Original image
Tanaka S, Sagara H, Kunieda.

Water Bears’ DNA Makes Them Practically Indestructible

Original image
Tanaka S, Sagara H, Kunieda.

Burn it. Freeze it. Chuck it into space. Water bear don’t care. The water bear, also known as the tardigrade or moss piglet, is one of the weirdest and toughest creatures on the planet. Now new research published in the journal Nature Communications suggests we might someday be able to borrow its resilience to use in our own flimsy, floppy bodies.

Tardigrades are extremophiles—that is, they can keep trucking in unbelievably hostile environments, from scorching deserts to the vacuum of space. This astonishing near-indestructibility has, understandably, made them especially appealing to scientists, who have been working for years to pick apart the genetic basis of the microscopic creatures’ badassery. But the more we learn about these creatures, the weirder they seem to get.

In 2015, a group of researchers reported one possible source of the tardigrade’s toughness: burglary. While looking at the genome of the tardigrade species Hypsibius dujardini, the team said they found all kinds of genes that belonged to other organisms, including fungi and bacteria. Horizontal gene transfer (when one organism swipes genes from another) is not unheard of, but H. dujardini appeared to have taken it to the next level, with a full 17 percent of its genes yoinked from other species.

Even for the moss piglet, this seemed kind of, well, extreme. When other scientists tried to replicate the original team’s results, they found only tiny amounts of horizontal gene transfer—about 1 or 2 percent. They said the original team’s samples had likely been contaminated. #tardigate ensued. The tardigrade remained a tiny, scrappy enigma.

Scientists kept at it. The latest research, published today, may have cracked some of the mystery. Researchers in Japan examined the genome of an especially hardy water bear named Ramazzottius varieornatus. In comparing the tardigrade’s genetic codes with those of worms and flies, they found way more genes related to surviving stressful conditions.

In the video below, by researcher Daiki D. Horikawa, you can see R. varieornatus encounter one stressful condition: a lack of water. The tardigrade dries out and shrinks up, seemingly dead. But it isn't. Given a drop of water, it plumps right up, stretches its little legs, and begins to move around.

Then the team took the study to the next level. They found a resilience-boosting protein they called Damage suppressor (Dsup) that appears to be completely unique to tardigrades. Then they inserted Dsup into human cells, which then became more resistant to damage from x-ray radiation.

There’s a lot here to get excited about, says Sujai Kumar, a genome informatician at the University of Edinburgh and a co-author on the #tardigate-triggering study. “The Japanese team's genome sequencing methodology is exemplary,” he tells mental_floss. The depth and breadth of their investigation have yielded a huge quantity of information that will continue to help other researchers unravel the tardigrade mystery.

Even better, Kumar says, were the Japanese researchers’ “really cool” studies in human cells. “Although not quite at the level of a superheroine origin story,” he says, “this is a great example of a gene from an extremotolerant species conferring a 'super power' to a human cell, and is an exciting finding.”

Know of something you think we should cover? Email us at

Original image
iStock // Ekaterina Minaeva
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
Original image
iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

Original image
Nick Briggs/Comic Relief
What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
Original image
Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]