25

It was whether GMO foods are safe.

00:27

[Woman] Asparagus, mashed potatoes,

00:30

and a special treat for them, chocolate layer cake pills.

00:35

Are they?

00:35

[riveting, dramatic music]

00:39

We use genetic engineering to give plants useful traits.

00:42

We've made crops that resist viruses

00:45

or make proteins that kill the insect pests that eat them.

00:48

We've made other crops that aren't harmed by a weed killer.

00:51

We've engineered rice to make an important vitamin.

00:54

[Woman] Golden rice is being marketed as the cure

00:57

to vitamin A deficiency, a leading cause

00:59

of blindness in the world.

01:01

These crops have lowered pesticide use

01:03

and increased farmers' income in developing countries.

01:06

While an engineered crop is undoubtedly different,

01:09

all of our crops are very different from how they started.

01:12

Our crops are hybrids of different strains

01:14

with many random mutations,

01:16

both natural and made using radiation.

01:19

Or here are two mutations in maize.

01:21

GMOs have smaller and far more targeted changes

01:24

than a crop strain does compared to its natural relatives.

01:27

But people have always been uneasy with genetic engineering,

01:31

starting back when we applied it to bacteria in the 1970s.

01:35

You know what kind they are? All I know is that they came

01:37

out of that test tube that you gave me.

01:39

They're the ones with kinds of bacteria

01:40

that cause food to spoil.

01:43

The controversy over genetic engineering followed

01:45

to crops.

01:46

People worry about the spread of engineered genes

01:49

into the environment, the way GMO crops provide an advantage

01:53

to large agricultural companies and our increasing reliance

01:56

on just a few strains of plants for our food.

02:00

Combined, these worries have led

02:01

to decades of protests, including arson and destroyed crops.

02:05

Due to all this, the use of GMOs in Europe

02:08

has been severely limited, and the US has even passed a law

02:12

requiring foods containing GMOs to be labeled.

02:15

But politics isn't driving the problems.

02:17

Polls show equal concerns about GMO foods

02:20

between conservative Republicans and liberal Democrats.

02:24

So why are they wrong?

02:26

Some of the controversy rises from issues related

02:29

to whether a few companies have too much control

02:31

over modern agriculture.

02:33

Other issues focus on the danger of relying

02:36

on a limited number of high-yield crop strains.

02:38

That's not a problem specific to GMOs, though.

02:41

It's just how agriculture works now.

02:44

Genetic engineering involves inserting a short stretch

02:46

of DNA into the genome of an organism, in this case a plant.

02:51

That DNA will typically encode a couple of genes,

02:53

at least one of which provides a useful function,

02:56

like virus resistance.

02:58

The modified DNA itself isn't dangerous

03:01

since the DNA of anything we eat gets broken up

03:04

in our digestive tract.

03:05

We also digest the proteins that the gene encodes.

03:09

But, just in case, we've tested whether these proteins

03:12

cause allergies before the engineering goes ahead.

03:16

If GMO critics were right, wouldn't we be seeing lots

03:19

of health problems tied to their use?

03:21

Yet GMO crops have now undergone decades

03:23

of testing and use, and no problems have been discovered.

03:27

While a few small studies have suggested a link

03:29

between GMOs and cancers, these studies

03:32

have had glaring flaws: too few animals,

03:35

inconsistent results, and they've been impossible to repeat.

03:39

If the engineered proteins were doing anything

03:41

in our bodies, we'd probably see the effects

03:44

during animal testing.

03:46

Then we'd be seeing it in our cells along

03:48

with all the other plant and animal DNA from our food.

03:51

Absolutely none of these things have been seen.

03:54

While it is possible to make a GMO crop that isn't safe,

03:58

what economic reason would a company have for doing that?

04:01

Sure, there could be risks if people use the crops poorly.

04:06

It's possible that the engineered genes

04:07

could spread to the wild relatives of the crops.

04:10

Insects could develop resistance to some

04:13

of the crops we've engineered.

04:14

But all things considered, these risks can be managed,

04:18

and they're not risks to human health.

04:20

[monster roaring]

04:21

So why are people so afraid of GMOs?

04:23

[woman screaming]

04:24

One thing to consider is that fewer people than ever

04:27

are involved in farming, which means

04:29

that fewer people directly reap the benefits of GMO crops.

04:33

Most of those benefits go to farmers.

04:35

Lots of people don't trust the companies

04:37

that dominate modern agriculture.

04:40

Finally, some people may view genetic engineering

04:43

as playing God and are uncomfortable with it.

04:46

[Narrator On TV] There is in this at least a hint

04:47

of the moral problems posed by modern genetics.

04:51

The leading poets, professors,

04:52

and politicians could furnish genetic material

04:55

for generations of offspring.

04:57

Who is to decide?

04:59

Religious dietary laws are the result

05:01

of a deep-seated desire for food that's pure and natural.

05:06

Some of that's reasonable.

05:07

We all want our food processed under clean conditions.

05:10

But there's nothing natural about any of our crops.

05:13

Remember what the ancestor of corn looks like?

05:16

Given all these issues, it's unlikely the public

05:19

will accept the science any time soon.

05:21

[dramatic music]