Type 2 diabetes and prion disease seem like an odd couple, but they have something in common: clumps of misfolded, damaging proteins.

Now new research finds that a dose of corrupted pancreas proteins induces normal ones to misfold and clump. This raises the possibility that, like prion disease, type 2 diabetes could be triggered by these deformed proteins spreading between cells or even individuals, the researchers say.

When the deformed pancreas proteins were injected into mice without type 2 diabetes, the animals developed symptoms of the disease, including overly high blood sugar levels, the researchers report online August 1 in the Journal of Experimental Medicine.
“It is interesting, albeit not super-surprising” that the deformed proteins could jump-start the process in other mice, says Bruce Verchere, a diabetes researcher at the University of British Columbia in Vancouver. But “before you could say anything about transmissibility of type 2 diabetes, there’s a lot more that needs to be done.”

Beta cells in the pancreas make the glucose-regulating hormone insulin. The cells also produce a hormone called islet amyloid polypeptide, or IAPP. This protein can clump together and damage cells, although how it first goes bad is not clear. The vast majority of people with type 2 diabetes accumulate deposits of misfolded IAPP in the pancreas, and the clumps are implicated in the death of beta cells.

Deposits of misfolded proteins are a hallmark of such neurodegenerative diseases as Alzheimer’s and Parkinson’s as well as prion disorders like Creutzfeldt-Jakob disease (SN: 10/17/15, p. 12).

Since IAPP misfolds like a prion protein, neurologist Claudio Soto of the University of Texas Health Science Center at Houston and his colleagues wondered if type 2 diabetes could be transmitted between cells, or even between individuals. With this paper, his group “just wanted to put on the table” this possibility.

The mouse version of the IAPP protein cannot clump — and mice don’t develop type 2 diabetes, a sign that the accumulation of IAPP is important in the development of the disease, says Soto. To study the disease in mice, the animals need to be engineered to produce a human version of IAPP. When pancreas cells containing clumps of misfolded IAPP, taken from an engineered diabetic mouse, were mixed in a dish of healthy human pancreas cells, it triggered the clumping of IAPP in the human cells.
The same was true when non-diabetic mice got a shot made with the diabetic mouse pancreas cells. The non-diabetic mice developed deposits of clumped IAPP that grew over time, and the majority of beta cells died. When the mice were alive, more than 70 percent of the animals had blood sugar levels beyond the healthy range.

Soto’s group plans to study if IAPP could be transmitted in a real world scenario, such as through a blood transfusion. They’ve already begun work on transfusing blood from mice with diabetes to healthy mice, to see if they can induce the disease. “More work needs to be done to see if this ever operates in real life,” Soto says.

Even if transmission of the misfolded protein occurs only within an individual, “this opens up a lot of opportunities for intervention,” Soto says, “because now you can target the IAPP.”

Verchere also believes IAPP is “a big player” in the progression of type 2 diabetes, and that therapies that prevent the clumps of proteins from forming are needed. Whether or not future research supports the idea that the disease is transmissible, the study is “good for appreciating the potential role of IAPP in diabetes.”

Cross two flashlight beams and they pass right through one another. That’s because particles of light, or photons, are mostly antisocial — they don’t interact with each other. But now scientists have spotted evidence of photons bouncing off other photons at the Large Hadron Collider at CERN, the European particle physics lab in Geneva.

“This is a very basic process. It’s never been observed before, and here it is finally emerging from the data,” says theoretical physicist John Ellis of King’s College London who was not involved with the study. Researchers with the ATLAS experiment at the LHC report the result August 14 in Nature Physics.
Because photons have no electric charge, they shouldn’t notice one another’s presence. But there’s an exception to that rule. According to quantum mechanics, photons can briefly transform into transient pairs of electrically charged particles and antiparticles — such as an electron and a positron — before reverting back to photons. Predictions made more than 80 years ago suggest that this phenomenon allows photons to interact and ricochet away from one another.

This light-by-light scattering is extremely rare, making it difficult to measure. But photons with more energy interact more often, providing additional chances to spot the scattering. To produce such energetic photons, scientists slammed beams of lead nuclei together in the LHC. Photons flit in and out of existence in the lead nuclei’s strong electromagnetic fields. When two nuclei got close enough that their electromagnetic fields overlapped, two photons could interact with one another and be scattered away.

To measure the interaction, ATLAS scientists sifted through their data to find collisions in which only two photons — the two that scattered away from the collision — appeared in the aftermath. “That’s the trickiest part of the whole thing,” says physicist Peter Steinberg of Brookhaven National Laboratory in Upton, N.Y., a member of the ATLAS collaboration. The scientists had to ensure that, in their enormous, highly sensitive particle detector, only two photons appeared, and convince themselves that no other particles had gone unaccounted for. The researchers found 13 such events over 19 days of data collection. Although other processes can mimic light-by-light scattering, the researchers predict that only a few such events were included in the sample.

The number of scattering events the researchers found agrees with the predictions of the standard model, physicists’ theory of particle physics. But a more precise measurement of the interaction might differ from expectations. If it does, that could hint at the existence of new, undiscovered particles.

A new species of hermit crab discovered in the shallow waters of southern Japan has been enjoying the perks of living like a peanut worm. Like the worms, the 7- to 8-millimeter-long hermit crab uses corals as a covering, researchers report September 20 in PLOS ONE.

Other kinds of hermit crabs live in coral reefs, but typically move in and out of a series of mollusk shells as the crabs grow. Diogenes heteropsammicola is the first hermit crab known to form a mutually beneficial relationship with two species of mobile corals called walking corals. Unlike more familiar coral species, these walking corals don’t grow in colonies and aren’t attached to the seafloor. Instead, each host coral grows with and around a crab, forming a cavity in the coral skeleton that provides a permanent home for the crustacean. In exchange, the crab helps the coral “walk.”
Walking corals are already known to be in a symbiotic relationship with a different sea creature — flexible, marine peanut worms called sipunculids. A symbiotic shift between such distantly related species as the worms and the crab is rare because organisms in a mutualistic relationship tend to be specialized and completely dependent on one other, says study coauthor Momoko Igawa, an ecologist at Kyoto University in Japan.
But similar to the worms, D. heteropsammicola appears to be well-adapted to live in the corals. Its extra slim body can slip inside the corals’ narrow cavity. And unlike other hermit crabs — whose tails curve to the right to fit into spiral shells — D.heteropsammicola’ s tail is symmetrical and can curl either way, just like the corals’ opening.
“Being able to walk around in something that is going to grow larger as you grow larger, that’s a big plus,” says Jan Pechenik, a biologist at Tufts University in Medford, Mass., who was not involved in the study. A typical hermit crab that can’t find a larger shell to move into “really is in trouble.”

D. heteropsammicola’s relationship with walking corals may begin in a similar way as it does with sipunculan worms, Igawa says. A walking coral larva latches onto a tiny mollusk shell containing a juvenile hermit crab and starts to grow. When the hermit crab outgrows the shell, the crustacean moves into the readily available host coral’s crevice, and the shell remains encapsulated in the coral.

By observing the hermit crab in an aquarium, Igawa and coauthor Makoto Kato, also an ecologist at Kyoto University, determined that the crab provides the corals with the same services as the worms: transportation and preventing the corals from being overturned by currents or buried in sediment.

Igawa hopes to search for this new hermit crab in Indonesia, a region where walking corals are normally found. Plus, because walking coral fossils are easy to come by in Japan, she also wants “to reveal the evolutionary history of the symbioses of walking corals [with] sipunculans and hermit crabs by observing these fossils.”

I recently wrote about the power that adults’ words can have on young children. Today, I’m writing about the power of adults’ actions. Parents know, of course, that their children keep a close eye on them. But a new study provides a particularly good example of a watch-and-learn moment: Toddlers who saw an adult struggle before succeeding were more likely to persevere themselves.

Toddlers are “very capable learners,” says study coauthor Julia Leonard, a cognitive developmental psychologist at MIT. Scientists have found that these youngsters pick up on abstract concepts and new words after just a few exposures. But it wasn’t clear whether watching adults’ actions would actually change the way toddlers tackle a problem.

To see whether toddlers could soak up an adult’s persistence, Leonard and her colleagues tested 262 13- to 18-month-olds (the average age was 15 months). Some of the children watched an experimenter try to retrieve a toy stuck inside a container. In some cases, the experimenter quickly got the toy out three times within 30 seconds — easy. Other times, the experimenter struggled for the entire 30 seconds before finally getting the toy out. The experimenter then repeated the process for a different problem, removing a carabiner toy from a keychain. Some kids didn’t see any experimenter demonstration.

Just after watching an adult struggle (or not), the toddlers were given a light-up cube. It had a big, useless button on one side. Another button — small and hidden — actually controlled the lights. The kids knew the toy could light up, but didn’t know how to turn the lights on.

Though the big button did nothing, that didn’t stop the children from poking it. But here’s the interesting part: Compared with toddlers who had just watched an adult succeed effortlessly, or not watched an adult do anything at all, the toddlers who had seen the adult struggle pushed the button more. These kids persisted, even though they never found success.

The sight of an adult persevering nudged the children toward trying harder themselves, the researchers conclude in the Sept. 22 Science. Leonard cautions that it’s hard to pull parenting advice from a single laboratory-based study, but still, “there may be some value in letting children see you work hard to achieve your goals,” she says.

Observing the adults wasn’t the only thing that determined the toddlers’ persistence, not by a long shot. Some kids might simply be more tenacious than others. In the experiments, some of the children who didn’t see an experimenter attempt a task, or who saw an experimenter quickly succeed, were “incredibly gritty,” Leonard says. And some of the kids who watched a persistent adult still gave up quickly themselves. That’s not to mention the fact that these toddlers were occasionally tired, hungry and cranky, all of which can affect whether they give up easily. Despite all of this variation, the copycat effect remained, so that kids were more likely to persist when they had just seen a persistent adult.

As Leonard says, this is just one study and it can’t explain the complex lives of toddlers. Still, one thing is clear, and it’s something that we would all do well to remember: “Infants are watching your behavior attentively and actively learning from what you do,” Leonard says.

WASHINGTON, D.C. — If it takes you a while to recover from a few lost hours of sleep, be grateful you aren’t an orb weaver.

Three orb-weaving spiders — Allocyclosa bifurca, Cyclosa turbinata and Gasteracantha cancriformis — may have the shortest natural circadian rhythms discovered in an animal thus far, researchers reported November 12 at the Society for Neuroscience’s annual meeting.

Most animals have natural body clocks that run closer to the 24-hour day-night cycle, plus or minus a couple hours, and light helps reset the body’s timing each day. But the three orb weavers’ body clocks average at about 17.4, 18.5 and 19 hours respectively. This means the crawlers must shift their cycle of activity and inactivity — the spider equivalent of wake and sleep cycles — by about five hours each day to keep up with the normal solar cycle.
“That’s like flying across more than five time zones, and experiencing that much jet lag each day in order to stay synchronized with the typical day-night cycle,” said Darrell Moore, a neurobiologist at East Tennessee State University in Johnson City.

“Circadian clocks actually keep us from going into chaos,” he added. “Theoretically, [the spiders] should not exist.”

For most animals, internal clocks help them perform recurring daily activities, like eat, sleep and hunt, at the most appropriate time of day. Previous studies have shown that animals that are out of sync with the 24-hour solar cycle are usually less likely to produce healthy offspring than those that aren’t.
Moore and his colleagues were surprised to find the short circadian clocks while studying aggression and passivity in an orb weaver. The team was trying to see if there was a circadian component to these predatory and preylike behaviors, when they discovered C. turbinata’s exceptionally short circadian cycles. “I was looking at this thing thinking, ‘That can’t be right,’” said Moore.

To measure spiders’ natural biological clocks without the resetting effect of the sun, the researchers placed 18 species of spiders in constant darkness and monitored their motion. Three orb weaver species in particular had incredibly short cycles of activity and inactivity.

As far as the researchers know, the short cycle does not seem to be a problem for these spiders. In fact, it might even be useful. Short clocks may help these orb weavers avoid becoming the proverbial “worm” to the earliest birds, the researchers hypothesize. Since the spiders become more active at dusk and begin spinning their webs three to five hours before dawn, they can avoid predators that hunt in the day.

Throughout the day, the spiders remain motionless on their web, prepared to pounce on their next meal. By midday, the spiders’ truncated circadian clocks should have reset, sparking a new round of activity. But in the five to seven hours of daylight left, the orb weavers remain inactive. It’s hard to say whether the spiders are actually resting, Moore said. The researchers suspect that light may delay the onset of another short circadian cycle each day, helping the spiders stay synchronized with the 24-hour environmental cycle.

“The method or molecular mechanism will be really fascinating to figure out,” said Sigrid Veasey, a neuroscientist at the University of Pennsylvania’s Perelman School of Medicine. She is curious to know how the spiders can be so far off from “normal” circadian periods, and still be able to match their activity to the 24-hour light and dark cycle.

Determining the differences between short and normal period clocks in spiders may help researchers find out why and how different circadian clocks are suited to the particular environmental challenges of each species, Moore said.

SAN FRANCISCO — Blowflies don’t sweat, but they have raised cooling by drooling to a high art.

In hot times, sturdy, big-eyed Chrysomya megacephala flies repeatedly release — and then retract — a droplet of saliva, Denis Andrade reported January 4 at the annual meeting of the Society for Integrative and Comparative Biology. This process isn’t sweating. Blowfly droplets put the cooling power of evaporation to use in a different way, said Andrade, who studies ecology and evolution at the Universidade Estadual Paulista in Rio Claro, Brazil.
As saliva hangs on a fly’s mouthparts, the droplet starts to lose some of its heat to the air around it. When the fly droplet has cooled a bit, the fly then slurps it back in, Andrade and colleagues found. Micro-CT scanning showed the retracted droplet in the fly’s throatlike passage near the animal’s brain. The process eased temperatures in the fly’s body by about four degrees Celsius below ambient temps. That may be preventing dangerous overheating, he proposed. The same droplet seemed to be released, cooled, drawn back in and then released again several times in a row.

Andrade had never seen a report of this saliva droplet in-and-out before he and a colleague noticed it while observing blowfly temperatures for other reasons. But in 2012, Chloé Lahondère and a colleague described how Anopheles stephensi mosquitoes that exude a liquid droplet that dangles and cools, but at the other end of the animals.

Mosquitoes, which let their body temperatures float with that of their environment, can get a heat rush when drinking from warm-blooded mammals. While drinking, the insects release a blood-tinged urine droplet, which dissipates some of the heat. There’s some fluid movement within the droplet, says Lahondère, now at Virginia Tech in Blacksburg, but whether any of the liquid gets recaptured by the body the way fly drool is, she can’t say.

Consider everything your smartphone has done for you today. Counted your steps? Deposited a check? Transcribed notes? Navigated you somewhere new?

Smartphones make for such versatile pocket assistants because they’re equipped with a suite of sensors, including some we may never think — or even know — about, sensing, for example, light, humidity, pressure and temperature.

Because smartphones have become essential companions, those sensors probably stayed close by throughout your day: the car cup holder, your desk, the dinner table and nightstand. If you’re like the vast majority of American smartphone users, the phone’s screen may have been black, but the device was probably on the whole time.

“Sensors are finding their ways into every corner of our lives,” says Maryam Mehrnezhad, a computer scientist at Newcastle University in England. That’s a good thing when phones are using their observational dexterity to do our bidding. But the plethora of highly personal information that smartphones are privy to also makes them powerful potential spies.
Online app store Google Play has already discovered apps abusing sensor access. Google recently booted 20 apps from Android phones and its app store because the apps could — without the user’s knowledge — record with the microphone, monitor a phone’s location, take photos, and then extract the data. Stolen photos and sound bites pose obvious privacy invasions. But even seemingly innocuous sensor data can potentially broadcast sensitive information. A smartphone’s movement may reveal what users are typing or disclose their whereabouts. Even barometer readings that subtly shift with increased altitude could give away which floor of a building you’re standing on, suggests Ahmed Al-Haiqi, a security researcher at the National Energy University in Kajang, Malaysia.

These sneaky intrusions may not be happening in real life yet, but concerned researchers in academia and industry are working to head off eventual invasions. Some scientists have designed invasive apps and tested them on volunteers to shine a light on what smartphones can reveal about their owners. Other researchers are building new smartphone security systems to help protect users from myriad real and hypothetical privacy invasions, from stolen PIN codes to stalking.

Message revealed
Motion detectors within smartphones, like the accelerometer and the rotation-sensing gyroscope, could be prime tools for surreptitious data collection. They’re not permission protected — the phone’s user doesn’t have to give a newly installed app permission to access those sensors. So motion detectors are fair game for any app downloaded onto a device, and “lots of vastly different aspects of the environment are imprinted on those signals,” says Mani Srivastava, an engineer at UCLA.

For instance, touching different regions of a screen makes the phone tilt and shift just a tiny bit, but in ways that the phone’s motion sensors pick up, Mehrnezhad and colleagues demonstrated in a study reported online April 2017 in the International Journal of Information Security. These sensors’ data may “look like nonsense” to the human eye, says Al-Haiqi, but sophisticated computer programs can discern patterns in the mess and match segments of motion data to taps on various areas of the screen.

For the most part, these computer programs are machine-learning algorithms, Al-Haiqi says. Researchers train them to recognize keystrokes by feeding the programs a bunch of motion sensor data labeled with the key tap that produces particular movement. A pair of researchers built TouchLogger, an app that collects orientation sensor data and uses the data to deduce taps on smartphones’ number keyboards. In a test on HTC phones, reported in 2011 in San Francisco at the USENIX Workshop on Hot Topics in Security, TouchLogger discerned more than 70 percent of key taps correctly.

Since then, a spate of similar studies have come out, with scientists writing code to infer keystrokes on number and letter keyboards on different kinds of phones. In 2016 in Pervasive and Mobile Computing, Al-Haiqi and colleagues reviewed these studies and concluded that only a snoop’s imagination limits the ways motion data could be translated into key taps. Those keystrokes could divulge everything from the password entered on a banking app to the contents of an e-mail or text message.

Story continues below graphs
A more recent application used a whole fleet of smartphone sensors — including the gyroscope, accelerometer, light sensor and magnetism-measuring magnetometer — to guess PINs. The app analyzed a phone’s movement and how, during typing, the user’s finger blocked the light sensor. When tested on a pool of 50 PIN numbers, the app could discern keystrokes with 99.5 percent accuracy, the researchers reported on the Cryptology ePrint Archive in December.

Other researchers have paired motion data with mic recordings, which can pick up the soft sound of a fingertip tapping a screen. One group designed a malicious app that could masquerade as a simple note-taking tool. When the user tapped on the app’s keyboard, the app covertly recorded both the key input and the simultaneous microphone and gyroscope readings to learn the sound and feel of each keystroke.

The app could even listen in the background when the user entered sensitive info on other apps. When tested on Samsung and HTC phones, the app, presented in the Proceedings of the 2014 ACM Conference on Security and Privacy in Wireless and Mobile Networks, inferred the keystrokes of 100 four-digit PINs with 94 percent accuracy.

Al-Haiqi points out, however, that success rates are mostly from tests of keystroke-deciphering techniques in controlled settings — assuming that users hold their phones a certain way or sit down while typing. How these info-extracting programs fare in a wider range of circumstances remains to be seen. But the answer to whether motion and other sensors would open the door for new privacy invasions is “an obvious yes,” he says.

Tagalong
Motion sensors can also help map a person’s travels, like a subway or bus ride. A trip produces an undercurrent of motion data that’s discernible from shorter-lived, jerkier movements like a phone being pulled from a pocket. Researchers designed an app, described in 2017 in IEEE Transactions on Information Forensics and Security, to extract the data signatures of various subway routes from accelerometer readings.

In experiments with Samsung smartphones on the subway in Nanjing, China, this tracking app picked out which segments of the subway system a user was riding with at least 59, 81 and 88 percent accuracy — improving as the stretches expanded from three to five to seven stations long. Someone who can trace a user’s subway movements might figure out where the traveler lives and works, what shops or bars the person frequents, a daily schedule, or even — if the app is tracking multiple people — who the user meets at various places.
Accelerometer data can also plot driving routes, as described at the 2012 IEEE International Conference on Communication Systems and Networks in Bangalore, India. Other sensors can be used to track people in more confined spaces: One team synced a smartphone mic and portable speaker to create an on-the-fly sonar system to map movements throughout a house. The team reported the work in the September 2017 Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.

“Fortunately there is not anything like [these sensor spying techniques] in real life that we’ve seen yet,” says Selcuk Uluagac, an electrical and computer engineer at Florida International University in Miami. “But this doesn’t mean there isn’t a clear danger out there that we should be protecting ourselves against.”

That’s because the kinds of algorithms that researchers have employed to comb sensor data are getting more advanced and user-friendly all the time, Mehrnezhad says. It’s not just people with Ph.D.s who can design the kinds of privacy invasions that researchers are trying to raise awareness about. Even app developers who don’t understand the inner workings of machine-learning algorithms can easily get this kind of code online to build sensor-sniffing programs.

What’s more, smartphone sensors don’t just provide snooping opportunities for individual cybercrooks who peddle info-stealing software. Legitimate apps often harvest info, such as search engine and app download history, to sell to advertising companies and other third parties. Those third parties could use the information to learn about aspects of a user’s life that the person doesn’t necessarily want to share.

Take a health insurance company. “You may not like them to know if you are a lazy person or you are an active person,” Mehrnezhad says. “Through these motion sensors, which are reporting the amount of activity you’re doing every day, they could easily identify what type of user you are.”

Sensor safeguards
Since it’s only getting easier for an untrusted third party to make private inferences from sensor data, researchers are devising ways to give people more control over what information apps can siphon off of their devices. Some safeguards could appear as standalone apps, whereas others are tools that could be built into future operating system updates.

Uluagac and colleagues proposed a system called 6thSense, which monitors a phone’s sensor activity and alerts its owner to unusual behavior, in Vancouver at the August 2017 USENIX Security Symposium. The user trains this system to recognize the phone’s normal sensor behavior during everyday tasks like calling, Web browsing and driving. Then, 6thSense continually checks the phone’s sensor activity against these learned behaviors.

If someday the program spots something unusual — like the motion sensors reaping data when a user is just sitting and texting — 6thSense alerts the user. Then the user can check if a recently downloaded app is responsible for this suspicious activity and delete the app from the phone.

Uluagac’s team recently tested a prototype of the system: Fifty users trained Samsung smartphones with 6thSense to recognize their typical sensor activity. When the researchers fed the 6thSense system examples of benign data from daily activities mixed in with segments of malicious sensor operations, 6thSense picked out the problematic bits with over 96 percent accuracy.
For people who want more active control over their data, Supriyo Chakraborty, a privacy and security researcher at IBM in Yorktown Heights, N.Y., and colleagues devised DEEProtect, a system that blunts apps’ abilities to draw conclusions about certain user activity from sensor data. People could use DEEProtect, described in a paper posted online at arXiv.org in February 2017, to specify preferences about what apps should be allowed to do with sensor data. For example, someone may want an app to transcribe speech but not identify the speaker.

DEEProtect intercepts whatever raw sensor data an app tries to access and strips that data down to only the features needed to make user-approved inferences. For speech-to-text translation, the phone typically needs sound frequencies and the probabilities of particular words following each other in a sentence.

But sound frequencies could also help a spying app deduce a speaker’s identity. So DEEProtect distorts the dataset before releasing it to the app, leaving information on word orders alone, since that has little or no bearing on speaker identity. Users can control how much DEEProtect changes the data; more distortion begets more privacy but also degrades app functions.

In another approach, Giuseppe Petracca, a computer scientist and engineer at Penn State, and colleagues are trying to protect users from accidentally granting sensor access to deceitful apps, with a security system called AWare.

Apps have to get user permission upon first installation or first use to access certain sensors like the mic and camera. But people can be cavalier about granting those blanket authorizations, Uluagac says. “People blindly give permission to say, ‘Hey, you can use the camera, you can use the microphone.’ But they don’t really know how the apps are using these sensors.”

Instead of asking permission when a new app is installed, AWare would request user permission for an app to access a certain sensor the first time a user provided a certain input, like pressing a camera button. On top of that, the AWare system memorizes the state of the phone when the user grants that initial permission — the exact appearance of the screen, sensors requested and other information. That way, AWare can tell users if the app later attempts to trick them into granting unintended permissions.

For instance, Petracca and colleagues imagine a crafty data-stealing app that asks for camera access when the user first pushes a camera button, but then also tries to access the mic when the user later pushes that same button. The AWare system, also presented at the 2017 USENIX Security Symposium, would realize the mic access wasn’t part of the initial deal, and would ask the user again if he or she would like to grant this additional permission.

Petracca and colleagues found that people using Nexus smartphones equipped with AWare avoided unwanted authorizations about 93 percent of the time, compared with 9 percent among people using smartphones with typical first-use or install-time permission policies.

The price of privacy
The Android security team at Google is also trying to mitigate the privacy risks posed by app sensor data collection. Android security engineer Rene Mayrhofer and colleagues are keeping tabs on the latest security studies coming out of academia, Mayrhofer says.

But just because someone has built and successfully tested a prototype of a new smartphone security system doesn’t mean it will show up in future operating system updates. Android hasn’t incorporated proposed sensor safeguards because the security team is still looking for a protocol that strikes the right balance between restricting access for nefarious apps and not stunting the functions of trustworthy programs, Mayrhofer explains.

“The whole [app] ecosystem is so big, and there are so many different apps out there that have a totally legitimate purpose,” he adds. Any kind of new security system that curbs apps’ sensor access presents “a real risk of breaking” legitimate apps.

Tech companies may also be reluctant to adopt additional security measures because these extra protections can come at the cost of user friendliness, like AWare’s additional permissions pop-ups. There’s an inherent trade-off between security and convenience, UCLA’s Srivastava says. “You’re never going to have this magical sensor shield [that] gives you this perfect balance of privacy and utility.”

But as sensors get more pervasive and powerful, and algorithms for analyzing the data become more astute, even smartphone vendors may eventually concede that the current sensor protections aren’t cutting it. “It’s like cat and mouse,” Al-Haiqi says. “Attacks will improve, solutions will improve. Attacks will improve, solutions will improve.”

The game will continue, Chakraborty agrees. “I don’t think we’ll get to a place where we can declare a winner and go home.”

People tend to think of memories as deeply personal, ephemeral possessions — snippets of emotions, words, colors and smells stitched into our unique neural tapestries as life goes on. But a strange series of experiments conducted decades ago offered a different, more tangible perspective. The mind-bending results have gained unexpected support from recent studies.

In 1959, James Vernon McConnell, a psychologist at the University of Michigan in Ann Arbor, painstakingly trained small flatworms called planarians to associate a shock with a light. The worms remembered this lesson, later contracting their bodies in response to the light.
One weird and wonderful thing about planarians is that they can regenerate their bodies — including their brains. When the trained flatworms were cut in half, they regrew either a head or a tail, depending on which piece had been lost. Not surprisingly, worms that kept their heads and regrew tails retained the memory of the shock, McConnell found. Astonishingly, so did the worms that grew replacement heads and brains. Somehow, these fully operational, complex arrangements of brand-spanking-new nerve cells had acquired the memory of the painful shock, McConnell reported.

In subsequent experiments, McConnell went even further, attempting to transfer memory from one worm to another. He tried grafting the head of a trained worm onto the tail of an untrained worm, but he couldn’t get the head to stick. He injected trained planarian slurry into untrained worms, but the recipients often exploded. Finally, he ground up bits of the trained planarians and fed them to untrained worms. Sure enough, after their meal, the untrained worms seemed to have traces of the memory — the cannibals recoiled at the light.

The implications were bizarre, and potentially profound: Lurking in that pungent planarian puree must be a substance that allowed animals to literally eat one another’s memories.

These outlandish experiments aimed to answer a question that had been needling scientists for decades: What is the physical basis of memory? Somehow, memories get etched into cells, forming a physical trace that researchers call an “engram.” But the nature of these stable, specific imprints is a mystery.
Today, McConnell’s memory transfer episode has largely faded from scientific conversation. But developmental biologist Michael Levin of Tufts University in Medford, Mass., and a handful of other researchers wonder if McConnell was onto something. They have begun revisiting those historical experiments in the ongoing hunt for the engram.

Applying powerful tools to the engram search, scientists are already challenging some widely held ideas about how memories are stored in the brain. New insights haven’t yet revealed the identity of the physical basis of memory, though. Scientists are chasing a wide range of possibilities. Some ideas are backed by strong evidence; others are still just hunches. In pursuit of the engram, some researchers have even searched for clues in memories that persist in brains that go through massive reorganization.
Synapse skeptics
One of today’s most entrenched explanations puts engrams squarely within the synapses, connections where chemical and electrical messages move between nerve cells, or neurons. These contact points are strengthened when bulges called synaptic boutons grow at the ends of message-sending axons and when hairlike protrusions called spines decorate message-receiving dendrites.

In the 1970s, researchers described evidence that as an animal learned something, these neural connections bulked up, forming more contact points of synaptic boutons and dendritic spines. With stronger connection points, cells could fire in tandem when the memory needed to be recalled. Stronger connections mean stronger memory, as the theory goes.

This process of bulking up, called long-term potentiation, or LTP, was thought to offer an excellent explanation for the physical basis of memory, says David Glanzman, a neuroscientist at UCLA who has studied learning and memory since 1980. “Until a few years ago, I implicitly accepted this model for memory,” he says. “I don’t anymore.”

Glanzman has good reason to be skeptical. In his lab, he studies the sea slug Aplysia, an organism that he first encountered as a postdoctoral student in the Columbia University lab of Nobel Prize–winning neuroscientist Eric Kandel. When shocked in the tail, these slugs protectively withdraw their siphon and gill. After multiple shocks, the animals become sensitized and withdraw faster. (The distinction between learning and remembering is hazy, so researchers often treat the two as similar actions.)

After neurons in the sea slugs had formed the memory of the shock, the researchers saw stronger synapses between the nerve cells that sense the shock and the ones that command the siphon and gill to move. When the memory was made, the synapse sprouted more message-sending bumps, Glanzman’s team reported in eLife in 2014. And when the memory was weakened with a drug that prevents new proteins from being made, some of these bumps disappeared. “That made perfect sense,” Glanzman says. “We expected the synaptic growth to revert and go back to the original, nonlearned state. And it did.”

But the answer to the next logical question was a curve ball. If the memory was stored in bulked-up synapses, as researchers thought, then the new contact points that appear when a memory is formed should be the same ones that vanish when the memory is subsequently lost, Glanzman reasoned. That’s not what happened — not even close. “We found that it was totally random,” Glanzman says. “Completely random.”
Research from Susumu Tonegawa, a Nobel Prize–winning neuroscientist at MIT, turned up a result in mice that was just as startling. His project relies on sophisticated tools, including optogenetics. With this technique, the scientists activated specific memory-storing neurons with light. The researchers call those memory-storing cells “engram cells.”

In a parallel to the sea slug experiment, Tonegawa’s team conditioned mice to fear a particular cage and genetically marked the cells that somehow store that fear memory. After the mice learned the association, the researchers saw more dendritic spines in the neurons that store the memory — evidence of stronger synapses.

When the researchers caused amnesia with a drug, that newly formed synaptic muscle went away. “We wiped out the LTP, completely wiped it out,” says neuroscientist Tomás Ryan, who conducted the study in Tonegawa’s lab and reported the results with Tonegawa and colleagues in 2015 in Science.

And yet the memory wasn’t lost. With laser light, the researchers could still activate the engram cells — and the memory they somehow still held. That means that the memory was stored in something that isn’t related to the strength of the synapses.

The surprising results suggest that researchers may have been sidetracked, focusing too hard on synaptic strength as a memory storage system, says Ryan, now at Trinity College Dublin. “That approach has produced about 12,000 or so papers on the topic, but it hasn’t been very successful in explaining how memory works.”

Silent memories
The finding that memory storage and synaptic strength aren’t always tied together raises an important distinction that may help untangle the research. The cellular machines that are required for calling up memories are not necessarily the same machines that store memories. The search for what stores memories may have been muddled with results on how cells naturally call up memories.

Ryan, Tonegawa and Glanzman all think that LTP, with its bulked-up synapses, is important for retrieving memories, but not the thing that actually stores them. It’s quite possible to have stored memories that aren’t readily accessible, what Glanzman calls “occult memories” and Tonegawa refers to as “silent engrams.” Both think the concept applies more broadly than in just the sea slugs and mice they study.

Glanzman explains the situation by considering a talented violin player. “If you cut off my hands, I’m not able to play the violin,” he says. “But it doesn’t mean that I don’t know how to play the violin.” The analogy is overly simple, he says, “but that’s how I think of synapses. They enable the memory to be expressed, but they are not where the memory is.”

In a paper published last October in Proceedings of the National Academy of Sciences, Tonegawa and colleagues created silent engrams of a cage in which mice received a shock. The mice didn’t seem to remember the room paired with the shock, suggesting that the memory was silent. But the memory could be called up after a genetic tweak beefed up synaptic connections by boosting the number of synaptic spines specifically among the neurons that stored the memory.

Story continues below diagram
Those results add weight to the idea that synaptic strength is crucial for memory recall, but not storage, and they also hint that, somehow, the brain stores many inaccessible memory traces. Tonegawa suspects that these silent engrams are quite common.

Finding and reactivating silent engrams “tells us quite a bit about how memory works,” Tonegawa says. “Memory is not always active for you. You learn it, you store it,” but depending on the context, it might slip quietly into the brain and remain silent, he says. Consider an old memory from high school that suddenly pops up. “Something triggered you to recall — something very specific — and that probably involves the conversion of a silent engram to an active engram,” Tonegawa says.

But engrams, silent or active, must still be holding memory information somehow. Tonegawa thinks that this information is stored not in synapses’ strength, but in synapses’ very existence. When a specific memory is formed, new connections are quickly forged, creating anatomical bridges between constellations of cells, he suspects. “That defines the content of memory,” he says. “That is the substrate.”

These newly formed synapses can then be beefed up, leading to the memory burbling up as an active engram, or pared down and weakened, leading to a silent engram. Tonegawa says this idea requires less energy than the LTP model, which holds that memory storage requires constantly revved up synapses full of numerous contact points. Synapse existence, he argues, can hold memory in a latent, low-maintenance state.
“The brain doesn’t even have to recognize that it’s a memory,” says Ryan, who shares this view. Stored in the anatomy of arrays of neurons, memory is “in the shape of the brain itself,” he says.
A temporary vessel
Tonegawa is confident that the very existence of physical links between neurons stores memories. But other researchers have their own notions.

Back in the 1950s, McConnell suspected that RNA, cellular material that can help carry out genetic instructions but can also carry information itself, might somehow store memories.

This unorthodox idea, that RNA is involved in memory storage, has at least one modern-day supporter in Glanzman, who plans to present preliminary data at a meeting in April that suggest injections of RNA can transfer memory between sea slugs.

Glanzman thinks that RNA is a temporary storage vessel for memories, though. The real engram, he suggests, is the folding pattern of DNA in cells’ nuclei. Changes to how tightly DNA is packed can govern how genes are deployed. Those changes, part of what’s known as the epigenetic code, can be made — and even transferred — by roving RNA molecules, Glanzman argues. He is quick to point out that his idea, memory transfer by RNA, is radical. “I don’t think you could find another card-carrying Ph.D. neuroscientist who believes that.”

Other researchers, including neurobiologist David Sweatt of Vanderbilt University in Nashville, also suspect that long-lasting epigenetic changes to DNA hold memories, an idea Sweatt has been pursuing for 20 years. Because epigenetic changes can be stable, “they possess the unique attribute necessary to contribute to the engram,” he says.

And still more engram ideas abound. Some results suggest that a protein called PKM-zeta, which helps keep synapses strong, preserves memories. Other evidence suggests a role for structures called perineuronal nets, rigid sheaths that wrap around neurons. Holes in these nets allow synapses to peek through, solidifying memories, the reasoning goes (SN: 11/14/15, p. 8). A different line of research focuses on proteins that incite others to misfold and aggregate around synapses, strengthening memories. Levin, at Tufts, has his own take. He thinks that bioelectrical signals, detected by voltage-sensing proteins on the outside of cells, can store memories, though he has no evidence yet.

Beyond the brain
Levin’s work on planarians, reminiscent of McConnell’s cannibal research, may even prod memory researchers to think beyond the brain. Planarians can remember the texture of their terrain, even using a new brain, Levin and Tal Shomrat, now at the Ruppin Academic Center in Mikhmoret, Israel, reported in 2013 in the Journal of Experimental Biology. The fact that memory somehow survived decapitation hints that signals outside of the brain may somehow store memories, even if temporarily.

Memory clues may also come from other animals that undergo extreme brain modification over their lifetimes. As caterpillars transition to moths, their brains change dramatically. But a moth that had learned as a caterpillar to avoid a certain odor paired with a shock holds onto that information, despite having a radically different brain, researchers have found.

Story continues below box
Similar results come from mammals, such as the Arctic ground squirrel, which massively prunes its synaptic connections to save energy during torpor in the winter. Within hours of the squirrel waking up, the pruned synaptic connections grow back. Remarkably, some old memories seem to survive the experience. The squirrels have been shown to remember familiar squirrels, as well as how to perform motor feats such as jumping between boxes and crawling through tubes. Even human babies retain taste and sound memories from their time in the womb, despite a very changed brain.

These extreme cases of memory persistence raise lots of basic questions about the nature of the engram, including whether memories must always be stored in the brain. But it’s important that the engram search isn’t restricted to the most advanced forms of humanlike memory, Levin says. “Memory starts, evolutionarily, very early on,” he says. “Single-celled organisms, bacteria, slime molds, fish, these things all have memory.… They have the ability to alter their future behavior based on what’s happened before.”

The diversity of ideas — and of experimental approaches — highlights just how unsettled the engram question remains. After decades of work, the field is still young. Even if the physical identity of the engram is eventually discovered and universally agreed on, a bigger question still looms, Levin says.

“The whole point of memory is that you should be able to look at the engram and immediately know what it means,” he says. Somehow, the physical message of a memory, in whatever form it ultimately takes, must be translated into the experience of a memory by the brain. But no one has a clue how this occurs.

At a 2016 workshop, a small group of researchers gathered to discuss engram ideas that move beyond synapse strength. “All the rebels came together,” Glanzman says. The two-day debate didn’t settle anything, but it was “very valuable,” says Ryan, who also attended. He coauthored a summary of the discussion that appeared in the May 2017 Annals of the New York Academy of Sciences. “Because the mind is part of the natural world, there is no reason to believe that it will be any less tangible and ultimately comprehensible than other components,” Ryan and coauthors optimistically wrote.

For now, the field hasn’t been able to explain memories in tangible terms. But research is moving forward, in part because of its deep implications. The hunt for memories gets at the very nature of identity, Levin says. “What does it mean to be a coherent individual that has a coherent bundle of memories?” The elusive identity of the engram may prove key to answering that question.