Adding high-performance computing to personalized medicine is an important next step

Argonne’s Jonathan Ozik (pictured) and Nicholson Collier are searching for clues on how to improve cancer immunotherapy by harnessing the power of supercomputers at Argonne and the University of Chicago. (Image by Argonne National Laboratory.)

What should personalized, precision treatment of cancer look like in the future?

We know that people are different, their tumors are different, and they respond differently to different therapies. Medical teams of the future might be able to create a ?virtual twin” of a person and their tumor. Then, by tapping supercomputers, physician-led teams could simulate how tumor cells behave to test millions (or billions) of possible treatment combinations. Ultimately, the best combinations might offer clues towards a personalized, effective treatment plan.

Sound like wishful thinking? The first steps towards this vision have been undertaken by a multi-institution research collaboration that includes Jonathan Ozik and Nicholson Collier, computational scientists at the U.S. Department of Energy’s Argonne National Laboratory.

The research team, which includes collaborators at Indiana University and the University of Vermont Medical Center, brought the power of high-performance computing to the thorny challenge of improving cancer immunotherapy. The team tapped twin supercomputers at Argonne and the University of Chicago, finding that high-performance computing can yield clues in fighting cancer, as discussed in a June 7 article published in Molecular Systems Design and Engineering.

With this new approach, researchers can use agent-based modeling in more scientifically robust ways.” — Nicholson Collier, computational scientist at Argonne and the University of Chicago

Standing up to cancer

Cancer immunotherapy is a promising treatment that realigns your immune system to reduce or eliminate cancer cells. The therapy, however, helps only 10 to 20 percent of patients — partly because the way in which cancer cells and immune cells mingle is complex and poorly understood. Proven rules are scarce.

To begin uncovering the rules of immunotherapy, the team turned to a set of three tools:

  • Agent-based modeling, which predicted the behavior of individual ?agents” – cancer and immune cells, in this case
  • Argonne’s award-winning workflow technology to take full advantage of the supercomputers
  • A guiding framework to explore models and dynamically direct and track results

The trio operate in a hierarchy. The framework, developed by Ozik, Collier, Argonne colleagues, and Gary An, a surgeon and professor at the University of Vermont Medical Center, is called Extreme-scale Model Exploration with Swift (EMEWS). It oversees the agent-based model and the workflow system, the Swift/T parallel scripting language, developed at Argonne and the University of Chicago.

What is unique about this combination of tools? ?We are helping more people in a variety of computational science fields to do large-scale experimentation with their models,” said Ozik, who — like Collier — holds a joint appointment at the University of Chicago. ?Building a model is fun. But without supercomputers, it is difficult to really understand the full potential of how models can behave.”

Working smarter, not harder

The team sought to find simulated scenarios in which:

  • No additional cancer cells grew
  • 90 percent of cancer cells died
  • 99 percent of cancer cells died

They found that no cancer cells grew in 19 percent of simulations, 9 in 10 cancer cells died in 6percent of simulations, and 99 in 100 cancer cells died in about 2 percent of the simulations.

The team began with an agent-based model, built with the PhysiCell framework, designed by Indiana University’s Paul Macklin to explore cancer and other diseases. They assigned each cancer and immune cell characteristics — birth and death rates, for example — that govern their behavior and then let them loose.

We use agent-based modeling to address many problems,” said Ozik. ?But these models are often computationally intensive and produce a lot of random noise.”

Exploring every possible scenario within the PhysiCell model would have been impractical. ?You can’t cover the entire model’s possible behavior space,” said Collier. So the team needed to work smarter, not harder.

The team relied on two approaches — genetic algorithms and active learning, which are forms of machine learning— to guide the PhysiCell model and find the parameters that best controlled or killed the simulated cancer cells.

Genetic algorithms seek those ideal parameters by simulating the model, say, 100 times and measuring the results. The model then repeats the process again and again using better-performing parameter values each time. ?The process allows you to find the best set of parameters quickly, without having to run every single combination,” said Collier.

Active learning is different. It also repeatedly simulates the model, but, as it does, it tries to discover regions of parameter values where it would be most advantageous to further explore in order to get a full picture of what works and what doesn’t. In other words, ?where you can sample to get the best bang for your buck,” said Ozik.

Meanwhile, Argonne’s EMEWS acted like a conductor, signaling the genetic and active learning algorithms at the right times and coordinating the large number of simulations on Argonne’s Bebop cluster in its Laboratory Computing Resource Center, as well as on the University of Chicago’s Beagle supercomputer.

Moving beyond medicine

The research team is applying similar approaches to challenges across different cancer types, including colon, breast and prostate cancer.

Argonne’s EMEWS framework can offer insights in areas beyond medicine. Indeed, Ozik and Collier are currently using the system to explore the complexities of rare earth metals and their supply chains. ?With this new approach, researchers can use agent-based modeling in more scientifically robust ways,” said Collier.

Learn more: Expanding the limits of personalized medicine with high-performance computing

 

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New molecule could help reduce growing level of salt contaminants flowing into freshwater streams and lakes

A computer-generated image of the six-triazole molecule. Image by Yun Liu, University of Illinois at Urbana-Champaign

Building a better salt trap: IU researchers synthesize a molecular ‘cage’ to trap chloride

 

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Online cognitive behavioral therapy reduces symptoms in cases of mild, moderate or severe depression

Analysis shows that online cognitive behavioral therapy reduces symptoms in cases of mild, moderate or severe depression

In a sweeping new study, Indiana University psychologists have found that a series of self-guided, internet-based therapy platforms effectively reduce depression.

The work, which reviewed 21 pre-existing studies with a total of 4,781 participants, was published in the November issue of the Journal of Medical Internet Research. The study was led by Lorenzo Lorenzo-Luaces, an assistant professor of clinical psychology in the IU Bloomington College of Arts and Sciences’ Department of Psychological and Brain Sciences.

In the past several years, many internet-based apps and websites have made claims to treat depression. The subjects of the IU study were specifically those applications that provide treatment with cognitive behavioral therapy, a form of psychotherapy that focuses on changing thought patterns and behavior to alleviate symptoms of depression and other mental disorders.

Previous studies had examined the effectiveness of individual internet-based cognitive behavioral therapy apps, or iCBT, using a range of methods. Until this study, however, no review had examined whether the effects of these treatments were inflated by excluding patients with more severe depression or additional conditions such as anxiety or alcohol abuse.

“Before this study, I thought past studies were probably focused on people with very mild depression, those who did not have other mental health problems, and were at low risk for suicide,” Lorenzo-Luaces said. “To my surprise, that was not the case. The science suggests that these apps and platforms can help a large number of people.”

For Lorenzo-Luaces, internet-based cognitive behavioral therapy apps are an important new tool for addressing a major public health issue: that individuals with mental health disorders like depression far outnumber the mental health providers available to treat them.

“Close to one in four people meet the criteria for major depressive disorder,” he said. “If you include people with minor depression or who have been depressed for a week or a month with a few symptoms, the number grows, exceeding the number of psychologists who can serve them.”

People with depression are also expensive for the health care system, he added.

“They tend to visit primary-care physicians more often than others,” Lorenzo-Luaces said. “They have more medical problems, and their depression sometimes gets in the way of their taking their medication for other medical problems.”

By conducting a “meta-regression analysis” of 21 studies, Lorenzo-Luaces and collaborators decisively determined that internet-based therapy platforms effectively alleviate depression. A central question was determining whether previous studies distorted the strength of these systems’ effects by excluding people with severe depression.

The conclusion was that the apps worked in cases of mild, moderate and severe depression.

Many of the studies in the analysis compared use of internet-based cognitive behavioral therapy apps to placement on a wait list for therapy or the use of a “fake app” that made weak recommendations to the user. In these cases, the iCBT apps worked significantly better.

“This is not to say that you should stop taking your medication and go to the nearest app store,” added Lorenzo-Luaces, who said both face-to-face therapy and antidepressants may still prove to be more effective than the iCBT apps alone.

“People tend to do better when they have a little bit of guidance,” he said. But he added that a 10- to 15-minute check-in may be sufficient for many people, freeing health care providers to see more patients.

App-based therapy also has an advantage in situations where access to face-to-face therapy is limited due to logistical barriers, such as long distances in rural areas or inflexible work schedules.

“ICBT apps take the methods we have learned and make them available to the many people who could benefit from them,” Lorenzo-Luaces said. “It’s an exciting development.”

Learn more: Internet therapy apps reduce depression symptoms, IU study finds

 

 

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Hoaxy, Fakey and Botometer are three powerful tools for studying and countering online misinformation and manipulation

A Hoaxy search traces the spread of a story on Twitter that claims the Syria Civil Defense, a volunteer search-and-rescue organization also known as the “White Helmets,” are staging mass casualty events like chemical weapons attacks. The red and dark pink dots indicate likely bots used to amplify the message. Image courtesy Hoaxy

What’s trending in fake news? IU tools show which stories go viral, and if ‘bots’ are to blame

Researchers at the Indiana University Observatory on Social Media have launched upgrades to two tools playing a major role in countering the spread of misinformation online.

The improvements to Hoaxy and Botometerare supported by the Knight Prototype Fund on Misinformation, a joint venture of the John S. and James L. Knight Foundation, the Rita Allen Foundation and the Democracy Fund to address concerns about the spread of misinformation and to build trust in quality journalism. A third tool — an educational game designed to make people smarter news consumers — also launches with the upgrades.

“The majority of the changes to Hoaxy and Botometer are specifically designed to make the tools more usable by journalists and average citizens,” said Filippo Menczer, a professor in the IU School of Informatics, Computing and Engineering and a member of the IU Network Science Institute. “You can now easily detect when information is spreading virally, and who is responsible for its spread.”

Hoaxy is a search engine that shows users how stories from low-credibility sources spread on Twitter. Botometer is an app that assigns a score to Twitter users based on the likelihood that the account is automated.

Hoaxy’s new functions show users which stories are trending on Twitter, including those from low-credibility sources. It also indicates what proportion of the users who are spreading the stories are likely to be “bots.” These new features were previewed April 12 at the International Symposium on Online Journalism in Austin, Texas, by Giovanni Luca Ciampaglia, a research scientist at the IU Network Science Institute who is part of the team that developed the tools.

The new version of Botometer employs updated machine learning algorithms to identify “bots” with greater accuracy and is strongly integrated with Hoaxy. Users can observe not only how information spreads across Twitter, but also whether these messages are mostly shared by real people or pushed by a computer program potentially designed to sway public opinion.

Automated accounts are commonly used to give the false impression that a large number of people are speaking about a specific topic online, Menczer said. Political campaigns, celebrities and advertisers are known to use bots to push specific agendas or products.

The updated Hoaxy also has a “trending stories” section that displays popular news stories along with claims from low-credibility sources. This is possible because Hoaxy can now trace the spread of any online news story or hashtag over time across Twitter. Previously, users could only analyze headlines from specific websites identified by nonpartisan groups as likely to post false or misleading information.

Ciampaglia said Hoaxy and Botometer currently process hundreds of thousands of daily online queries. The technology has enabled researchers, including a team at IU, to study how information flows online in the presence of bots. Examples are a study on the cover of the March issue of Science that analyzed the spread of false news on Twitter and an analysis from the Pew Research Center in April that found that nearly two-thirds of the links to popular websites on Twitter are shared by automated accounts.

The newly launched project is Fakey, a web and mobile news literacy game that mixes news stories with false reports, clickbait headlines, conspiracy theories and “junk science.” Players earn points by “fact-checking” false information and liking or sharing accurate stories. The project, led by IU graduate student Mihai Avram, was created to help people develop responsible social media consumption habits. An Android app is available, and an iOS versions will launch shortly.

All three tools are united through their creators’ goal to help individuals understand the role of misinformation online, Menczer said.

“By partnering with other groups,” he added, “we’re able to significantly amplify the power of our work in the fight against online disinformation.”

Learn more: What’s trending in fake news? IU tools show which stories go viral, and if ‘bots’ are to blame

 

 

 

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New molecule harvests sunlight to create useable material from carbon dioxide in the atmosphere

The new molecule employs a nanographene complex (on left) to absorb light and drive the conversion of carbon dioxide (upper center) to carbon monoxide (on right). | Photo by Ben Noffke and Richard Schaugaard

IU chemists create molecular ‘leaf’ that collects and stores solar power without solar panels

An international team of scientists led by Liang-shi Li at Indiana University has achieved a new milestone in the quest to recycle carbon dioxide in the Earth’s atmosphere into carbon-neutral fuels and others materials.

The chemists have engineered a molecule that uses light or electricity to convert the greenhouse gas carbon dioxide into carbon monoxide — a carbon-neutral fuel source — more efficiently than any other method of “carbon reduction.”

The process is reported today in the Journal of the American Chemical Society.

“If you can create an efficient enough molecule for this reaction, it will produce energy that is free and storable in the form of fuels,” said Li, associate professor in the IU Bloomington College of Arts and Sciences’ Department of Chemistry. “This study is a major leap in that direction.”

Burning fuel — such as carbon monoxide — produces carbon dioxide and releases energy. Turning carbon dioxide back into fuel requires at least the same amount of energy. A major goal among scientists has been decreasing the excess energy needed.

This is exactly what Li’s molecule achieves: requiring the least amount of energy reported thus far to drive the formation of carbon monoxide. The molecule — a nanographene-rhenium complex connected via an organic compound known as bipyridine — triggers a highly efficient reaction that converts carbon dioxide to carbon monoxide.

The ability to efficiently and exclusively create carbon monoxide is significant due to the molecule’s versatility.

“Carbon monoxide is an important raw material in a lot of industrial processes,” Li said. “It’s also a way to store energy as a carbon-neutral fuel since you’re not putting any more carbon back into the atmosphere than you already removed. You’re simply re-releasing the solar power you used to make it.”

The secret to the molecule’s efficiency is nanographene — a nanometer-scale piece of graphite, a common form of carbon (i.e. the black “lead” in pencils) — because the material’s dark color absorbs a large amount of sunlight.

Li said that bipyridine-metal complexes have long been studied to reduce carbon dioxide to carbon monoxide with sunlight. But these molecules can use only a tiny sliver of the light in sunlight, primarily in the ultraviolet range, which is invisible to the naked eye. In contrast, the molecule developed at IU takes advantage of the light-absorbing power of nanographene to create a reaction that uses sunlight in the wavelength up to 600 nanometers — a large portion of the visible light spectrum.

Essentially, Li said, the molecule acts as a two-part system: a nanographene “energy collector” that absorbs energy from sunlight and an atomic rhenium “engine” that produces carbon monoxide. The energy collector drives a flow of electrons to the rhenium atom, which repeatedly binds and converts the normally stable carbon dioxide to carbon monoxide.

The idea to link nanographene to the metal arose from Li’s earlier efforts to create a more efficient solar cell with the carbon-based material. “We asked ourselves: Could we cut out the middle man — solar cells — and use the light-absorbing quality of nanographene alone to drive the reaction?” he said.

Next, Li plans to make the molecule more powerful, including making it last longer and survive in a non-liquid form, since solid catalysts are easier to use in the real world. He is also working to replace the rhenium atom in the molecule — a rare element — with manganese, a more common and less expensive metal.

Learn more: IU chemists create molecular ‘leaf’ that collects and stores solar power without solar panels

 

 

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