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Wednesday, September 4th, 2019
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| 12:00p |
Soft robotics breakthrough manages immune response for implanted devices Researchers from the Institute for Medical Engineering and Science (IMES) at MIT; the National University of Ireland Galway (NUI Galway); and AMBER, the SFI Research Centre for Advanced Materials and BioEngineering Research, recently announced a significant breakthrough in soft robotics that could help patients requiring in-situ (implanted) medical devices such as breast implants, pacemakers, neural probes, glucose biosensors, and drug and cell delivery devices.
The implantable medical devices market is currently estimated at approximately $100 billion, with significant growth potential into the future as new technologies for drug delivery and health monitoring are developed. These devices are not without problems, caused in part by the body’s own protection responses. These complex and unpredictable foreign-body responses impair device function and drastically limit the long-term performance and therapeutic efficacy of these devices.
One such foreign body response is fibrosis, a process whereby a dense fibrous capsule surrounds the implanted device, which can cause device failure or impede its function. Implantable medical devices have various failure rates that can be attributed to fibrosis, ranging from 30-50 percent for implantable pacemakers or 30 percent for mammoplasty prosthetics. In the case of biosensors or drug/cell delivery devices, the dense fibrous capsule which can build up around the implanted device can seriously impede its function, with consequences for the patient and costs to the health care system.
A radical new vision for medical devices to address this problem was published in the internationally respected journal, Science Robotics. The study was led by researchers from NUI Galway, IMES, and the SFI research center AMBER, among others. The research describes the use of soft robotics to modify the body’s response to implanted devices. Soft robots are flexible devices that can be implanted into the body.
The transatlantic partnership of scientists has created a tiny, mechanically actuated soft robotic device known as a dynamic soft reservoir (DSR) that has been shown to significantly reduce the build-up of the fibrous capsule by manipulating the environment at the interface between the device and the body. The device uses mechanical oscillation to modulate how cells respond around the implant. In a bio-inspired design, the DSR can change its shape at a microscope scale through an actuating membrane.
IMES core faculty member, assistant professor at the Department of Mechanical Engineering, and W.M. Keck Career Development Professor in Biomedical Engineering Ellen Roche, the senior co-author of the study, is a former researcher at NUI Galway who won international acclaim in 2017 for her work in creating a soft robotic sleeve to help patients with heart failure. Of this research, Roche says “This study demonstrates how mechanical perturbations of an implant can modulate the host foreign body response. This has vast potential for a range of clinical applications and will hopefully lead to many future collaborative studies between our teams.”
Garry Duffy, professor in anatomy at NUI Galway and AMBER principal investigator, and a senior co-author of the study, adds “We feel the ideas described in this paper could transform future medical devices and how they interact with the body. We are very excited to develop this technology further and to partner with people interested in the potential of soft robotics to better integrate devices for longer use and superior patient outcomes. It’s fantastic to build and continue the collaboration with the Dolan and Roche labs, and to develop a trans-Atlantic network of soft roboticists.”
The first author of the study, Eimear Dolan, lecturer of biomedical engineering at NUI Galway and former researcher in the Roche and Duffy labs at MIT and NUI Galway, says “We are very excited to publish this study, as it describes an innovative approach to modulate the foreign-body response using soft robotics. I recently received a Science Foundation Ireland Royal Society University Research Fellowship to bring this technology forward with a focus on Type 1 diabetes. It is a privilege to work with such a talented multi-disciplinary team, and I look forward to continuing working together.” | | 1:00p |
How “information gerrymandering” influences voters Many voters today seem to live in partisan bubbles, where they receive only partial information about how others feel regarding political issues. Now, an experiment developed in part by MIT researchers sheds light on how this phenomenon influences people when they vote.
The experiment, which placed participants in simulated elections, found not only that communication networks (such as social media) can distort voters’ perceptions of how others plan to vote, but also that this distortion can increase the chance of electoral deadlock or bias overall election outcomes in favor of one party.
“The structure of information networks can really fundamentally influence the outcomes of elections,” says David Rand, an associate professor at the MIT Sloan School of Management and a co-author of a new paper detailing the study. “It can make a big difference and is an issue people should be taking seriously.”
More specifically, the study found that “information gerrymandering” can bias the outcome of a vote, such that one party wins up to 60 percent of the time in simulated elections of two-party situations where the opposing groups are equally popular. In a follow-up empirical study of the U.S. federal government and eight European legislative bodies, the researchers also identified actual information networks that show similar patterns, with structures that could skew over 10 percent of the vote in the study’s experiments.
The paper, “Information gerrymandering and undemocratic decisions,” is being published today in Nature.
The authors are Alexander J. Stewart of the University of Houston; Mohsen Mosleh, a research scientist at MIT Sloan; Marina Diakonova of the Environmental Change Institute at Oxford University; Antonio Arechar, an associate research scientist at MIT Sloan and a researcher at the Center for Research and Teaching in Economics (CIDE) in Aguascalientes, Mexico; Rand, who is also the principal investigator for MIT Sloan’s Human Cooperation Lab; and Joshua B. Plotkin of the University of Pennsylvania. Stewart is the lead author.
Formal knowledge
While there is a burgeoning academic literature on media preferences, political ideology, and voter choices, the current study is an effort to create general models of the fundamental influence that information networks can have. Through abstract mathematical models and experiments, the researchers can analyze how strongly networks can influence voter behavior, even when long-established layers of voter identity and ideology are removed from the political arena.
“Part of the contribution here is to try to formalize how information about politics flows through social networks, and how that can influence voters’ decisions,” says Stewart.
The study used experiments involving 2,520 particpants, who played a “voter game” in one of a variety of conditions. (The participants were recruited via Amazon’s Mechanical Turk platform and took part in the simulated elections via Breadboard, a platform generating multiplayer network interactions.) The players were divided into two teams, a “yellow” team and a “purple” team, usually with 24 people on each side, and were allowed to change their voting intentions in response to continuously updated polling data.
The participants also had incentives to try to produce certain vote outcomes reflective of what the authors call a “compromise worldview.” For instance, players would receive a (modest) payoff if their team received a super-majority vote share; a smaller payoff if the other team earned a super-majority; and zero payoff if neither team reached that threshold. The election games usually lasted four minutes, during which time each voter had to decide how to vote.
In general, voters almost always voted for their own party when the polling data showed it had a chance of reaching a super-majority share. They also voted for their own side when the polling data showed a deadlock was likely. But when the opposing party was likely to achieve a super-majority, half the players would vote for it, and half would continue to vote for their own side.
During a baseline series of election games where all the players had unbiased, random polling information, each side won roughly a quarter of the time, and a deadlock without a super-majority resulted about half the time. But the researchers also varied the game in multiple ways. In one iteration of the game, they added information gerrymandering to the polls, such that some members of one team were placed inside the other team’s echo chamber. In another iteration, the research team deployed online bots, comprising about 20 percent of voters, to behave like “zealots,” as the scholars called them; the bots would strongly support one side only.
After months of iterations of the game, the researchers concluded that election outcomes could be heavily biased by the ways in which the polling information was distributed over the networks, and by the actions of the zealot bots. When members of one party were led to believe that most others were voting for the other party, they often switched their votes to avoid deadlock.
“The network experiments are important, because they allow us to test the predictions of the mathematical models,” says Mosleh, who led the experimental portion of the research “When we added echo chambers, we saw that deadlock happened much more often — and, more importantly, we saw that information gerrymandering biased the election results in favor of one party over the other.”
The empirical case
As part of the larger project, the team also sought out some empirical information about similar scenarios among elected governments. There are many instances where elected officials might either support their first-choice legislation, settle for a cross-partisan compromise, or remain in deadlock. In those cases, having unbiased information about the voting intentions of other legislators would seem to be very important.
Looking at the co-sponsorship of bills in the U.S. Congress from 1973 to 2007, the researchers found that the Democratic Party had greater “influence assortment” — more exposure to the voting intentions of people in their own party — than the Republican Party of the same time. However, after Republicans gained control of Congress in 1994, their own influence assortment became equivalent to that of the Democrats, as part of a highly polarized pair of legislative influence networks. The researchers found similar levels of polarization in the influence networks of six out of the eight European parliaments they evaluated, generally during the last decade.
Rand says he hopes the current study will help generate additional research by other scholars who want to keep exploring these dynamics empirically.
“Our hope is that laying out this information gerrymandering theory, and introducing this voter game, we will spur new research around these topics to understand how these effects play out in real-world networks,” Rand says.
Support for the research was provided by the U.S. Defense Advanced Research Projects Agency, the Ethics and Governance of Artificial Intelligence Initiative of the Miami Foundation, the Templeton World Charity Foundation and the John Templeton Foundation, the Army Research Office, and the David and Lucile Packard Foundation. | | 4:59p |
A tech intervention to tame tuberculosis For tuberculosis patients, complying with a full course of treatment can be daunting and difficult. But a new experiment conducted by MIT researchers in Kenya, in collaboration with the digital health company Keheala, shows that a digital program used on mobile phones helps patients successfully finish their treatments.
The program created interactive communication between patients and providers — rather than, say, one-way reminders about medication — and also used behavioral-science insights to help motivate patients to continue their recovery regimens.
After the experimental intervention, only 4 percent of tuberculosis patients had unsuccessful treatment outcomes. For comparison, 13 percent of patients in a control group, who did not use the platform, didn’t finish their treatment.
“Patients who we supported with our mobile platform were two-thirds less likely to fail to complete treatment,” says Erez Yoeli, a research scientist at the MIT Sloan School of Management and co-author of a newly published paper outlining the experiment’s results.
The paper, “Mobile Self-verification and Support for Successful Tuberculosis Treatment,” appears today in the New England Journal of Medicine.
The co-authors are Yoeli; David Rand, an associate professor in the MIT Sloan School of Management; Jon Rathauser, CEO of Keheala, a digital health care firm based in Tel Aviv; Syon P. Bhanot, an assistant professor of economics at Swarthmore College; Maureen K. Kimenye and Eunice Mailu of the Kenya Ministry of Health; Enos Masini of the World Health Organization; and Philip Owiti of the International Union Against Tuberculosis and Lung Disease.
Tuberculosis treatments often take six months, and a substantial number of patients break off treatment when they are feeling better but have not fully recovered. If individuals stop taking medicine and relapse, it can also have harmful effects for larger communities as well, since tuberculosis is contagious.
So why do people break off their treatments?
“Stigma, access to care challenges, burdensome treatment protocols, and a lack of information, motivation, and support make it difficult for patients to do the right thing and take their medication,” says Rathauser, who founded Keheala in 2014 to try to create tools to try to overcome logistical hurdles to health care delivery in the developing world.
To conduct the study, the researchers teamed up with 17 health care clinics in Nairobi, the capital of Kenya, to create a randomized trial. There were 569 patients who participated in the intervention, and 535 patients in the control group who did not use the mobile digital program. The study was approved by the institutional review boards of Kenyatta National Hospital and the University of Nairobi.
The researchers, working with Keheala, developed a health platform for the tuberculosis patients that works on “feature phones,” which are generally limited to talk and texting functionality, and are relatively common in Kenya in areas more prone to contagious disease outbreaks.
Among other things, the program sent daily messages to patients asking them to verify that they were sticking to their medical routines. If patients did not respond to the daily messages, they would get follow-up messages and then ultimately phone calls from members of the research team who themselves had experience with TB treatment. The clinic treating the patient would be notified as well.
In this way, Yoeli explains, the program used two key behavioral principles to improve patient actions: both “increased observability” of treatment adherence and “eliminating plausible deniability,” that is, reducing their ability to make excuses for not taking their medication.
The program also provided information about tuberculosis, motivational messages, an “adherence contest,” and emphasized the community benefits of continuing treatment. “Throughout, we tried to give the individual as much credit as possible for their good deed toward the community,” adds Yoeli.
The success of the experiment, Rand says, reinforces how crucial the behavior and psychology of patients can be in these situations.
“Nonadherence with treatment regimes is a major problem in medicine that leads to serious negative health outcomes,” Rand says. “But critically, the challenge is not medical — it’s behavioral.”
As a result, Rand adds, “this is a space where behavioral science can play a major role in improving health outcomes. To me, what is so exciting about this paper is that we show how an intervention which is technologically quite simple has a really large positive impact because it is designed in a psychologically sophisticated way.”
Researchers with global expertise in the field say the findings are valuable. Jessica Haberer, an associate professor of medicine at Harvard Medical School and the director of global health research at Massachusetts General Hospital, who has read the paper, observes that “the study was well done,” adding, “The primary outcome shows great promise for the intervention.” As she notes, tuberculosis causes more deaths worldwide than any other infectious disease — an estimated 1.7 million in 2017 — and methods like the one in this experiment could reduce the incomplete treatment courses that are one source of the problem.
Haberer also notes that although the long-term tracking of tuberculosis patients is costly and difficult, in the future, the “impact of the intervention could be better assessed through long-term follow-up,” in order to find out how many patients have reached, for instance, 18 months of disease-free survival. Such longitudinal data, she notes, has been historically “underutilized” in the area of tuberculosis research.
Indeed, as the researchers acknowledge, any one study can have limitations. In this case, they would also like to see how the method fares in rural settings, which may present even greater health care access challenges.
“One key thing the next study needs to show is that this approach works not just in the city of Nairobi, but for a more diverse population, including rural patients,” Yoeli states.
In fact, the researchers are now in the midst of a three-year randomized controlled trial which expands the geographic scope of the experiment, and also evaluates its cost-effectiveness more thoroughly. The team says it would also like to apply the concept to HIV treatment programs in the future as well.
The researchers, and Keheala, received support from Development Innovation Ventures (DIV), a fund of the United States Agency for International Development (USAID) that tests solutions to global development challenges through a year-round grant competition. |
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