MIT Research News' Journal
[Most Recent Entries]
[Calendar View]
Wednesday, July 6th, 2016
| Time |
Event |
| 12:00a |
Is your meal really gluten free? For people with celiac disease or gluten intolerances, dining out can be stressful. Even trace amounts of the protein — found in wheat, barley, and rye — in a whole plate of food can cause adverse reactions.
Now MIT spinout Nima — co-founded by CEO Shireen Yates MBA ’13 and Chief Product Officer Scott Sundvor ’12 — has developed a portable, highly sensitive gluten sensor that lets diners know if their food is, indeed, safe to eat.
According to the National Institutes of Health, celiac disease, an autoimmune disorder that leads to intestinal damage when gluten is eaten, affects around 1 percent of the U.S. population, or roughly 3 million people. According to the National Foundation for Celiac Awareness, millions more may suffer from nonceliac gluten intolerances.
Nima’s sensor, also called Nima, is a 3-inch-tall triangular device with disposable capsules. Diners put a sample of food — about the size of a pea — or liquid into the capsule, screw on the top, and insert the capsule into the device, which mixes the food into a solution that detects gluten. In two to three minutes, a digital display appears on the sensor, indicating if the food sample does or doesn’t contain gluten.
Every time someone runs a test, the result is automatically sent to an app Nima has developed. The diner can enter information about where and what they ate, and whether the food contained gluten. Any Nima user can log in to see the results.
The aim is to create “a peace of mind at mealtime,” Sundvor says. By amassing data on food, he adds, the startup hopes to provide people with better information about what they eat. “Right now, we don’t know what’s in our food, whether it is allergens, pesticides, or other harmful chemicals,” he says. “There’s not a good way to get that data. We want to give people the ability to understand their food better and how it affects their health.”
Sensitive sensor
Nima can sense gluten at 20 parts per million (ppm) or more, the maximum concentration for “gluten-free” foods as determined by the U.S. Food and Drug Administration.
Nima’s high sensitivity comes from the immunoassay inside the sensor, developed primarily by MIT chemical engineering alumnus Jingqing Zhang SM ’12, PhD ’13, who is now the lead scientist at Nima. The immunoassay contains custom antibodies that are highly sensitive to gluten molecules. When gluten is present, the antibody bonds to the gluten molecules, causing a color change in the immunoassay, which is captured by an optical reader. If any gluten is detected, the sensor will display an icon with a “gluten found” message. If the sample has less than 20 ppm of gluten, the sensor will display a smiley face.
Nima can detect gluten in foods that are labeled as “gluten-free” but may have picked up microscopic amounts of the protein during the production or cooking process. A steak may have been fried on the same grill as gluten-based foods, for example, or a salad dressing may contain trace amounts of wheat flour. The device can even detect if someone touched a piece of bread that contained gluten, before handling the food in question. “It’s the equivalent to finding a breadcrumb in an entire plate of food,” Sundvor says.
Moreover, Sundvor says, the device seamlessly integrates that chemistry with electronics and mechanics. “We’ve created this grinding, mixing, and extracting system, and together it works really well,” he says.
Filling the consumer gap
Nima was founded in 2013 as GlutenTech, when Yates, then an MIT Sloan School of Management student, dreamt up an idea for a portable gluten sensor. Seeking an engineer to bring the device to life, she met Sundvor, a recent MIT graduate who had studied mechanical engineering and product design.
Together, they set up shop at the now-defunct MIT Beehive, a startup incubator on MIT’s campus, with aims of filling “a huge consumer gap” in food-allergen testing, Sundvor says. Conventional at-home tests, he says, require equipment such as test tubes, pipettes, a mortar and pestle, and microscale. “You can’t bring test tubes to a restaurant,” he says.
Sundvor began working long hours in an MIT machine shop building a prototype, while Yates brought the idea around to her MIT Sloan classes. Of note was a particular pricing class, where students sketched out pricing and demand models for the product. “The result of that was that I found there’s a real opportunity here: There’s a need and a willingness to pay,” Yates says.
In spring 2013, GlutenTech entered the MIT $100K Entrepreneurship Competition with a proof-of-concept model, and they earned the Audience Choice Award in the Accelerate contest. That summer, the team entered the Global Founders Skills Accelerator (GFSA), a 12-week startup program held at the Martin Trust Center for MIT Entrepreneurship.
Participating in the $100K forced the team develop a business plan they could pitch to investors, Yates says. “It was a testing period to see, if we position ourselves in a certain way, will it resonate with investors?” she says.
“The GFSA was incredible,” Sundvor adds, “It gave us the opportunity to have a safe space to go full-out on this for three months, have mentors, and have just enough money to squeak by.”
By the time the GFSA Demo Day rolled around in September, GlutenTech had its first working prototypes — “which were so ugly,” Sundvor says, laughing.
The 9-inch-long aluminum tubes “looked like lightsaber handles,” Sundvor says. Inside the tubes were chemicals used in conventional food tests, and the system took about 10 minutes to detect gluten. When it did, a bright light flashed and a loud alarm went off. “We got many looks at restaurants,” Sundvor says. “But they worked and got us our first investors.”
Three years ago, GlutenTech moved headquarters from Boston to San Francisco, and changed its name to 6SensorLabs. This year, they renamed the startup as Nima. In three years, the startup has gained more than $14 million in capital venture funding.
New opportunities
Consumers are the startup’s first market. But as more individuals start using Nima, restaurants will have more data on their food to better serve patrons, Sundvor says. A couple of restaurants in San Francisco, in fact, are working with Nima on validating their gluten-free menu items.
Next year, Nima plans to release two new sensors, one for peanuts and one for dairy, which is “surprisingly sneaky,” Sundvor says. Bread at a restaurant, for instance, could have been fried in a pan with remnants of butter. “A lot of people are getting sick from dairy allergies, so that will be a big market,” Sundvor says. | | 12:00a |
New technique provides detailed views of metals’ crystal structure Researchers at MIT and elsewhere have developed a new combination of methods that can provide detailed information about the microstructure of polycrystalline metals.
Such materials — composed of a random matrix of multiple small crystals rather than one single large crystal — are widely used for such applications as nuclear reactors, civil infrastructure, and aircraft. However understanding the details of their crystal structure and the boundaries between the crystal areas has been difficult.
The new findings are published in the journal Nature Computational Materials, in a paper by Matteo Seita, an MIT postdoc; Michael Demkowicz, a professor of materials science and engineering; Christopher Schuh, the Danae and Vasilis Salapatas Professor of Metallurgy, and five others.
“This is a unique combination of different technologies,” Seita explains. The new approach he and the team developed addresses “one of the most common problems in materials science: How do we quantify the characteristics of materials in a high-throughput fashion?”
Some techniques offer a great deal of detail about structures, but they take time to carry out and can’t reveal rapid changes within the material. Others work rapidly but provide much less structural detail, and still other methods provide both spatial and temporal detail but are prohibitively expensive or only available in limited places. The new combination of techniques, Seita says, can help resolve these limitations by providing fast, high-resolution, and low-cost imaging of the materials.
In polycrystalline metals, which are composed of many small crystal grains, it is important to know the location, dimensions, angles of contact, and other characteristics of the different grains making up the material. In particular, the interfaces between the crystal grains, called grain boundaries, “happen to be critical,” Seita says, “to many individual properties of the material — its strength, radiation tolerance, hardness, electrical resistance, and so on — but they are very difficult to characterize experimentally, because they are very complex.”
There are five basic characteristics about these grain boundaries that researchers would like to be able to quantify, but most tools for studying the materials can only yield some subset of two or three of those. One method for getting all five characteristics at once is high-energy synchrotron radiation, which is only available in a few facilities that are expensive and tend to be oversubscribed.
“Our solution was to try to create a very simple technology that can be used by anyone, in their own lab, using software and hardware that are easily available,” Seita says. And that’s what they achieved, using a combination of two existing methods — optical microscopy and electron microscopy.
“We take two different datasets and combine them using our numerical image analysis,” he explains. To do so, they used sheets of polycrystalline metal foil, which were thin enough that single grains could be seen from both sides. They then took optical microscope images of the foil from one side, flipped the sheet over, and imaged the other side, and used software to connect the grain boundaries from one side to the other. From that, he says, “We can reconstruct the 3-D orientation of these grain boundaries.”
Then, that information is combined with electron microscope images that describe the actual pattern of atoms within the grains, showing the orientation of the individual crystal lattices within each grain — and how they relate to those of adjacent grains. The combined information provides all five characteristics of the grain boundaries in the metal foils.
“The beauty of this is that it’s high-throughput technology,” Seita says. “On one sample, we can measure up to 500 grain boundaries or so, and can build up datasets rapidly. And it’s nondestructive,” unlike existing methods that consume the sample in the process. That means the sample can then be subjected to other tests, for example tests of mechanical or electrical properties, whose results can be compared with the data about the grain boundaries.
The new methodology, Seita says, “is very versatile, so many groups out there can use it.” What’s more, though the initial tests were done with polycrystalline metals, the technique “is materials agnostic,” and could be applied to insulators or semiconductors as well as metals. “We can test for different kinds of properties and build up large datasets,” he says, and ultimately use that data to predict the characteristics of new polycrystalline materials.
“We can figure out what kind of grain boundaries we want to have” for a material being designed for a particular application, “and figure out how to make a material with those grain boundaries.” Manipulating the characteristics of these grain boundaries, by modifying the material to increase their abundance or relative orientations, can produce significant changes in the material’s property. So, for example, the technique might be used to figure out how to reduce the rate of corrosion of metals exposed to harsh environments, such as oil or gas drilling equipment, he says.
This work is “an inspiring step forward in rapid, data-rich characterization of the structure of crystalline materials,” says Brad Boyce, a distinguished member of the technical staff at Sandia National Laboratories in New Mexico, who was not involved in this research. “Grain boundaries, which are interfacial disruptions in the crystalline lattice of polycrystals, influence a wide range of material phenomena ranging from how the material deforms to the electrical resistivity … yet materials scientists possess a limited range of techniques to explore the grain boundary character.”
Now, with this new technique, Boyce says, “I am excited to see how this work will inspire further developments that provide rapid, high-throughput characterization, especially techniques that can be used to decipher local grain boundary character below the spatial resolution limits of optical microscopy.”
The team also included Marco Volpi and Maria Vittora Diamanti of the Polytechnic University of Milan, in Italy; Srikanth Patala at North Carolina State University; and Ian McCue and Jonah Erlebacher at Johns Hopkins University, in Baltimore. The work was supported by the U.S. Department of Energy, the National Science Foundation, and the MISTI Seed Fund. | | 1:00p |
Dead X-ray satellite reveals “quiet” center of massive galaxy cluster At the center of the Perseus galaxy cluster — a swarm of thousands of galaxies that spans 2 million light years across and is one of the most massive known objects in the universe — a black hole is attempting to stir things up, blowing giant bubbles and jets and ripples of gas out into the galactic plasma.
However, scientists from the Hitomi Collaboration, including researchers from MIT, have found that, despite the black hole’s efforts, the core of the cluster is surprisingly “quiet,” meaning the plasma surrounding the central black hole is not swirling around nearly as fast as scientists had suspected.
To be exact, the scientists observed that the gas at the center of the galaxy cluster is moving at a velocity of 164 kilometers per second, or about 366,000 miles per hour — positively pokey compared to the galaxies and stars within the cluster, which are thought to travel at least 10 times as fast.
“You’d expect the gas in this region to be quite stirred up, but it’s not,” says Eric Miller, a research scientist at MIT’s Kavli Institute for Astrophysics and Space Research. “It’s really kind of quiet compared to how much disorder we see coming from the black hole.”
The team’s results are published today in Nature. In addition to Miller, co-authors include MIT Kavli Institute Associate Director Mark Bautz and MIT postdoc Esra Bulbul, along with scientists from 70 other institutions, as part of the Hitomi Collaboration. The results are based on data taken by an instrument that was designed in part by co-authors and MIT alumni Richard Kelley PhD ’82, Hitomi’s U.S. principal investigator, and project scientist Robert Petre PhD ’82.
Going dark
The international team measured the speed of the gas at the center of the Perseus cluster using X-ray data collected by the Hitomi satellite, a joint mission that was launched in February by NASA and the Japan Aerospace Exploration Agency (JAXA).
Hitomi was designed as a high-resolution X-ray telescope, capable of observing the most extreme processes in the universe, including exploding stars, supermassive black holes, and galaxy clusters such as Perseus — extremely high-temperature phenomena that can only be seen in the X-ray region of the electromagnetic spectrum. Scientists even planned to point the telescope toward suspected regions of dark matter.
Hitomi was meant to explore the universe for at least three years. But just a month after it launched, the satellite spun out of control, jettisoning its two solar panels, and with them, its only source of power. Scientists soon lost contact with Hitomi, and on April 28, JAXA ended its efforts to recover the satellite.
“Everyone was numb for several days,” Miller recalls.
A broad spike
However, before its demise, the satellite was able to collect a month’s worth of data as it pointed toward its first target, the Perseus cluster, 250 million light years from Earth. During that month, the satellite picked up incoming X-rays at various wavelengths, with higher precision than any previous X-ray detectors.
The X-ray data formed a spectrum that peaked at certain wavelengths, indicating the presence of particular elements, such as iron and hydrogen. Such a spectrum can reveal the type and abundance of elements in a cluster’s interstellar medium, which scientists can then use to estimate the temperatures within that medium.
In this case, the Hitomi Collaboration used the X-ray spectrum to estimate the velocity of gas at the center of the Perseus cluster — a measure that may help scientists understand how black holes affect their immediate surroundings, and how galaxy clusters form.
The team detected a spike in the X-ray spectrum that was broader than expected. If that spike were simply a vertical line, it would indicate the gas giving off the X-rays was relatively still. But because the spike was relatively broad, scientists interpreted the signal as a Doppler-like effect, produced by gas that was on the move.
By studying this broad signal further, the team was able to estimate that the speed of the gas at the core of the cluster was 164 kilometers per second — slower than expected, given the bubbles and jets of gas that the central black hole is generating, according to previous observations. Bautz says that this relatively quiet atmosphere may mean that the gas, or plasma, is thicker than scientists thought, and that it may be less easy to push around as a result.
“It is somewhat surprising that it is so quiet,” Bautz says. “We don’t know how this works in detail. One possibility is that the plasma is relatively viscous, more like a pot of boiling oatmeal than a pot of boiling water. This characteristic of the cluster plasma, namely its viscosity, is something we had almost no idea about before Hitomi.”
William Forman, an astrophysicst at the Harvard-Smithsonian Center for Astrophysics, says that since the 1960s, the sensitivity of X-ray telescopes such has the Chandra X-ray Observatory has vastly improved, bringing “a revolution in understanding the high energy universe. … With Hitomi, we are on the verge of a second revolution.”
“We are on the verge of measuring the velocity structure in gas-rich systems, from galaxies to groups to clusters,” says Forman, who was not involved in the research. “The properties of the cluster plasma have puzzled astrophysicists for more than a quarter of a century. Future missions will complete the revolution that we just glimpse through Hitomi.”
While the satellite itself has gone irreparably dark, scientists may still make new discoveries in the limited amount of data Hitomi was able to collect. Miller says the team plans to make the most of the data, in hopes of uncovering new information on the behavior of black holes, the origin of galaxy clusters, and even the existence of dark matter.
“We took this data because it was something we could do to demonstrate the capability in the instrument, but there was a lot more that was supposed to be done over the long haul, which unfortunately we don’t have,” Miller says. “On the plus side, we got some really great data, and this shows the community the need to try to fly one of these [X-ray missions] successfully.”
This research was supported, in part, by NASA and JAXA. |
|