The findings, detailed in a recent article in the journal Nature Electronics, show that neuromorphic simulations employing the statistical method called random walks can track X-rays passing through bone and soft tissue, disease passing through a population, information flowing through social networks and the movements of financial markets, among other uses, said Sandia theoretical neuroscientist and lead researcher James Bradley Aimone.

“Basically, we have shown that neuromorphic hardware can yield computational advantages relevant to many applications, not just artificial intelligence to which it’s obviously kin,” said Aimone. “Newly discovered applications range from radiation transport and molecular simulations to computational finance, biology modeling and particle physics.”

In optimal cases, neuromorphic computers will solve problems faster and use less energy than conventional computing, he said.

The bold assertions should be of interest to the high-performance computing community because finding capabilities to solve statistical problems is of increasing concern, Aimone said.

“These problems aren’t really well-suited for GPUs [graphics processing units], which is what future exascale systems are likely going to rely on,” Aimone said. “What’s exciting is that no one really has looked at neuromorphic computing for these types of applications before.”

Sandia engineer and paper author Brian Franke said, “The natural randomness of the processes you list will make them inefficient when directly mapped onto vector processors like GPUs on next-generation computational efforts. Meanwhile, neuromorphic architectures are an intriguing and radically different alternative for particle simulation that may lead to a scalable and energy-efficient approach for solving problems of interest to us.”

Franke models photon and electron radiation to understand their effects on components.

The team successfully applied neuromorphic-computing algorithms to model random walks of gaseous molecules diffusing through a barrier, a basic chemistry problem, using the 50-million-chip Loihi platform Sandia received approximately a year and a half ago from Intel Corp., said Aimone. “Then we showed that our algorithm can be extended to more sophisticated diffusion processes useful in a range of applications.”

The claims are not meant to challenge the primacy of standard computing methods used to run utilities, desktops and phones. “There are, however, areas in which the combination of computing speed and lower energy costs may make neuromorphic computing the ultimately desirable choice,” he said.

Unlike the difficulties posed by adding qubits to quantum computers — another interesting method of moving beyond the limitations of conventional computing — chips containing artificial neurons are cheap and easy to install, Aimone said.

There can still be a high cost for moving data on or off the neurochip processor. “As you collect more, it slows down the system, and eventually it won’t run at all,” said Sandia mathematician and paper author William Severa. “But we overcame this by configuring a small group of neurons that effectively computed summary statistics, and we output those summaries instead of the raw data.”

Severa wrote several of the experiment’s algorithms.

Like the brain, neuromorphic computing works by electrifying small pin-like structures, adding tiny charges emitted from surrounding sensors until a certain electrical level is reached. Then the pin, like a biological neuron, flashes a tiny electrical burst, an action known as spiking. Unlike the metronomical regularity with which information is passed along in conventional computers, said Aimone, the artificial neurons of neuromorphic computing flash irregularly, as biological ones do in the brain, and so may take longer to transmit information. But because the process only depletes energies from sensors and neurons if they contribute data, it requires less energy than formal computing, which must poll every processor whether contributing or not. The conceptually bio-based process has another advantage: Its computing and memory components exist in the same structure, while conventional computing uses up energy by distant transfer between these two functions. The slow reaction time of the artificial neurons initially may slow down its solutions, but this factor disappears as the number of neurons is increased so more information is available in the same time period to be totaled, said Aimone.

The process begins by using a Markov chain — a mathematical construct where, like a Monopoly gameboard, the next outcome depends only on the current state and not the history of all previous states. That randomness contrasts, said Sandia mathematician and paper author Darby Smith, with most linked events. For example, he said, the number of days a patient must remain in the hospital are at least partially determined by the preceding length of stay.

Beginning with the Markov random basis, the researchers used Monte Carlo simulations, a fundamental computational tool, to run a series of random walks that attempt to cover as many routes as possible.

“Monte Carlo algorithms are a natural solution method for radiation transport problems,” said Franke. “Particles are simulated in a process that mirrors the physical process.”

The energy of each walk was recorded as a single energy spike by an artificial neuron reading the result of each walk in turn. “This neural net is more energy efficient in sum than recording each moment of each walk, as ordinary computing must do. This partially accounts for the speed and efficiency of the neuromorphic process,” said Aimone. More chips will help the process move faster using the same amount of energy, he said.

The next version of Loihi, said Sandia researcher Craig Vineyard, will increase its current chip scale from 128,000 neurons per chip to up to one million. Larger scale systems then combine multiple chips to a board.

“Perhaps it makes sense that a technology like Loihi may find its way into a future high-performance computing platform,” said Aimone. “This could help make HPC much more energy efficient, climate-friendly and just all around more affordable.”

The work was funded under the NNSA Advanced Simulation and Computing program and Sandia’s Laboratory Directed Research and Development program.

Video: https://youtu.be/O_8E26axKFY

“Vascular diseases afflict hundreds of millions of people in the world,” said Chang-Hyun Gil, MS, PhD, a postdoctoral fellow in the Department of Surgery and co-first author of the study. “In this study, we focused on the retinal vessel in type 2 diabetes. Our results demonstrate the safe, efficient and robust derivation of hiPSC-derived specific mesoderm subset for use as a novel therapy to rescue ischemic tissues and repair blood vessels in individuals with vascular diseases. The results provide a foundation for an early phase clinical trial.”

In the multi-site, early phase study recently published in Science Advances, investigators genetically reprogrammed diabetic and non-diabetic peripheral blood cells into hiPSCs and matured the cells into special blood vessel reparative cells. Upon injection into animal models with type 2 diabetic murine (T2D) retinal dysfunction, results showed significant improvement in visual acuity and electroretinograms with restoration of vascular perfusion. They hypothesized hiPSC-derived vascular reparative cells may serve as a source of endothelial precursors that will display in vivo vessel reparative properties in these diabetic subjects.

“Unlike the use of embryonic stem cells (ESCs), genetically engineered hiPSCs do not carry the ethical challenges ESCs possess that limit their possible usage, and hiPSCs are being increasingly recognized as a viable alternative in study design and application as a cell therapy for human disorders,” Gil said.

According to the U.S. Centers for Disease Control and Prevention, more than 37 million people in the United States have diabetes-more than 11 percent of the U.S. population. What’s more, diabetes-related complications have risen among both young adults ages 18 to 44 years of age and adults ages 45 to 64. These complications cause major metabolic disturbances that damage the cardiovascular, visual, peripheral nerve and renal systems through harming small and large microvessels that feed these tissues. In 2019, more than 11 percent of adults ages 18 and older reported severe vision issues or blindness and more than 1.87 million adults were diagnosed with major cardiovascular disease.

“This work by Dr. Gil represents a monumental step forward in the application of induced pluripotent stem cells in treating the complications of diabetes,” said Michael P. Murphy, MD, the Cryptic Medical Research Foundation Professor of Vascular Biology Research at IU School of Medicine, a vascular surgeon at IU Health and Eskenazi Health and a coauthor of the study.

Researchers converted hiPSC into a specific mesoderm subset that was enriched to generate endothelial cells with vessel reparative properties similar to endothelial colony forming cells (ECFC). Endothelial cells are cells found in the inner lining of blood vessels, lymph vessels and the heart and are a major component in regulating vascular function and inflammatory reactions. Endothelial cells control blood flow and regulate the transfer of proteins from blood into tissues.

Gil said the specific mesoderm subset expressing KDR, NCAM1 and APLNR (KNA⁺ mesoderm) exhibits enhanced capacity to differentiate into ECFC and form functional blood vessels in vivo and that mesoderm populations correct vasodegeneration of injured retinal vessels. Electroretinograms indicate enhanced function of neural retina and optokinetic nystagmus studies show improved vision.

“The next translational step of the work is to transfer the research protocols reported for differentiation of the hiPSC into to S^–KNA⁺ cells into large scale manufacturing processes,” said Mervin C. Yoder, MD, distinguished professor emeritus and research advisor for the Indiana Center for Regenerative Medicine and Engineering. Yoder is another coauthor of the study and is the scientific founder of Vascugen, a company driven to advance treatments for life-threatening conditions caused by microvascular conditions. “Selected aspects of this work have been licensed by Vascugen, Inc., through the Indiana University Innovation and Commercialization Office, who are focused on developing vascular reparative cells from induced pluripotent stem cells.”

Another study coauthor is Maria B. Grant, MD, the former Marilyn Glick Professor of Ophthalmology at the IU School of Medicine Eugene and Marilyn Glick Eye Institute and current endowed chair of ophthalmology at UAB. Grant said this is a highly translational study that is a continuation of a grant she and Yoder have been working on for the last 20 years regarding stems cells and how they can be used to repair blood vessels in the eye. While hiPSCs can take a long time to grow, the study team simplified the process to shorten the time to grow them and make them more feasible to translate into a human therapy to repair blood vessels in the eye.

“At UAB, we took the stem cells and hiPSC cells and studied them,” she said. “Science is really team science. I bring all the eye experience and some stem cell experience, and Dr. Yoder brings a lot of stem cell experience. It’s a complementary collaboration.”

“I want to express my greatest thanks to Dr. Yoder, Dr. Grant and Dr. Murphy for their support,” Gil said. He will remember Yoder for “his dedication, passion, patience and kindness” and Murphy for supporting him in completing the study.

Their findings are published March 10 in the journal Cell Metabolism.

The discovery can advance CAR-T cell therapy, which harnesses the immune response of T cells to cancers by introducing tumor-detecting molecules into the cells. In the last decade, the U.S. Food and Drug Administration has approved six CAR-T cell therapies to treat B cell lymphomas and multiple myeloma. But despite early successes, the effectiveness of the treatment tends to diminish over time, which has launched a search for ways to boost function of T cells.

Also, there are currently no approved CAR-T cell therapies to treat solid tumors.

For the new study, researchers in the lab of Sidi Chen, associate professor of genetics at Yale and senior author of the paper, devised an ingenious way to efficiently scan the genome of CD8 T cells for specific genes that might enhance the cells’ ability to attack cancer cells.

“We developed a new kind of genome-wide gain of function screen to find a molecular enzyme that acts like a foot on a gas pedal to increase metabolic activity in T cells,” Chen said.

They found high levels of activity in several genes, including PRODH2, a gene involved in cell metabolism, stimulate increased CAR-T cell activity in mouse models used to study three different types of cancers, including solid-tumor breast cancer. The findings show it is possible to produce hyper-metabolic CAR-T cells that outperform existing cell therapies, researchers say.

Using these systems and findings, future studies can test the newly identified types of metabolically enhanced CAR-Ts in clinical settings, to identify other T cell super-chargers, and to extend cell-based immunotherapy to different cancer types, especially solid tumors, Chen said.

Chen is affiliated with the Yale Cancer Center, the Yale Stem Cell Center, the Yale Center for Biomedical Data Science, and the Systems Biology Institute and Center for Cancer Systems Biology at Yale’s West Campus.

Yale’s Lupeng Ye, Jonathan Park, Lei Peng, and Quanjun Yang are co-first authors of the paper.

The research was primarily funded by the National Institutes of Health and the U.S. Department of Defense.

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Materials provided by Yale University. Original written by Bill Hathaway. Note: Content may be edited for style and length.