News in Briefs

Over the past few decades, scientists have developed many devices that can reopen clogged arteries, including angioplasty balloons and metallic stents. While generally effective, each of these treatments has drawbacks, including the risk of side effects.

A new study from MIT analyzes the potential usefulness of a new treatment that combines the benefits of angioplasty balloons and drug-releasing stents, but may pose fewer risks. With this new approach, a balloon is inflated in the artery for only a brief period, during which it releases a drug that prevents cells from accumulating and clogging the arteries over time.

While approved for limited use in Europe, these drug-coated balloons are still in development in the United States and have not received FDA approval. The MIT study, which models the behavior of the balloons, should help scientists optimize their performance and aid regulators in evaluating their effectiveness and safety.

“Until now, people who evaluate such technology could not distinguish hype from promise,” says Elazer Edelman, the Thomas D. and Virginia W. Cabot Professor of Health Sciences and Technology and senior author of the paper describing the study, which appeared online recently in the journal Circulation.

Lead author of the paper is Vijaya Kolachalama, a former MIT postdoc who is now a principal member of the technical staff at the Charles Stark Draper Laboratory.

Evolution of technology

Until the late 1970s, the standard treatment for patients with blocked arteries near the heart was bypass surgery. Doctors then turned to the much less invasive process of reopening arteries with angioplasty balloons. Angioplasty quickly became the standard treatment for narrowed arteries, but it is not always a long-term solution because the arteries can eventually collapse again.

To prevent that, scientists developed stents — metal, cage-like structures that can hold an artery open indefinitely. However, these stents have problems of their own: When implanted, they provoke an immune response that can cause cells to accumulate near the stent and clog the artery again.

In 2003, the FDA approved the first drug-eluting stent for use in the United States, which releases drugs that prevent cells from clumping in the arteries. Drug-eluting stents are now the primary choice for treating blocked arteries, but they also have side effects: The drugs can cause blood to clot over time, which has led to death in some patients. Patients who receive these stents now need to take other medications, such as aspirin and Plavix, to counteract blood clotting.

Edelman’s lab is investigating a possible alternative to the current treatments: drug-coated balloons. “We’re trying to understand how and when this therapy could work and identify the conditions in which it may not,” Kolachalama says. “It has its merits; it has some disadvantages.”

Modeling drug release

The drug-coated balloons are delivered by a catheter and inflated at the narrowed artery for about 30 seconds, sometimes longer. During that time, the balloon coating, containing a drug such as Zotarolimus, is released from the balloon. The properties of the coating allow the drug to be absorbed in the body’s tissues. Once the drug is released, the balloon is removed.

In their new study, Kolachalama, Edelman and colleagues set out to rigorously characterize the properties of the drug-coated balloons. After performing experiments in tissue grown in the lab and in pigs, they developed a computer model that explains the dynamics of drug release and distribution. They found that factors such as the size of the balloon, the duration of delivery time, and the composition of the drug coating all influence how long the drug stays at the injury site and how effectively it clears the arteries.

One significant finding is that when the drug is released, some of it sticks to the lining of the blood vessels. Over time, that drug is slowly released back into the tissue, which explains why the drug’s effects last much longer than the initial 30-second release period.

“This is the first time we can explain the reasons why drug-coated balloons can work,” Kolachalama says. “The study also offers areas where people can consider thinking about optimizing drug transfer and delivery.”

Most previous efforts to develop drug-coated balloons have focused on a different drug, Paclitaxel. “For the first time, this study establishes a basis for drug-coated balloons based on Zotarolimus to work,” says Juan Granada, executive director of the Cardiovascular Research Foundation Skirball Research Center, who was not part of the research team. “It explains in a very elegant way the important implications for technology development based on these findings.”

In future studies, Edelman, Kolachalama and colleagues plan to further examine how blood flow affects drug delivery. They also plan to study a variety of different drugs and drug coating compositions, as well as how the balloons behave in different types of arteries.

The National Institutes of Health and Abbott Vascular funded the research.
By web.mit.edu

Clumps of proteins that accumulate in brain cells are a hallmark of neurological diseases such as dementia, Parkinson’s disease and Alzheimer’s disease. Over the past several years, there has been much controversy over the structure of one of those proteins, known as alpha synuclein.

MIT computational scientists have now modeled the structure of that protein, most commonly associated with Parkinson’s, and found that it can take on either of two proposed states — floppy or rigid. The findings suggest that forcing the protein to switch to the rigid structure, which does not aggregate, could offer a new way to treat Parkinson’s, says Collin Stultz, an associate professor of electrical engineering and computer science at MIT.

“If alpha synuclein can really adopt this ordered structure that does not aggregate, you could imagine a drug-design strategy that stabilizes these ordered structures to prevent them from aggregating,” says Stultz, who is the senior author of a paper describing the findings in a recent issue of the Journal of the American Chemical Society.

For decades, scientists have believed that alpha synuclein, which forms clumps known as Lewy bodies in brain cells and other neurons, is inherently disordered and floppy. However, in 2011 Harvard University neurologist Dennis Selkoe and colleagues reported that after carefully extracting alpha synuclein from cells, they found it to have a very well-defined, folded structure.

That surprising finding set off a scientific controversy. Some tried and failed to replicate the finding, but scientists at Brandeis University, led by Thomas Pochapsky and Gregory Petsko, also found folded (or ordered) structures in the alpha synuclein protein.

Stultz and his group decided to jump into the fray, working with Pochapsky’s lab, and developed a computer-modeling approach to predict what kind of structures the protein might take. Working with the structural data obtained by the Brandeis researchers, Stultz created a model that calculates the probabilities of many different possible structures, to determine what set of structures would best explain the experimental data.

The calculations suggest that the protein can rapidly switch among many different conformations. At any given time, about 70 percent of individual proteins will be in one of the many possible disordered states, which exist as single molecules of the alpha synuclein protein. When three or four of the proteins join together, they can assume a mix of possible rigid structures, including helices and beta strands (protein chains that can link together to form sheets).

“On the one hand, the people who say it’s disordered are right, because a majority of the protein is disordered,” Stultz says. “And the people who would say that it’s ordered are not wrong; it’s just a very small fraction of the protein that is ordered.”

“This paper seems to bridge the gap” between the two camps, says Trevor Creamer, an associate professor of molecular and cellular biochemistry at the University of Kentucky who was not involved in this research. Also important is the model’s prediction of new structures for the protein that experimental biologists can now look for, Creamer adds.

The MIT researchers also found that when alpha synuclein adopts an ordered structure, similar to that described by Selkoe and co-workers, the portions of the protein that tend to aggregate with other molecules are buried deep within the structure, explaining why those ordered forms do not clump together.

Stultz is now working to figure out what controls the protein’s configuration. There is some evidence that other molecules in the cell can modify alpha synuclein, forcing it to assume one conformation or another.

“If this structure really does exist, we have a new way now of potentially designing drugs that will prevent aggregation of alpha synuclein,” he says.

Lead authors of the paper are Thomas Gurry, an MIT graduate student in computational and systems biology, and Orly Ullman, an MIT graduate student in chemistry; other authors are Pochapsky, a professor of chemistry and biochemistry at Brandeis; Iva Perovic, a graduate student in Pochapsky’s lab; and Charles Fisher, a Harvard graduate student in biophysics.
By web.mit.edu

Professor Peter Szolovits has been named the recipient of the 2013 Morris F. Collen Award of Excellence. The award is presented annually by the American College of Medical Informatics (ACMI) in honor of Morris F. Collen, a pioneer in the field.

According to the ACMI, the award is the “highest honor in informatics that is presented by the American College of Medical Informatics to an individual whose personal commitment and dedication to biomedical informatics has made a lasting impression on healthcare and biomedicine.”

Szolovits leads the Clinical Decision Making Group at CSAIL and is a professor in the MIT Department of Electrical Engineering and Computer Science and in the Harvard/MIT Division of Health Sciences and Technology (HST).

His research centers on the application of artificial intelligence methods to problems of medical decision-making, the use of natural language processing to extract meaningful data from clinical narratives to support translational medicine, and the design of information systems for health care institutions and patients. Szolovits has worked on problems of diagnosis, therapy planning, execution and monitoring for various medical conditions, computational aspects of genetic counseling, controlled sharing of health information, and privacy and confidentiality issues in medical record systems.
By web.mit.edu

Since the mid-1800s, doctors have used drugs to induce general anesthesia in patients undergoing surgery. Despite their widespread use, little is known about how these drugs create such a profound loss of consciousness.

In a new study that tracked brain activity in human volunteers over a two-hour period as they lost and regained consciousness, researchers from MIT and Massachusetts General Hospital (MGH) have identified distinctive brain patterns associated with different stages of general anesthesia. The findings shed light on how one commonly used anesthesia drug exerts its effects, and could help doctors better monitor patients during surgery and prevent rare cases of patients waking up during operations.

Anesthesiologists now rely on a monitoring system that takes electroencephalogram (EEG) information and combines it into a single number between zero and 100. However, that index actually obscures the information that would be most useful, according to the authors of the new study, which appears in the Proceedings of the National Academy of Sciences the week of March 4.

“When anesthesiologists are taking care of someone in the operating room, they can use the information in this article to make sure that someone is unconscious, and they can have a specific idea of when the person may be regaining consciousness,” says senior author Emery Brown, an MIT professor of brain and cognitive sciences and health sciences and technology and an anesthesiologist at MGH.

Lead author of the paper is Patrick Purdon, an instructor of anesthesia at MGH and Harvard Medical School.

Distinctive patterns

Last fall, Purdon, Brown and colleagues published a study of brain activity in epileptic patients as they went under anesthesia. Using electrodes that had been implanted in the patients’ brains as part of their treatment for epilepsy, the researchers were able to identify a signature EEG pattern that emerged during anesthesia.

In the new study, the researchers studied healthy volunteers, measuring their brain activity with an array of 64 electrodes attached to the scalp. Not only did they find patterns that appeared to correspond to what they saw in last year’s study, they were also able to discern much more detail, because they gave the dose of propofol over a longer period of time and followed subjects until they came out of anesthesia.

While the subjects received propofol, the researchers monitored their responsiveness to sounds. Every four seconds, the subjects heard either a mechanical tone or a word, such as their name. The researchers measured EEG activity throughout the process, as the subjects pressed a button to indicate whether they heard the sound.

As the subjects became less responsive, distinct brain patterns appeared. Early on, when the subjects were just beginning to lose consciousness, the researchers detected an oscillation of brain activity in the low frequency (0.1 to 1 hertz) and alpha frequency (8 to 12 hertz) bands, in the frontal cortex. They also found a specific relationship between the oscillations in those two frequency bands: Alpha oscillations peaked as the low-frequency waves were at their lowest point.

When the brain reached a slightly deeper level of anesthesia, a marked transition occurred: The alpha oscillations flipped so their highest points occurred when the low frequency waves were also peaking.

The researchers believe that these alpha and low-frequency oscillations, which they also detected in last year’s study, produce unconsciousness by disrupting normal communication between different brain regions. The oscillations appear to constrain the amount of information that can pass between the frontal cortex and the thalamus, which normally communicate with each other across a very broad frequency band to relay sensory information and control attention.

The oscillations also prevent different parts of the cortex from coordinating with each other. In last year’s study, the researchers found that during anesthesia, neurons within small, localized brain regions are active for a few hundred milliseconds, then shut off again for a few hundred milliseconds. This flickering of activity, which creates the slow oscillation pattern, prevents brain regions from communicating normally.

Better anesthesia monitoring

When the researchers began to slowly decrease the dose of propofol, to bring the subjects out of anesthesia, they saw a reversal of the brain activity patterns that appeared when the subjects lost consciousness. A few minutes before regaining consciousness, the alpha oscillations flipped so that they were at their peak when the low-frequency waves were at their lowest point.

“That is the signature that would allow someone to determine if a patient is coming out of anesthesia too early, with this drug,” Purdon says.

Cases in which patients regain consciousness during surgery are alarming but very rare, with one or two occurrences in 10,000 operations, Brown says.

“It’s not something that we’re fighting with every day, but when it does happen, it creates this visceral fear, understandably, in the public. And anesthesiologists don’t have a way of responding because we really don’t know when you’re unconscious,” he says. “This is now a solved problem.”

Purdon and Brown are now starting a training program for anesthesiologists and residents at MGH to train them to interpret the information necessary to measure depth of anesthesia. That information is available through the EEG monitors that are now used during most operations, Purdon says. Because propofol is the most widely used anesthesia drug, the new findings should prove valuable for most operations.

Michael Ramsay, the chief of anesthesiology at Baylor University Medical Center, says he believes the new findings will improve patient care. The current monitoring system “has never been that accurate, and no one’s ever been able to show that it prevents awareness,” says Ramsay, who was not part of the research team. “What they have done is really brought back the value of interpreting the EEG signal that you’re looking at.”

In follow-up studies, the researchers are now studying the brain activity patterns produced by other anesthesia drugs.

The research was funded by the National Institutes of Health, including an NIH Director’s Pioneer Award, New Innovator Award and K-Award, and the Harvard Clinical and Translational Science Center.
By web.mit.edu

A typical cancer cell has thousands of mutations scattered throughout its genome and hundreds of mutated genes. However, only a handful of those genes, known as drivers, are responsible for cancerous traits such as uncontrolled growth. Cancer biologists have largely ignored the other mutations, believing they had little or no impact on cancer progression.

But a new study from MIT, Harvard University, the Broad Institute and Brigham and Women’s Hospital reveals, for the first time, that these so-called passenger mutations are not just along for the ride. When enough of them accumulate, they can slow or even halt tumor growth.

The findings, reported in this week’s Proceedings of the National Academy of Sciences, suggest that cancer should be viewed as an evolutionary process whose course is determined by a delicate balance between driver-propelled growth and the gradual buildup of passenger mutations that are damaging to cancer, says Leonid Mirny, an associate professor of physics and health sciences and technology at MIT and senior author of the paper.

Furthermore, drugs that tip the balance in favor of the passenger mutations could offer a new way to treat cancer, the researchers say, beating it with its own weapon — mutations. Although the influence of a single passenger mutation is minuscule, “collectively they can have a profound effect,” Mirny says. “If a drug can make them a little bit more deleterious, it’s still a tiny effect for each passenger, but collectively this can build up.”

Lead author of the paper is Christopher McFarland, a graduate student at Harvard. Other authors are Kirill Korolev, a Pappalardo postdoctoral fellow at MIT, Gregory Kryukov, a senior computational biologist at the Broad Institute, and Shamil Sunyaev, an associate professor at Brigham and Women’s.

Power struggle

Cancer can take years or even decades to develop, as cells gradually accumulate the necessary driver mutations. Those mutations usually stimulate oncogenes such as Ras, which promotes cell growth, or turn off tumor-suppressing genes such as p53, which normally restrains growth.

Passenger mutations that arise randomly alongside drivers were believed to be fairly benign: In natural populations, selection weeds out deleterious mutations. However, Mirny and his colleagues suspected that the evolutionary process in cancer can proceed differently, allowing mutations with only a slightly harmful effect to accumulate.

To test this theory, the researchers created a computer model that simulates cancer growth as an evolutionary process during which a cell acquires random mutations. These simulations followed millions of cells: every cell division, mutation and cell death.

They found that during the long periods between acquisition of driver mutations, many passenger mutations arose. When one of the cancerous cells gains a new driver mutation, that cell and its progeny take over the entire population, bringing along all of the original cell’s baggage of passenger mutations. “Those mutations otherwise would never spread in the population,” Mirny says. “They essentially hitchhike on the driver.”

This process repeats five to 10 times during cancer development; each time, a new wave of damaging passengers is accumulated. If enough deleterious passengers are present, their cumulative effects can slow tumor growth, the simulations found. Tumors may become dormant, or even regress, but growth can start up again if new driver mutations are acquired. This matches the cancer growth patterns often seen in human patients.

“Cancer may not be a sequence of inevitable accumulation of driver events, but may be actually a delicate balance between drivers and passengers,” Mirny says. “Spontaneous remissions or remissions triggered by drugs may actually be mediated by the load of deleterious passenger mutations.”

When they analyzed passenger mutations found in genomic data taken from cancer patients, the researchers found the same pattern predicted by their model — accumulation of large quantities of slightly deleterious mutations.

The findings “really put front and center these mutations that we have often seen as not being clinically relevant,” says Denis Wirtz, a professor of chemical and biomolecular engineering at Johns Hopkins University, who was not part of the research team. “This suggests the opportunity for an alternative cancer therapy, which is always exciting.”

Tipping the balance

In computer simulations, the researchers tested the possibility of treating tumors by boosting the impact of deleterious mutations. In their original simulation, each deleterious passenger mutation reduced the cell’s fitness by about 0.1 percent. When that was increased to 0.3 percent, tumors shrank under the load of their own mutations.

The same effect could be achieved in real tumors with drugs that interfere with proteins known as chaperones, Mirny suggests. After proteins are synthesized, they need to be folded into the correct shape, and chaperones help with that process. In cancerous cells, chaperones help proteins fold into the correct shape even when they are mutated, helping to suppress the effects of deleterious mutations.

Several potential drugs that inhibit chaperone proteins are now in clinical trials to treat cancer, although researchers had believed that they acted by suppressing the effects of driver mutations, not by enhancing the effects of passengers.

In current studies, the researchers are comparing cancer cell lines that have identical driver mutations but a different load of passenger mutations, to see which grow faster. They are also injecting the cancer cell lines into mice to see which are likeliest to metastasize.

The research was funded by the National Institutes of Health/National Cancer Institute Physical Sciences Oncology Center at MIT.
By web.mit.edu

With the recent launch of MIT’s Institute for Medical Engineering and Science, MIT News examines research with the potential to reshape medicine and health care through new scientific knowledge, novel treatments and products, better management of medical data, and improvements in health-care delivery.

At the end of 2012, the National Public Radio show “Fresh Air” featured a segment in which its linguistics commentator argued that “big data” should be the word of the year. The term refers not only to the deluge of data produced by the proliferation of Internet-connected, sensor-studded portable devices but also to innovative techniques for analyzing that data; and big data has received a good deal of credit for Barack Obama’s victory in the last presidential election.

Certainly, the term was in heavy use around MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), which in 2012 launched a new big-data initiative called bigdata@CSAIL. Several of the researchers affiliated with bigdata@CSAIL are developing new techniques for processing medical data, to make it more accessible to both physicians and patients and to find correlations that could improve diagnosis or choice of therapies.

Peter Szolovits, a professor in the Department of Electrical Engineering and Computer Science (EECS) and the Harvard-MIT Division of Health Sciences and Technology (HST), directs the Clinical Decision Making group at CSAIL, which is researching a whole host of methods for bringing artificial intelligence to bear on medical care. The group participates in a large initiative, sponsored by the National Institutes of Health, to create a database system that would link genomic data and clinical data so that physicians could more easily test hypotheses about connections between genetic variations and particular diseases.

The group is also investigating ways to automatically extract useful data from doctors’ free-form clinical notes. Recently, the group presented a promising new approach to the problem of word-sense disambiguation, or inferring from context which of a word’s several meanings is intended. (The word “discharge,” for instance, shows up frequently in physicians’ notes, but with radically different meanings.) The same line of research has spun off several papers on anonymizing medical data — automatically stripping it of identifying information to protect patients’ privacy.

Tracking disease

John Guttag, the Dugald C. Jackson Professor in EECS and another member of bigdata@CSAIL, directs CSAIL’s Data-Driven Medicine group. Among other things, the group is investigating techniques for detecting and predicting hospital-borne infections. In several papers last year, Jenna Wiens, a graduate student in the group, used machine-learning techniques to comb through dozens of variables — some static, such as age and complaint upon admission, and some dynamic, such as vital signs and lab results — to find patients that suggested elevated risk of infection with the nasty intestinal bug Clostridium difficile.

The one member of bigdata@CSAIL who is not already a CSAIL researcher is Sandy Pentland of the MIT Media Lab. Pentland’s group mines data from portable sensors — whether special-purpose devices or cellphones — to find data pertinent to a whole host of questions, from how to improve productivity at large companies to the likelihood that two people who just met will start dating. But the same techniques are also useful for epidemiological research. At last year’s International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, Pentland and his students won the best-paper award for a study tracking the spread of flu through the social networks of a group of MIT students.

Chats, graphs

Also based at the Media Lab is the New Media Medicine Group, headed by Frank Moss, professor of the practice of media arts and sciences. The group’s Collective Discovery project, which involves Moss and his graduate students John Moore and Ian Eslick, seeks to provide tools to enable members of online discussion boards — a source of rich but erratic and unstructured information — gather and organize medically relevant data about their own experiences with particular diseases and courses of treatment.

But while a number of research groups at both CSAIL and the Media Lab specifically focus on medical applications, much of the theoretical work at CSAIL on machine-learning and statistical inference will inevitably have medical applications. The Stochastic Systems Group, for instance, which is led by Alan Willsky, the Edwin S. Webster Professor of Electrical Engineering and Computer Science and head of the Laboratory for Information and Decision Systems, concentrates on signal processing, image processing and machine learning, often using mathematical constructs known as graphs. But while the group hasn’t explicitly focused on medical applications, “the applicability of graphical to medical analysis has been recognized for some time,” Willsky says.

A graph is a data structure that consists of nodes — which are usually depicted as circles — and edges — which are usually depicted as lines. Generally, Willsky says, in his group’s work, “the edges between nodes encode statistical relationships.” So if the nodes of a graph represented environmental, physiological and genetic factors observed in a population, techniques developed by Willsky’s group could, in principle, help researchers evaluate the statistical correlations between those factors and, say, incidence of asthma.

Full circle

A good example of the convergence of computer science and medicine in the age of big data is David Reshef, who has both bachelor’s and master’s degrees in electrical engineering and computer science from MIT. For his master’s thesis, however, Reshef chose as an advisor Pardis Sabeti, an assistant professor of biology at Harvard and a member of MIT and Harvard’s joint Broad Institute. Reshef’s plan was to develop algorithms for analyzing epidemiological datasets, to extract information about the conditions that contribute most to disease outbreaks.

That work came to fruition in late 2011, when Reshef and his brother, Yakir — both of whom are now MD-PhD students in HST — were lead authors on a paper in Science, “Detecting Novel Associations in Large Data Sets.” In some ways, that paper brings the crosstalk between computer science and medicine full circle: although born of research on epidemiological data, the algorithms the Reshefs developed — together with Sabeti, Michael Mitzenmacher of Harvard, and other colleagues — are in fact generalizable to all types of data.
By web.mit.edu

MIT engineers have created a new polymer film that can generate electricity by drawing on a ubiquitous source: water vapor.

The new material changes its shape after absorbing tiny amounts of evaporated water, allowing it to repeatedly curl up and down. Harnessing this continuous motion could drive robotic limbs or generate enough electricity to power micro- and nanoelectronic devices, such as environmental sensors.

“With a sensor powered by a battery, you have to replace it periodically. If you have this device, you can harvest energy from the environment so you don’t have to replace it very often,” says Mingming Ma, a postdoc at MIT’s David H. Koch Institute for Integrative Cancer Research and lead author of a paper describing the new material in the Jan. 11 issue of Science.

“We are very excited about this new material, and we expect as we achieve higher efficiency in converting mechanical energy into electricity, this material will find even broader applications,” says Robert Langer, the David H. Koch Institute Professor at MIT and senior author of the paper. Those potential applications include large-scale, water-vapor-powered generators, or smaller generators to power wearable electronics.

Other authors of the Science paper are Koch Institute postdoc Liang Guo and Daniel Anderson, the Samuel A. Goldblith Associate Professor of Chemical Engineering and a member of the Koch Institute and MIT’s Institute for Medical Engineering and Science.

Harvesting energy

The new film is made from an interlocking network of two different polymers. One of the polymers, polypyrrole, forms a hard but flexible matrix that provides structural support. The other polymer, polyol-borate, is a soft gel that swells when it absorbs water.

Previous efforts to make water-responsive films have used only polypyrrole, which shows a much weaker response on its own. “By incorporating the two different kinds of polymers, you can generate a much bigger displacement, as well as a stronger force,” Guo says.

The film harvests energy found in the water gradient between dry and water-rich environments. When the 20-micrometer-thick film lies on a surface that contains even a small amount of moisture, the bottom layer absorbs evaporated water, forcing the film to curl away from the surface. Once the bottom of the film is exposed to air, it quickly releases the moisture, somersaults forward, and starts to curl up again. As this cycle is repeated, the continuous motion converts the chemical energy of the water gradient into mechanical energy.

Such films could act as either actuators (a type of motor) or generators. As an actuator, the material can be surprisingly powerful: The researchers demonstrated that a 25-milligram film can lift a load of glass slides 380 times its own weight, or transport a load of silver wires 10 times its own weight, by working as a potent water-powered “mini tractor.” Using only water as an energy source, this film could replace the electricity-powered actuators now used to control small robotic limbs.

“It doesn’t need a lot of water,” Ma says. “A very small amount of moisture would be enough.”

A key advantage of the new film is that it doesn’t require manipulation of environmental conditions, as do actuators that respond to changes in temperature or acidity, says Ryan Hayward, an associate professor of polymer science and engineering at the University of Massachusetts at Amherst.

“What’s really impressive about this work is that they were able to figure out a scheme where a gradient in humidity would cause the polymer to cyclically roll up, flip over and roll in the other direction, and were able to harness that energy to do work,” says Hayward, who was not part of the research team.

Generating electricity

The mechanical energy generated by the material can also be converted into electricity by coupling the polymer film with a piezoelectric material, which converts mechanical stress to an electric charge. This system can generate an average power of 5.6 nanowatts, which can be stored in capacitors to power ultra-low-power microelectronic devices, such as temperature and humidity sensors.

If used to generate electricity on a larger scale, the film could harvest energy from the environment — for example, while placed above a lake or river. Or, it could be attached to clothing, where the mere evaporation of sweat could fuel devices such as physiological monitoring sensors. “You could be running or exercising and generating power,” Guo says.

On a smaller scale, the film could power microelectricalmechanical systems (MEMS), including environmental sensors, or even smaller devices, such as nanoelectronics. The researchers are now working to improve the efficiency of the conversion of mechanical energy to electrical energy, which could allow smaller films to power larger devices.

The research was funded by the National Heart, Lung, and Blood Institute Program of Excellence in Nanotechnology, the National Cancer Institute, and the Armed Forces Institute of Regenerative Medicine.
By web.mit.edu

With the recent launch of MIT’s Institute for Medical Engineering and Science, MIT News examines research with the potential to reshape medicine and health care through new scientific knowledge, novel treatments and products, better management of medical data, and improvements in health-care delivery.

To understand the progression of complex diseases such as cancer, scientists have had to tease out the interactions between cells at progressively finer scales — from the behavior of a single tumor cell in the body on down to the activity of that cell’s inner machinery.

To foster such discoveries, mechanical engineers at MIT are designing tools to image and analyze cellular dynamics at the micro- and nanoscale. Such tools, including microfluidics, membrane technology and metamaterials, may help scientists better characterize and develop therapies for cancer and other complex diseases.

New medical discoveries depend on engineering advances in real-time, multifunctional imaging and quantitative analysis, says Nicholas Fang, an associate professor of mechanical engineering.

“What we’ve learned so far is more or less the architecture of cells, and the next layer is the dynamics of cells,” says Fang, who is developing optical sensors to illuminate individual components within a cell. “Cells operate like a city, or a metropolitan area: You have traffic, flow of information, and logistics of materials, and responses related to different events. Medicine requires new modes of seeing these events with better precision in time and space.”

Materials beyond nature

Fang is developing new imaging tools from metamaterials — materials engineered to exhibit properties not normally found in nature. Such materials may be designed as “superlenses” that bend and refract light to image extremely small objects. For example, Fang says that today’s best imaging tools can capture signaling between individual neurons, which may appear as a fuzzy “plume” of neurotransmitters. A superlens, in contrast, would let scientists see individual neurotransmitter molecules at the scale of a few nanometers. Such acuity, he says, would allow scientists to identify certain chemical transmitters that are directly related to particular diseases.

Metamaterials may also help scientists manipulate cells at the microscale. Fang is exploring the use of metamaterials as optical antennae to improve a technique known as optogenetics. This technique, developed in 2005 (and pioneered by MIT’s Ed Boyden, the Benesse Career Development Associate Professor of Research in Education), involves genetically engineering proteins to respond to light. Using various colors of light, scientists may control the activity or expression of such proteins to study the progression of disease. However, researchers have found that the technique requires a large amount of light to prompt a response, risking overheating or damaging the proteins of interest.

To solve this problem, Fang and his colleagues are looking to metamaterials to design tiny optical receivers, similar to radio antennae. Such receivers would attach to a given protein, boosting its receptivity to light, and thereby requiring less light to activate the protein. The project is in its initial stages; Fang says his group is now seeking materials that are compatible with proteins and other biological tissues.

Sorting cells

MIT researchers are also developing tools to sort individual cells — part of an effort to provide simple, cost-effective diagnostic tools for certain diseases. Rohit Karnik, an associate professor of mechanical engineering, is approaching cell sorting from a variety of directions. His lab is fabricating microfluidic, or “lab-on-a-chip,” devices — chips as small as a dime that efficiently sort cells, separating out those of interest from a sample of blood or biological fluid.

Karnik’s group employs nanofabrication techniques to etch tiny, precisely patterned channels into small squares of polymer. The arrangement of the channels directs fluid, capturing cells of interest via “cell rolling,” a phenomenon by which cells roll to one side of a channel, attracted by a wall’s surface coating. The device is a relatively simple, passive cell-sorter that Karnik says may efficiently sort out material such as white blood cells — cells that may quickly be counted to identify conditions such as sepsis and inflammation. 

Karnik is also developing small membranes punctured with microscopic pores. Each pore is a few nanometers wide, small enough to let individual DNA molecules through. By passing an electric current through the nanopore, the researchers can measure certain characteristics of a DNA molecule, such as its size and the presence of any additional proteins bound to it.

Such membrane technology may drastically simplify the process of sizing DNA molecules and mapping DNA modifications, which are critical for understanding gene regulation and the dynamics of cellular machinery — now a lengthy process that involves expensive bench-top instruments. Instead, Karnik says, nanopore membranes may be a faster, cheaper alternative that could work with single DNA molecules with no loss of information from DNA-amplification steps.

Cancer in a chip

Researchers are investigating microfluidics not only as a means to sort cells, but as a way of replicating whole biological environments at the microscale.

“We use microfluidics to develop more realistic models of organs and human physiology so that we can look at, for example, how a tumor cell interacts with other cells in the local environment,” says Roger Kamm, the Cecil and Ida Green Distinguished Professor of Biological and Mechanical Engineering.

Kamm and his colleagues have developed a microfluidic chip that contains tiny channels and reservoirs, in which they can seed various cell types. The group is using the device to study how cancer spreads through the body. Cancer becomes metastatic when tumor cells break off from a primary tumor and cross through a blood vessel wall and into the bloodstream. Kamm is using the group’s microfluidic designs to mimic the metastatic process and identify agents to prevent it.

To replicate the lining of a blood vessel, Kamm seeds one channel in the chip with endothelial cells. In a neighboring channel, he injects a gel, mimicking the body’s extracellular matrix. The group can introduce tumor cells into the gel, along with other chemical agents. In the controlled setup, they can monitor the behavior of tumor cells, and the conditions in which the cells penetrate the endothelial lining, in order to enter a blood vessel.

“This allows us to put cells in close proximity so they can signal with each other in a more realistic fashion,” Kamm says.

Compared with conventional cancer-screening techniques, the microfluidic technique more closely resembles natural processes in the body, Kamm says. For example, pharmaceutical companies tend to test potential drugs in large batches, injecting a drug into tiny, isolated wells containing tumor cells. That works well to test for drugs that kill the tumor, but not so well for identifying drugs that can prevent metastatic disease.

“What we’re finding is that cells behave completely differently when you have a realistic environment, with cells communicating with different cell types, and when a cell is in a three-dimensional matrix, as opposed to when you have a single cell type inside a well on a two-dimensional, rigid surface,” Kamm says. “High-throughput systems probably miss a lot of potentially good drugs, and they also identify drugs that fail at subsequent stages of testing.”

Karnik, who has collaborated with Kamm on a few lab-on-a-chip designs, sees such devices and other engineering tools as a key connection in pushing medical discoveries, and effective therapies, forward.

“A clinician might say, ‘I need to know whether the patient has this disease or that disease,’ and the biologist would say, ‘Oh, in order to do that, you need to measure molecules A, B and C,’ and it’s up to the engineers to figure out how to do it,” Karnik says. “That’s our key role, bridging in between.”
By web.mit.edu

Pedro Valencia, who earned his PhD in chemical engineering at MIT in November, was named in Forbes magazine’s 2012 list of the top 30 rising stars in science and health.

Valencia was cited for figuring out “how to more quickly synthesize nanoparticles that can be used to make drugs more effective and less toxic and to put multiple drugs inside the same nanotech medicine. This has resulted in many top-notch scientific publications and the formation of a start-up, Blend Therapeutics.”

Valencia, a former student of Robert Langer, the David H. Koch Institute Professor, earned his BS in chemical engineering from the University of Wisconsin-Madison in 2007, and was at the top of his class. He completed his MS in chemical engineering practice at MIT in 2009.

Valencia was the recipient of the NSF Graduate Fellowship. He was co-advised by Professor Langer and Dr. Omid Farokhzad of the Brigham Women’s Hospital – Harvard Medical School.
By web.mit.edu

Finding ways to diagnose cancer earlier could greatly improve the chances of survival for many patients. One way to do this is to look for specific proteins secreted by cancer cells, which circulate in the bloodstream. However, the quantity of these biomarkers is so low that detecting them has proven difficult.

A new technology developed at MIT may help to make biomarker detection much easier. The researchers, led by Sangeeta Bhatia, have developed nanoparticles that can home to a tumor and interact with cancer proteins to produce thousands of biomarkers, which can then be easily detected in the patient’s urine.

This biomarker amplification system could also be used to monitor disease progression and track how tumors respond to treatment, says Bhatia, the John and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science at MIT.

“There’s a desperate search for biomarkers, for early detection or disease prognosis, or looking at how the body responds to therapy,” says Bhatia, who is also a member of MIT’s David H. Koch Institute for Integrative Cancer Research. She adds that the search has been complicated because genomic studies have revealed that many cancers, such as breast cancer, are actually groups of several diseases with different genetic signatures.

The MIT team, working with researchers from Beth Israel Deaconess Medical Center, described the new technology in a paper appearing in Nature Biotechnology on Dec. 16. Lead author of the paper is Gabriel Kwong, a postdoc in MIT’s Institute for Medical Engineering and Science and the Koch Institute.

Amplifying cancer signals

Cancer cells produce many proteins not found in healthy cells. However, these proteins are often so diluted in the bloodstream that they are nearly impossible to identify. A recent study from Stanford University researchers found that even using the best existing biomarkers for ovarian cancer, and the best technology to detect them, an ovarian tumor would not be found until eight to 10 years after it formed.

“The cell is making biomarkers, but it has limited production capacity,” Bhatia says. “That’s when we had this ‘aha’ moment: What if you could deliver something that could amplify that signal?”

Serendipitously, Bhatia’s lab was already working on nanoparticles that could be put to use detecting cancer biomarkers. Originally intended as imaging agents for tumors, the particles interact with enzymes known as proteases, which cleave proteins into smaller fragments.

Cancer cells often produce large quantities of proteases known as MMPs. These proteases help cancer cells escape their original locations and spread uncontrollably by cutting through proteins of the extracellular matrix, which normally holds cells in place.

The researchers coated their nanoparticles with peptides (short protein fragments) targeted by several of the MMP proteases. The treated nanoparticles accumulate at tumor sites, making their way through the leaky blood vessels that typically surround tumors. There, the proteases cleave hundreds of peptides from the nanoparticles, releasing them into the bloodstream.

The peptides rapidly accumulate in the kidneys and are excreted in the urine, where they can be detected using mass spectrometry.

This new system is an exciting approach to overcoming the problem of biomarker scarcity in the body, says Sanjiv Gambhir, chairman of the Department of Radiology at Stanford University School of Medicine. “Instead of being dependent on the body to naturally shed biomarkers, you’re sampling the site of interest and causing biomarkers that you engineered to be released,” says Gambhir, who was not part of the research team.

Distinctive signatures

To make the biomarker readings as precise as possible, the researchers designed their particles to express 10 different peptides, each of which is cleaved by a different one of the dozens of MMP proteases. Each of these peptides is a different size, making it possible to distinguish them with mass spectrometry. This should allow researchers to identify distinct signatures associated with different types of tumors.

In this study, the researchers tested their nanoparticles’ ability to detect the early stages of colorectal cancer in mice, and to monitor the progression of liver fibrosis.

Liver fibrosis is an accumulation of scarring in response to liver injury or chronic liver disease. Patients with this condition have to be regularly monitored by biopsy, which is expensive and invasive, to make sure they are getting the right treatment. In mice, the researchers found that the nanoparticles could offer much more rapid feedback than biopsies.

They also found that the nanoparticles could accurately reveal the early formation of colorectal tumors. In ongoing studies, the team is studying the particles’ ability to measure tumor response to chemotherapy and to detect metastasis.

The research was funded by the National Institutes of Health and the Kathy and Curt Marble Cancer Research Fund.
By web.mit.edu