Making smarter decisions about classroom technologies

In the 21st century, the proliferation of digital media and technology has fundamentally changed the way we learn. More than ever, children carry computers in their pockets and ever-expanding internet connectivity promises to reach even the most remote classrooms, putting a wealth of information at student’s fingertips. And there are growing demands from parents, educators, governments, and donors to incorporate educational technologies as part of children’s core curricula. 

But how does a teacher or administrator decide which technology is a good fit for their classroom? And especially in a global development context, how does a donor know that an investment in technology is the right approach to ensure learning outcomes — that a donation of tablets won’t end up in the corner after a year, collecting dust?

To answer these kinds of common, but challenging questions, MIT researchers have just launched a new decision-making tool for teachers, administrators, governments, global development practitioners, and other stakeholders trying to make smart decisions about incorporating technology in the classroom.

The tool, “A Framework for Evaluating Appropriateness of Educational Technology Use in Global Development Programs,” is an initiative of the Comprehensive Initiative on Technology Evaluation (CITE), a program supported by the U.S. Agency for International Development (USAID) and led by a multidisciplinary team of faculty, staff, and students at MIT. Launched at MIT in 2012, CITE is a pioneering program dedicated to developing methods for product evaluation in global development.

The framework seeks to help stakeholders explore how well a particular technology may fit their educational context by posing straight-forward questions such as: “Does the technology create a burden of extra management for the teacher?” and “Is there evidence that use of this technology aids learning? Is this evidence generalizable to your context?” Questions fall into eight categories: teachers; students; culture; sustainability; community, social, and political; learning; infrastructure; and scalability and market impact. 

The framework was developed following an extensive literature review by MIT researchers, and then tested in India by CITE’s partners at the India Institute of Management Ahmedabad, who looked at the deployment of English language learning technologies by NGO and government initiatives.

Why educational technologies? 

Despite the enthusiasm and promise of emerging technologies for education, there are a myriad of reasons technologies can fail that have little to do with the technology itself. Variables such as school funding, teacher preparedness, educational philosophy, and technical infrastructure play a major role in determining whether or not, for example, an English-language learning software actually helps children learn English.

“In doing this research, you realize how often adoption of educational technology is done without much forethought,” says Scot Osterweil, CITE Educational Technology Evaluation lead and creative director of the MIT Education Arcade. “Frequently, the decision to use a particular technology is based on who can make the most appealing sales pitch to the buyer, who will not be the user. Then, [the technology] ends up in a classroom where people haven’t prepared for it. There’s always a need to improve the process, even more so in developing countries where these technologies are new.”

MIT research assistant and PhD student Jennifer Groff adds that it's easy to see the positives about a new technology without thinking through potential challenges.

“Naturally, we get excited by the opportunity of something new,” Jennifer explains. “On a deeper level, we have to pause and ask ourselves what the challenges are to implementing something like this meaningfully. The framework is a tool that we hope helps people think through all of the facets of incorporating something new.”

Testing the framework

To test the framework, CITE’s research partners at the Indian Institute of Management Ahmedabad conducted a pilot study which entailed semi-structured interviews and group discussions with various stakeholders in sites where technologies studied were being deployed. The schools involved in the study varied from the most basic to the most modern, including everything from a rural village school in Uttar Pradesh without a building or dedicated classroom to a series of computer labs in public schools and community centers in Mumbai run by an influential NGO, the Pratham Education Foundation.

“One of the most interesting things that became apparent during our fieldwork was the role of continual intermediation by the developers at the sites of implementation,” said local research lead, Professor Ankur Sarin of Indian Institute of Management Ahmedabad. “Technology still remains an external intervention and facilitators play a critical role in determining the efficacy with which the education technology comes to be used. Based on what we learned, the framework was then adapted to account for the role, background and motivations for the facilitators.”

Putting the framework to use

The tool is designed to be useful for many different kinds of stakeholders who work with educational technologies, including developers, adopters, and funders of new technologies. It can be used before the adoption of an intervention, or as an assessment of an intervention as it is being deployed.

The next phase of work for this framework will be turning it into an online, interactive version that would guide the user step-by-step through a series of questions to identify the potential challenges around deploying a certain technology in the classroom.

“We would also like to create a knowledge network of people in different developing countries interested in using the framework who could help us refine it,” Scot says. “We tested our framework in India, but could learn other things in Latin America, Africa, or other parts of Asia if we identify partners elsewhere who could play a role in supporting or advancing the framework.”

In addition, the researchers hope illuminating the complexities of deploying an educational technology in a developing country setting will add to the existing literature in a meaningful way.

“There is a significant body of literature on educational technology and factors for change in developed contexts,” Jennifer explains. “And sometimes in developing countries, there’s an assumption that a technology is just better than what already exists, so a school is pressured to adopt it with questions. But there are many of the same barriers to change in these classrooms. It’s still change management, which isn’t just about bits and bytes, it’s about the way of delivering teaching and learning being much, much different.”

“As someone who’s worked in this area for 25 years, I know that a class could be successful without any technology,” Scot says. “You should only be using technology when you’ve identified a goal it can help you achieve. And we hope to help stakeholders make smart decisions from the very beginning with this new tool.”  

CITE’s research is funded by the USAID U.S. Global Development Lab. CITE is led by principal investigator Bishwapriya Sanyal of MIT’s Department of Urban Studies and Planning, and supported by MIT faculty and staff from D-Lab, Priscilla King Gray Public Service Center, Sociotechnical Systems Research Center, the Center for Transportation and Logistics, School of Engineering, and Sloan School of Management.

In addition to Osterweil and Groff, co-authors on the report include Eric Klopfer, Ankur Sarin, Prateek Shah, Stacey Allen, Sai Priya Kodidala, and Ilana Schoenfeld. CITE conducted its research in partnership with the Indian Institute of Management Ahmedabad.

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Engaging industry in addressing climate change

The mission of the Oil and Gas Climate Initiative (OGCI), a two-year-old organization comprised of 10 major oil and gas companies, is one not commonly associated with the industry: to catalyze practical action to reduce greenhouse gas emissions. Intent on confronting the challenge of climate change head-on, the OGCI committed last October to support the Paris climate agreement’s target of capping the rise in mean global surface temperature since preindustrial times at 2 degrees Celsius by 2100, and has been working ever since to develop a plan for the industry to help advance this objective.

To that end, the OGCI held its second Low Emission Roadmap Roundtable on Sept. 23 at the World Economic Forum in New York City. During the three-hour event, timed to coincide with the city’s annual Climate Week, the OGCI sought input from stakeholders as they develop practical steps for reducing the industry’s emissions. While the formal membership of the OGCI represents about 20 percent of global oil and gas production, invitations were open to a broader group of industry and environmental non-governmental organizations. To bring academic rigor to the discussion of how to help reduce greenhouse gas emissions in alignment with the 2 C goal, the OGCI partnered in the roundtable with the MIT Joint Program on the Science and Policy of Global Change.

Early in the event, Joint Program Co-Director John Reilly previewed a set of scenarios illustrating the significant transformation of the global energy system that’s needed, and various technology paths that could be pursued, to achieve the 2 C goal. These scenarios were released on Sept. 28 in the Joint Program’s 2016 Food, Water, Energy and Climate Outlook.

“A key to understanding steps that industry can take to reduce greenhouse gas emissions are estimates of emissions pathways consistent with stabilization of greenhouse gases in the atmosphere,” said Reilly, who is also a senior lecturer at the Sloan School of Management. “Our contribution to the discussion was to develop illustrative pathways and to suggest the potential role of a variety of low-carbon technologies in enabling deep emissions cuts, emphasizing that uncertainty in climate response and in technology development call for a risk-based planning process.”

Joint Program Co-Director Emeritus Henry D. Jacoby, the William F. Pounds Professor of Management (Emeritus) at the MIT Sloan School of Management, who moderated the Roundtable, added, “There is a growing effort in the international negotiations to involve non-state actors in managing climate risk, and this OGCI effort is a timely response.” To that end, the Roundtable included opening presentations by Vidar Helgesen, the minister of climate and environment of Norway, two executives of OGCI companies — Bjorn Otto Sverdrup of Statoil and Valérie Quiniou-Ramus of Total — and Granville Martin from JP MorganChase. The event covered both the intentions and plans of the OGCI member companies and active discussion of ways they could make their most effective contribution to the goals of the Paris Agreement.

The OGCI chose to partner with the MIT Joint Program because it is “one of the key research centers that’s driving the thinking around the energy transition, with strong technical capabilities,” says OGCI Executive Board Chair Gerard Moutet. “The MIT Joint Program’s input at the Low Emission Roadmap Roundtable, along with that of OGCI stakeholders, helps us to determine what oil and gas companies should focus on to enable an efficient energy transition to zero net emissions,” said Moutet. 

Informed by the Joint Program’s analysis that a sharp turn in the current direction of the energy system is needed, the discussion centered on how fast the system could respond; whether a technological revolution was already underway that would sweep aside the fossil energy industry; the need to protect and expand forest carbon sinks; and prospects for global carbon pricing, which many in attendance deemed essential to providing enough incentive for investment in low and zero-carbon sources of energy. Practical steps the OGCI is considering to reduce greenhouse gas emissions include improving the energy efficiency of their operations and products, developing carbon capture and storage, reducing carbon dioxide and methane emissions by utilizing gas instead of flaring it, and developing and deploying new low-carbon energy technologies.

Viewing private sector engagement as essential to solving the climate problem, the Joint Program has for 25 years engaged with industry, including OGCI member companies, on comprehensive studies of the impact of the changing climate, and the need to transform the energy system.

“Through its comprehensive modeling and analysis, the MIT Joint Program provided us with useful insights into the nature and timeline of changes that will be needed to transition to a lower-carbon energy system,” said Charlotte Wolff-Bye, host and organizer of the roundtable; co-chair of the OGCI Low Emission Roadmap work stream; and vice president for sustainability at Statoil.

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Scientists identify neurons devoted to social memory

Mice have brain cells that are dedicated to storing memories of other mice, according to a new study from MIT neuroscientists. These cells, found in a region of the hippocampus known as the ventral CA1, store “social memories” that help shape the mice’s behavior toward each other.

The researchers also showed that they can suppress or stimulate these memories by using a technique known as optogenetics to manipulate the cells that carry these memory traces, or engrams.

“You can change the perception and the behavior of the test mouse by either inhibiting or activating the ventral CA1 cells,” says Susumu Tonegawa, the Picower Professor of Biology and Neuroscience and director of the RIKEN-MIT Center for Neural Circuit Genetics at the Picower Institute for Learning and Memory.

Tonegawa is the senior author of the study, which appears in the Sept. 29 online edition of Science. MIT postdoc Teruhiro Okuyama is the paper’s lead author.

Tracking social memory

In a well-known study published in 2005, researchers at Caltech identified neurons in the human brain that respond specifically to images of celebrities such as Halle Berry or Brad Pitt, leading them to conclude that the brain has cells devoted to storing memories of people who are familiar.

Many of these cells were found in and around the hippocampus, which is also where the brain stores memories of events, known as episodic memories. The MIT team suspected that in mice, social memories may be stored in the hippocampus’ ventral CA1, in part because previous studies have suggested that this region is not involved in storing episodic memories.

The researchers set out to test this hypothesis using optogenetics: By engineering neurons of the ventral CA1 to express light-sensitive proteins, they could artificially activate or inhibit these cells by shining light on them as the mice interacted with each other.

First, the researchers allowed one mouse, known as the “test mouse,” to spend time with another mouse for two hours, letting the mice become familiar with each other. Soon after, the test mouse was placed in a cage with the familiar mouse and a new mouse.

Under normal circumstances, mice prefer to interact with mice they haven’t seen before. However, when the researchers used light to shut off a circuit that connects the ventral CA1 to another part of the brain called the nucleus accumbens, the test mouse interacted with both of the other mice equally, because its memory of the familiar mouse was blocked.

“The inhibition of ventral CA1 leads to impairment of the social memory,” Okuyama says. “They cannot show any preference for the novel mouse. They approach both mice equally.”

On the other hand, when the researchers stimulated ventral CA1 cells while the test mouse was interacting with a novel mouse, the test mouse began to treat the novel mouse as if they were already acquainted.

This effect was specific to social interactions: Interfering with the ventral CA1 did not have any effect on the mice’s ability to recognize objects or locations that they had previously seen.

Re-awakening memories

When the researchers monitored activity of neurons in the ventral CA1, they found that after a mouse was familiarized with another mouse, a certain population of these neurons began to respond specifically to the familiar mouse.

These patterns could be seen even after the mice appeared to “forget” the once-familiar mice. After about 24 hours of separation, the test mice began to treat their former acquaintances as strangers, but the neurons that had been tuned to the familiar mice still fired, although not as frequently. This suggests that the memories are still being stored even though the test mice no longer appear to remember the mice they once knew.

Furthermore, the researchers were able to “re-awaken” these memories using optogenetics. In one experiment, when the test mouse first interacted with another mouse, the researchers used a light-sensitive protein called channelrhodopsin to tag only the ventral CA1 cells that were turned on by the familiarization treatment. When these neurons were re-activated with light 24 hours later, the memory of the once-familiar mouse returned. The researchers were also able to artificially link the memory of the familiar mouse with a positive or negative emotion.  

Tonegawa’s lab has previously used this technique to identify hippocampal cells that store engrams representing episodic memories. The new study offers strong evidence that memory traces for specific individuals are being stored in the neurons of the ventral CA1, Tonegawa says. “There is some kind of persistent change that takes place in those cells as long as memory is still detectable,” he says.

Larry Young, a professor of psychiatry and director of the Center for Translational Social Science at Emory University, described the study as “one of the most fascinating papers related to social neuroscience I’ve ever seen.”

“In this paper, they identified a subset of cells in a particular brain region that is the engram — a set of cells that through its connections in the nucleus accumbens, actually holds the memory of another individual,” says Young, who was not involved in the study. “They showed that the same group of neurons fired repeatedly in response to the same animal, which is absolutely incredible. Then to go in and control those specific cells is really on the cutting edge.”

The MIT researchers are now investigating a possible link between social memory and autism. Some people with autism have a mutation of the receptor for a hormone called oxytocin, which is abundant on the surface of ventral CA1 cells. Tonegawa’s lab hopes to uncover whether these mutations might impair social interactions.

The research was funded by the RIKEN Brain Science Institute, the Howard Hughes Medical Institute, the JPB Foundation, and the Japan Society for the Promotion of Science.

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Collaborating with community colleges to innovate educational technology

Nearly one in every two undergraduates in the United States attends community college. Serving a large and diverse pool of students, community colleges are critical in bridging the job-skills gap, in empowering students to transition to four-year institutions, and in enabling opportunities for non-traditional pathways. But community colleges face an important hurdle: How can they scale so as to offer high-quality, affordable education to growing student numbers?

Now, researchers from MIT’s Department of Aeronautics and Astronautics, Office of Digital Learning, and Teaching and Learning Lab are collaborating with community colleges to develop innovative educational technology that tackles this issue.

A need for on-demand resources

The question of scaling up is one faced by Arapahoe Community College (ACC), located in the urban-metro area of Denver, Colorado, with a population of over 10,000 students. The average ACC student juggles between taking classes and working at least one part-time job, and many are considered to have a higher probability of failing or dropping out of school.

Jose Albareda is such a student.* He graduated from high school six years ago, and after a decade working different jobs, now looks to earn a four-year degree. To do so, he must pass College Algebra, a course that is standardized across the state of Colorado and guaranteed for transfer to a four-year institution. This semester, he is enrolled in a section of College Algebra. Five weeks into term, he is feeling anxious. He feels rusty on math, and with every assignment, slips a little more behind. He tries to attend office hours when they do not conflict with his part-time job, but wishes he had more immediate help during his homework time in the evenings.

This case highlights key issues of access and student completion. Even though the community college provides out-of-class resources, it cannot provide on-demand resources to meet the diverse needs of every student. And failing algebra is often the biggest hurdle for students, regardless of their ultimate degree goals.

Heidi Barrett and Danielle Staples are instructors of the College Algebra course at ACC. Typically in a semester, Staples teaches four classes, each with 25-30 students, totaling up to 120 students. Barrett, echoing faculty across community colleges, says: “It is very difficult to keep tabs on every individual student, to give the student the individualized attention they need, when every week you have a few hundred assignments to look at, to punch in grades for, to keep track of.” 

Fine-tuning educational needs in real-time

Enter Fly-by-Wire.

A blended-learning technology developed at MIT, Fly-by-Wire draws inspiration from aerospace engineering and artificial intelligence. There are two components: The Fly-by-Wire Student App adapts to a student’s need in real-time, serving up dynamic formative assessments that scaffold the student to mastery, while the Fly-by-Wire Instructor App analyzes the data and makes recommendations to the instructor in a way that lets them fine-tune their instruction in real-time.

Project lead Karen Willcox, professor of aeronautics and astronautics at MIT, explains: “An instructor using Fly-by-Wire in-class is like a pilot using a computer to help fly a plane. Just as a pilot cannot keep track of hundreds of flashing sensors, an instructor cannot keep tabs on hundreds of students learning the material in different ways and at different rates. This is a big challenge for all faculty members — not just in community colleges, but also for us at MIT. But just as digital fly-by-wire systems have revolutionized how human pilots fly modern aircraft, we believe that digital technologies open the door to personalized instruction at scale in the modern classroom.”

How it works

At the start of a recent College Algebra class, Barrett tapped on the Fly-By-Wire Instructor App and saw the questions students got wrong on the last homework — and why they got them wrong. She reviewed the fundamental misunderstanding and tapped on her screen to get another question with which to ask students. At the end of class, she assigned six questions as homework on the Fly-By-Wire Student App.  

In the evening after work, Albareda sat down to complete his homework on the student app. He got stuck on the first problem – solving a quadratic equation. But instead of giving up or hopelessly flipping through his notes, he got specific feedback from the Fly-By-Wire app on why he got the question wrong. The app gave him an easier formative assessment question to target his misunderstanding. After six such adaptive questions, he correctly answered the original question.

The next day, he approached Barrett and showed her the path he took through the Fly-By-Wire app.

“This is really cool. I really like that it tells me why I got this wrong and what I need to work on. It’s like the teacher is next to me,” Albareda said enthusiastically during a user experience interview. “But I don’t like that it doesn’t give me anything for going through this [scaffold].”

The Fly-By-Wire team is eager for such comments. Willcox emphasizes, “This is a collaborative, iterative, and agile design effort with the community colleges; user needs drive the design of Fly-by-Wire technology.”

According to Sanjay Sarma, MIT’s vice president for open learning, the collaboration between MIT and Arapahoe Community College “allows us to work closely with teachers to develop digitally-enabled education technologies that increase the likelihood of improved learning outcomes for all. We may be able to provide new ways to personalize learning to fit students’ individual needs.”

The Fly-by-Wire project is progressing rapidly thanks to funding from the U.S. Department of Education's Fund for the Improvement of Postsecondary Education First in the World program. In October, the team plans to launch a pre-pilot, during which students in a section of College Algebra at Arapahoe Community College use the student app to complete a single assignment. In November, faculty from Arapahoe and Quinsigamond Community Colleges will visit MIT to participate in a Fly-by-Wire tech workshop. Next spring, the team plans to pilot in four class sections, and in fall 2017 will conduct a randomized control trial.

*Real name and specific details have been changed.

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Algorithm could enable visible-light-based imaging for medical devices, autonomous vehicles

MIT researchers have developed a technique for recovering visual information from light that has scattered because of interactions with the environment — such as passing through human tissue.

The technique could lead to medical-imaging systems that use visible light, which carries much more information than X-rays or ultrasound waves, or to computer vision systems that work in fog or drizzle. The development of such vision systems has been a major obstacle to self-driving cars.

In experiments, the researchers fired a laser beam through a “mask” — a thick sheet of plastic with slits cut through it in a certain configuration, such as the letter A  — and then through a 1.5-centimeter “tissue phantom,” a slab of material designed to mimic the optical properties of human tissue for purposes of calibrating imaging systems. Light scattered by the tissue phantom was then collected by a high-speed camera, which could measure the light’s time of arrival.

From that information, the researchers’ algorithms were able to reconstruct an accurate image of the pattern cut into the mask.

“The reason our eyes are sensitive only in this narrow part of the spectrum is because this is where light and matter interact most,” says Guy Satat, a graduate student at the MIT Media Lab and first author on the new paper. “This is why X-ray is able to go inside the body, because there is very little interaction. That’s why it can’t distinguish between different types of tissue, or see bleeding, or see oxygenated or deoxygenated blood.”

The imaging technique’s potential applications in automotive sensing may be even more compelling than those in medical imaging, however. Many experimental algorithms for guiding autonomous vehicles are highly reliable under good illumination, but they fall apart completely in fog or drizzle; computer vision systems misinterpret the scattered light as having reflected off of objects that don’t exist. The new technique could address that problem.

Satat’s coauthors on the new paper, published today in Scientific Reports, are three other members of the Media Lab’s Camera Culture group: Ramesh Raskar, the group’s leader, Satat’s thesis advisor, and an associate professor of media arts and sciences; Barmak Heshmat, a research scientist; and Dan Raviv, a postdoc.

Expanding circles

Like many of the Camera Culture group’s projects, the new system relies on a pulsed laser that emits ultrashort bursts of light, and a high-speed camera that can distinguish the arrival times of different groups of photons, or light particles. When a light burst reaches a scattering medium, such as a tissue phantom, some photons pass through unmolested; some are only slightly deflected from a straight path; and some bounce around inside the medium for a comparatively long time. The first photons to arrive at the sensor have thus undergone the least scattering; the last to arrive have undergone the most.

Where previous techniques have attempted to reconstruct images using only those first, unscattered photons, the MIT researchers’ technique uses the entire optical signal. Hence its name: all-photons imaging.

The data captured by the camera can be thought of as a movie — a two-dimensional image that changes over time. To get a sense of how all-photons imaging works, suppose that light arrives at the camera from only one point in the visual field. The first photons to reach the camera pass through the scattering medium unimpeded: They show up as just a single illuminated pixel in the first frame of the movie.

The next photons to arrive have undergone slightly more scattering, so in the second frame of the video, they show up as a small circle centered on the single pixel from the first frame. With each successive frame, the circle expands in diameter, until the final frame just shows a general, hazy light.

The problem, of course, is that in practice the camera is registering light from many points in the visual field, whose expanding circles overlap. The job of the researchers’ algorithm is to sort out which photons illuminating which pixels of the image originated where.

Cascading probabilities

The first step is to determine how the overall intensity of the image changes in time. This provides an estimate of how much scattering the light has undergone: If the intensity spikes quickly and tails off quickly, the light hasn’t been scattered much. If the intensity increases slowly and tails off slowly, it has.

On the basis of that estimate, the algorithm considers each pixel of each successive frame and calculates the probability that it corresponds to any given point in the visual field. Then it goes back to the first frame of video and, using the probabilistic model it has just constructed, predicts what the next frame of video will look like. With each successive frame, it compares its prediction to the actual camera measurement and adjusts its model accordingly. Finally, using the final version of the model, it deduces the pattern of light most likely to have produced the sequence of measurements the camera made.

One limitation of the current version of the system is that the light emitter and the camera are on opposite sides of the scattering medium. That limits its applicability for medical imaging, although Satat believes that it should be possible to use fluorescent particles known as fluorophores, which can be injected into the bloodstream and are already used in medical imaging, as a light source. And fog scatters light much less than human tissue does, so reflected light from laser pulses fired into the environment could be good enough for automotive sensing.

“People have been using what is known as time gating, the idea that photons not only have intensity but also time-of-arrival information and that if you gate for a particular time of arrival you get photons with certain specific path lengths and therefore [come] from a certain specific depth in the object,” says Ashok Veeraraghavan, an assistant professor of electrical and computer engineering at Rice University. “This paper is taking that concept one level further and saying that even the photons that arrive at slightly different times contribute some spatial information.”

“Looking through scattering media is a problem that’s of large consequence,” he adds. But he cautions that the new paper does not entirely solve it. “There’s maybe one barrier that’s been crossed, but there are maybe three more barriers that need to be crossed before this becomes practical,” he says.

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Nanosensors could help determine tumors’ ability to remodel tissue

MIT researchers have designed nanosensors that can profile tumors and may yield insight into how they will respond to certain therapies. The system is based on levels of enzymes called proteases, which cancer cells use to remodel their surroundings.

Once adapted for humans, this type of sensor could be used to determine how aggressive a tumor is and help doctors choose the best treatment, says Sangeeta Bhatia, the John and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science and a member of MIT’s Koch Institute for Integrative Cancer Research.

“This approach is exciting because people are developing therapies that are protease-activated,” Bhatia says. “Ideally you’d like to be able to stratify patients based on their protease activity and identify which ones would be good candidates for these therapies.”

Once injected into the tumor site, the nanosensors are activated by a magnetic field that is harmless to healthy tissue. After interacting with and being modified by the target tumor proteins, the sensors are secreted in the urine, where they can be easily detected in less than an hour.

Bhatia and Polina Anikeeva, the Class of 1942 Associate Professor of Materials Science and Engineering, are the senior authors of the paper, which appears in the journal Nano Letters. The paper’s lead authors are Koch Institute postdoc Simone Schurle and graduate student Jaideep Dudani.

Heat and release

Tumors, especially aggressive ones, often have elevated protease levels. These enzymes help tumors spread by cleaving proteins that compose the extracellular matrix, which normally surrounds cells and holds them in place.

In 2014, Bhatia and colleagues reported using nanoparticles that interact with a type of protease known as matrix metalloproteinases (MMPs) to diagnose cancer. In that study, the researchers delivered nanoparticles carrying peptides, or short protein fragments, designed to be cleaved by the MMPs. If MMPs were present, hundreds of cleaved peptides would be excreted in the urine, where they could be detected with a simple paper test similar to a pregnancy test.

In the new study, the researchers wanted to adapt the sensors so that they could report on the traits of tumors in a known location. To do that, they needed to ensure that the sensors were only producing a signal from the target organ, unaffected by background signals that might be produced in the bloodstream. They first designed sensors that could be activated with light once they reached their target. That required the use of ultraviolet light, however, which doesn’t penetrate very far into tissue.

“We started thinking about what kinds of energy we might use that could penetrate further into the body,” says Bhatia, who is also a member of MIT’s Institute for Medical Engineering and Science.

To achieve that, Bhatia teamed up with Anikeeva, who specializes in using magnetic fields to remotely activate materials. The researchers decided to encapsulate Bhatia’s protease-sensing nanoparticles along with magnetic particles that heat up when exposed to an alternating magnetic field. The field is produced by a small magnetic coil that changes polarity some half million times per second.

The heat-sensitive material that encapsulates the particles disintegrates as the magnetic particles heat up, allowing the protease sensors to be released. However, the particles do not produce enough heat to damage nearby tissue.

“It has been challenging to examine tumor-specific protease activities from patients’ biofluids because these proteases are also present in blood and other organs,” says Ji Ho (Joe) Park, an associate professor of bio and brain engineering at the Korea Advanced Institute of Science and Technology.

“The strength of this work is the magnetothermally responsive protease nanosensors with spatiotemporal controllability,” says Park, who was not involved in the research. “With these nanosensors, the MIT researchers could assay protease activities involved more in tumor progression by reducing off-target activation significantly.”

Choosing treatments

In a study of mice, the researchers showed that they could use these particles to correctly profile different types of colon tumors based on how much protease they produce.

Cancer treatments based on proteases, now in clinical trials, consist of antibodies that target a tumor protein but have “veils” that prevent them from being activated before reaching the tumor. The veils are cleaved by proteases, so this therapy would be most effective for patients with high protease levels.

The MIT team is also exploring using this type of sensor to image cancerous lesions that spread to the liver from other organs. Surgically removing such lesions works best if there are fewer than four, so measuring them could help doctors choose the best treatment.

Bhatia says this type of sensor could be adapted to other tumors as well, because the magnetic field can penetrate deep into the body. This approach could also be expanded to make diagnoses based on detecting other kinds of enzymes, including those that cut sugar chains or lipids.

The study was funded in part by the Ludwig Center for Molecular Oncology, a Koch Institute Support Grant from the National Cancer Institute, and a Core Center Grant from the National Institute of Environmental Health Sciences.

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Innovation for everyone

Four rising firms snagged top honors in MIT’s Inclusive Innovation Competition (IIC) on Tuesday evening, as part of a new $1 million contest rewarding companies whose technologies can improve economic opportunity for people from a full range of income levels and social circumstances. 

Among 20 companies receiving monetary awards, four were named as grand-prize champions: the work-force training firm Year Up, software job-training firm Laboratoria, apparel maker 99Degrees Custom, and health care delivery service Iora Health.

The winners, chosen from a field of 243 applicants worldwide, were honored at a reception on Tuesday evening at the MIT Media Lab, following an afternoon showcase where leaders from nominated firms made on-stage presentations about their work.

Speaking at the afternoon event, MIT Provost Martin Schmidt said it was “really exciting today to see the finalists here to present their pitches,” and noted that the IIC was a natural outgrowth of the now-annual MIT Solve conference. Founded in 2015, Solve highlights the role of innovative technologies in addressing “the world’s most challenging problems,” as Schmidt put it. The IIC event, developed by the MIT Initiative on the Digital Economy in collaboration with MIT Solve, is part of the “Make” pillar of Solve, one of the conference’s four thematic categories.

MIT President L. Rafael Reif has stated that Solve’s purpose is to “accelerate positive change” in the world. Solve is aligned with Boston’s HUBWeek, a celebration of innovation and creativity in Greater Boston.

Tuesday’s IIC pitches featured a broad array of startup firms working globally to advance social progress in areas such as access to health care, job-training skills, and advanced manufacturing jobs, among other things. Some firms that were IIC finalists also focus on outreach to underrepresented social groups.

“All the studies show that when we have diversity at the table in a meeting, everybody performs better,” said Maria Contreras-Sweet, the administrator of the U.S. Small Business Administration (SBA), in an on-stage discussion at the IIC event on Tuesday afternoon.

In a related vein, Contreras-Sweet noted, the SBA has developed tools to encourage further access to capital for small business founders regardless of gender or ethnicity; currently, she noted, only about 4 percent of venture capital goes to firms led by women and only about 1 percent is invested in firms led by African-Americans.

The four grand prize champions received $125,000 each, while 16 other firms received $25,000 apiece. The competition received support from the Rockefeller Foundation, the Joyce Foundation, the NASDAQ Foundation, Joseph Eastin, and Eric and Wendy Schmidt.

Entries to the IIC fell into four main categories: “Skills,” for companies centered on job training; “Matching,” for firms finding new ways of linking workers to jobs; “Human + Machines,” for companies using technology to augment human labor; and “New Models,” novel business practices or business models creating new labor-market opportunities.

The four grand prize champions include the Boston-based nonprofit firm Year Up, which won in the “Skills” category; it provides market-driven job training to low-income young adults.

Laboratoria, a firm that provides job-training focused on software, and helps women enter the information technology profession, won in the “Matching” category. Laboratoria is based in Peru but has expanded to Chile and Mexico.

99Degrees Custom, an apparel manufacturer based in Lawrence, Massachusetts, was the winner of the “Human + Machines” category. The firm uses technology to automate some aspects of the clothing-production process, while paying a living wage and benefits to its 50 employees. The company would like to expand nationally.

In the “New Models” category, Iora Health took the top honors. The company, headquartered in Boston but located in 10 cities, offers health care services using “health coaches” and aims to reduce clients’ medical costs by keeping them healthy.

The categories represent marketplace trends, said Devin Wardell Cook, executive producer of the IIC, which suggests “that we truly can create an economy that works for people … for the many, and not just for the few.”

The full list of honorees is available at the MIT Inclusive Innovation website.

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