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How the Brain Gives Rise to the Mind

A professor gives a presentation to students.

This Year’s Blavatnik National Awards for Young Scientists Laureate in the Life Sciences is connecting the activity of cells and synapses to emotions and social behavior

Published October 21, 2021

By Roger Torda

Neuroscientist Kay Tye has challenged orthodoxy in her field by studying the connection between the brain and the mind. The work has led to breakthroughs in basic science. It also points to new approaches to mental illness, with significant potential impact.

Tye is a professor in the Systems Neurobiology Laboratory at the Salk Institute for Biological Studies. She and her research team work to identify the neural mechanism of emotional and social processing, in health and disease. Tye explained to the New York Academy of Sciences why this work is so important.

Impacts on Mental Health

“Mental health disorders have a prevalence of one in two. This is half the population. If we could understand how the brain gives rise to the mind, we could de-stigmatize mental health, and everyone would go and get the treatment that they need,” she says.

Current therapies for mental disorders are developed by trial-and-error, with drugs that have broad ranges of effects. Tye envisions a much different approach, with treatments that target specific mechanisms in the brain.

“Our insights could revolutionize our approach to mental health treatments, supporting individualized therapies that would be effective for everyone and have the precision to be free of side effects,” she says.

Neuroscientist Kay Tye at the Salk Institute

Tye’s work is widely recognized, and this year the Blavatnik National Awards for Young Scientists named Tye its 2021 Life Sciences Laureate.

Tye’s Background

Tye is the daughter of two scientists—a biologist and a physicist—who met while travelling to the U.S. from Hong Kong to pursue their educations. From a young age, Tye says she was fascinated by subjective experiences, foreshadowing her studies on the connection between brain and mind.

“How do I feel the way I feel?” Tye recalls wondering as a child. “How can two people listen to the same song and one person loves it and one person hates it? What are emotions?”

Tye with her children

Tye went to MIT for her undergraduate degree and received her Ph.D. from the University of California, San Francisco. After a postdoctoral fellowship at Stanford, she opened her lab as an assistant professor at MIT in 2012. In 2019, she moved across the country again, to the Salk Institute.

As Tye gained confidence as a young scientist, she took on a difficult professional challenge as she sought to examine questions that had not traditionally been the purview of her field.

“As a neuroscientist, I’m often told I am not allowed to study how internal states like anxiety, or craving, or loneliness are represented by the brain,” she recalled in a TED Talk. “And so, I decided to set out and do exactly that.”

Research in Optogenetics

In her research, Tye uses technology called “optogenetics,”  which transfers the light sensitivity of certain proteins found in some algae to specific neurons in the brains of lab animals. Researchers can then use light to control signaling by the neuron, and they can establish links between the neuron and specific behavior. Tye developed an approach using this tool called “projection-specific optogenetic manipulation.”

“This permits scientists to dissect the tangled mess of wires that is our brains to understand where each wire goes and what each wire does,” Tye said.

Kay Tye in the lab

Tye’s postdoctoral training was in the Stanford University lab of Karl Deisseroth, who had recently developed optogenetics. Many young neuroscientists wanted to be among the first to use optogenetics, and Tye was eager to use it to study behavior and emotion. Tye recalled that period.

“It was a very exciting time in neuroscience, and in 2009 I already felt like I had come late to the party, and knew I needed to push the field forward to make a new contribution,” Tye says. “I worked absurdly hard during my postdoc, fueled by the rapidly changing landscape of neuroscience, and feel like I did five years of work in that two-year period.”

Analyzing Neural Circuits

Tye’s research program initially focused on the neural circuits that process emotional valence, the degree to which the brain assigns positive or negative value to certain sensory information.  Her lab has analyzed the neural circuits controlling valence processing in psychiatric and substance abuse disorders.

This work includes the discovery of a group of neurons connecting the cerebral cortex to the brainstem that can serve as a biomarker to predict whether an animal will develop compulsive alcohol drinking behavior. Recent research has focused on neurons activated when animals experience social isolation and enter “loneliness-like” states.

Kay Tye in the lab

Tye and her research team are also exploring how the brain represents “social homeostasis”— a new field of research which seeks to understand how individuals know their place within a social group and identify optimal amounts of social contact.

Kay Tye and her lab team

Pushing Boundaries in Her Field

Even after considerable success in her field, Tye says she still feels as though she is pushing boundaries of her discipline. In doing so, she is continuing to bring neuroscience rigor to the study of feelings and emotions. Referring to her recent work, Tye said:

We faced a lot of pushback with this line of research, just because “loneliness” isn’t a word that has been used in neuroscience until now. These types of processes, these psychological constructs didn’t belong in what people considered to be hardcore neuroscience.

We are now bringing rigorous neuroscience approaches to ideas that were purely conceptual before. And so we’re being quantitative. We are being mechanistic. We are creating biologically grounded, predictive dynamical models for these nebulous ideas like “feelings” and “emotions.” And this is something that I find extremely gratifying.

Kay and colleagues at Salk Insitute

Targeting Molecules with Tiny Sponges

Two men smile and shake hands.

Growing up in Romania, Mircea Dincă’s was first exposed to science. Now he’s engineering an electric Lamborghini.

Published October 1, 2021

By Roger Torda

Mircea Dincă (left) poses with Nick Dirks, President and CEO of The New York Academy of Sciences.

Mircea Dincă creates materials in the lab with surface features that can’t be found in nature. He then makes variants with electrical properties that other scientists once thought impossible. This is groundbreaking basic research with many emerging applications. One is particularly exciting: a supercapacitor to power a Lamborghini supercar.

Dincă, a professor of chemistry at MIT, is this year’s Blavatnik National Awards for Young Scientists Laureate in Chemistry. He heads a lab that synthesizes novel organic-inorganic hybrid materials and manipulates their electrochemical and photophysical properties.

Dincă and his students work with metal-organic frameworks, or MOFs. “These are basically what I like to call sponges on steroids because they are enormously porous,” Dincă told the Academy in a recent interview. “They have fantastically high surface areas, higher than anything that humanity has ever known.”

Metal-Organic Frameworks (MOFs)

MOFs have a hollow, crystalline, cage-like structure, consisting of an array of metal ions surrounded by organic “linker” molecules. Scientists can “tune” their porosity, creating MOFs that can capture molecules of different properties and size.

To help conceptualize the large surface area of MOFs, Dincă says a gram of the material would, if flattened out, cover an entire football field. This means their pores can hold an almost unimaginably large number of molecules. One application capitalizing on this capacity is gas storage. For example, a canister filled with MOFs would hold nine times more COthan an empty canister. Other emerging uses have included devices to manage heat, antimicrobial products, gas separation, and devices for scrubbing emissions and carbon capture.

Dincă first encountered MOFs as a graduate student. Several years later, after considerable research on the electronic structure of materials, he started envisioning MOFs with properties that had not been widely considered before. “Previously, people thought that metal-organic frameworks are just ideal insulators,” Dincă said. “But we realized that there are certain types of building blocks that, when put together, would allow the free flow of electrical charges.”  This was something of a paradigm shift in the field.

A Partnership with Lamborghini

Dincă and his students started synthesizing MOFs with a variety of organic ligands and metal combinations to create materials that are both porous and conducting. They also developed ways to grow MOF crystals so they can be more easily studied with imaging tools, permitting analysis of their structure, atom-by-atom.  The new techniques and materials have led to MOFs that might prove valuable for batteries, fuel cells, and energy storage.  Dincă’s lab and MIT have signed a partnership with Lamborghini to use MOF supercapcitors in the company’s planned Terzo Millennio sportscar.

Dincă and his students also study the use of MOFs as catalysts, and as chemical sensors. They explore how these materials interact with light, which could lead to smart windows that lighten or darken automatically. Better solar cells are yet another possible application.

More efficient air conditioning, with considerable environmental benefit, is another goal. Dincă has co-founded a start-up called Transaera to build  MOF-based cooling equipment that pulls water molecules out of air so that the AC doesn’t work as hard. The key is tuning the pores of the MOFs to just the right size to capture water at just the right humidity.

Scaling up remains a challenge for many of these applications. “It’s one thing to make a few grams in a laboratory, it’s quite another to make hundreds of kilograms so you can take them out into the real world,” Dincă said.

“Thirsty for Knowledge”

Dincă grew up in Romania, and says he got his first taste of chemistry in 7th grade. An MIT departmental biography playfully suggests “that having a dedicated teacher that did spectacular demonstrations with relatively limited regard for safety” was the initial influence.  One imagines awe-inspiring, semi-controlled explosions in the front of a classroom of 12 year olds. In the following years, Dincă started participating in the Chemistry Olympiads, and in 1998, when he was in high school, he won first place at an international competition in Russia.

At the time, Dincă found he was running up against limits to his education. “I think the biggest challenges to my becoming a scientist were, early on in Romania where I grew up, that we just didn’t have access to labs, to books,” Dincă said. “That made me thirsty for knowledge.” So Dincă was eager to travel to the U.S. when he was offered a scholarship for undergraduate studies at Princeton. He then earned a Ph.D. from UC Berkeley. He has been teaching and conducting research at MIT since 2008.

Dincă met his wife, who is also from Romania, while they were both students at Princeton. She is a lawyer, and the couple have two children, Amalia and Gruia. Dincă’s father is a retired Romanian Orthodox priest, and his mother, a retired kindergarten teacher.

When he is not with his family or at work, Dincă might be running, hiking, or taking photographs.

Constant Exposure to the Unknown

Dincă enjoys teaching, including freshmen chemistry. For his more advanced students and postdocs, Dincă says he fosters original thinking by giving them as much responsibility as possible. “As a Principal Investigator myself, I tend to be very hands-off,” Dincă explained. “And that’s good because it allows students to take ownership of their projects and become creative themselves. In fact, most of the best ideas in my lab come from the students, not myself.”

One of the best things about being a scientist, Dincă said, is constant exposure to the unknown, and he is pleased when his commitment to basic research is recognized. “Being a Blavatnik National Award Laureate is, of course, fantastic recognition of my research, of my group’s efforts,” Dincă said. “But also, most importantly for me, it is recognition of the fact that curiosity-driven research is still appreciated.”

While curiosity may drive Dincă’s scientific inquiries, he believes applied research with new classes of MOFs will help address important environmental challenges. At the same time, there can be no doubt that one application may prove especially thrilling. “Never in my wildest dreams did I believe that just thinking about electrical current in porous materials would take me on a path to helping make an electric Lamborghini,” Dincă said. “But that is where our research has led us.”

Also read: Exploring Metamaterials and Photonics

Exploring Metamaterials and Photonics

A man smiles for the camera.

Andrea Alù is challenging the laws of physics to improve data transmission. Oh yeah, he’s working on an invisibility cloak, too!

Published October 1, 2021

By Roger Torda

Andrea Alù

Andrea Alù isn’t satisfied with how light waves and sound travel through objects and space. So he engineers new materials that appear to violate some well-established laws of physics. Enhanced wireless communication and computing technologies, improved bio-medical sensors, and invisibility cloaks are just some of the achievements of his lab.

“We create our own materials, engineered at the nanoscale,” explained Alù, who is Director of the Photonics Initiative at the Advanced Science Research Center at the City University of New York (CUNY). “We call them metamaterials, which push technologies forward, to realize optical properties, electromagnetic properties, or acoustic properties that go well beyond what nature and natural materials offer us.”

This work has led to many honors, and this year the Blavatnik National Awards for Young Scientists is recognizing Alù as its 2021 Laureate in Physical Sciences and Engineering.

In a recent interview with The New York Academy of Sciences (the Academy), Alù explained a core behavior of light that is at the heart of his research:

One of the most basic phenomena in optics is light refraction, which describes the change in direction of propagation of an optical beam as it enters a material. We can understand this as the collective excitation of molecules and charges in the material, produced by light. In metamaterials, we make up our own molecules—we call them metamolecules.

Metamaterials feature many different geometries of at the nanoscale. Some can be engineered to interact with light in such a way that they may actually make objects disappear from sight. It is a phenomenon called “cloaking.” Alù continued:

Engineering at the Nanoscale

This engineering at the nanoscale allows us to change the ways in which light refracts as it enters a metamaterial. By bending light in unusual ways, we can actually realize highly unusual optical phenomena, like enhancing or suppressing the reflections and scattering of light from an interface, making a small object appear much larger, or conversely, even disappear altogether, by hiding it from the impinging electromagnetic waves.

“Invisibility” has long been part of our popular imagination and science fiction, from H.G. Wells’ novels to Star Trek and Harry Potter. A pioneering theoretical step dates back to 1968, when a Russian physicist wondered if a phenomenon called “negative refraction” might be possible. But no materials featuring this property were known, and some scientists believed none would be found because negative refraction might violate widely-used equations describing the propagation of light. Thirty years later, in 2000, a team of scientists was able to demonstrate negative refraction in a metamaterial for a certain frequency of electromagnetic radiation. A few years later, experiments demonstrated actual metamaterial cloaking, and Scientific American proclaimed: “Invisibility Cloak Sees Light of Day.”

Alù started working on metamaterials in 2002, when he spent a year at the University of Pennsylvania as a visiting student. He has conducted pioneering research in the field ever since. A major achievement came in 2013. Alù, then at the University of Texas at Austin, and his collaborators, demonstrated the cloaking of a three-dimensional object using radio waves. The work showed that antennas, like the ones in our cell phones, could be made transparent to radio-waves, a finding of potential commercial and military value, as it eliminates interference between closely-spaced transmitters.

A Childhood Fascination

Alù’s interest in light and other electromagnetic waves began as a child in Italy when he was fascinated by how our radios and television sets receive broadcast information without wiring. His interest intensified in high school when he realized a “beautiful common mathematical framework” describes the propagation of light, radio signals, and sound, and the fact that no information can be transmitted faster than the speed of light.

Alù went on to study at the University of Roma Tre, where he earned a Ph.D. in electronic engineering. After a postdoctoral fellowship at the University of Pennsylvania, he joined the faculty of UT Austin in 2009, and moved to CUNY in 2018.

Nanomaterials being developed in Alù’s lab may also improve near-field microscopy for better biomedical imaging, and lead to optical computers, enabling faster and more efficient PCs that use light instead of electric signals.

Yet another area of intense research for Alù and his research team has been “breaking reciprocity,” with implications for improved transmission of sound as well as radio waves and light. “Light, sound, and radio waves, typically travel with symmetry between two points in space,” Alù explained. “If you hear me, I can hear you back. If you can see me, typically you can see me back. This property is rooted into the time reversal symmetry of the wave equations.”

Connecting Basic and Applied Research

Alù said his lab’s work in breaking this symmetry with metamaterials is a good illustration of the connection between basic and applied research:

Interestingly, making materials that transmit waves one way and not the other started as a curiosity, but it has rapidly become extremely useful, from improving data rates with which our cell phones or WiFi technologies operate to protecting sensitive lasers from reflections. This has been a very exciting quest, from basic research to applications.

Alù began his research and teaching career in the U.S. only after he earned his Ph.D. in Italy and, as a result, he found he initially had a smaller professional network than many of his peers. But Alù says the U.S. was very welcoming, and he quickly caught up:

I come from Italy and I did all my undergraduate and graduate studies there. So, coming to the U.S. first as a postdoc, then as a faculty member, I didn’t have a large support network around me, I didn’t initially have a lot of connections…. But at the same time, I have to say, the United States offers tremendous opportunities, in particular to young scientists, to help build up their research groups, and to thrive.

Alù continued: “The U.S. is an amazing country in welcoming young people, new talent, and supporting them in the broadest possible terms… An excellent example of this is the Blavatnik National Awards program, and the broad range of scientists it recognizes.”

The Economic Imperative for Better Battery Technology

A graphic illustration of a battery.

A married research duo are studying ways to better predict the feasibility and potential economic benefits of adopting battery technologies for renewable energy.

Published May 13, 2021

By Roger Torda

(Left to Right) Graham Elliott and Shirley Meng at the 2019 Blavatnik National Awards Ceremony at the American Museum of Natural History

What can we learn from a marriage of physical and social sciences?

Materials scientist and Blavatnik National Awards for Young Scientists Finalist (2018, 2019) Shirley Meng, PhD, shares her answer to this question. She and her husband, economist Graham Elliott, PhD, combine their expertise in battery chemistry and economic modeling.

In an intriguing collaboration, they developed ways to better predict the feasibility and potential economic benefits of adopting battery technologies to integrate renewable energy, such as solar and wind energy, into energy grids. Together with their research team members, they published “Combined Economic and Technological Evaluation of Battery Energy Storage for Grid Applications” in the journal Nature Energy.

Meng is the Zable Chair Professor in Energy Technologies and Director of the Institute for Materials Design and Discovery at the University of California San Diego (UCSD). Elliott is also at UCSD, where he is Professor and Chair of the Department of Economics. We recently interviewed both to discuss this collaboration and what they learned through the process.

Can you tell us how this collaboration was initiated?  

Meng: UCSD is a place where interdisciplinary and convergent research is not only highly valued but practiced.  I founded the Sustainable Power and Energy Center (SPEC) at UCSD in 2015. SPEC reaches out beyond engineering and physical sciences to study economic and sociological issues that need to be addressed to create truly robust ecosystems for low-carbon electric vehicles and carbon-neutral microgrids. We won a competitive grant from the US Department of Energy, which provided the resources for this work.

Why did you choose to study batteries for energy grid applications? What question about batteries did you study?

Meng: With energy grids showing their age and continuing to distribute energy generated with high environmental costs, efforts that enable grids to distribute cleaner, renewable energy more efficiently would be a technological advance with a positive societal impact. While there have been exciting moves toward renewables, many problems lie ahead if we are to move from renewables being important to renewables being dominant.

Elliott: Grid energy storage remains a major challenge both scientifically and economically. Batteries, or energy storage systems, play critical roles in the successful operation of energy grids by better matching the energy supply with demand and by providing services that help grids function. They will not just transform the market for supplying energy but also transform consumer demand by lowering the prices of energy for households and businesses.

In this work, we studied the potential revenues that different battery technologies deployed in the grid will generate through models that consider market rules, realistic market prices for services, and the energy and power constraints of the batteries under real-world applications.

Bringing these together in an interactive way—examining the engineering and economic aspects as two parts of the problem together—allows for a complete look at the problem, and ultimately a better outcome for the economy.

Graham Elliott

What was the biggest finding of this collaboration? Were you surprised by your findings?

Meng: We found that while some battery technologies hold the greatest potential from an engineering perspective, the choice based on economics is less clear. The current rules of grid operations dictate which battery technologies are used for those particular grids—some of these rules may be out-of-date, and will be updated as the grids modernize. So even though we continue to see improvement in the energy/power performance of battery technologies and reduction in cost, policymakers are the ultimate decision-makers. Policymakers setting those rules have considerable influence on how fast and how successfully those battery technologies can be deployed, and therefore industry needs to work closely with policymakers to define the best practices for faster deployment of battery technologies.

We also found that there are a wide variety of factors that should be considered in choosing a battery technology. For instance, the battery recycling method is an important technical variable that determines the sustainability of a particular battery technology.

How could your findings eventually affect individual people and society? How can it help our economy?

Elliott: All gains in human welfare arise from what economists call productivity gains—people creating more with less effort, so there is more to go around. Technological advances in energy storage enable productivity gains. But for it to work, we need not only to be able to provide effective energy storage from an engineering perspective, but also it needs to be economically feasible. Different choices at the engineering stage mean differences in the economic feasibility, and how markets are arranged impacts engineering choices. Bringing these together in an interactive way—examining the engineering and economic aspects as two parts of the problem together—allows for a complete look at the problem, and ultimately a better outcome for the economy.

Meng: We are delighted to see to see that battery grid storage is starting to gain more momentum—policymakers are becoming informed about both economic and scientific, and engineering aspects of battery technologies.

A small-scale energy grid at the University of California San Diego, consisting of a network of solar cells with battery storage (Credit: University of California San Diego)

What did you learn from this collaboration? Are there any tips you would like to share with other researchers who would like to pursue similar collaborations between physical and social sciences?

Meng: Perhaps the most important thing for the collaborative team to do is to build a common vocabulary so we can truly understand each other. In our case, we started by explaining the most basic symbols and units in engineering, like the energy unit Wh (Watt-hour) and the power unit W (Watt). Without understanding the differences between these symbols, we will make mistakes in constructing important parameters in our economic modeling.

Elliott: Another thing we learned is that different fields have very different understandings of the big picture. Collaboration across fields helps focus everyone’s efforts. For example, engineers typically view markets as fixed, and the engineering problem is to find something that works for the market. Economists tend to think of products (such as batteries) as fixed and design markets that work for the available products.

There is a whole research area waiting patiently for economists to understand which parts of the engineering problem are important and for scientists and engineers to understand from their perspective which parts of the market design are important.

The Challenge of Quantum Error Correction

An illustrated graphic of a computer chip, or a similar piece of electronic equipment.

Shruti Puri, PhD, helps explain the challenges and the potential computational power this exciting new technology may bring about.

Published March 22, 2021

By Liang Dong, PhD

Shruti Puri, PhD, Yale University

Quantum computing is a radically new way to store and process information based on the principles of quantum mechanics. While conventional computers store information in binary “bits” that are either 0s or 1s, quantum computers store information in quantum bits, or qubits. A qubit can be both 0 and 1 at the same time, and a series of qubits together remember many different things simultaneously.

Everyone agrees on the huge computational power this technology may bring about, but why are we still not there yet? To understand the challenges in this field and its potential solutions, we recently interviewed Shruti Puri, PhD, who works at the frontier of this exciting field. Puri is an Assistant Professor in the Department of Applied Physics at Yale University, and a Physical Sciences & Engineering Finalist of the 2020 Blavatnik Regional Awards for Young Scientists, recognized for her remarkable theoretical discoveries in quantum error correction that may pave the way for robust quantum computing technologies.

What is the main challenge you are addressing in quantum computing?

Thanks to recent advances in research and development, there are already small to mid-sized quantum computers made available by big companies. But these quantum computers have not been able to implement any practical applications such as drug and materials discovery. The reason is that quantum computers at this moment are extremely fragile, and even very small noise from their working environment can very quickly destroy the delicate quantum states. As it is almost impossible to completely isolate the quantum states from the environment, we need a way to correct quantum states before they are destroyed.

At a first glance, quantum error correction seems impossible. Due to the measurement principle of quantum mechanics, we cannot directly probe a quantum state to check if there was an error in it or not, because such operations will destroy the quantum state itself.

Fortunately, in the 1990s, people found indirect ways to faithfully detect and correct errors in quantum states. They are, however, at a cost of large resource overheads. If one qubit is affected by noise, we have to use at least five additional qubits to correct this error. The more errors we want to correct, the larger number of additional qubits it will consume. A lot of research efforts, including my own, are devoted to improving quantum error correction techniques.

What is your discovery? How will this discovery help solve the challenge you mention above?

In recent years, I have been interested in new qubit designs that have some in-built protection against noise. In particular, I developed the “Kerr-cat” qubit, in which one type of quantum error is automatically suppressed by design. This reduces the total number of quantum errors by half! So, quantum computers that adopt Kerr-cat require far fewer physical qubits for error correction than the other quantum computers.

Kerr-cat is not the only qubit with this property, but what makes the Kerr-cat special is that it is possible to maintain this protection while a user tries to modify the quantum state in a certain non-trivial way. As a comparison, for ordinary qubits, the act of the user modifying the state automatically destroys the protection. Since its discovery, the Kerr-cat has generated a lot of interest in the community and opened up a new direction for quantum error correction.

As a theoretician, do you collaborate with experimentalists? How are these synergized efforts helping you?

Yes, I do collaborate quite closely with experimentalists. The synergy between experiments and theory is crucial for solving the practical challenges facing quantum information science. Sometimes an experimental observation or breakthrough will provide a new tool for a theorist with which they can explore or model new quantum effects. Other times, a new theoretical prediction will drive experimental progress.

At Yale, I have the privilege to work next to the theoretical group of Steve Girvin and the experimental groups of Michel Devoret and Rob Schoelkopf, who are world leaders in superconducting quantum information processing. The theoretical development of the Kerr-cat qubit was actually a result of trying to undo a bug in the experiment. Members of Michel’s group also contributed to the development of this theory. What is more, Michel’s group first experimentally demonstrated the Kerr-cat qubit. It was just an amazing feeling to see this theory come to life in the lab!

Are there any other experimental developments that you are excited about?

I am very excited about a new generation of qubits that are being developed in several other academic groups, which have some inherent protection against noise. Kerr-cat is one of them, along with Gottesman-Kitaev-Preskill qubit, cat-codes, binomial codes, 0−π qubit, etc. Several of these designs were developed by theorists in the early 2000s, and were not considered to be practical. But with experimental progress, these have now been demonstrated and are serious contenders for practical quantum information processing.  In the coming years, the field of quantum error correction is going to be strongly influenced by the capabilities that will be enabled by these new qubit designs. So, I really look forward to learning how the experiments progress.

Harnessing CRISPR to Revolutionize COVID Testing

A gloved hand holds a COVID-19 test.

Professor Pardis Sabeti was able to apply findings from her research on Ebola to now develop a test for detecting COVID-19.

Published March 9, 2021

By Brittany Aguilar, PhD

Pardis Sabeti, MD, DPhil, MSc

This isn’t the first time that Pardis Sabeti, MD, DPhil, MSc, a professor of organismic and evolutionary biology at Harvard University, and newly elected member of the National Academy of Medicine, has worn the hat of viral genome detective in the earliest days of a deadly outbreak or viral disease. Sabeti and her team began sequencing Ebola samples just days after the virus was first detected in Sierra Leone during the 2013-2016 West African outbreak. Since January 2020, she has been working on diagnostics for COVID-19, developing models to predict the most sensitive and accurate assay design candidates for the rapid detection of SARS-CoV-2, including an assay that harnesses the powerful accuracy of CRISPR technology.

Describe the innovative, rapid COVID-19 test that you helped create—how does it work, and why is it an improvement on current testing methods?

Over the last several years, my lab, colleagues, and I have been developing an assortment of technologies for genomic surveillance of pathogens. In particular, we have been deeply invested in CRISPR technologies. CRISPR was first discovered within bacterial immune systems, where it is used to protect the bacteria from invading pathogens by rapidly identifying and targeting a genomic sequence with very high fidelity. Thus, it is immensely powerful as a diagnostic tool, since it can be designed to detect any sequence of genetic material with impressive accuracy.

It is an incredibly exciting technology: it is highly accurate, it would be able to rapidly detect pathogens using little equipment and a simple, paper-strip read-out, and it could be developed in a matter of days to detect newly discovered pathogens or new variants of known pathogens. Crucially, the test is also inexpensive to manufacture, which means it could be easily scaled and distributed as pathogens—or novel variants of pathogens—emerge.

Throughout the duration of the COVID-19 pandemic, some have suggested that testing is optional, unnecessary or unreliable—can you describe why the creation of rapid, reliable tests is so important?  Does that change depending on where we are in the infection curve?

Testing is extremely critical to fighting the spread of any infectious disease, and this has been demonstrated through history. However, testing technology has been achievable but not prioritized—if we had invested in this space after the SARS-CoV epidemic [the SARS outbreak in 2003], I believe we could have been poised to respond to SARS-CoV-2 before it spread throughout the world.

The need for diagnostics is critical everywhere, from pre-empting a pandemic, to response and recovery. To be as useful as possible, diagnostics must also be affordable and accessible to all—this is not just in infectious disease but throughout all medicine. The sooner individuals and communities have information, the better they can respond, enabling better outcomes.

You wrote a book last year entitled “Outbreak Culture.” Are there any key learnings from that book that can be applied to COVID or future pandemics?

In this book we argue that a dysfunctional “outbreak culture”—the collective mindset that develops among responders and communities that emerges in the chaos and crucible that is disease outbreaks—poses a great threat to our ability to curb outbreaks and save lives, and that we must continually watch for and dismantle toxic response systems where possible. This includes the data and resource hoarding, perverse capitalistic incentives, the spread of misinformation, and the loss of empathy and good citizenship.

I think people are still just beginning to understand the gravity of outbreak culture and how it is operating amidst COVID. For example, we all now know the importance of detecting outbreaks, through track-and-trace methods, before they have the chance to spread widely. But what is given less attention is how those efforts can be sidelined or undermined by many surrounding societal and political forces.

I always advocate for a massively increased effort for empathy during outbreaks. We need resilient communities to be able to do the best work against infectious disease. With our trust in our fellow citizens, our leaders, and our scientists undermined during this time, it is crucial to work within the community and low to the ground. We must listen to others, respect their opinions, and understand their fears. For that reason, I believe we must double down on empathy when it comes to community participation. If we do not work with communities and support them in the right ways, we end up causing more harm than good.

About Prof. Sabeti

Pardis Sabeti, MD, DPhil, MSc is a Professor at the Center for Systems Biology and Department of Organismic and Evolutionary Biology at Harvard University and the Department of Immunology and Infectious Disease at the Harvard School of Public Health.  She was a 2016 and 2017 Finalist for the Academy’s Blavatnik National Award for Young Scientists. To learn more about Dr. Sabeti and her work, click here to listen to the “Deciphering Zika” podcast.

When Artificial Intelligence Meets Physical Sciences

Artificial intelligence is quickly becoming a ubiquitous part of our daily lives. What can we expect as this technology continues to grow? And how will it impact you?

Published September 14, 2020

By Liang Dong

Alexandra Boltasseva, PhD

From virtual assistants like Siri to self-driving cars and computer-aided medical diagnoses, artificial intelligence (AI) affects our lives with unprecedented speed. Slowly but steadily, scientists in a broad range of fields have started to embrace AI in their research, hoping to significantly reduce the time needed to achieve new discoveries. This trend has become more obvious in the physical sciences, and in the field of materials science in particular, which is focused on the discovery and production of new, advanced materials imbued with desirable properties or functions. Think: screens of foldable smartphones; batteries that power electric cars; or materials that bend light around them, rendering them invisible.

How exactly could AI help materials scientists? We recently interviewed three honorees of the Blavatnik Awards for Young ScientistsAlexandra Boltasseva, PhD, Professor of Electrical and Computer Engineering at Purdue University; Léon Bottou, PhD, Principal Researcher at Facebook AI Research; and Sergei V. Kalinin, PhD, Corporate Fellow at Oak Ridge National Laboratory, who are contributing to an upcoming virtual symposium on October 6 and 7, AI for Materials: From Discovery to Production. Here’s what they had to say about the opportunities, as well as the challenges, in this rising field.

It is only recently that researchers in the physical sciences, like materials scientists, have begun to incorporate AI techniques into their work. Why do we need to take advantage of AI for this field? What benefits may AI offer materials science?    

Kalinin
Sergei V. Kalinin, PhD

AI offers a set of powerful tools to explore large volumes of multidimensional data in the physical sciences, and promises to uncover hidden functional relationships between the physical properties that we can observe. As such, AI methods are poised to become an inseparable part of all physical sciences, to enable discovery and hypothesis-driven research and to guide planning of experiments. We can take advantage of a broad range of AI techniques—from multivariate statistics to convolutional networks, unsupervised and semi-supervised methods, Gaussian processing, and reinforcement learning.

In addition, the proliferation of laboratory automation in areas from materials synthesis to imaging of materials’ molecular structures opens up broad opportunities for AI-driven experiments. For example, we will be able to adopt large-scale robotic systems or the microscale lab-on-a-chip platforms in our experiments, producing thousands or more materials in a single process.

Boltasseva

My own field, photonics, has truly been transformed by the concept of “inverse design,” meaning scientists input desired performances of photonic systems into computers and run physics-informed algorithms to figure out the best possible optical designs. The daunting challenge of this field lies in the inconceivably high computational power required for an exhaustive search within the extremely large, hyper-dimensional space of optical design parameters and constituent materials. Merging AI techniques with photonics is expected to not only enhance and enrich the design space, but, most importantly, to unlock novel functionalities and bring about disruptive performance improvements.

As compared to life sciences and pharmaceutical sciences, the application of AI in physical sciences is at least 10 years behind. What do you think is the biggest challenge for applying AI in physical sciences? How could the AI and physical sciences communities work together to address these challenges? 

Bottou
Léon Bottou, PhD

Using machine learning in physical sciences is not an obvious proposition. Recent advances in AI have shown how tasks in computer science, such as computer vision and machine translation, can be achieved using big data. Yet it would be unwise to claim that this success can be replicated in all scientific fields. Big data only reveal statistical correlations that are not always indicative of the causal relations that physicists often seek. To solve this question, the AI and physics communities may take the strategy of defining a hierarchy of problems for which one could envision using AI, such as:

  • Visualizing or measuring an ongoing physical phenomenon. These problems are the most accessible to AI/machine learning because they can directly leverage recent advances in computer vision and signal analysis in collecting data from physical experiments and computations.
  • Explaining a physical phenomenon. These problems belong to the next rung of difficulty because we need AI/machine learning systems that incorporate enough of our current knowledge of physics, and can then clarify the phenomenon of interest by constructing something interpretable on top of our current knowledge.
  • Designing a physical system that leverages a certain phenomenon in new ways. These are by far the most difficult problems, because they require AI/machine learning systems to accurately predict how the physical phenomenon will be affected by changes that are not included or prominent in the experimental data on which AI models have been trained.
Boltasseva

The physical sciences community should ultimately build extensive databases to unleash the power of AI. We should even set up an ‘optical structures and materials genome’ project to construct a comprehensive dataset of photonic concepts, architectures, components, and photonic materials to enable hierarchical machine learning algorithms that could provide ultimate-efficiency devices.

Kalinin

I agree with Alexandra. AI tends to proliferate in the communities that adopt the model of open sharing of codes and data. While some areas of physics research have undergone this transformation, many more require both enabling tools and proof-of-benefit to accelerate this process.

I also want to add on to Léon’s comment on the fundamental difference between the AI and physics communities. AI starts with purely correlative models, and tends to rely on big data. In comparison, research in physical sciences is strongly based on prior knowledge to explore the cause and effect relationships, and often assumes the presence of simple rules or descriptors that can give rise to complex behaviors in macroscopic systems. Experiments in physical sciences can give rise to huge data volumes, but these data can pertain only to one specific situation of the system and hence are not “big.”

In order to further leverage the benefits of AI in physical sciences, researchers have to possess both sufficient domain knowledge in physical sciences and expertise in machine learning, or forge robust interdisciplinary collaborations. Conferences like AI for Materials will help researchers in both fields form these kinds of interdisciplinary teams.

Also read: The Challenge of Quantum Error Correction

Game Changers: Scientists Shaping the Future of Research in the UK

On March 5, 2020, the New York Academy of Sciences celebrated the Laureates and Finalists and winners of the 2020 Blavatnik Awards for Young Scientists in the United Kingdom. The one-day symposium featured fast-paced, engaging research updates from nine scientists working in diverse fields within life sciences, chemistry, and physical sciences and engineering. This year’s Blavatnik UK honorees are probing the deepest mysteries ranging from the universe to the human mind, tackling longstanding questions that have occupied scientists and philosophers for millennia. Is there life beyond our Solar system? How is knowledge organized in the brain? What is the fundamental nature of gravity? Find out how this game-changing group of young scientists is working to answer these questions in this summary of the symposium.

Symposium Highlights

  • Environmental factors can influence the defense strategies bacteria use to fend off invading viruses. Insights into this process are advancing the potential for phage therapy as an alternative to antibiotics.
  • New analytical and computational tools are revealing the neural machinery that allows the brain to create models of the world and facilitates decision-making and behavior.
  • Chemists can exploit chirality to create novel molecules with a wide variety of applications in drug design, consumer electronics, and catalysis.
  • The scientific community is closer now than ever to realizing the commercial potential of nuclear fusion as a source of clean energy.
  • The first viable theory of massive gravity might help explain some of the biggest mysteries in physics, including the accelerated expansion of the universe.

Hosted By

Victoria Gill
Science Correspondent
BBC News

Speakers

Tim Behrens, DPhil
University of Oxford and University College London

Ian Chapman, PhD
UK Atomic Energy Authority

Matthew J. Fuchter, PhD
Imperial College London

Stephen M. Goldup, PhD
University of Southampton

Kirsty Penkman, PhD
University of York

Claudia de Rham, PhD
Imperial College London

Eleanor Stride, PhD
University of Oxford

Amaury Triaud, PhD
University of Birmingham

Edze Westra, PhD
University of Exeter

Program Supporter

Changing the Game in Life Sciences

Speakers

Eleanor Stride, PhD
University of Oxford

Edze Westra, PhD
University of Exeter

Tim Behrens, DPhil
University of Oxford & University College London

Engineering Bubbles

Mechanical engineer Eleanor Stride never planned to design drug delivery systems. She was “convinced I wanted to spend my career designing Aston Martins,” until a chance discussion with a supervisor piqued her interest in therapeutic applications of engineered microbubbles. Just two microns in diameter, microbubbles can be used as ultrasound contrast agents, but Stride sees a role for these tiny tools in the fight against cancer. “In many cases, the problem with cancer drugs [is] how we deliver them,” she said, explaining that systemic chemotherapy agents often cannot penetrate far enough into tumors to be effective. These drugs can also cause side effects and damage healthy tissues.

Microbubbles can help sidestep these challenges, safely encapsulating drug molecules within a stabilizing shell.  The shell can be functionalized with magnetic nanoparticles, allowing clinicians to direct the bubbles’ aggregation at tumor sites and visualize them with ultrasound. As the bubbles compress and release in response to the ultrasound beam, the oscillation helps the bubbles penetrate into the surrounding tissue. “If we increase the ultrasound energy, we can destroy the bubble, allowing us to release the drugs on demand,” said Stride, noting that molecules released from a single 2-micron microbubble can circulate up to 100 times that diameter, pumping drugs deep into tumor tissues. This approach is highly localized—drugs are only released at the tumor site—which eliminates the potential for systemic toxic effects.

Ultrasound-stimulated oscillation of microbubbles creates a vortex in surrounding fluids. The vortex pumps drug molecules deep into tumor sites.

In 2019, Stride and a team of collaborators published the results of trials using oxygen-loaded magnetic microbubbles to treat malignant pancreatic tumors. In animal models, tumors treated with microbubble-delivered drugs showed dramatic spikes in cell death and also shrank in size, “which can mean the difference between a surgeon being able to remove a tumor or not,” said Stride. Additional experiments have helped hone techniques for external magnetic control of microbubbles within blood vessels to ensure precise, targeted drug delivery—a critical step toward tailoring this method for use in humans. Stride and her collaborators aim to launch a clinical trial in pancreatic cancer patients “in the very near future.”

Insights From Bacteria-Phage Interactions

As the fight against viruses dominates the news cycle, 2020 Blavatnik Awards UK Finalist Edze Westra shared an update from the front lines of a viral war billions of years in duration: the “evolutionary arms race” between bacteria and the viruses that infect them, called phages. The interactions between bacteria and phages—the most abundant biological entities on Earth—have profound implications for the development of phage-based therapies as alternatives to antibiotics.

Phages are often successful killers, but bacteria have evolved sophisticated immune strategies to resist attacks. Understanding how and when bacteria deploy each of these defensive tactics is key to designing phage therapies to treat bacterial infections.

Like humans, bacteria utilize both innate and adaptive immune responses to invading pathogens. In bacteria, innate immunity relies on the modification of surface structures to prevent phages from attaching. This system is effective, yet it creates no “record,” or memory, of which phages it encounters. The adaptive immune system, however, allows bacteria to build a database of previously encountered pathogens in the form of bits of genetic material snipped from invading phages and incorporated into the bacterium’s own DNA. The adaptive immune system, known as CRISPR immunity, forms the basis of CRISPR-Cas genome editing techniques. “There’s a critical balance between these two systems, and both are critical for survival,” said Westra, whose research aims to determine the factors that influence whether a bacterium mounts an innate or adaptive immune defense against a particular phage.

Using Pseudomonas aeruginosa, an antibiotic-resistant pathogen that often infects cystic fibrosis patients, Westra determined that a bacterium’s environment—specifically, the level of available nutrients—determined which defensive strategy was utilized. In high-nutrient environments, almost all bacteria deployed an innate immune response to phage attacks, whereas in lower nutrient settings, CRISPR immunity dominated.

The level of available nutrients influences which immune strategy bacteria use to defend against phage attacks.

In experiments using moth larvae, Westra discovered that infections were more severe when bacteria utilized CRISPR immunity, whereas bacteria that evolved innate immunity often caused less aggressive infections. “If we can manipulate how bacteria evolve resistance to phages, this could potentially revolutionize the way we approach antimicrobial resistance, with major benefits to our healthcare,” Westra said.

Building Models of the World

Computational neuroscientist Timothy Behrens is fascinated with the basic functions and decisions of everyday life—the process of navigating our home or city, the steps involved in completing household tasks, the near-subconscious inferences that inform our understanding of the relationships between people and things. Behrens designs analytical tools to understand how neuronal activity in the brain gives rise to these thought processes and behaviors, and his research is illuminating how knowledge is organized in the brain.

The activities of grid cells and place cells are well understood. By creating spatial maps of the world, grid and place cells allow us to navigate familiar spaces and locate items, such as car keys. Behrens explained that much less is known about how the brain encodes non-spatial, abstract concepts and sequence-based tasks, such as loading, running, and emptying a dishwasher. Over the past several years, Behrens and his collaborators have demonstrated that abstract information is similarly mapped as grid-like codes within the brain. “On some level, all relational structures are the same, and all are handled by the same neural machinery,” he said. This insight helps explain the effects of diseases like Alzheimer’s, which targets grid and place cells first and impacts both spatial and non-spatial knowledge.

Relational information is encoded by the same neural machinery that encodes spatial and navigational maps.

In another line of research, Behrens is probing a phenomenon called replay, during which the brain revisits recent memories as a means to consolidate knowledge about current events and anticipate future ones. Behrens illustrated the concept by showing patterns of neuronal activity as a rat runs around a track, then rests. Even at rest, the rat’s brain displays millisecond-long flashes of neuronal activity that mimic those that take place during running. “He’s not running down the track anymore, but his brain is,” said Behrens. Replay also underlies the human ability to understand a simple story even when it’s told in the wrong order. “Our knowledge of the world tells us…what the correct order is, and replay will rapidly stitch together the events in the correct order.”

Computational tools developed in Behrens’ lab have been shared with thousands of scientists around the globe as they pursue new hypotheses about the neural computations that control cognition and behavior. “It’s an exciting time to be thinking about the brain,” Behrens said.

Further Readings

Stride

Beguin E, Shrivastava S, Dezhkunov NV, et al.

Direct Evidence of Multibubble Sonoluminescence Using Therapeutic Ultrasound and Microbubbles

ACS Appl Mater Interfaces. 2019 Jun 5;11(22):19913-19919

Beguin E, Bau L, Shrivastava S, Stride E.

Comparing Strategies for Magnetic Functionalization of Microbubbles

ACS Appl Mater Interfaces. 2019 Jan 16;11(2):1829-1840

Westra

Alseth EO, Pursey E, Luján AM, et al.

Bacterial Biodiversity Drives the Evolution of CRISPR-based Phage Resistance in Pseudomonas Aeruginosa

Nature. 2019 Oct;574(7779):549-552

Westra ER, van Houte S, Gandon S, Whitaker R.

The Ecology and Evolution of Microbial CRISPR-Cas Adaptive Immune Systems

Philos Trans R Soc Lond B Biol Sci. 2019 May.13;374(1772):20190101

Behrens

Liu Y, Dolan RJ, Kurth-Nelson Z, Behrens TEJ

Human Replay Spontaneously Reorganizes Experience

Cell. 2019 Jul 25;178(3):640-652.e14

Constantinescu AO, O’Reilly JX , Behrens TEJ

Organizing Conceptual Knowledge in Humans With a Gridlike Code

Science. 2016 Jun 17;352(6292):1464-1468

Behrens TEJ, Muller TH, Whittington James CR

What Is a Cognitive Map? Organizing Knowledge for Flexible Behavior

Neuron. 2018 Oct 24;100(2):490-509

Changing the Game in Chemistry

Speakers

Matthew J. Fuchter, PhD
Imperial College London

Stephen M. Goldup, PhD
University of Southampton

Kirsty Penkman, PhD
University of York

Exploiting Molecular Shape to Develop Materials and Medicines

Consider the handshake: a greeting so automatic it takes place without thinking. Two right hands extend and naturally lock together, but as Matthew Fuchter explained, that easy connection becomes impossible if one party offers their left hand instead. The fumbling that ensues stems from a type of asymmetry called chirality. Chiral objects, such as hands, are mirror-image forms that cannot be superimposed or overlapped, and when one chiral object interacts with another, their chirality dictates the limits of their interaction. Chirality can be observed throughout nature, from the smallest biological molecules to the structures of skyscrapers.

In organic chemistry, molecular chirality can be exploited to tremendous advantage. Fuchter explained that the shape of molecules “is not only critical for their molecular properties, but also for how they interact with their environment.” By controlling subtle aspects of molecular shape, Fuchter is pioneering new strategies in drug design and devising solutions to technological problems that plague common electronic devices.

The notion of pairing complementary molecular geometries to achieve a specific effect is not unique to drug design—such synchronicities can be found throughout nature, including in the “lock and key” structure of enzymes and their substrates. Fuchter’s work aims to invent new drug molecules with geometries perfectly suited to bind to specific biological targets, including those implicated in diseases such as malaria and cancer.

Only one of these two chiral molecules has the correct orientation, or “handedness” to bind to the receptor site on the target protein.

Fuchter is also exploring applications for chirality in a field where the concept is less prominent—consumer electronics. Organic LED, or OLED, technology has “revolutionized the display industry,” allowing manufacturers to create ultra-thin, foldable screens for smartphones and other displays. Yet these features come at a steep efficiency cost—more than half of the light generated by OLED pixels is blocked by anti-glare filters added to the screens to minimize reflectiveness. A novel solution, in the form of chiral molecules bound to non-chiral OLED-optimized polymers, induces a chiral state of light called circularly polarized light. These circularly polarized, chiral light molecules are capable of bypassing the anti-glare filter on OLED screens. Fuchter noted that displays are far from the only technology that stands to be impacted by the introduction of chiral molecules. “Our research is generating new opportunities for chiral molecules to control electron transport and electron spin, which could lead to new approaches in data storage,” he said.

Making Use of the Mechanical Bond

Most molecules are bound by chemical bonds—strong, glue-like connections that maintain the integrity of molecules, which can be both simple, such as hydrogen, and highly complex, such as DNA. 2020 Blavatnik Awards UK Finalist Stephen Goldup’s work focuses on a less familiar bond. Mechanical bonds join molecules in a manner akin to an interconnected chain of links—the components retain movement, yet cannot separate.

Mechanically interlocked molecules have the potential to yield materials with “exciting properties,” according to Goldup, but in the decades since they were first synthesized, they have largely been regarded as “molecular curiosities.” Goldup’s lab is working to push these molecules beyond the laboratory bench by characterizing the properties of interlocked molecules and probing their potential applications in unprecedented ways. His work focuses on two types of mechanically bound molecules—catenanes, in which components are linked together like a chain, and rotaxanes, which consist of a ring component threaded through a dumbbell-shaped axle.

Goldup’s lab has taken cues from nature to introduce additional elements into rotaxanes, resulting in novel molecules with a variety of potential applications. For example, much as enzymes contain “pockets” within which small molecules can bind, rotaxanes too contain a space that can trap a molecule or ion of interest. Rotaxanes that bind metal ions have unique magnetic and electronic properties that could be used in memory storage devices or medical imaging. Inspired by proteins and enzymes that bind DNA, Goldup’s lab has also designed rotaxanes in which DNA itself is the “axle.” In theory, these molecules can be used to effectively “hide” portions of DNA and alter its biological behavior.

Just as enzymes bind small molecules with their structures, rotaxanes can bind molecules in the cavity between the ring and the axle.

Perhaps most significantly, Goldup’s lab has solved a longstanding obstacle to studying rotaxanes: the difficulty of making them. The problem lies in the fact that rotaxanes can be chiral even when their components are not, making it extremely challenging to synthesize a distinct “hand,” or version, of the molecule. Recalling Matthew Fuchter’s example of how an awkward left-hand/right-hand handshake differentiates the “handedness” of two chiral objects, Goldup explained how his lab developed a technique for synthesizing distinctly “left” or “right” handed rotaxanes by utilizing a chiral axle to build the molecules. “Our insight was that by making the axle portion chiral on its own, when we thread the axle into the ring, the rotaxanes we make are no longer mirror-images of each other. They have different properties, and they can now be separated,” he said. Once separate, the chiral portion of the axle can be chemically removed and replaced with other functional groups.

Goldup’s lab is conducting experiments with new mechanically-locked molecules—including chiral rotaxane catalysts— to determine where they may outperform existing catalysts.

Amino Acids as a Portal to the Past

Scientists have multiple methods for peering into the history of Earth’s climate, including sampling marine sediment and ice cores that encapsulate environmental conditions stretching back millions of years. “But this is an incomplete picture—akin to a musical beat with no notes,” said Kirsty Penkman, the 2020 Blavatnik Awards UK Laureate in Chemistry. The records of life on land—fossil records—provide “the notes to our tune, and if we know the timing, that gives us the whole melody,” she said.  Archaeologists, paleontologists, and climate scientists can harmonize fossil records with climate history to understand the past, yet their efforts stall with fossils older than 50,000 years—the limit of radiocarbon dating.

Penkman’s lab is developing dating methods for organic remains that reach far deeper into the history of life on Earth. Their strategy relies not on the decay of carbon, but the conversion of amino acid molecules from one form to another. Continuing the theme of chirality from previous presentations, Penkman explained that amino acids exist in two mirror-image forms. However, the body only synthesizes amino acids in the “left-handed,” or L-form. This disequilibrium shifts after death, when a portion of L-amino acids begins a slow, predictable conversion to the right-handed, or D-form. The older the fossil, the greater the balance between D and L isomers. This conversion process, called racemization, was first proposed as a dating method in the 1960s. Yet, it became clear that some of the fossil amino acids were vulnerable to environmental factors that impact the racemization rate, and therefore the date.

About 15 years ago, Penkman discovered that minute stores of proteins within the remains of snail shells are entrapped in intracrystalline voids. These tiny time capsules are unaffected by environmental factors. Studies have since confirmed that shells found in older horizons, for example deeper underground, contain higher ratios of D-amino acids versus those found at younger sites, thus validating the technique.

Calcitic snail shells found at older horizons have higher ratios of D-amino acids than those found at younger horizons.

Snail shells are often found in archeological sites, a serendipity that has led to astonishing findings about early human migration. Shells found alongside several Paleolithic tools “dated as far back as 700,000 years,” according to Penkman. “We’ve successfully shown that early humans were living in Northern Europe 200,000 years earlier than previously believed,” she said.

Penkman’s team has analyzed remains of ostrich eggshells at some of the earliest human sites in Africa, discovering fully preserved, stable sequences of proteins in shells dating back 3.8 million years. Mammalian remains are the next frontier for Penkman’s lab. They have analyzed amino acids in ancient tooth enamel—including that of a 1.7-million-year-old rhinoceros—and are developing microfluidic techniques to sample enamel from early human remains.

Further Readings

Fuchter

Yang Y, Rice B, Shi X, et al.

Emergent Properties of an Organic Semiconductor Driven by its Molecular Chirality

ACS Nano. 2017 Aug 22;11(8):8329-8338

Yang Y, Correa da Costa R, Fuchter MJ, Campbell AJ

Circularly polarized light detection by a chiral organic semiconductor transistor

Nat. Photonics. 2013 July 21;7:634–638

Goldup

Jamieson EMG, Modicom F, Goldup SM

Chirality in Rotaxanes and Catenanes

Chem Soc Rev. 2018 Jul 17;47(14):5266-5311

Lewis JEM, Beer PD, Loeb SJ, Goldup SM

Metal Ions in the Synthesis of Interlocked Molecules and Materials

Chem Soc Rev. 2017 May 9;46(9):2577-2591

Galli M, Lewis JEM, Goldup SM

A Stimuli-responsive Rotaxane–Gold Catalyst: Regulation of Activity and Diastereoselectivity

Angewandte Chemie International Edition. 2015

Penkman

Penkman KEH, Kaufman DS, Maddy D, Collins MJ

Closed-system Behavior of the Intra-crystalline Fraction of Amino Acids in Mollusk Shells

Quaternary Geochronology. 2008. Feb-May; 3, 1–2:2-25

Demarchi B, Hall S, Roncal-Herrero T, et al

Protein Sequences Bound to Mineral Surfaces Persist Into Deep Time

eLife. 2016 Sep 27;5:e17092

Penkman KEH, Preece RC, Bridgland DR, et al

A Chronological Framework for the British Quaternary Based on Bithynia Opercula

Nature. 2011 Jul 31;476(7361):446-9

Changing the Game in Physical Sciences and Engineering

Speakers

Amaury Triaud
University of Birmingham

Ian Chapman
UK Atomic Energy Authority and Culham Centre for Fusion Energy

Claudia de Rham
Imperial College London

Worlds Beyond Our Solar System

For millennia, humans have wondered whether life exists beyond our planet.  Amaury Triaud, 2020 Blavatnik Awards UK Finalist believes we are closer to answering that question now than at any other time in history. The study of exoplanets—planets that orbit stars other than the Sun—offers what Triaud believes is “the best hope for finding out how often genesis happens, and under what conditions.”

The search for exoplanets has revealed remarkable variety among stars and planets in our galaxy. “The universe is far more surprising and diverse than we anticipated,” said Triaud. Astronomers have identified thousands of exoplanets since 1995, and now estimate that there are more planets in the Milky Way than stars—”something we had no idea about ten years ago,” Triaud said. Many exoplanets orbit stars so much smaller than the Sun that these stars cannot be seen with the naked eye.  Yet these comparatively small stars provide “optimal conditions” for exoplanet hunters.

Exoplanets are often detected using the transit method—as an orbiting planet passes in front of a star, its shadow temporarily dims the star’s brightness. The larger the planet relative to the star, the greater its impact on the brightness curve and the easier for astronomers to detect. While monitoring a small star 39 light-years from Earth, TRAPPIST-1, a team of astronomers, including Triaud, discovered an exoplanet system comprised of seven rocky planets similar in size to Earth, Venus, and Mercury.

“The next question is to find out whether biology is happening out there,” said Triaud, joking that the biology of interest is not little green men, but rather green algae or microbes similar to the ones that fill our atmosphere with oxygen. The presence of oxygen “acts like a beacon through space, broadcasting that here on Earth, there is life,” said Triaud, explaining that the only way to gauge the presence of life on exoplanets is through atmospheric analysis. Using transmission spectroscopy, Triaud and other astronomers will look for exoplanets that possess an atmosphere and chemical signatures of life, such as oxygen, ozone, or methane, in the atmospheric composition of exoplanets.

Measurements of spectral signatures in a planet’s atmosphere can reveal the presence of gases associated with life, including oxygen and methane. 

Such analyses will begin with the launch of the James Webb telescope in 2021.  In the meantime, a land-based mission called Speculoos, based partially in Chile’s Atacama desert, is monitoring 1,400 stars in search of additional exoplanets. “It’s rather poetic that from one of the most inhospitable places on Earth, we are on the path to investigating habitability and the presence of life in the cosmos,” Triaud said.

The Path to Delivering Fusion Power

“There’s an old joke that nuclear fusion is 30 years away and somehow always will be,” said 2020 Blavatnik Awards UK Finalist Ian Chapman, but he insists that the joke will end soon. According to Chapman, the “ultimate energy source” is entering the realm of reality. “We’re now in the delivery era, where fusion lives up to its potential,” he said. Low-carbon, low-waste, capable of producing tremendous amounts of energy from an unlimited fuel source—seawater—and far safer than nuclear fission, fusion power has a long list of desirable qualities. Chapman is the first to acknowledge that fusion is “really hard,” but his work is helping to ease the challenges and bring a future of fusion into focus.

Nuclear fusion relies on the collision of two atoms—deuterium, or “heavy” hydrogen, and tritium, an even heavier isotope of hydrogen. Inside the Sun, these atoms collide and fuse, producing the heat and energy that powers the star. Replicating that process on Earth requires enough energy to heat the fuel. of deutrium and tritium gases to temperatures ten times hotter than the Sun, a feat that Chapman admits “sounds bonkers, but we do it every day.”

Within fusion reactors called tokamaks, this superhot fuel is trapped between arrays of powerful magnets that “levitate” the jet as it spins around a central magnetic core, preventing the fuel from melting reactor walls. Yet this is an imperfect process, explained Chapman, and due to fuel instabilities, eruptions akin to “throwing a hand grenade into the bottom of the machine” happen as often as once per second. Chapman devised a method based on his numerical calculations for preventing these eruptions using additional magnet arrays that induce three-dimensional perturbations, or “lobes” at the edge of the plasma stream. Just as a propped-open lid on a pot of boiling water allows steam to escape, these lobes provide a path to release excess pressure.

An array of magnets near the plasma edge creates perturbations in the fuel stream, allowing pressure to escape safely.

Chapman’s technique has been incorporated into the “the biggest scientific experiment ever undertaken by humankind”—a massive tokamak called ITER, roughly the size of a football stadium and equipped with a central magnet strong enough to lift an aircraft carrier. Scheduled to begin producing power in 2025, ITER aims to demonstrate the commercial viability of nuclear fusion. “We can put 50 megawatts of power into the machine, and it produces 500 megawatts of power out,” said Chapman. “That’s enough to power a medium-sized city for a day.”

Even before ITER’s completion, Chapman and others are setting their sights on designing less expensive fusion devices. Late last year, the UK committed to building a compact tokamak that offers the benefits of fusion with a smaller footprint, and Chapman is the leader of this project.

The Nature of Gravity

Claudia de Rham, the 2020 Blavatnik Awards UK Laureate in Physical Sciences and Engineering, concluded the day’s research presentations with an exploration of nothing less than “the biggest mystery in physics today.”  For decades, cosmologists and physicists have grappled with discrepancies between observations about the universe—for example, its accelerated expansion— and Einstein’s general theory of relativity, which dictates that gravity should gradually slow that expansion. “The universe is behaving in unexpected ways,” said de Rham, whose efforts to resolve this question stand to profoundly impact all areas of physics.

Understanding the fundamental nature of gravity is key to understanding the origin and evolution of the universe. As de Rham explained, gravity can be detected in the form of gravitational waves, which are produced when two black holes or neutron stars rotate around each other, perturbing the fabric of spacetime and sending rippling waves outward like a stone tossed into a pond. But gravity can also be represented as a fundamental particle, the graviton, similar to the way light can be considered as a particle, the photon, or an electromagnetic wave.  Unlike the other fundamental particles such as the photon, the electron, the neutrino, or even the famously elusive Higgs boson, the graviton has never been observed. In theory, the graviton would, like all fundamental particles, exist even in a perfect vacuum, a phenomenon known as vacuum quantum fluctuation. Unknown in Einstein’s day, vacuum quantum fluctuations, when factored into the general theory of relativity, do predict an accelerated expansion of the universe. “That’s the good news,” said de Rham. “The bad news is that the predicted rate of expansion is too fast by at least 28 orders of magnitude.”

This raises the possibility that “general relativity may not be the correct description of gravity on large cosmological scales,” said de Rham. If the graviton had mass, however, it would impact the behavior of gravity on the largest scales and could explain the observed rate of expansion.

Signal patterns from gravitational wave events can serve as models for estimating the mass of the graviton. By comparing the expected signals produced by either a massless particle or a high-mass particle with actual signal patterns from detected events, physicists can place an upper and lower boundary on the graviton’s potential mass.

The idea of a massive graviton has been considered—and refuted—by physicists as far back as the 1930s. Several years ago, de Rham, along with collaborators Andrew Tolley and Gregory Gabadadze, “realized a loophole that had evaded the whole community.” Together, they derived the first theory of massive gravity. “Through gravity, we can now connect small vacuum fluctuations with the acceleration of the universe, linking the infinitely small with the infinitely large,” de Rham said.

Determining the mass of the graviton requires the most precise scale imaginable, and de Rham believes that gravitational wave observatories are perfectly suited to the task. Whether her theory will hold up in future tests remains to be seen, but when it comes to solving this epic mystery, “the possibility is now open.”

Further Readings

Triaud

Gillon M, Triaud AH, Demory BO, et al.

Seven temperate terrestrial planets around the nearby ultracool dwarf star TRAPPIST-1

Nature. 2017 Feb 22;542(7642):456-460

Gillon M,  1 , Jehin E, Lederer SM, et al

Temperate Earth-sized Planets Transiting a Nearby Ultracool Dwarf Star

Nature. 2016 May 12;533(7602):221-4

de Wit J, Wakeford HR, Gillon M, et al

A Combined Transmission Spectrum of the Earth-sized Exoplanets TRAPPIST-1 B and C

Nature. 2016 Sep 1;537(7618):69-72

Chapman

Kirk A, Harrison J, Liu Y, et al.

Observation of Lobes Near the X Point in Resonant Magnetic Perturbation Experiments on MAST

Phys Rev Lett. 2012 Jun 22;108(25):255003

Chapman IT, Morris AW

UKAEA Capabilities to Address the Challenges on the Path to Delivering Fusion Power

Philos Trans A Math Phys Eng Sci. 2019 Mar 25;377(2141):20170436

Claudia de Rham

de Rham C.

Massive Gravity

Living Rev Relativ. 2014;17(1):7.

de Rham C, Gabadadze G, Tolley AJ

Resummation of Massive Gravity

Phys Rev Lett. 2011 Jun 10;106(23):231101

de Rham C, Deskins JT, Tolley AJ, Zhou S.

Graviton Mass Bounds

Rev. Mod. Phys. 89 (2017), 025004

Panel Discussion: Hopes for the Future

Speakers

Ian Chapman, PhD
UK Atomic Energy Authority

Kirsty Penkman, PhD
University of York

Eleanor Stride, PhD
University of Oxford

Edze Westra, PhD
University of Exeter

Victoria Gill
BBC News (Moderator)

Several Laureates and Finalists of the 2020 Blavatnik Awards in the UK joined BBC science reporter Victoria Gill for the final session of the day, a wide-ranging panel discussion that touched on issues both current and future-looking.

Two themes—fear and opportunity— emerged as powerful forces shaping science and society, especially as it relates to climate change and the threat of emerging infectious disease. Gill noted that climate change is “the biggest challenge ever to face humanity,” and that many efforts to raise awareness of its impacts focus on bleak projections for the future. Asked for insights on shifting the tone of climate change communications, Kirsty Penkman acknowledged that “there needs to be a certain level of fear to get people’s attention.” She then advocated for a solutions-oriented plan rooted in the fast pace of scientific progress in clean energy, among other areas. “This is an amazing opportunity,” she said. “Humans are ingenious….in the last 120 years we’ve moved from a horse-drawn economy to a carbon-based economy, and in 5 or 20 years we could be in a fusion-based economy. We have the potential to open up a whole new world.” Eleanor Stride suggested combatting complacency by emphasizing the power of small changes in mitigating the impact of climate change. “One billion people making a tiny change has a huge impact,” she said.

The specter of a coronavirus pandemic had not yet become a reality at the time of the symposium. But Edze Westra presciently detailed the challenges of containing a highly contagious emerging pathogen in a “tightly connected world.” He commented that detecting and containing emerging diseases hinges on the development of new diagnostics, and that preventing future outbreaks will require cultural shifts to limit high-risk interactions with wildlife. For zoonotic diseases such as the novel coronavirus, “it’s all about opportunity,” Westra said.

Panelists also looked to the future of science, touching on issues of equality, discrimination, and diversity, and emphasizing the importance of raising the bar for science education. Stride noted that children are natural scientists, gravitating toward problem-solving and puzzles regardless of nationality or gender. “But something happens later,” she said, lamenting the drop in interest in science as children progress in school. “One of the things that gets lost is that creativity, which is what science really is—we’re coming up with a guess and trying to gather evidence for it—we’re not just learning a huge number of facts and regurgitating them,” she said.

In the wake of Brexit, panelists expressed concern about potential difficulties in attracting international students to their labs. “Diversity is so important,” said Penkman. “Getting ideas from all around the world from people with different backgrounds is essential to making science in the UK—and the world—the best it can be.” In her closing comments, Penkman said that ultimately, the trajectory of science comes down to the people in the field. “My eternal optimism is in the people I work with and the people I talk to when I visit schools—it’s that innate interest and curiosity. Whenever I see it, I feel that is the future of science,” she said.

Shaping the Future of Science: 2019 Blavatnik Science Symposium

Overview

The New York Academy of Sciences and the Blavatnik Family Foundation hosted the annual Blavatnik Science Symposium on July 15–16, 2019, uniting 75 Finalists, Laureates, and Winners of the Blavatnik Awards for Young Scientists. Honorees from the UK and Israel Awards programs joined Blavatnik National and Regional Awards honorees from the U.S. for what one speaker described as “two days of the impossible.” Nearly 30 presenters delivered research updates over the course of nine themed sessions, offering a fast-paced peek into the latest developments in materials science, quantum optics, sustainable technologies, neuroscience, chemical biology, and biomedicine.

Symposium Highlights

  • Computer vision and machine learning have enabled novel analyses of satellite and drone images of wildlife, food crops, and the Earth itself. 
  • Next-generation atomic clocks can be used to study interactions between particles in complex many-body systems.
  • Bacterial communities colonizing the intestinal tract produce bioactive molecules that interact with the human genome and may influence disease susceptibility.
  • New catalysts can reduce carbon emissions associated with industrial chemical production.
  • Retinal neurons display a surprising degree of plasticity, changing their coding in response to repetitive stimuli.
  • New approaches for applying machine learning to complex datasets is improving predictive algorithms in fields ranging from consumer marketing to healthcare.
  • Breakthroughs in materials science have resulted in materials with remarkable strength and responsiveness.
  • Single-cell genomic studies are revealing some of the mechanisms that drive cancer development, metastasis, and resistance to treatment.

Speakers

Emily Balskus, PhD
Harvard University

Chiara Daraio, PhD
Caltech

William Dichtel, PhD Northwestern University

Elza Erkip, PhD
New York University

Lucia Gualtieri, PhD
Stanford University

Ive Hermans, PhD
University of Wisconsin – Madison

Liangbing Hu, PhD
University of Maryland, College Park

Jure Leskovec, PhD
Stanford University

Heather J. Lynch, PhD
Stony Brook University

Wei Min, PhD
Columbia University

Seth Murray, PhD
Texas A & M University

Nicholas Navin, PhD, MD
MD Anderson Cancer Center

Ana Maria Rey, PhD
University of Colorado Boulder

Michal Rivlin, PhD
Weizmann Institute of Science

Nieng Yan, PhD
Princeton University

Event Sponsor

Technology for Sustainability

Speakers

Heather J. Lynch
Stony Brook University

Lucia Gualtieri
Stanford University

Seth Murray
Texas A & M University

Highlights

  • Machine learning algorithms trained to analyze satellite imagery have led to the discovery of previously unknown colonies of Antarctic penguins.
  • Seismographic data can be used to analyze more than just earthquakes—typhoons, hurricanes, iceberg-calving events and landslides are reflected in the seismic record.
  • Unmanned aerial systems are a valuable tool for phenotypic analysis in plant breeding, allowing researchers to take frequent measurements of key metrics during the growing season and identify spectral signatures of crop yield.

Satellites, Drones, and New Insights into Penguin Biogeography

Satellite images have been used for decades to document geological changes and environmental disasters, but ecologist and 2019 Blavatnik National Awards Laureate in Life Sciences, Heather Lynch, is one of the few to probe the database in search of penguin guano. She opened the symposium with the story of how the Landsat satellite program enabled a surprise discovery of several of Earth’s largest colonies of Adélie penguins, a finding that has ushered in a new era of insight into these iconic Antarctic animals.

Steady streams of high quality spatial and temporal data regularly support environmental science. In contrast, Lynch noted that wildlife biology has advanced so slowly that many field techniques “would be familiar to Darwin.” Collecting information on animal populations, including changes in population size or migration patterns, relies on arduous and imprecise counting methods. The quest for alternative ways to track wildlife populations—in this case, Antarctic penguin colonies—led Lynch to develop a machine learning algorithm for automated identification of penguin guano in high resolution commercial satellite imagery, which can be combined with lower resolution imagery like that coming from NASA’s Landsat program. Pairing measurements of vast, visible tracts of penguin guano—the excrement colored bright pink due to the birds’ diet—with information about penguin colony density yields near-precise population information. The technique has been used to survey populations in known penguin colonies and enabled the unexpected discovery of a “major biological hotspot” in the Danger Islands, on the tip of the Antarctic Peninsula. This Antarctic Archipelago is so small that it is doesn’t appear on most maps of the Antarctic continent, yet it hosts one of the world’s largest Adélie penguin hotspots.

Satellite images of the pink stains of Antarctic penguin guano have been used to identify and track penguin populations.

Lynch and her colleagues are developing new algorithms that utilize high-resolution drone and satellite imagery to create centimeter-scale, 3D models of penguin terrain. These models feed into detailed habitat suitability and population-tracking analyses that further basic research and can even influence environmental policy decisions. Lynch noted that the discovery of the Danger Island colony led to the institution of crucial environmental protections for this region that may have otherwise been overlooked.  “Better technology actually can lead to better conservation,” she said.

Listening to the Environment with Seismic Waves

The study of earthquakes has dominated seismology for decades, but new analyses of seismic wave activity are broadening the field. “The Earth is never at rest,” said Lucia Gualtieri, 2018 Blavatnik Regional Awards Finalist, while reviewing a series of non-earthquake seismograms that show constant, low-level vibrations within the Earth. Long discarded as “seismic noise,” these data, which comprise more than 90% of seismograms, are now considered a powerful tool for uniting seismology, atmospheric science, and oceanography to produce a holistic picture of the interactions between the solid Earth and other systems.

In addition to earthquakes, events such as hurricanes, typhoons, and landslides are reflected in the seismic record.

Nearly every environmental process generates seismic waves. Hurricanes, typhoons, and landslides have distinct vibrational patterns, as do changes in river flow during monsoons and “glacial earthquakes” caused by ice calving events. Gualtieri illustrated how events on the surface of the Earth are reflected within the seismic record—even at remarkably long distances—including a massive landslide in Alaska detected by a seismic sensor in Massachusetts. Gualtieri and her collaborators are tapping this exquisite sensitivity to create a new generation of tools capable of measuring the precise path and strength of hurricanes and tropical cyclones, and for making predictive models of cyclone strength and behavior based on decades of seismic data.

Improving Crop Yield Using Unmanned Aerial Systems and Field Phenomics

Plant breeders like Seth Murray, 2019 Blavatnik National Awards Finalist, are uniquely attuned to the demands a soaring global population places on the planet’s food supply. Staple crop yields have skyrocketed thanks to a century of advances in breeding and improved management practices, but the pressure is on to create new strategies for boosting yield while reducing agricultural inputs. “We need to grow more plants, measure them better, use more genetic diversity, and create more seasons per year,” Murray said. It’s a tall order, but one that he and a transdisciplinary group of collaborators are tackling with the help of a fleet of unmanned aerial systems (UAS), or drones.

Drones facilitate frequent measurement of plant height, revealing variations between varietals early in the growth process.

Genomics has transformed many aspects of plant breeding, but phenotypic, rather than genotypic, information is more useful for predicting crop yield. Using drones equipped with specialized equipment, Murray has not only automated many of the time-consuming measurements critical for plant phenotyping, such as tracking height, but has also identified novel metrics that can accelerate the development of new varietals. Spectral signatures obtained via drone can be used to identify top-yielding varietals of maize even before the plants are fully mature. Phenotypic features distilled from drone images are also being used to determine attributes such as disease resistance, which directly influence crop management. Murray’s team is modeling the influence of thousands of phenotypes on overall crop performance, paving the way for true phenomic selection in plant breeding.

Further Readings

Lynch

Borowicz A, McDowall P, Youngflesh C, et al.

Multi-modal survey of Adélie penguin mega-colonies reveals the Danger Islands as a seabird hotspot.

Sci Rep. 2018 Mar 2;8(1):3926.

Che-Castaldo C, Jenouvrier S, Youngflesh C, et al.

Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise.

Nat Commun. 2017 Oct 10;8(1):832.

Murray

Zhang M, Cui Y, Liu YH, et al.

Accurate prediction of maize grain yield using its contributing genes for gene-based breeding.

Genomics. 2019 Feb 28. pii: S0888-7543(18)30708-0.

Shi Y, Thomasson JA, Murray SC, et al.

Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research.

PLoS One. 2016 Jul 29;11(7):e0159781.

Quantum Optics

Speakers

Ana Maria Rey
University of Colorado Boulder

Highlights

  • Quantum mechanics underlies the technologies of modern computing, including transistors and integrated circuits.
  • Most quantum insights are derived from studies of single quantum particles, but understanding interactions between many particles is necessary for the development of devices such as quantum computers.
  • Atoms cooled to one billionth of a degree above absolute zero obey the laws of quantum mechanics, and can be used as quantum simulators to study many-particle interactions.

Atomic Clocks: From Timekeepers to Quantum Computers

The discovery of quantum mechanics opened “a new chapter in human knowledge,” said 2019 Blavatnik National Awards Laureate in Physical Sciences & Engineering, Ana Maria Rey, describing how the study of quantum phenomena has revolutionized modern computing, telecommunications, and navigation systems. Transistors, which make up integrated circuits, and lasers, which are the foundation of the atomic clocks that maintain the precision of satellites used in global positioning systems, all stem from discoveries about the nature of quantum particles.

The next generation of innovations—such as room temperature superconductors and quantum computers—will be based on new quantum insights, and all of this hinges on our ability to study interactions between many particles in quantum systems. The complexity of this task is beyond the scope of even the most powerful supercomputers. As Rey explained, calculating the possible states for a small number of quantum particles (six, for example) is simple. “But if you increase that by a factor of just 10, you end up with a number of states larger than the number of stars in the known universe,” she said.

Calculating the number of possible states for even a small number of quantum particles is a task too complex for even the most powerful supercomputer.

Researchers have developed several experimental platforms to clear this hurdle and explore the quantum world. Rey shared the story of how her work developing ultra-precise atomic clocks inadvertently led to one experimental platform that is already demystifying some aspects of quantum systems.

Atomic clocks keep time by measuring oscillations of atoms—typically in cesium atoms—as they change energy levels. Recently, Rey and her collaborators at JILA built the world’s most sensitive atomic clock using strontium atoms instead of cesium and using many more atoms that are typically found in these clocks. The instrument had the potential to be 1,000 times more sensitive than its predecessors, yet collisions between the atoms compromised its precision. Rey explained that by suppressing these collisions, their clock became “a window to explore the quantum world.” Within this framework, the atoms can be manipulated to simulate the movement and interactions of quantum particles in solid-state materials. Rey reported that this clock-turned-quantum simulator has already generated new findings about phenomena including superconductivity and quantum magnetism.

Further Readings

Rey

Goban A, Hutson R, Marti GE, et al.

Emergence of multi-body interactions in a fermionic lattice clock.

Nature. 2018 Nov;563(7731):369-373.

Kolkowitz S, Bromley SL, Bothwell T, et al.

Spin-orbit-coupled fermions in an optical lattice clock.

Nature. 2017 Feb 2;542(7639):66-70.

Chemical Biology

Speakers

Emily Balskus
Harvard University

Highlights

  • The human gut is colonized by trillions of bacteria that are critical for host health, yet may also be implicated in the development of diseases including colorectal cancer.
  • For over a decade, chemists have sought to resolve the structure of a genotoxin called colibactin, which is produced by a strain of E. coli commonly found in the gut microbiome of colorectal cancer patients.
  • By studying the specific type of DNA damage caused by colibactin, researchers found a trail of clues that led to a promising candidate structure of the colibactin molecule.

Gut Reactions: Understanding the Chemistry of the Human Gut Microbiome

The composition of the trillions-strong microbial communities that colonize the mammalian intestinal tract is well characterized, but a deeper understanding of their chemistry remains elusive. Emily Balskus, the 2019 Blavatnik National Awards Laureate in Chemistry, described her lab’s hunt for clues to solve one chemical mystery of the gut microbiome—a mission that could have implications for colorectal cancer (CRC) screening and early detection.

Some commensal E. coli strains in the human gut produce a genotoxin called colibactin. When cultured with human cells, these strains cause cell cycle arrest and DNA damage, and studies have shown increased populations of colibactin-producing E. coli in CRC patients. Previous studies have localized production of colibactin within the E. coli genome and hypothesized that the toxin is synthesized through an enzymatic assembly line. Yet every attempt to isolate colibactin and determine its chemical structure had failed.

Balskus’ group took “a very different approach,” in their efforts to discover colibactin’s structure. By studying the enzymes that make the toxin, the team uncovered a critical clue: a cyclopropane ring in the structure of a series of molecules they believed could be colibactin precursors. This functional group, when present in other molecules, is known to damage DNA, and its detection in the molecular products of the colibactin assembly line led the researchers to consider it as a potential mechanism of colibactin’s genotoxicity.

In collaboration with researchers at the University of Minnesota School of Public Health, Balskus’ team cultured human cells with colibactin-producing E. coli strains as well as strains that cannot produce the toxin. They identified and characterized the products of colibactin-mediated DNA damage. “Starting from the chemical structure of these DNA adducts, we can work backwards and think about potential routes for their production,” Balskus explained.

A proposed structure for the genotoxin colibactin, which is associated with colorectal cancer, features two cyclopropane rings capable of interacting with DNA to generate interstrand cross links, a type of DNA damage.

Further studies revealed that colibactin triggers a specific type of DNA damage that requires two reactive groups—likely represented by two cyclopropane rings in the final toxin structure—a pivotal discovery in deriving what Balskus believes is a strong candidate for the true colibactin structure. Balskus emphasized that this work could illuminate the role of colibactin in carcinogenesis, and may lead to cancer screening methods that rely on detecting DNA damage before cells become malignant. The findings also have implications for understanding microbiome-host interactions. “These studies reveal that human gut microbiota can interact with our genomes, compromising their integrity,” she said.

Further Readings

Balskus

Jiang Y, Stornetta A, Villalta PW et al.

Reactivity of an Unusual Amidase May Explain Colibactin’s DNA Cross-Linking Activity.

J Am Chem Soc. 2019 Jul 24;141(29):11489-11496.

Wilson MR, Jiang Y, Villalta PW, et al.

The human gut bacterial genotoxin colibactin alkylates DNA.

Science. 2019 Feb 15;363(6428).

Synthetic Methodology

Speakers

Ive Hermans
University of Wisconsin – Madison

William Dichtel
Northwestern University

Highlights

  • The chemical industry is a major producer of carbon dioxide, and efforts to create more efficient and sustainable chemical processes are often stymied by cost or scale.
  • Boron nitride is not well known as a catalyst, yet experiments show it is highly efficient at converting propane to propylene—one of the most widely used chemical building blocks in the world.
  • Two-dimensional polymers called covalent organic frameworks (COFs) can be used for water filtration, energy storage, and chemical sensing.
  • Until recently, researchers have struggled to control and direct COF formation, but new approaches to COF synthesis are advancing the field.

Boron Nitride: A Surprising Catalyst

Industrial chemicals “define our standard of living,” said Ive Hermans, 2019 Blavatnik National Awards Finalist, before explaining that nearly 96% of the products used in daily life arise from processes requiring bulk chemical production. These building block molecules are produced at an astonishingly large scale, using energy-intensive methods that also produce waste products, including carbon dioxide.

Despite pressure to reduce carbon emissions, the pace of innovation in chemical production is slow. The industry is capital-intensive — a chemical production plant can cost more than $2 billion—and it can take a decade or more to develop new methods of synthesizing chemicals.  Concepts that show promise in the lab often fail at scale or are too costly to make the transition from lab to plant. “The goal is to come up with technologies that are both easily implemented and scalable,” Hermans said.

Catalysts are a key area of interest for improving chemical production processes. These molecules bind to reactants and can boost the speed and efficiency of chemical reactions. Hermans’ research focuses on catalyst design, and one of his recent discoveries, made “just by luck,” stands to transform production of one of the most in-demand chemicals worldwide—propylene.

Historically, propylene was one product (along with ethylene and several others) produced by “cracking” carbon–carbon bonds in naphtha, a crude oil component that has since been replaced by ethane (from natural gas) as a preferred starting material. However, ethane yields far less propylene, leaving manufacturers and researchers to seek alternative methods of producing the chemical.

Boron nitride catalyzes a highly efficient conversion of propane to propylene.

Enter boron nitride, a two-dimensional material whose catalytic properties took Hermans by surprise when a student in his lab discovered its efficiency at converting propane, also a component of natural gas, to propylene. Existing methods for running this reaction are endothermic and produce significant CO2. Boron nitride catalysts facilitate an exothermic reaction that can be conducted at far cooler temperatures, with little CO2 production. Better still, the only significant byproduct is ethylene, an in-demand commodity.

Hermans sees this success as a step toward a more sustainable future, where chemical production moves “away from a linear economy approach, where we make things and produce CO2 as a byproduct, and more toward a circular economy where we use different starting materials and convert CO2 back into chemical building blocks.”

Polymerization in Two Dimensions

William Dichtel, a Blavatnik National Awards Finalist in 2017 and 2019, offered an update from one of the most exciting frontiers in polymer chemistry—two-dimensional polymerization. The synthetic polymers that dominate modern life are comprised of linear, repeating chains of linked building blocks that imbue materials with specific properties. Designing non-linear polymer architectures requires the ability to precisely control the placement of components, a feat that has challenged chemists for a decade.

Dichtel described the potential of a class of polymers called covalent organic frameworks, or COFs—networks of polymers that form when monomers are polymerized into well-defined, two-dimensional structures. COFs can be created in a variety of topologies, dictated by the shape of the monomers that comprise it, and typically feature pores that can be customized to perform a range of functions. These materials hold promise for applications including water purification membranes, energy and gas storage, organic electronics, and chemical sensing.

Dichtel explained that COF development is a trial and error process that often fails, as the mechanisms of their formation are not well understood. “We have very limited ability to improve these materials rationally—we need to be able to control their form so we can integrate them into a wide variety of contexts,” he said.

Two-dimensional polymer networks can be utilized for water purification, energy storage, and many other applications, but chemists have long struggled to understand their formation and control their structure.

A breakthrough in COF synthesis came when chemist Brian Smith, a former postdoc in Dichtel’s lab, discovered that certain solvents allowed COFs to disperse as nanoparticles in solution rather than precipitating as powder. These particles became the basis for a new method of growing large, controlled crystalline COFs using nanoparticles as structural “seeds,” then slowly adding monomers to maximize growth while limiting nucleation. “This level of control parallels living polymerization, with well-defined initiation and growth phases,” Dichtel said.

More recently, Dichtel’s group has made significant advances in COF fabrication, successfully casting them into thin films that could be used in membrane and filtration applications.

Further Readings

Hermans

Zhang Z, Jimenez-Izal E, Hermans I, Alexandrova AN.

Dynamic Phase Diagram of Catalytic Surface of Hexagonal Boron Nitride under Conditions of Oxidative Dehydrogenation of Propane.

J Phys Chem Lett. 2019 Jan 3;10(1):20-25.

Love AM, Thomas B, Specht SE, et al.

Probing the Transformation of Boron Nitride Catalysts under Oxidative Dehydrogenation Conditions.

J Am Chem Soc. 2019 Jan 9;141(1):182-190.

Dichtel

Côté AP, Benin AI, Ockwig NW, et al.

Porous, crystalline, covalent organic frameworks.

Science. 2005 Nov 18;310(5751):1166-70.

Bisbey RP, Dichtel WR.

Covalent Organic Frameworks as a Platform for Multidimensional Polymerization.

ACS Cent Sci. 2017 Jun 28;3(6):533-543.

Mulzer CR, Shen L, Bisbey RP, et al.

Superior Charge Storage and Power Density of a Conducting Polymer-Modified Covalent Organic Framework.

ACS Cent Sci. 2016 Sep 28;2(9):667-673.

Smith BJ, Parent LR, Overholts AC, et al.

Colloidal Covalent Organic Frameworks.

ACS Cent Sci. 2017 Jan 25;3(1):58-65.

Li H. Evans AM, Castano I, et al.

Nucleation-Elongation Dynamics of Two-Dimensional Covalent Organic Frameworks.

ChemRxiv, 2019.

Advances in Neuroscience

Speakers

Michal Rivlin
Weizmann Institute of Science

Nieng Yan
Princeton University

Highlights

  • The 80 subtypes of retinal ganglion cells each encode different aspects of vision, such as direction and motion.
  • The “preferences” of these cells were believed to be hard-wired, yet experiments show that retinal ganglion cells can be reprogrammed by exposure to repetitive stimuli.
  • Sodium ion channels control electrical signaling in cells of the heart, muscles, and brain, and have long been drug targets due to their connection to pain signaling.
  • Cryo-electron microscopy has allowed researchers to visualize Nav 7, a sodium ion channel implicated in pain syndromes, and to identify molecules that interfere with its function.

Retinal Computations: Recalculating

The presentation from Michal Rivlin, the Life Sciences Laureate of the 2019 Blavatnik Awards in Israel, began with an optical illusion, a dizzying exercise during which a repetitive, unidirectional pattern of motion appeared to rapidly reverse direction. “You probably still perceive motion, but the image is actually stable now,” Rivlin said, completing a powerful demonstration of the action of direction-sensitive retinal ganglion cells (RGCs), whose mechanisms she has studied for more than a decade. The approximately 80 subtypes of RGCs each encode a different aspect, or modality of vision—motion, color, and edges, as well as perception of visual phenomena such as direction. These modalities are hard-wired into the cells and were thought to be immutable—a retinal ganglion cell that perceived left-to-right motion was thought incapable of responding to visual signals that move right-to-left. Rivlin’s research has challenged not only this notion, but also many other beliefs about the function and capabilities of the retina.

Rather than simply capturing discrete aspects of visual information like a camera and relaying that information to the visual thalamus for processing, the cells of the retina actually perform complex processing functions and display a surprising level of plasticity. Rivlin’s lab is probing both the anatomy and functionality of various types of retinal ganglion cells, including those that demonstrate selectivity, such as a preference for movement in one direction or attunement to increases or decreases in illumination. By exposing these cells to various repetitive stimuli, Rivlin has shown that the selectivity of RGCs can be reversed, even in adult retinas.

Direction-selective retinal ganglion cells that prefer left-to-right motion (Before) can change their directional preference (After) following a repetitive visual stimulus.

These dynamic changes in cells whose preferences were believed to be singular and hard-wired have implications not just for understanding retinal function but for understanding the physiological basis of visual perception. Stimulus-dependent changes in the coding of retinal ganglion cells also have downstream impacts on the visual thalamus, where retinal signals are processed. This unexpected plasticity in retinal cells has led Rivlin and her collaborators to investigate the possibility that the visual thalamus and other parts of the visual system might also display greater plasticity than previously believed.

Targeting Sodium Channels for Pain Treatment

Nature’s deadliest predators may seem an unlikely inspiration for developing new analgesic drugs, but as Nieng Yan, 2019 Blavatnik National Awards Finalist, explained, the potent toxins of some snails, spiders, and fish are the basis for research that could lead to safer alternatives to opioid medications.

Voltage-gated ion channels are responsible for electrical signaling in cells of the brain, heart, and skeletal muscles. Sodium channels are one of many ion channel subtypes, and their connection to pain signaling is well documented. Sodium channel blockers have been used as analgesics for a century, but they can be dangerously indiscriminate, inhibiting both the intended channel as well as others in cardiac or muscle tissues. The development of highly selective small molecules capable of blocking only channels tied to pain signaling seemed nearly impossible until two breakthroughs—one genetic, the other technological—brought a potential path for success into focus.

A 2006 study of families with a rare genetic mutation that renders them fully insensitive to pain turned researchers’ focus to the role of the gene SCN9A, which codes for the voltage-gated sodium ion channel Nav 1.7, in pain syndromes. Earlier studies showed that overexpression of SCN9A caused patients to suffer extreme pain sensitivity, and it was now clear that loss of function mutations resulted in the opposite condition.

A powerful natural toxin derived from corn snails blocks the pore of a voltage-gated sodium channel, halting the flow of ions and inhibiting the initiation of an action potential.

As Yan explained, understanding this channel required the ability to resolve its structure, but imaging techniques available at that time were poorly suited to large, membrane-bound proteins. With the advent of cryo-electron microscopy­­­, Yan and other researchers have not only resolved the structure of Nav 1.7, but also characterized small molecules—mostly derived from animal toxins—that precisely and selectively interfere with its function. Developing synthetic drugs based on these molecules is the next phase of discovery, and it’s one that may happen more quickly than expected. “When I started my lab, I thought resolving this protein’s structure would be a lifetime project, but we shortened it to just five years,” said Yan.

Further Readings

Rivlin

Warwick RA, Kaushansky N, Sarid N, et al.

Inhomogeneous Encoding of the Visual Field in the Mouse Retina.

Curr Biol. 2018 Mar 5;28(5):655-665.e3

Rivlin-Etzion M, Grimes WN, Rieke F.

Flexible Neural Hardware Supports Dynamic Computations in Retina.

Trends Neurosci. 2018 Apr;41(4):224-237.

Vlasits AL, Bos R, Morrie RD, et al.

Visual stimulation switches the polarity of excitatory input to starburst amacrine cells.

Neuron. 2014 Sep 3;83(5):1172-84.

Rivlin-Etzion M, Wei W, Feller MB.

Visual stimulation reverses the directional preference of direction-selective retinal ganglion cells.

Neuron. 2012 Nov 8;76(3):518-25.

Yan

Shen H, Liu D, Wu K, et al.

Structures of human Nav1.7 channel in complex with auxiliary subunits and animal toxins.

Science. 2019 Mar 22;363(6433):1303-1308.

Pan X, Li Z, Huang X, et al.

Molecular basis for pore blockade of human Na+ channel Nav1.2 by the μ-conotoxin KIIIA.

Science. 2019 Mar 22;363(6433):1309-1313.

Pan X, Li Z, Zhou Q, et al.

Structure of the human voltage-gated sodium channel Nav1.4 in complex with β1.

Science. 2018 Oct 19;362(6412).

Shen H, Li Z, Jiang Y, et al.

Structural basis for the modulation of voltage-gated sodium channels by animal toxins.

Science. 2018 Oct 19;362(6412).

Computer Science

Speakers

Jure Leskovec
Stanford University

Elza Erkip
New York University


Highlights

  • A novel approach to developing machine learning algorithms has improved applications for non-linear datasets.
  • Neural networks can now be used for complex predictive tasks, including forecasting polypharmacy side effects.
  • 5G wireless networks will expand the capabilities of internet-connected devices, providing dramatically faster data transmission and increased reliability.
  • Tools used to design wireless networks can also be used to understand vulnerabilities in the design of online platforms and social networks, particularly as it pertains to user privacy and data anonymization.

Machine Learning with Networks

“For the first time in history, we are using computers to process data at scale to gain novel insights,” said Jure Leskovec, a Blavatnik National Awards Finalist in 2017, 2018, and 2019, describing one aspect of the digital transformation of science, technology, and society. This shift, from using computers to run calculations or simulations to using them to generate insights, is driven in part by the massive data streams available from the Internet and internet-connected devices. Machine learning has catalyzed this transformation, allowing researchers to not only glean useful information from large datasets, but to make increasingly reliable predictions based on it. Just as new imaging techniques reveal previously unknown structures and phenomena in biology, astronomy, and other fields, so too are big data and machine learning bringing previously unobservable models, signals, and patterns to the surface.

This “new paradigm for discovery” has limitations, as Leskovec explained. Machine learning has advanced most rapidly in areas where data can be represented as simple sequences or grids, such as computer vision, image analysis, and speech processing. Analysis of more complex datasets—represented by networks rather than linear sequences—was beyond the scope of neural networks until recently, when Leskovec and his collaborators approached the challenge from a different angle.

The team considered networks as computation graphs, recognizing that the key to making predictions was understanding how information propagates across the network. By training each node in the network to collect information about neighboring nodes and aggregating the resulting data, they can use node-level information to make predictions within the context of the entire network.

Each node within a network collects information from neighboring nodes. Together, this information can be used to make predictions within the context of the network as a whole.

Leskovec shared two case studies demonstrating the broad applicability of this approach. In healthcare, a neural network designed by Leskovec is identifying previously undocumented side effects from drug-drug interactions. Each network node represents a drug or a protein target of a drug, with links between the nodes emerging based on shared side effects, protein targets, and protein-protein interactions. This type of polydrug side effects analysis is infeasible through clinical trials, and Leskovec is working to optimize it as a point-of-care tool for clinicians.

A similar system has been deployed on the online platform Pinterest, where Leskovec serves as Chief Scientist. It has improved the site’s ability to classify users’ preferences and suggest additional content. “We’re generalizing deep learning methodologies to complex data types, and this is leading to new frontiers,” Leskovec said.

Understanding and Engineering Communications Networks

Elza Erkip has never seen a slide rule. In two decades as a faculty researcher and electrical and computer engineer, Erkip, 2010 Blavatnik Awards Finalist, has corrected her share of misconceptions about her field, and about the role of engineering among the scientific disciplines. She joked about stereotypes portraying engineers—most of them men—wielding slide rules or wearing hard hats, but emphasized the importance of raising awareness about the real-life work of engineers. “Scientists want to understand the universe, but engineers use existing scientific knowledge to design and build things,” she explained. “We contribute to discovery, but mostly we want to solve problems, to find solutions that work in the real world.”

Erkip focuses on one of the most impactful areas of 21st century living—wireless communication—and the ever-evolving suite of technologies that support it. She reviewed the rapid progression of wireless device capabilities, from phones that featured only voice calling and text messaging, through the addition of Wi-Fi capability and web browsing, all the way to the smartphones of today, which boast more computing power than the Apollo 11 spacecraft that landed on the moon. She described the next revolution in wireless—5G networks and devices—which promises higher data rates and significant increases in speed and reliability. Tapping the millimeter-wave bands of the electromagnetic spectrum, 5G will rely on different wireless architectures featuring massive arrays of small antennae, which are better suited to propagating shorter wavelengths. The increased bandwidth will enable many more devices to come online. “It won’t just be humans communicating—we’ll have devices communicating with each other,” Erkip said, describing the future connectivity between robots, autonomous cars, home appliances, and sensors embedded in transportation, manufacturing, and industrial equipment.

Despite efforts to anonymize data, many social media sites and online databases remain vulnerable to efforts to match users’ identities across platforms.

Erkip also discussed the application of tools used to understand and build wireless networks to gain insight into privacy issues within social networks. De-anonymization of user data has long plagued online platforms. Studies have shown that it’s often possible to identify and match users across multiple social platforms or databases using publicly available information—a breach that has greater implications for a database of health or voting records than it does for a consumer-oriented site such as Netflix. Erkip is working to understand the fundamental properties of these networks to elucidate the factors that predispose them to de-anonymization attacks.

Further Readings

Leskovec

Zitnik M, Agrawal M, Leskovec J.

Modeling polypharmacy side effects with graph convolutional networks.

Bioinformatics. 2018 Jul 1;34(13):i457-i466.

Erkip

Shirani F, Garg S, Erkip E.

A Concentration of Measure Approach to Database De-anonymization.

IEEE International Symposium on Information Theory. 2019.

Shirani F, Garg S, Erkip E.

Optimal Active social Network De-anonymization Using Information Thresholds.

IEEE International Symposium on Information Theory. 2018.

Materials Science

Speakers

Chiara Daraio
Caltech

Liangbing Hu
University of Maryland, College Park

Highlights

  • Computer-aided manufacturing is enabling researchers to design materials with precisely tuned properties, such as responsiveness to light, temperature, or moisture.
  • Structured materials can mimic robots or machines, changing shape and form repeatedly in the presence of various stimuli.
  • Ultra-strong, lightweight wood-based materials made of nanocellulose fibers may one day resolve some of the world’s most pressing challenges in water, energy and sustainability, replacing transparent plastic packaging, window glass, and even steel and other alloys in vehicles and buildings.

Mechanics of Robotic Matter

Chiara Daraio’s work challenges the traditional definition of words like material, structure, and robot.  Working at the intersection of physics, materials science, and computer science, she designs materials with novel properties and functionalities, enabled by computer-aided design and 3D fabrication. Rather than considering a material as the foundation for assembling a structure, Daraio, 2019 Blavatnik National Awards Finalist, designs materials with intricate structures in unique and complex geometries.

Daraio demonstrated a series of responsive materials—those that morph in the presence of stimuli such as temperature, light, moisture, or salinity. In their simplest forms, these materials change shape—a piece of heat-responsive material folds and unfolds as air temperature changes, or a leaf-shaped hydro-sensitive material opens and closes as it transitions from wet to dry. In more complex forms, materials can display time-dependent responses, as shown in a video demonstration of a row of polymer strips changing shape at different rates, depending on their thickness. Daraio showed how computer-graphical approaches allow researchers to design a single material with different properties in different regions, allowing complex actuation in a time-dependent manner, such as a polymer “flower” with interconnecting leaves taking shape and a polymer “ribbon” slowly interweaving a knot.

A thin foil elastomer comprised of materials with alternating temperature-sensitivity (heat and cold) folds up and “walks” across a table as the temperature varies.

Conventional ideas dictate that a robot is a programmable machine capable of completing a task. “But what if the material is the machine?” asked Daraio, showing the remarkable capabilities of a thin liquid crystal elastomer foil composed of one heat-sensitive and one cold-sensitive material. At room temperature, the foil is flat. Heat from a warm table causes it to curl upward, turn over, and “walk” forward. “As long as there’s some kind of external environmental stimulus, we can design a material that can repeatedly perform actions in time,” Daraio said. Similar responsive materials have been used in a self-deploying solar panel that [remove folds and] unfolds in response to heat.

Materials have been “the seeds of technological innovation” throughout human history, and Daraio believes that structured materials will enable new functionalities at the macroscale—for use in wearables such as helmets as well as in smart building technologies—and at the microscale, where responsive materials could be used for medical diagnostics or drug delivery.

Sustainable Applications for Wood Nanotechnologies

Wood, glass, plastic, and steel are among the most ubiquitous materials on Earth, and Liangbing Hu, 2019 Blavatnik National Awards Finalist, is rethinking them all. Inspired by the global need to develop sustainable materials, Hu turned to the most plentiful source of biomass on Earth— trees—to create a new generation of wood-based materials with astonishing properties. Hu relies on nanocellulose fibers, which can be engineered to serve as alternatives to commonly used unsustainable or energy-intensive materials.

Hu introduced a transparent film that could pass for plastic and can be used for packaging, yet is ten times stronger and far more versatile. This transparent nanopaper, made of nanocellulose fibers, could also be used as a display material in flexible electronics or as a photonic overlay that boosts the efficiency of solar cells by 30%.

Hu has also tested transparent wood—a heavier-gauge version of nanopaper made by removing lignin from wood and injecting the channels with a clear polymer—as an energy-saving building material. More than half of home energy loss is due to poor wall insulation and leakage through window glass. By Hu’s calculations, replacing glass windows with transparent wood would also provide a six-fold increase in thermal insulation. Pressed, delignified wood has also proven to be a superior material for wall insulation. Used on roofs, it is a highly efficient means of passive cooling—the material absorbs heat and then re-radiates it, cooling the surface below it by about ten degrees.

White delignified wood is pressed to increase its strength. It can be used on roofs to passively cool homes by absorbing and re-radiating light, cooling the area below it by about ten degrees.

Comparisons of mechanical strength between wood and steel are almost laughable, unless the wood is another of Hu’s creations—the aptly named “superwood.” Delignified and compressed to align the nanocellulose fibers, even inexpensive woods become thinner and 10-20 times stronger. Superwood rivals steel in strength and durability, and could become a viable alternative to steel and other alloys in buildings, vehicles, trains, and airplanes. Sustainable sourcing would eliminate pollution and carbon dioxide associated with steel production, and its lightweight profile could drastically improve vehicle fuel efficiency.

Further Readings

Daraio

Celli P, McMahan C, Ramirez B, et al.

Shape-morphing architected sheets with non-periodic cut patterns.

Soft Matter. 2018 Dec 12;14(48):9744-9749.

Chen T, Bilal OR, Shea K, Daraio C.

Harnessing bistability for directional propulsion of soft, untethered robots.

Proc Natl Acad Sci USA. 2018 May 29;115(22):5698-5702.

Bauhofer AA, Krödel S, Rys J, et al.

Harnessing Photochemical Shrinkage in Direct Laser Writing for Shape Morphing of Polymer Sheets.

Adv Mater. 2017 Nov;29(42).

Hu

Song J, Chen C, Zhu S, et al.

Processing bulk natural wood into a high-performance structural material.

Nature. 2018 Feb 7;554(7691):224-228.

Huang J, Zhu H, Chen Y, et al.

Highly transparent and flexible nanopaper transistors.

ACS Nano. 2013 Mar 26;7(3):2106-13.

Huang J, Zhu H, Chen Y, et al.

Novel nanostructured paper with ultrahigh transparency and ultrahigh haze for solar cells.

Nano Lett. 2014 Feb 12;14(2):765-73.

Zhu M, Song J, Li T, et al.

Highly Anisotropic, Highly Transparent Wood Composites.

Adv Mater. 2016 Jul;28(26):5181-7.

Li T, Zhai Y, He S, et al.

A radiative cooling structural material.

Science. 2019 May 24;364(6442):760-763.

Zhu H, Luo W, Ciesielski PN, et al.

Wood-Derived Materials for Green Electronics, Biological Devices, and Energy Applications.

Chem Rev. 2016 Aug 24;116(16):9305-74.

Medicine and Medical Diagnostics

Speakers

Nicholas Navin
MD Anderson Cancer Center

Wei Min
Columbia University

Highlights

  • Tumor cells are genetically heterogeneous, complicating efforts to sequence DNA from tumor tissue samples.
  • Techniques for isolating and sequencing single-cell samples have transformed the study of cancer genetics.
  • Stimulated Ramen scattering, a non-invasive imaging technique, can visualize processes including glucose uptake and fatty acid metabolism within living cells.

Single Cell Genomics: A Revolution in Cancer Biology

Nicholas Navin, 2019 Blavatnik National Awards Finalist, doesn’t use the word “revolution” lightly, but when it comes to the field of single-cell genomics and its impact on cancer research, he stands by the term. Over the past ten years, DNA sequencing of single tumor cells has led to major discoveries about the progression of cancer and the process by which cancer cells resist treatment.

Unlike healthy tissue cells, tumor cells are characterized by genomic heterogeneity. Samples from different areas of the same tumor often contain different mutations or numbers of chromosomes. This diversity has long piqued researchers’ curiosity. “Is it stochastic noise generated as tumor cells acquire different mutations, or could this diversity be important for resistance to therapy, invasion, or metastasis?” Navin asked.

Answering that question required the ability to do comparative studies of single tumor cells, a task that was long out of reach. DNA sequencing technologies historically required a large sample of genetic material—a tricky proposition when sampling a highly diverse population of tumor cells. Some mutations, which could drive invasion or resistance, may be present in just a few cells and thus not be represented in the results. Navin was part of the first team to develop a method for excising a single cancer cell from a tumor, amplifying the DNA, and producing an individualized genetic sequence. As amplification and sequencing methods have improved, so too have the insights gleaned from single-cell genomic studies, which Navin likens to “paleontology in tumors”—the notion that a sample taken at a single point in time can allow researchers to make inferences about tumor evolution.

Single-cell genomic studies reveal that some cancer cells have innate mechanisms of resistance to chemotherapy, and undergo further transcriptional changes that enhance this resistance.

Single-cell studies have contradicted the idea of a stepwise evolution of cancer cells, with one mutation leading to another and ultimately tipping the scales toward malignancy. Instead, Navin’s studies reveal a punctuated evolution, whereby many cells simultaneously become genetically unstable. Longitudinal studies of single-cell samples in patients with triple-negative breast cancer are beginning to answer questions about how cancer cells evade treatment, showing that cells that survive chemotherapy have innate resistance, and then undergo further transcriptional changes during treatment, which increase resistance.

Translating these findings to the clinic is a longer-term process, but Navin envisions single-cell genomics will significantly impact strategies for targeted therapy, non-invasive monitoring, and early cancer detection.

Chemical Imaging in Biomedicine

Wei Min, a Blavatnik Awards Finalist in 2012 and 2019, concluded the session with a visually striking glimpse into the world of stimulated Raman scattering (SRS) microscopy. This noninvasive imaging technique provides both sub-cellular resolution and chemical information about living cells, while transcending some of the limitations of fluorescence-based optical microscopy. The probes used to tag molecules for fluorescent imaging can alter or destroy small molecules of interest, including glucose, lipids, amino acids, or neurotransmitters. Rather than using tags, SRS builds on traditional Raman spectroscopy, which captures and analyzes light scattered by the unique vibrational frequencies between atoms in biomolecules. The original method, first pioneered in the 1930s, is slow and lacks sensitivity, but in 2008, Min and others improved the technique.

SRS has since become a leading method for label-free visualization of living cells, providing an unprecedented window into cellular activities. Using SRS and a variety of custom chemical tags—“vibrational tags,” as Min described them—bound to biomolecules such as DNA or RNA bases, amino acids, or even glucose, researchers can observe the dynamics of biological functions. SRS has visualized glucose uptake in neurons and malignant tumors, and has been used to observe fatty acid metabolism, a critical step in understanding lipid disorders. Imaging small drug molecules is notoriously difficult, but Min reported the results of experiments using SRS to tag therapeutic drug molecules and study their activity within tissues.

Stimulated Raman scattering microscopy uses chemical tags to image small biological molecules in living cells. The technique can visualize cellular processes including glucose uptake in healthy cells and tumor cells.

A recent breakthrough in SRS technology involves pairing it with Raman dyes to break the “color barrier” in optical imaging. Due to the width of the fluorescent spectrum, labels are limited to five or six colors per sample, which prevents researchers from imaging many structures within a tissue sample simultaneously. Min has introduced a hybrid imaging technique that allows for super-multiplexed imaging—up to 10 colors in a single cell image—and utilizes a dramatically expanded palette of Raman frequencies that yield at least 20 distinct colors.

Further Readings

Navin

Kim C, Gao R, Sei E, et al.

Chemoresistance Evolution in Triple-Negative Breast Cancer Delineated by Single-Cell Sequencing.

Cell. 2018 May 3;173(4):879-893.e13.

Casasent AK, Schalck A, Gao R, et al.

Multiclonal Invasion in Breast Tumors Identified by Topographic Single Cell Sequencing.

Cell. 2018 Jan 11;172(1-2):205-217.e12.

Gao R, Davis A, McDonald TO, et al.

Punctuated copy number evolution and clonal stasis in triple-negative breast cancer.

Nat Genet. 2016 Oct;48(10):1119-30.

Wang Y, Navin NE.

Advances and applications of single-cell sequencing technologies.

Mol Cell. 2015 May 21;58(4):598-609.

Navin NE.

Cancer genomics: one cell at a time.

Genome Biol. 2014 Aug 30;15(8):452.

Wang Y, Waters J, Leung ML, et al.

Clonal evolution in breast cancer revealed by single nucleus genome sequencing.

Nature. 2014 Aug 14;512(7513):155-60.

Min

Xiong H, Shi L, Wei L, et al.

Stimulated Raman excited fluorescence spectroscopy and imaging.

Nat Photonics. 2019; (3) 412–417.

Xiong H, Qian N, Miao Y, et al.

Stimulated Raman Excited Fluorescence Spectroscopy of Visible Dyes.

J Phys Chem Lett. 2019 Jul 5;10(13):3563-3570.

Zhang L, Shi L, Shen Y, et al.

Spectral tracing of deuterium for imaging glucose metabolism.

Nat Biomed Eng. 2019 May;3(5):402-413.

Shen Y, Hu F, Min W.

Raman Imaging of Small Biomolecules.

Annu Rev Biophys. 2019 May 6;48:347-369.

Wei M, Shi L, Shen Y, et al.

Volumetric chemical imaging by clearing-enhanced stimulated Raman scattering microscopy.

Proc Natl Acad Sci U S A. 2019 Apr 2;116(14):6608-6617.

Shi L, Zheng C, Shen Y, et al.

Optical imaging of metabolic dynamics in animals.

Nat Commun. 2018 Aug 6;9(1):2995.

Recognizing Breakthrough Scientists in the Tri-State

New breakthroughs in controlling mosquito populations, quantum gravity and reducing chemical byproduct waste are among the cutting edge research being honored by the 2019 Blavatnik Regional Awards for Young Scientists.

Published September 14, 2019

By Kamala Murthy

This year the Blavatnik Regional Awards for Young Scientists received 137 nominations from 20 academic institutions in the tri-state area. A jury of distinguished senior scientists and engineers from leading academic institutions selected three outstanding scientists as Winners who will each receive a $30,000 unrestricted prize, and six Finalists (two from each category) who each will collect a $10,000 unrestricted prize.

Supporting outstanding scientists from academic research institutions across New York, New Jersey, and Connecticut since 2007, the Blavatnik Regional Awards for Young Scientists recognize and honor postdoctoral researchers in three scientific disciplinary categories: Life Sciences, Physical Sciences & Engineering, and Chemistry.

The 2019 Blavatnik Regional Awards Winners are:

Life Sciences: Laura Duvall, PhD, nominated by The Rockefeller University (now at Columbia University). Dr. Duvall’s discovery of two key molecules in mosquitos that inhibit blood-feeding and breeding has worldwide implications for controlling mosquito populations and the spread of diseases such as Dengue and Zika. At the time of nomination, Dr. Duvall was a trainee of the 2007 Blavatnik Regional Awards Faculty Winner, Leslie Vosshall of The Rockefeller University.

Physical Sciences & Engineering: Netta Engelhardt, PhD, nominated by Princeton University (now at Massachusetts Institute of Technology). Dr. Engelhardt’s research at the interface of general relativity and quantum field theory is answering complex questions about the fundamentals of our universe, including the remarkable explanation for the origin of black hole entropy. Her work is integral to the understanding of how the fabric of the universe at large-scale is encoded in quantum gravity.

Chemistry: Juntao Ye, PhD, nominated by Cornell University (now at Shanghai Jiao Tong University in China). Improving synthetic efficiency while lowering the cost of synthesis is a primary goal for pharmaceutical industries. Ye invented several new methods that allow for converting readily available chemicals into value-added and pharmaceutically relevant products in a highly efficient and economical manner, while reducing chemical byproduct waste. These methods could accelerate the pace of drug discovery through improving efficiency in synthesizing complex and bioactive compounds.

The cutting-edge discoveries being recognized this year cover an incredibly disparate breadth of work in quantum gravity, drug discovery, control of mosquito populations and underwater photographic imagery. These are the advances that will change our world.

Ellis Rubinstein

2019 Blavatnik Regional Awards Finalists

Life Sciences

Carla Nasca, PhD, nominated by The Rockefeller University — recognized for the discovery of acetyl-L-carnitine (LAC) as a novel modulator of brain rewiring and a possible new treatment for depression that acts by turning on and off specific genes related to the neurotransmitter glutamate.

Liling Wan, PhD, nominated by The Rockefeller University (currently transitioning to the University of Pennsylvania) — recognized for identifying a previously unknown function of a protein called ENL, which has the ability to read epigenetic information on our chromosomes and activate genes that perpetuate tumor growth. Elucidating the structure and mechanism of ENL has guided ongoing development of drugs to treat cancers.

Physical Sciences & Engineering

Derya Akkaynak, PhD, nominated by Princeton University — recognized for significant breakthroughs in computer vision and underwater imaging technologies, resolving a fundamental technological problem in the computer vision community — the reconstruction of lost colors and contrast in underwater photographic imagery — which will have real implications for oceanographic research.

Matthew Yankowitz, PhD, nominated by Columbia University (now at the University of Washington) — recognized for groundbreaking experimental work modifying the electronic properties of a new class of two-dimensional materials, known as van der Waal materials. van der Waal materials have generated tremendous interest due to their properties and the promise they show for use in next-generation optoelectronic and electronic devices, future computing, and telecommunications technologies. Dr. Yankowitz’s work led to the discovery that applied pressure can be used to induce superconductive properties in multi-layer graphene, and has significantly advanced a new area of research recently coined “twistronics.”

Chemistry

Yaping Zang, PhD, nominated by Columbia University — recognized for innovatively using electrochemistry and electrical fields in conjunction with scanning tunneling microscopy techniques to drive chemical reactions. This work provides a deeper understanding of the reaction mechanisms and opens new avenues for the use of electricity as a catalyst in chemical reactions.

Igor Dikiy, PhD, nominated by the Advanced Science Research Center at The Graduate Center, CUNY — recognized for completing the first study of G-protein–coupled receptor (GPCR) fast sidechain dynamics using NMR (nuclear magnetic resonance) spectroscopy to shed light on the molecular mechanisms of cell signaling. GPCRs control a variety of processes in the human body and are targets for over 30% of all FDA-approved drugs. Elucidating the mechanisms of GPCR signaling will enable researchers to design more effective drugs.

Honoring the Blavatnik Regional Award Winners and Finalists

The 2019 Blavatnik Regional Awards Winners and Finalists will be honored at the New York Academy of Sciences’ Annual Gala at Cipriani 25 Broadway in New York on Monday, November 11, 2019.

To learn more about this year’s Blavatnik Awards honorees, please visit the Blavatnik Awards website and follow us on Facebook and Twitter: @BlavatnikAwards