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Monday, May 1st, 2017

    Time Event
    10:00a
    Detecting walking speed with wireless signals

    We’ve long known that blood pressure, breathing, body temperature and pulse provide an important window into the complexities of human health. But a growing body of research suggests that another vital sign – how fast you walk – could be a better predictor of health issues like cognitive decline, falls, and even certain cardiac or pulmonary diseases.

    Unfortunately, it’s hard to accurately monitor walking speed in a way that’s both continuous and unobtrusive. Professor Dina Katabi’s group at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has been working on the problem, and believes that the answer is to go wireless.

    In a new paper, the team presents “WiGait,” a device that can measure the walking speed of multiple people with 95 to 99 percent accuracy using wireless signals.

    The size of a small painting, the device can be placed on the wall of a person’s house and its signals emit roughly one-hundredth the amount of radiation of a standard cellphone. It builds on Katabi’s previous work on WiTrack, which analyzes wireless signals reflected off people’s bodies to measure a range of behaviors from breathing and falling to specific emotions

    “By using in-home sensors, we can see trends in how walking speed changes over longer periods of time,” says lead author and PhD student Chen-Yu Hsu. “This can provide insight into whether someone should adjust their health regimen, whether that’s doing physical therapy or altering their medications.”

    WiGait is also 85 to 99 percent accurate at measuring a person’s stride length, which could allow researchers to better understand conditions like Parkinson’s disease that are characterized by reduced step size.

    Hsu and Katabi developed WiGait with CSAIL PhD student Zachary Kabelac and master’s student Rumen Hristov, alongside undergraduate Yuchen Liu from the Hong Kong University of Science and Technology, and Assistant Professor Christine Liu from the Boston University School of Medicine. The team will present their paper in May at ACM’s CHI Conference on Human Factors in Computing Systems in Colorado.  

    How it works

    Today, walking speed is measured by physical therapists or clinicians using a stopwatch. Wearables like FitBit can only roughly estimate speed based on step count, and GPS-enabled smartphones are similarly inaccurate and can’t work indoors. Cameras are intrusive and can only monitor one room. VICON motion tracking is the only method that’s comparably accurate to WiGate, but it is not widely available enough to be practical for monitoring day-to-day health changes.

    Meanwhile, WiGait measures walking speed with a high level of granularity, without requiring that the person wear or carry a sensor. It does so by analyzing the surrounding wireless signals and their reflections off a person’s body. The CSAIL team’s algorithms can also distinguish walking from other movements, such as cleaning the kitchen or brushing one's teeth.

    Katabi says the device could help reveal a wealth of important health information, particularly for the elderly. A change in walking speed, for example, could mean that the person has suffered an injury or is at an increased risk of falling. The system's feedback could even help the person determine if they should move to a different environment such as an assisted-living home.

    “Many avoidable hospitalizations are related to issues like falls, congestive heart disease, or chronic obstructive pulmonary disease, which have all been shown to be correlated to gait speed,” Katabi says. “Reducing the number of hospitalizations, even by a small amount, could vastly improve health care costs.”

    The team developed WiGait to be more privacy-minded than cameras, showing you as nothing more than a moving dot on a screen. In the future they hope to train it on people with walking impairments from Parkinson’s, Alzheimer’s or multiple sclerosis, to help physicians accurately track disease progression and adjust medications.

    “The true novelty of this device is that it can map major metrics of health and behavior without any active engagement from the user, which is especially helpful for the cognitively impaired,” says Ipsit Vahia, a geriatric clinician at McLean Hospital and Harvard Medical School, who was not involved in the research. “Gait speed is a proxy indicator of many clinically important conditions, and down the line this could extend to measuring sleep patterns, respiratory rates, and other vital human behaviors.”

    10:59a
    New model could speed up colon cancer research

    Using the gene-editing system known as CRISPR, MIT researchers have shown in mice that they can generate colon tumors that very closely resemble human tumors. This advance should help scientists learn more about how the disease progresses and allow them to test new therapies.

    Once formed, many of these experimental tumors spread to the liver, just like human colon cancers often do. These metastases are the most common cause of death from colon cancer.

    “That’s been a missing piece in the study of colon cancer. There is really no reliable method for recapitulating the metastatic progression from a primary tumor in the colon to the liver,” says Omer Yilmaz, an MIT assistant professor of biology, a member of MIT’s Koch Institute for Integrative Cancer Research, and the lead senior author of the study, which appears in the May 1 issue of Nature Biotechnology.

    The study builds on recent work by Tyler Jacks, the director of the Koch Institute, who has also used CRISPR to generate lung and liver tumors in mice.

    "CRISPR-based technologies have begun to revolutionize many aspects of cancer research, including building mouse models of the disease with greater speed and greater precision. This study is a good example of both,” says Jacks, who is also an author of the Nature Biotechnology paper.

    The paper’s lead authors are Jatin Roper, a research affiliate at the Koch Institute and a gastroenterologist at Tufts Medical Center, and Tuomas Tammela, a research scientist at the Koch Institute.

    Mimicking human tumors

    For many years, cancer biologists have taken two distinct approaches to modeling cancer. One is to grow immortalized human cancer cells known as cancer cell lines in a lab dish. “We’ve learned a lot by studying these two-dimensional cell lines, but they have limitations,” Yilmaz says. “They don’t really reproduce the complex in vivo environment of a tumor.”

    Another widely used technique is genetically engineering mice with mutations that predispose them to develop cancer. However, it can take years to breed such mice, especially if they have more than one cancer-linked mutation.

    Recently, researchers have begun using CRISPR to generate cancer models. CRISPR, originally discovered by biologists studying the bacterial immune system, consists of a DNA-cutting enzyme called Cas9 and short RNA guide strands that target specific sequences of the genome, telling Cas9 where to make its cuts. Using this process, scientists can make targeted mutations in the genomes of living animals, either deleting genes or inserting new ones.

    To induce cancer mutations, the investigators package the genes for Cas9 and the RNA guide strand into viruses called lentiviruses, which are then injected into the target organs of adult mice.

    Yilmaz, who studies colon cancer and how it is influenced by genes, diet, and aging, decided to adapt this approach to generate colon tumors in mice. He and members of his lab were already working on a technique for growing miniature tissues known as organoids — three-dimensional growths that, in this case, accurately replicate the structure of the colon.

    In the new paper, the researchers used CRISPR to introduce cancer-causing mutations into the organoids and then delivered them via colonoscopy to the colon, where they attached to the lining and formed tumors.

    “We were able to transplant these 3-D mini-intestinal tumors into the colon of recipient mice and recapitulate many aspects of human disease,” Yilmaz says.

    More accurate modeling

    Once the tumors are established in the mice, the researchers can introduce additional mutations at any time, allowing them to study the influence of each mutation on tumor initiation, progression, and metastasis.

    Almost 30 years ago, scientists discovered that colon tumors in humans usually acquire cancerous mutations in a particular order, but they haven’t been able to accurately model this in mice until now.

    “In human patients, mutations never occur all at once,” Tammela says. “Mutations are acquired over time as the tumor progresses and becomes more aggressive, more invasive, and more metastatic. Now we can model this in mice.”

    To demonstrate that ability, the MIT team delivered organoids with a mutated form of the APC gene, which is the cancer-initiating mutation in 80 percent of colon cancer patients. Once the tumors were established, they introduced a mutated form of KRAS, which is commonly found in colon and many other cancers.

    The scientists also delivered components of the CRISPR system directly into the colon wall to quickly model colon cancer by editing the APC gene. They then added CRISPR components to also edit the gene for P53, which is commonly mutated in colon and other cancers.

    “These new approaches reduce the time frame to develop genetically engineered mice from two years to just a few months, and involve very basic gene engineering with CRISPR,” Roper says. “We used P53 and KRAS to demonstrate the principle that the CRISPR editing approach and the organoid transplantation approach can be used to very quickly model any possible cancer-associated gene.”

    In this study, the researchers also showed that they could grow tumor cells from patients into organoids that could be transplanted into mice. This could give doctors a way to perform “personalized medicine” in which they test various treatment options against a patient’s own tumor cells.

    Fernando Camargo, a professor of stem cell and regenerative biology at Harvard University, says the study represents an important advance in colon cancer research.

    “It allows investigators to have a very flexible model to look at multiple aspects of colorectal cancer, from basic biology of the genes involved in progression and metastasis, to testing potential drugs,” says Camargo, who was not involved in the research.

    Yilmaz’ lab is now using these techniques to study how other factors such as metabolism, diet, and aging affect colon cancer development. The researchers are also using this approach to test potential new colon cancer drugs.

    The research was funded by the Howard Hughes Medical Institute, the National Institutes of Health, the Department of Defense, the V Foundation V Scholar Award, the Sidney Kimmel Scholar Award, the Pew-Stewart Trust Scholar Award, the Koch Institute Frontier Research Program through the Kathy and Curt Marble Cancer Research Fund, the American Federation of Aging Research, and the Hope Funds for Cancer Research.

    4:00p
    Testing their patients

    Waiting to see a doctor is frustrating, as anyone who has spent too much time flipping through old magazines or warily eyeing coughing strangers can attest. According to a new study by MIT researchers, Medicaid patients experience more of this frustration than people with private health insurance.

    Consider: Medicaid recipients are 20 percent more likely to wait more than 20 minutes to begin a scheduled appointment, compared to privately insured patients. The median wait time of Medicaid enrollees is longer as well. As the findings show, much — but not all — of this disparity is because Medicaid patients tend to use providers who generally have longer wait times for their patients.

    The results shed new light on the full range of experiences people have with the health care system, even apart from treatment outcomes.

    “People want to focus on health care quality, but if you’ve ever had any experience with the health care system, you know there are a lot of nonhealth amenities associated with your visit,” says Amy Finkelstein, the John and Jennie S. MacDonald Professor of Economics at MIT and co-author of a newly published paper that details the results of the study.

    The study uses the issue of wait times to compare the quality of health care access provided through public means, such as Medicaid, and through private insurance.

    “It’s a different way of looking at an older problem,” says Tamar Oostrom, a doctoral candidate in MIT’s Department of Economics, who is the lead author of the new paper.

    The study also uncovered a variety of new findings about differences in wait times. For instance, wait times are generally shorter in the mornings, as well as in larger medical practices. People spend less time waiting for doctors in New England than in any other region of the country. And here’s a data point that may reassure some harried parents: Young children are late for 40 percent of their medical visits.

    The paper, “Outpatient Office Wait Times And Quality of Care for Medicaid Patients,” is being published today in the journal Health Affairs. The authors are Oostrom, Finkelstein, and Liran Einav, a professor in the Department of Economics at Stanford University.

    The researchers examined 21.4 million anonymized records from athenahealth, the electronic records provider. The data cover all outpatient visits the firm processed in 2013, from 2,581 different medical practices. Wait time was measured based on information the athenahealth software captures showing the patient’s arrival and check-in times, the scheduled appointment time, and the time when the “intake” phase of the visit begins.

    The study accounted for varying characteristics of both providers and the nature of the medical visits. This approach allowed the researchers to determine that most of the variation in waiting time, between Medicaid patients and privately insured patients, is attributable to the type of provider in question.

    “Most of this difference in wait times is explained by the practices and providers Medicaid recipients see,” Oostrom says. There may be many reasons for this: For instance, Medicaid patients may be more likely to visit providers with larger loads of patients in the first place, making delays more likely.

    And yet, even when adjusting for the type of provider, Medicaid patients still wait 5 percent longer than patients with private insurance, something the researchers regard as difficult to interpret. In the paper, they suggest this could reflect “triaging of patients by insurance status within an office.” Medicaid patients also face more pronounced delays in states with less extensive Medicaid reimbursement policies.

    All told, the average wait times were 4.1 minutes for patients with private insurance and 4.6 minutes for patients enrolled in Medicaid. Finkelstein, for one, acknowledges she was surprised by those figures.

    “My intuition, going into it, was that wait times were going to be much longer, based on my own biased recall,” she says. “We tend to remember that visit where we waited forever. A key value of measuring wait times based on information captured by office software is it doesn’t suffer from such biased recall.”

    That said, Finkelstein adds, she was not surprised to see some of the more specific results, such as the fact that families with young children are so frequently running late to their appointments.

    In the past, Finkelstein has collaborated with several other researchers on groundbreaking studies about Medicaid, the health care insurance program that often gives coverage to low-income citizens and is funded by both the federal government and states. Her research has shown that newly enrolled Medicaid patients make more trips overall to providers after acquiring insurance, make more visits to emergency rooms, and benefit financially from having insurance, among other findings.

    The current study could open up new questions about the influence of the overall experience during health care visits. Future research could explore how negative perceptions of wait times affect the willingness of patients to seek more care. And the study bears on what researchers call the “opportunity cost” of visiting the doctor — that is, the fact that patients often have to take time out from their jobs to receive health care.

    “I hope this is the tip of the iceberg for us and others in trying to think about the nonhealth amenities in the health care system,” Finkelstein says.

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