Institute News: Announcements

How general anesthesia reduces pain

by Sabbi Lall |

General anesthesia is medication that suppresses pain and renders patients unconscious during surgery, but whether pain suppression is simply a side effect of loss of consciousness has been unclear. Fan Wang and colleagues have now identified the circuits linked to pain suppression under anesthesia in mouse models, showing that this effect is separable from the unconscious state itself.

“Existing literature suggests that the brain may contain a switch that can turn off pain perception,” explains Fan Wang, a professor at Duke University and lead author of the study. “I had always wanted to find this switch, and it occurred to me that general anesthetics may activate this switch to produce analgesia.”

Wang, who will join the McGovern Institute in January 2021, set out to test this idea with her student, Thuy Hua, and postdoc, Bin Chen.

Pain suppressor

Loss of pain, or analgesia, is an important property of anesthetics that helps to make surgical and invasive medical procedures humane and bearable. In spite of their long use in the medical world, there is still very little understanding of how anesthetics work. It has generally been assumed that a side effect of loss of consciousness is analgesia, but several recent observations have brought this idea into question, and suggest that changes in consciousness might be separable from pain suppression.

A key clue that analgesia is separable from general anesthesia comes from the accounts of patients that regain consciousness during surgery. After surgery, these patients can recount conversations between staff or events that occurred in the operating room, despite not feeling any pain. In addition, some general anesthetics, such as ketamine, can be deployed at low concentrations for pain suppression without loss of consciousness.

Following up on these leads, Wang and colleagues set out to uncover which neural circuits might be involved in suppressing pain during exposure to general anesthetics. Using CANE, a procedure developed by Wang that can detect which neurons activate in response to an event, Wang discovered a new population of GABAergic neurons activated by general anesthetic in the mouse central amygdala.

These neurons become activated in response to different anesthetics, including ketamine, dexmedetomidine, and isoflurane. Using optogenetics to manipulate the activity state of these neurons, Wang and her lab found that they led to marked changes in behavioral responses to painful stimuli.

“The first time we used optogenetics to turn on these cells, a mouse that was in the middle of taking care of an injury simply stopped and started walked around with no sign of pain,” Wang explains.

Specifically, activating these cells blocks pain in multiple models and tests, whereas inhibiting these neurons rendered mice aversive to gentle touch — suggesting that they are involved in a newly uncovered central pain circuit.

The study has implications for both anesthesia and pain. It shows that general anesthetics have complex, multi-faceted effects and that the brain may contain a central pain suppression system.

“We want to figure out how diverse general anesthetics activate these neurons,” explains Wang. “That way we can find compounds that can specifically activate these pain-suppressing neurons without sedation. We’re now also testing whether placebo analgesia works by activating these same central neurons.”

The study also has implications for addiction as it may point to an alternative system for central pain suppression that could be a target of drugs that do not have the devastating side effects of opioids.

Fan Wang joins the McGovern Institute

by Sabbi Lall |

The McGovern Institute is pleased to announce that Fan Wang, currently a Professor at Duke University, will be joining its team of investigators in 2021. Wang is well-known for her work on sensory perception, pain, and behavior. She takes a broad, and very practical approach to these questions, knowing that sensory perception has broad implications for biomedicine when it comes to pain management, addiction, anesthesia, and hypersensitivity.

“McGovern is a dream place for doing innovative and transformative neuroscience.” – Fan Wang

“I am so thrilled that Fan is coming to the McGovern Institute,” says Robert Desimone, director of the institute and the Doris and Don Berkey Professor of Neuroscience at MIT. “I’ve followed her work for a number of years, and she is making inroads into questions that are relevant to a number of societal problems, such as how we can turn off the perception of chronic pain.”

Wang brings with her a range of techniques developed in her lab, including CANE, which precisely highlights neurons that become activated in response to a stimulus. CANE is highlighting new neuronal subtypes in long-studied brain regions such as the amygdala, and recently elucidated previously undefined neurons in the lateral parabrachial nucleus involved in pain processing.

“I am so excited to join the McGovern Institute,” says Wang. “It is a dream place for doing innovative and transformative neuroscience. McGovern researchers are known for using the most cutting-edge, multi-disciplinary technologies to understand how the brain works. I can’t wait to join the team.”

Wang earned her PhD in 1998 with Richard Axel at Columbia University, subsequently conducting postdoctoral research at Stanford University with Mark Tessier-Lavigne. Wang joined Duke University as a Professor in the Department of Neurobiology in 2003, and was later appointed the Morris N. Broad Distinguished Professor of Neurobiology at Duke University School of Medicine. Wang will join the McGovern Institute as an investigator in January 2021.

National Science Foundation announces MIT-led Institute for Artificial Intelligence and Fundamental Interactions

by Laboratory for Nuclear Science |

The U.S. National Science Foundation (NSF) announced today an investment of more than $100 million to establish five artificial intelligence (AI) institutes, each receiving roughly $20 million over five years. One of these, the NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI), will be led by MIT’s Laboratory for Nuclear Science (LNS) and become the intellectual home of more than 25 physics and AI senior researchers at MIT and Harvard, Northeastern, and Tufts universities.

By merging research in physics and AI, the IAIFI seeks to tackle some of the most challenging problems in physics, including precision calculations of the structure of matter, gravitational-wave detection of merging black holes, and the extraction of new physical laws from noisy data.

“The goal of the IAIFI is to develop the next generation of AI technologies, based on the transformative idea that artificial intelligence can directly incorporate physics intelligence,” says Jesse Thaler, an associate professor of physics at MIT, LNS researcher, and IAIFI director.  “By fusing the ‘deep learning’ revolution with the time-tested strategies of ‘deep thinking’ in physics, we aim to gain a deeper understanding of our universe and of the principles underlying intelligence.”

IAIFI researchers say their approach will enable making groundbreaking physics discoveries, and advance AI more generally, through the development of novel AI approaches that incorporate first principles from fundamental physics.

“Invoking the simple principle of translational symmetry — which in nature gives rise to conservation of momentum — led to dramatic improvements in image recognition,” says Mike Williams, an associate professor of physics at MIT, LNS researcher, and IAIFI deputy director. “We believe incorporating more complex physics principles will revolutionize how AI is used to study fundamental interactions, while simultaneously advancing the foundations of AI.”

In addition, a core element of the IAIFI mission is to transfer their technologies to the broader AI community.

“Recognizing the critical role of AI, NSF is investing in collaborative research and education hubs, such as the NSF IAIFI anchored at MIT, which will bring together academia, industry, and government to unearth profound discoveries and develop new capabilities,” says NSF Director Sethuraman Panchanathan. “Just as prior NSF investments enabled the breakthroughs that have given rise to today’s AI revolution, the awards being announced today will drive discovery and innovation that will sustain American leadership and competitiveness in AI for decades to come.”

Research in AI and fundamental interactions

Fundamental interactions are described by two pillars of modern physics: at short distances by the Standard Model of particle physics, and at long distances by the Lambda Cold Dark Matter model of Big Bang cosmology. Both models are based on physical first principles such as causality and space-time symmetries.  An abundance of experimental evidence supports these theories, but also exposes where they are incomplete, most pressingly that the Standard Model does not explain the nature of dark matter, which plays an essential role in cosmology.

AI has the potential to help answer these questions and others in physics.

For many physics problems, the governing equations that encode the fundamental physical laws are known. However, undertaking key calculations within these frameworks, as is essential to test our understanding of the universe and guide physics discovery, can be computationally demanding or even intractable. IAIFI researchers are developing AI for such first-principles theory studies, which naturally require AI approaches that rigorously encode physics knowledge.

“My group is developing new provably exact algorithms for theoretical nuclear physics,” says Phiala Shanahan, an assistant professor of physics and LNS researcher at MIT. “Our first-principles approach turns out to have applications in other areas of science and even in robotics, leading to exciting collaborations with industry partners.”

Incorporating physics principles into AI could also have a major impact on many experimental applications, such as designing AI methods that are more easily verifiable. IAIFI researchers are working to enhance the scientific potential of various facilities, including the Large Hadron Collider (LHC) and the Laser Interferometer Gravity Wave Observatory (LIGO).

“Gravitational-wave detectors are among the most sensitive instruments on Earth, but the computational systems used to operate them are mostly based on technology from the previous century,” says Principal Research Scientist Lisa Barsotti of the MIT Kavli Institute for Astrophysics and Space Research. “We have only begun to scratch the surface of what can be done with AI; just enough to see that the IAIFI will be a game-changer.”

The unique features of these physics applications also offer compelling research opportunities in AI more broadly. For example, physics-informed architectures and hardware development could lead to advances in the speed of AI algorithms, and work in statistical physics is providing a theoretical foundation for understanding AI dynamics.

“Physics has inspired many time-tested ideas in machine learning: maximizing entropy, Boltzmann machines, and variational inference, to name a few,” says Pulkit Agrawal, an assistant professor of electrical engineering and computer science at MIT, and researcher in the Computer Science and Artificial Intelligence Laboratory (CSAIL). “We believe that close interaction between physics and AI researchers will be the catalyst that leads to the next generation of machine learning algorithms.”

Cultivating early-career talent

AI technologies are advancing rapidly, making it both important and challenging to train junior researchers at the intersection of physics and AI. The IAIFI aims to recruit and train a talented and diverse group of early-career researchers, including at the postdoc level through its IAIFI Fellows Program.

“By offering our fellows their choice of research problems, and the chance to focus on cutting-edge challenges in physics and AI, we will prepare many talented young scientists to become future leaders in both academia and industry,” says MIT professor of physics Marin Soljacic of the Research Laboratory of Electronics (RLE).

IAIFI researchers hope these fellows will spark interdisciplinary and multi-investigator collaborations, generate new ideas and approaches, translate physics challenges beyond their native domains, and help develop a common language across disciplines. Applications for the inaugural IAIFI fellows are due in mid-October.

Another related effort spearheaded by Thaler, Williams, and Alexander Rakhlin, an associate professor of brain and cognitive science at MIT and researcher in the Institute for Data, Systems, and Society (IDSS), is the development of a new interdisciplinary PhD program in physics, statistics, and data science, a collaborative effort between the Department of Physics and the Statistics and Data Science Center.

“Statistics and data science are among the foundational pillars of AI. Physics joining the interdisciplinary doctoral program will bring forth new ideas and areas of exploration, while fostering a new generation of leaders at the intersection of physics, statistics, and AI,” says Rakhlin.

Education, outreach, and partnerships 

The IAIFI aims to cultivate “human intelligence” by promoting education and outreach. For example, IAIFI members will contribute to establishing a MicroMasters degree program at MIT for students from non-traditional backgrounds.

“We will increase the number of students in both physics and AI from underrepresented groups by providing fellowships for the MicroMasters program,” says Isaac Chuang, professor of physics and electrical engineering, senior associate dean for digital learning, and RLE researcher at MIT. “We also plan on working with undergraduate MIT Summer Research Program students, to introduce them to the tools of physics and AI research that they might not have access to at their home institutions.”

The IAIFI plans to expand its impact via numerous outreach efforts, including a K-12 program in which students are given data from the LHC and LIGO and tasked with rediscovering the Higgs boson and gravitational waves.

“After confirming these recent Nobel Prizes, we can ask the students to find tiny artificial signals embedded in the data using AI and fundamental physics principles,” says assistant professor of physics Phil Harris, an LNS researcher at MIT. “With projects like this, we hope to disseminate knowledge about — and enthusiasm for — physics, AI, and their intersection.”

In addition, the IAIFI will collaborate with industry and government to advance the frontiers of both AI and physics, as well as societal sectors that stand to benefit from AI innovation. IAIFI members already have many active collaborations with industry partners, including DeepMind, Microsoft Research, and Amazon.

“We will tackle two of the greatest mysteries of science: how our universe works and how intelligence works,” says MIT professor of physics Max Tegmark, an MIT Kavli Institute researcher. “Our key strategy is to link them, using physics to improve AI and AI to improve physics. We’re delighted that the NSF is investing the vital seed funding needed to launch this exciting effort.”

Building new connections at MIT and beyond

Leveraging MIT’s culture of collaboration, the IAIFI aims to generate new connections and to strengthen existing ones across MIT and beyond.

Of the 27 current IAIFI senior investigators, 16 are at MIT and members of the LNS, RLE, MIT Kavli Institute, CSAIL, and IDSS. In addition, IAIFI investigators are members of related NSF-supported efforts at MIT, such as the Center for Brains, Minds, and Machines within the McGovern Institute for Brain Research and the MIT-Harvard Center for Ultracold Atoms.

“We expect a lot of creative synergies as we bring physics and computer science together to study AI,” says Bill Freeman, the Thomas and Gerd Perkins Professor of Electrical Engineering and Computer Science and researcher in CSAIL. “I’m excited to work with my physics colleagues on topics that bridge these fields.”

More broadly, the IAIFI aims to make Cambridge, Massachusetts, and the surrounding Boston area a hub for collaborative efforts to advance both physics and AI.

“As we teach in 8.01 and 8.02, part of what makes physics so powerful is that it provides a universal language that can be applied to a wide range of scientific problems,” says Thaler. “Through the IAIFI, we will create a common language that transcends the intellectual borders between physics and AI to facilitate groundbreaking discoveries.”

Nine MIT School of Science professors receive tenure for 2020

by School of Science |

Beginning July 1, nine faculty members in the MIT School of Science have been granted tenure by MIT. They are appointed in the departments of Brain and Cognitive Sciences, Chemistry, Mathematics, and Physics.

Physicist Ibrahim Cisse investigates living cells to reveal and study collective behaviors and biomolecular phase transitions at the resolution of single molecules. The results of his work help determine how disruptions in genes can cause diseases like cancer. Cisse joined the Department of Physics in 2014 and now holds a joint appointment with the Department of Biology. His education includes a bachelor’s degree in physics from North Carolina Central University, concluded in 2004, and a doctoral degree in physics from the University of Illinois at Urbana-Champaign, achieved in 2009. He followed his PhD with a postdoc at the École Normale Supérieure of Paris and a research specialist appointment at the Howard Hughes Medical Institute’s Janelia Research Campus.

Jörn Dunkel is a physical applied mathematician. His research focuses on the mathematical description of complex nonlinear phenomena in a variety of fields, especially biophysics. The models he develops help predict dynamical behaviors and structure formation processes in developmental biology, fluid dynamics, and even knot strengths for sailing, rock climbing and construction. He joined the Department of Mathematics in 2013 after completing postdoctoral appointments at Oxford University and Cambridge University. He received diplomas in physics and mathematics from Humboldt University of Berlin in 2004 and 2005, respectively. The University of Augsburg awarded Dunkel a PhD in statistical physics in 2008.

A cognitive neuroscientist, Mehrdad Jazayeri studies the neurobiological underpinnings of mental functions such as planning, inference, and learning by analyzing brain signals in the lab and using theoretical and computational models, including artificial neural networks. He joined the Department of Brain and Cognitive Sciences in 2013. He achieved a BS in electrical engineering from the Sharif University of Technology in 1994, an MS in physiology at the University of Toronto in 2001, and a PhD in neuroscience from New York University in 2007. Prior to joining MIT, he was a postdoc at the University of Washington. Jazayeri is also an investigator at the McGovern Institute for Brain Research.

Yen-Jie Lee is an experimental particle physicist in the field of proton-proton and heavy-ion physics. Utilizing the Large Hadron Colliders, Lee explores matter in extreme conditions, providing new insight into strong interactions and what might have existed and occurred at the beginning of the universe and in distant star cores. His work on jets and heavy flavor particle production in nuclei collisions improves understanding of the quark-gluon plasma, predicted by quantum chromodynamics (QCD) calculations, and the structure of heavy nuclei. He also pioneered studies of high-density QCD with electron-position annihilation data. Lee joined the Department of Physics in 2013 after a fellowship at CERN and postdoc research at the Laboratory for Nuclear Science at MIT. His bachelor’s and master’s degrees were awarded by the National Taiwan University in 2002 and 2004, respectively, and his doctoral degree by MIT in 2011. Lee is a member of the Laboratory for Nuclear Science.

Josh McDermott investigates the sense of hearing. His research addresses both human and machine audition using tools from experimental psychology, engineering, and neuroscience. McDermott hopes to better understand the neural computation underlying human hearing, to improve devices to assist hearing impaired, and to enhance machine interpretation of sounds. Prior to joining MIT’s Department of Brain and Cognitive Sciences, he was awarded a BA in 1998 in brain and cognitive sciences by Harvard University, a master’s degree in computational neuroscience in 2000 by University College London, and a PhD in brain and cognitive sciences in 2006 by MIT. Between his doctoral time at MIT and returning as a faculty member, he was a postdoc at the University of Minnesota and New York University, and a visiting scientist at Oxford University. McDermott is also an associate investigator at the McGovern Institute for Brain Research and an investigator in the Center for Brains, Minds and Machines.

Solving environmental challenges by studying and manipulating chemical reactions is the focus of Yogesh Surendranath’s research. Using chemistry, he works at the molecular level to understand how to efficiently interconvert chemical and electrical energy. His fundamental studies aim to improve energy storage technologies, such as batteries, fuel cells, and electrolyzers, that can be used to meet future energy demand with reduced carbon emissions. Surendranath joined the Department of Chemistry in 2013 after a postdoc at the University of California at Berkeley. His PhD was completed in 2011 at MIT, and BS in 2006 at the University of Virginia. Suendranath is also a collaborator in the MIT Energy Initiative.

A theoretical astrophysicist, Mark Vogelsberger is interested in large-scale structures of the universe, such as galaxy formation. He combines observational data, theoretical models, and simulations that require high-performance supercomputers to improve and develop detailed models that simulate galaxy diversity, clustering, and their properties, including a plethora of physical effects like magnetic fields, cosmic dust, and thermal conduction. Vogelsberger also uses simulations to generate scenarios involving alternative forms of dark matter. He joined the Department of Physics in 2014 after a postdoc at the Harvard-Smithsonian Center for Astrophysics. Vogelsberger is a 2006 graduate of the University of Mainz undergraduate program in physics, and a 2010 doctoral graduate of the University of Munich and the Max Plank Institute for Astrophysics. He is also a principal investigator in the MIT Kavli Institute for Astrophysics and Space Research.

Adam Willard is a theoretical chemist with research interests that fall across molecular biology, renewable energy, and material science. He uses theory, modeling, and molecular simulation to study the disorder that is inherent to systems over nanometer-length scales. His recent work has highlighted the fundamental and unexpected role that such disorder plays in phenomena such as microscopic energy transport in semiconducting plastics, ion transport in batteries, and protein hydration. Joining the Department of Chemistry in 2013, Willard was formerly a postdoc at Lawrence Berkeley National Laboratory and then the University of Texas at Austin. He holds a PhD in chemistry from the University of California at Berkeley, achieved in 2009, and a BS in chemistry and mathematics from the University of Puget Sound, granted in 2003.

Lindley Winslow seeks to understand the fundamental particles shaped the evolution of our universe. As an experimental particle and nuclear physicist, she develops novel detection technology to search for axion dark matter and a proposed nuclear decay that makes more matter than antimatter. She started her faculty position in the Department of Physics in 2015 following a postdoc at MIT and a subsequent faculty position at the University of California at Los Angeles. Winslow achieved her BA in physics and astronomy in 2001 and PhD in physics in 2008, both at the University of California at Berkeley. She is also a member of the Laboratory for Nuclear Science.

Saxe Lab examines social impact of COVID-19

by Julie Pryor |

After being forced to relocate from their MIT dorms during the COVID19 crisis, two members of the Saxe lab are now applying their psychology skills to study the impact of mandatory relocation and social isolation on mental health.

“When ‘social distancing’ measures hit MIT, we tried to process how the implementation of these policies would impact the landscape of our social lives,” explains graduate student Heather Kosakowski, who conceived of the study late one evening with undergraduate Michelle Hung.  This landscape is broad, examining the effects of being uprooted and physically relocated from a place, but also changes in social connections, including friendships and even dating life.

MIT undergrad Michelle Hung in the Saxe lab. Photo: Michelle Hung

“I started speculating about how my life and the lives of other MIT students would change,” says Hung. “I was overwhelmed, sad, and scared. But then we realized that we were actually equipped to find the answers to our questions by conducting a study.”

Together, Kosakowski and Hung developed a survey to measure how the social behavior of MIT students, postdocs, and staff is changing over the course of the pandemic. Survey questions were designed to measure loneliness and other aspects of mental health. The survey was sent to members of the MIT community and shared on social media in mid-March, when the pandemic hit the US, and MIT made the unprecedented decision to send students home, shift to online instruction, and dramatically ramp down operations on campus.

More than 500 people responded to the initial survey, ranging in age from 18 to 60, living in cities and countries around the world. Many but not all of those who responded were affiliated with MIT. Kosakowski and Hung are sending follow-up surveys to participants every two weeks and the team plans to collect data for the duration of the pandemic.

“Throwing myself into creating the survey was a way to cope with feeling sad about leaving a community I love,” explains Hung, who flew home to California in March and admits that she struggles with feelings of loneliness now that she’s off campus.

Although it is too soon to form any conclusions about their research, Hung predicts that feelings of loneliness may actually diminish over the course of the pandemic.

“Humans have an impressive ability to adapt to change,” she says. “And I think in this virtual world, people will find novel ways to stay connected that we couldn’t have predicted.”

Whether we find ourselves feeling more or less lonely as this COVID-19 crisis comes to an end, both Kosakowski and Hung agree that it will fundamentally change life as we know it.

The Saxe lab is looking for more survey participants. To learn more about this study or to participate in the survey, click here.

 

Three from MIT awarded 2020 Guggenheim Fellowships

by Julie Pryor |

MIT faculty members Sabine Iatridou, Jonathan Gruber, and Rebecca Saxe are among 175 scientists, artists, and scholars awarded 2020 fellowships from the John Simon Guggenheim Foundation. Appointed on the basis of prior achievement and exceptional promise, the 2020 Guggenheim Fellows were selected from almost 3,000 applicants.

“It’s exceptionally encouraging to be able to share such positive news at this terribly challenging time” says Edward Hirsch, president of the foundation. “A Guggenheim Fellowship has always offered practical assistance, helping fellows do their work, but for many of the new fellows, it may be a lifeline at a time of hardship, a survival tool as well as a creative one.”

Since 1925, the foundation has granted more the $375 million in fellowships to over 18,000 individuals, including Nobel laureates, Fields medalists, poets laureate, and winners of the Pulitzer Prize, among other internationally recognized honors. This year’s MIT recipients include a linguist, an economist, and a cognitive neuroscientist.

Rebecca Saxe is an associate investigator of the McGovern Institute and the John W. Jarve (1978) Professor in Brain and Cognitive Sciences. She studies human social cognition, using a combination of behavioral testing and brain imaging technologies. She is best known for her work on brain regions specialized for abstract concepts such as “theory of mind” tasks that involve understanding the mental states of other people. She also studies the development of the human brain during early infancy. She obtained her PhD from MIT and was a Harvard University junior fellow before joining the MIT faculty in 2006. Saxe was chosen in 2012 as a Young Global Leader by the World Economic Forum, and she received the 2014 Troland Award from the National Academy of Sciences. Her TED Talk, “How we read each other’s minds” has been viewed over 3 million times.

Jonathan Gruber is the Ford Professor of Economics at MIT, the director of the Health Care Program at the National Bureau of Economic Research, and the former president of the American Society of Health Economists. He has published more than 175 research articles, has edited six research volumes, and is the author of “Public Finance and Public Policy,” a leading undergraduate text; “Health Care Reform,” a graphic novel; and “Jump-Starting America: How Breakthrough Science Can Revive Economic Growth and the American Dream.” In 2006 he received the American Society of Health Economists Inaugural Medal for the best health economist in the nation aged 40 and under. He served as deputy sssistant secretary for economic policy at the U.S. Department of the Treasury. He was a key architect of Massachusetts’ ambitious health reform effort, and became an inaugural member of the Health Connector Board, the main implementing body for that effort. He served as a technical consultant to the Obama administration and worked with both the administration and Congress to help craft the Affordable Care Act. In 2011, he was named “One of the Top 25 Most Innovative and Practical Thinkers of Our Time” by Slate magazine.

Sabine Iatridou is professor of linguistics in MIT’s Department of Linguistics and Philosophy. Her work focuses on syntax and the syntax-semantics interface, as well as comparative linguistics. She is the author and coauthor of a series of innovative papers about tense and modality that opened up whole new domains of research for the field. Since those publications, she has made foundational contributions to many branches of linguistics that connect form with meaning. She is the recipient of the National Young Investigator Award (USA), of an honorary doctorate from the University of Crete in Greece, and of an award from the Royal Dutch Academy of Sciences. She was elected fellow of the Linguistic Society of America. She is co-founder and co-director of the CreteLing Summer School of Linguistics.

“As we grapple with the difficulties of the moment, it is also important to look to the future,” says Hirsch. “The artists, writers, scholars, and scientific researchers supported by the fellowship will help us understand and learn from what we are enduring individually and collectively, and it is an honor for the foundation to help them do their essential work.”

Rising to the challenge

by Bob Desimone |

Dear members and friends of the McGovern Institute,

I am writing to you under unprecedented circumstances. Rather than walking through the vast atrium of our building, stopping to talk with researchers about their work, I am at home, as are many of you. The last couple of weeks have been a whirlwind as we downsized personnel within the institute from 100% to 10% capacity. Thank you tremendously to everybody that helped this huge transition to go smoothly.

As the dust settles, what is striking is how we are all still finding ways to connect. Faculty meetings have resumed, and have included vibrant discussions. Grants are still being written, and processed by the excellent finance team, and papers are being published. In addition, some of our researchers have turned their attention to COVID-19. To name a few, Feng Zhang is not only continuing to develop SHERLOCK, his CRISPR-based diagnostic, to rapidly detect the novel coronavirus. He also just released the How We Feel app with Ben Silbermann, CEO of Pinterest, and a team of global researchers. This app will allow symptom tracking and researchers to ask pressing questions about the symptoms and progression of the virus. McGovern Fellows, Omar Abudayyeh and Jonathan Gootenberg, are also working on rapid COVID-19 diagnostics.

Other researchers are mobilizing to bring their knowledge and skills to mitigate some of the unexpected shortages. Jill Crittenden, a research scientist in the Graybiel lab, has been working with a consortium to gather and curate information about the three main approaches for decontaminating N95 face masks. Shortages of these masks are causing health workers to resort to reusing these masks. The consortium has put together a website and a document that help hospitals and other frontline organizations to quickly, easily examine the effectiveness of, and use, different decontamination protocols. Michael Wells, a former graduate student in Guoping Feng‘s lab has been collaborating to set up a database where researchers that want to volunteer to help can offer up their skills.

Labs are also look at the effects of the response to COVID-19. Rebecca Saxe is working to understand some of the effects of social isolation. Her lab recently posted their findings indicating that loneliness in social isolation leads to neural craving responses similar to hunger. Also from the Saxe lab, Heather Kosakowski and Michelle Hung are also examining the effects of social isolation.

We also have a new page on our website that features stories from members of the McGovern community who have risen to the challenge during this pandemic. I have been so heartened to read about the ways in which our members are supporting one another during this unprecedented time.

But those not working directly on COVID-19 have also greatly impressed me. The diligent, efficient, and calm way in which everybody responded to help to wind down research will help us to ramp up quickly when the time comes, and it will come. In the meantime, please be assured that my team and I are here to help however is needed. If you are a researcher, we are still here to support your communications, grant submissions, and resolve logistical issues that may come up.

If you are interested in following our research, continue to stay tuned as excellent research continues to emerge. And if you are one of the Friends and donors that has come forward to support our research, thank you. Indeed, thank you to all readers for everything that you do to support the research missions of the McGovern Institute. Wishing all the best to you and your families at this difficult time,

 

Bob Desimone
Director

How We Feel app to track spread of COVID-19 symptoms

by Sabbi Lall |

A major challenge with containing the spread of COVID-19 in many countries, has been an ability to quickly detect infection. Feng Zhang, along with Pinterest CEO Ben Silberman, and collaborators across scientific and medical disciplines, are coming together to launch an app called How We Feel, that will allow citizen scientists to self-report symptoms.

“It is so important to find a way to connect scientists to fight this pandemic,” explained Zhang. We wanted to find a fast and agile way to ultimately build a dynamic picture of symptoms associated with the virus.”

Designed to help scientists track and stop the spread of the novel coronavirus by creating an exchange of information between the citizens and scientists at scale, the new How We Feel app does just this. The app lets people self-report symptoms in 30 seconds or less and see how others in their area are feeling. To protect user privacy, the app explicitly does not require an account sign in, and doesn’t ask for identifying information such as the user’s name, phone number, or email address before they donate their data. Reporting symptoms only takes about 30 seconds, but the data shared by users has the potential to reveal and even predict outbreak hotspots, potentially providing insight into the spread and progression of COVID-19. To further contribute to the fight against COVID-19, Ben and Divya Silbermann will donate a meal to Feeding America for every download of the How We Feel app—up to 10 million meals.

The app was created by the How We Feel Project, a nonprofit collaboration between Silbermann, doctors, and an interdisciplinary group of researchers including Feng Zhang, investigator at the McGovern Institute for Brain Research, Broad Institute, and the James and Patricia Poitras Professor of Neuroscience at MIT. Other institutions currently involved include Harvard University T.H. Chan School of Public Health and Faculty of Arts and Sciences, University of Pennsylvania, Stanford University, University of Maryland School of Medicine, and the Weizmann Institute of Science.

Silbermann partnered closely with Feng Zhang, best known for his work on CRISPR, a pioneering gene-editing technique designed to treat diseases. Zhang and Silbermann first met in high school in Iowa. As the outbreak grew in the US, they called each other to figure out how the fields of biochemistry and technology could come together to find a solution for the lack of reliable health data from testing.

“Since high school, my friend Feng Zhang and I have been talking about the potential of the internet to connect regular people and scientists for the public good,” said Ben Silbermann, co-founder and CEO of, Pinterest. “When we saw how quickly COVID-19 was spreading, it felt like a critical moment to finally build that bridge between citizens and scientists that we’ve always wanted. I believe we’ve done that with How We Feel.”

Silbermann and Zhang formed the new HWF nonprofit because they believed a fully independent organization with a keen understanding of the needs of doctors and researchers should develop and manage the app. Now, they’re looking for opportunities to collaborate globally. Zhang is working to organize an international consortium of researchers from 11 countries that have developed similar health status surveys. The consortium is called the Coronavirus Census Collective (CCC).

The How We Feel app is available for download today in the US on iOS and Android, and via the web at http://www.howwefeel.org.

New COVID-19 resource to address shortage of face masks

by Sabbi Lall |

When the COVID-19 crisis hit the United States this March, McGovern scientist Jill Crittenden wanted to help. One of her greatest concerns was the shortage of face masks, which are a key weapon for healthcare providers, frontline service workers, and the public to protect against respiratory transmission of COVID-19. For those caring for COVID-19 patients, face masks that provide a near 100% seal are essential. These critical pieces of equipment, called N95 masks, are now scarce, and healthcare workers are now faced with reusing potentially contaminated masks.

To address this, Crittenden joined a team of 60 scientists and engineers, students and clinicians, drawn from universities and the private sector to synthesize the scientific literature about mask decontamination and create a set of best practices for bad times. Today the group unveiled its website, N95decon.org, which provides a summary of this critical information.

McGovern research scientist Jill Crittenden helped the N95DECON consortium assess face mask decontamination protocols so healthcare workers can easily access them for COVID-19 protection. Photo: Caitlin Cunningham

 

“I first heard about the group from Larissa Little, a Harvard graduate student with John Doyle,” explains Crittenden, who is a research scientist in Ann Graybiel‘s lab at the McGovern Institute. “The three of us began communicating because we are all also members of the Boston-based MGB COVID-19 Innovation Center and we agreed that helping to assess the flood of information on N95 decontamination would be an important contribution.”

The team members who came together over several weeks scoured hundreds of peer-reviewed publications, and held continuous online meetings to review studies of decontamination methods that had been used to inactivate previous viral and bacterial pathogens, and to then assess the potential for these methods to neutralize the novel SARS-CoV-2 virus that causes COVID-19.

“This group is absolutely amazing,” says Crittenden. “The zoom meetings are very productive because it is all data and solutions driven. Everyone throws out ideas, what they know and what the literature source is, with the only goal being to get to a data-based consensus efficiently.”

Reliable resource

The goal of the consortium was to provide overwhelmed health officials who don’t have the time to study the literature for themselves, reliable, pre-digested scientific information about the pros and cons of three decontamination methods that offer the best options should local shortages force a choice between decontamination and reuse, or going unmasked.

The three methods involve (1) heat and humidity (2) a specific wavelength of light called ultraviolet C (UVC) and (3) treatment with hydrogen peroxide vapors (HPV). The scientists did not endorse any one method but instead sought to describe the circumstances under which each could inactivate the virus provided rigorous procedures were followed. Devices that rely on heat, for instance, could be used under specific temperature, humidity, and time parameters. With UVC devices – which emit a particular wavelength and energy level of light – considerations involve making sure masks are properly oriented to the light so the entire surface is bathed in sufficient energy. The HPV method has the potential advantage of decontaminating masks in volume, as the U.S. Food and Drug Administration, acting in this emergency, has certified certain vendors to offer hydrogen peroxide vapor treatments on a large scale. In addition to giving health officials the scientific information to assess the methods best suited to their circumstances, N95decon.org points decision makers to sources of reliable and detailed how-to information provided by other organizations, institutions, and commercial services.

“While there is no perfect method for decontamination of N95 masks, it is crucial that decision-makers and users have as much information as possible about the strengths and weaknesses of various approaches,” said Manu Prakash, an associate professor of bioengineering at Stanford who helped coordinate this ad hoc, volunteer undertaking. “Manufacturers currently do not recommend N95 mask reuse. We aim to provide information and evidence in this critical time to help those on the front lines of this crisis make risk-management decisions given the specific conditions and limitations they face.”

The researchers stressed that decontamination does not solve the N95 shortage, and expressed the hope that new masks should be made available in large numbers as soon as possible so that health care workers and first providers could be issued fresh protective gear whenever needed as specified by the non-emergency guidelines set by the U.S. the Centers for Disease Control.

Forward thinking

Meanwhile, these ad hoc volunteers have pledged to continue working together to update N95decon.org website as new information becomes available, and to coordinate their efforts to do research to plug the gaps in current knowledge to avoid duplication of effort.

“We are, at heart, a group of people that want to help better equip hospitals and healthcare personnel in this time of crisis,” says Brian Fleischer, a surgeon at the University of Chicago Medical Center and a member of the N95DECON consortium. “As a healthcare provider, many of my colleagues across the country have expressed concern with a lack of quality information in this ever-evolving landscape. I have learned a great deal from this team and I look forward to our continued collaboration to positively affect change.”

Crittenden is hopeful that the new website will help healthcare workers make informed decisions about the safest methods available for decontamination and reuse of N95 masks. “I know physicians personally who are very grateful that teams of scientists are doing the in-depth data analysis so that they can feel confident in what is best for their own health,” she says.

The members of the N95decon.org team come from institutions including UC Berkeley, the University of Chicago, Stanford, Georgetown University, Harvard University, Seattle University, University of Utah, the McGovern Institute for Brain Research at MIT, the University of Michigan, and from Consolidated Sterilizers and X, the Moonshot Factory.