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Painting Frogs, Licking Wounds & Other Adventures with Poisonous Animals

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Wikimedia Commons

In the current issue of the magazine, I’ve got an article called “Fifty Shades of Prey,” about poison dart frogs and some new research into why they come in so many dazzling colors and patterns. 

I was drawn to the story not only because of what Canadian biologist Mathieu Choteau discovered about these frogs (which is pretty cool all by itself), but also by all the stuff he went through along the way. His research involved hand-molding and painting several thousand fake frogs with the help of his girlfriend, getting them on a plane to Peru (worried what airport security might say when they opened his bag), and then painstakingly pinning them to leaves while trudging through the rainforest. 

Going back even further into what we know about dart frogs and other poisonous animals, there are plenty of other intrepid scientists and strange sounding field work. I couldn’t fit all of their stories into the magazine piece, so I wanted to share a little bit about two of them here. 

The first is a guy named John W. Daly. In the early 1960s, not long after he took a job at the National Institutes of Health, he was sent on a research errand by the head of his lab. Certain native tribesmen in Colombia were known to coat the tips of their hunting arrows and blowgun darts with skin secretions from local frogs, which gave the weapons a toxic punch. The senior scientist wanted someone to go down to the rainforest, harvest some frogs, and analyze the chemicals in their skin. He’d been unable to find someone in the lab, though, who 1) had experience in the field and could handle a trip to the rainforest, and 2) he could afford to commit to research that might not pan out. 

Daly fit the bill perfectly. He was a chemist by training, but always had an interest in biology. He’d grown up in Oregon collecting frogs, snakes, and lizards and keeping them in his own little zoo in the basement. He was also young and a new hire, so they could get away with paying less for the field work than the other scientists. 

Daly was soon in the Amazon collecting frogs for a $16 per diem. Without many resources to work with, he developed an unusual way to figure out which frogs were worth examining and which weren’t. He’d slide a finger along a frog's skin, and then touch his tongue. If he experienced a burning sensation in his mouth, then the frog was worth a look. Fortunately, Daly took the locals’ advice about one particular frog. Even experienced tribal hunters only handled Phyllobates terribilis with the utmost care—it’s the most poisonous of the dart frogs and may be the most poisonous vertebrate in the world. 

Daly’s time tasting frogs in the rainforest eventually led to the discovery of the batrachotoxins (“frog poison”), the class of alkaloid poisons that make some of these frogs so deadly. In the early 1970s, Daly and colleagues published the chemical structure of the toxin and detailed its biological effects. 

Almost 20 years later and thousands of miles away, John Dumbacher, a grad student at the University of Chicago, was studying the courtship and mating behaviors of the Raggiana Bird-of-paradise in Papua New Guinea. He and his research team stretched nets between trees to capture the birds for study, and sometimes caught other birds by accident. Some of these were songbirds known as Hooded Pitohuis

As Dumbacher tried to free these birds, they’d bite or scratch at his hands and sometimes he would get cut. Rather than stopping his work and finding a place to wash his wounds, he would usually just pop the injured finger in his mouth to give the cut a quick clean. Just a few minutes later, though, his tongue and lips would start to tingle and burn a little. The sensation wasn’t awful—Dumbacher has compared it to eating a chili pepper or touching your tongue to a 9-volt battery—but it was puzzling, and after another student experienced the same thing, Dumbacher began to wonder if it was the bird’s fault. 

The next time a pitohui got caught in one of the nets, Dumbacher and the other student tasted one of the feathers. Sure enough, their mouths started to tingle and burn. They asked a few of the team’s forest guides about it and learned that the locals called the pitohuis “rubbish birds” or “garbage birds” and wouldn’t eat them, unless they were skinned and specially prepared for safety and flavor. The birds, Dumbacher realized, might be poisonous. 

While poisonous birds were sometimes rumored to exist, none had ever been scientifically confirmed, and the idea wasn’t always considered legitimate. Dumbacher wanted some pitohui feathers analyzed for toxins, but couldn’t find a chemist who would take his hypothesis seriously. Dumbacher returned to the U.S. with a bunch of feathers in 1990. Knowing about Daly’s experience with poisonous vertebrates, he called the NIH, a little bit worried that Daly would laugh him off as “just a nutty kid.” 

Daly was curious, though, and took the feathers and began to run some tests. When he took extracts from the feather and injected them into a mouse, it began to convulse and quickly died. He called Dumbacher back looking for more samples from the birds—the young man seemed to be onto something. 

Daly eventually isolated what he believed to be the toxic compound and had a colleague run a chemical analysis on it. When the colleague called him with the compound’s analysis, Daly recognized the characteristics and patterns immediately. It was the same chemical he’d found, identified, described, and named decades earlier. Batrachotoxin, the “frog poison,” had turned up in a bird.

Daly, Dumbacher, and their colleagues announced their discovery two years later in a paper in Science, and the hooded pitohui became the first confirmed poisonous bird. A decade later, the blue-capped ifrita became the second

What was frog poison doing in two different types of birds? How could the frogs and birds, separated by vast oceans and so many twists and turns of evolutionary history, produce the same toxin—not a similar toxin, but the exact same one?

More than a decade of work by Dumbacher, Daly and other researchers suggests that these odd, toxic bedfellows get their toxins from their diets. In Papua New Guinea, Dumbacher heard reports from locals of a few types of beetle that caused tingling and burning sensations on contact. He found those same beetles in the stomachs of the pitohuis and later found that they contained high concentrations of batrachotoxin. In a 2004 paper, he suggested that the bugs provided a natural toxin source for the birds, and that other bugs might do the same for poison dart frogs. 

Daly had touched on the same idea before, noticing that a change in the frogs’ diet altered their toxic profile. Around the same time as Dumbacher’s study, Daly and colleagues from the NIH and elsewhere found evidence that ants and “moss mites” in Central America contained some of the same alkaloids as the frogs and made up a large portion of their diet. This second study supporting the toxic diet idea was one of the last papers Daly published before his death in 2008. 

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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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!

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Why Your iPhone Doesn't Always Show You the 'Decline Call' Button
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iStock

When you get an incoming call to your iPhone, the options that light up your screen aren't always the same. Sometimes you have the option to decline a call, and sometimes you only see a slider that allows you to answer, without an option to send the caller straight to voicemail. Why the difference?

A while back, Business Insider tracked down the answer to this conundrum of modern communication, and the answer turns out to be fairly simple.

If you get a call while your phone is locked, you’ll see the "slide to answer" button. In order to decline the call, you have to double-tap the power button on the top of the phone.

If your phone is unlocked, however, the screen that appears during an incoming call is different. You’ll see the two buttons, "accept" or "decline."

Either way, you get the options to set a reminder to call that person back or to immediately send them a text message. ("Dad, stop calling me at work, it’s 9 a.m.!")

[h/t Business Insider]

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