A medical device designed by a UH professor will close the loop with high frequency brain waves to prevent seizures from occurring. Photo via uh.edu

A professor at the University of Houston has received a federal grant aimed at helping stop epileptic seizures before they start.

The BRAIN Initiative at the National Institute of Neurological Disorders and Stroke awarded the $3.7 million grant to Nuri Firat Ince, an associate professor of biomedical engineering at UH. The grant will go toward Ince's work to create a seizure-halting device based on his research.

According to UH, Ince has reduced by weeks the time it takes to locate the seizure onset zone (SOZ), the part of the brain that causes seizures in patients with epilepsy. He's done this by detecting high-frequency oscillations (HFO) forming "repetitive waveform patterns" that identify their location in the SOZ.

Ince plans to use those HFOs to help control seizures. But he first must determine whether the HFOs can be detected with an implantable closed-loop device, enabling delivery of electrical stimulation that can control seizures. The device is called a brain interchange system. A closed-loop system supplies stimulation only when it detects the onset of a seizure.

Ince's neurotechnology partner, Cortec GMBH of Freiburg, Germany, is supplying the brain interchange system. Houston's Baylor College of Medicine eventually will be the site where medical professionals implant the device in pediatric and adult epilepsy patients.

"If the outcomes of our research in acute settings become successful, we will execute a clinical trial and run our methods with the implanted … system in a chronic ambulatory setting," Ince says in a UH news release.

Research published recently in the journal AJOB Neuroscience found that a closed-loop brain implant being used to treat refractory epilepsy does not alter patients' personalities or self-perception.

Nuri Firat Ince associate professor of biomedical engineering. Photo via uh.edu

"Next-generation brain stimulation devices can modulate brain activity without human intervention, which raises new ethical and policy questions," lead author Tobias Haeusermann of the University of California, San Francisco, says in a news release. "But while there is a great deal of speculation about the potential consequences of these innovative treatments, very little is currently known about patients' experiences of any device approved for clinical use."

The study, however, found no evidence that the device Haeusermann and his colleagues studied had changed patients' personalities or self-perception.

Haeusermann and his fellow researchers based their study on a closed-loop device that's currently available. In 2013, the U.S. Food and Drug Administration (FDA) approved this brain stimulation system for treatment of refractory epilepsy. It's the first clinically approved and commercially available closed-loop brain stimulation device for epilepsy patients. Refractory epilepsy occurs when medication no longer controls seizures.

According to a research article published in 2018, epilepsy ranks among the most common neurological disorders, affecting about 1% of the global population. For patients who suffer seizures that cannot be treated with drugs, a frequent treatment is surgical removal of the SOZ.

In this country, about 3 million adults and 470,000 children have epilepsy, according to the U.S. Centers for Disease Control and Prevention, including nearly 293,000 Texans. In the U.S., epilepsy is the fourth most common neurological disorder, preceded by migraine, stroke and Alzheimer's disease, the Epilepsy Foundation of Michigan says.

About 150,000 Americans are diagnosed each year with epilepsy.

Epilepsy is prevalent among people with autism, cerebral palsy, Down syndrome, and intellectual disabilities.

About 30 types of seizure occur among the more than 60 types of epilepsy, the Michigan foundation says. A seizure briefly disturbs electrical activity in the braining, causing temporary changes in movement, awareness, feelings, behavior, and other bodily functions.

Daily medication is the standard treatment for epilepsy, according to the Michigan foundation. Still, 30 percent to 40 percent of people with epilepsy continue to experience seizures.

Each year, U.S. health care costs associated with epilepsy add up to roughly $28 billion, according to the American Journal of Managed Care.

"Most people with epilepsy are able to lead productive and fulfilling lives, but for many, epilepsy can be a devastating condition," the foundation says.

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Houston doctor wins NIH grant to test virtual reality for ICU delirium

Virtual healing

Think of it like a reverse version of The Matrix. A person wakes up in a hospital bed and gets plugged into a virtual reality game world in order to heal.

While it may sound far-fetched, Dr. Hina Faisal, a Houston Methodist critical care specialist in the Department of Surgery, was recently awarded a $242,000 grant from the National Institute of Health to test the effects of VR games on patients coming out of major surgery in the intensive care unit (ICU).

The five-year study will focus on older patients using mental stimulation techniques to reduce incidences of delirium. The award comes courtesy of the National Institute on Aging K76 Paul B. Beeson Emerging Leaders Career Development Award in Aging.

“As the population of older adults continues to grow, the need for effective, scalable interventions to prevent postoperative complications like delirium is more important than ever,” Faisal said in a news release.

ICU delirium is a serious condition that can lead to major complications and even death. Roughly 87 percent of patients who undergo major surgery involving intubation will experience some form of delirium coming out of anesthesia. Causes can range from infection to drug reactions. While many cases are mild, prolonged ICU delirium may prevent a patient from following medical advice or even cause them to hurt themselves.

Using VR games to treat delirium is a rapidly emerging and exciting branch of medicine. Studies show that VR games can help promote mental activity, memory and cognitive function. However, the full benefits are currently unknown as studies have been hampered by small patient populations.

Faisal believes that half of all ICU delirium cases are preventable through VR treatment. Currently, a general lack of knowledge and resources has been holding back the advancement of the treatment.

Hopefully, the work of Faisal in one of the busiest medical cities in the world can alleviate that problem as she spends the next half-decade plugging patients into games to aid in their healing.

Houston scientists develop breakthrough AI-driven process to design, decode genetic circuits

biotech breakthrough

Researchers at Rice University have developed an innovative process that uses artificial intelligence to better understand complex genetic circuits.

A study, published in the journal Nature, shows how the new technique, known as “Combining Long- and Short-range Sequencing to Investigate Genetic Complexity,” or CLASSIC, can generate and test millions of DNA designs at the same time, which, according to Rice.

The work was led by Rice’s Caleb Bashor, deputy director for the Rice Synthetic Biology Institute and member of the Ken Kennedy Institute. Bashor has been working with Kshitij Rai and Ronan O’Connell, co-first authors on the study, on the CLASSIC for over four years, according to a news release.

“Our work is the first demonstration that you can use AI for designing these circuits,” Bashor said in the release.

Genetic circuits program cells to perform specific functions. Finding the circuit that matches a desired function or performance "can be like looking for a needle in a haystack," Bashor explained. This work looked to find a solution to this long-standing challenge in synthetic biology.

First, the team developed a library of proof-of-concept genetic circuits. It then pooled the circuits and inserted them into human cells. Next, they used long-read and short-read DNA sequencing to create "a master map" that linked each circuit to how it performed.

The data was then used to train AI and machine learning models to analyze circuits and make accurate predictions for how untested circuits might perform.

“We end up with measurements for a lot of the possible designs but not all of them, and that is where building the (machine learning) model comes in,” O’Connell explained in the release. “We use the data to train a model that can understand this landscape and predict things we were not able to generate data on.”

Ultimately, the researchers believe the circuit characterization and AI-driven understanding can speed up synthetic biology, lead to faster development of biotechnology and potentially support more cell-based therapy breakthroughs by shedding new light on how gene circuits behave, according to Rice.

“We think AI/ML-driven design is the future of synthetic biology,” Bashor added in the release. “As we collect more data using CLASSIC, we can train more complex models to make predictions for how to design even more sophisticated and useful cellular biotechnology.”

The team at Rice also worked with Pankaj Mehta’s group in the department of physics at Boston University and Todd Treangen’s group in Rice’s computer science department. Research was supported by the National Institutes of Health, Office of Naval Research, the Robert J. Kleberg Jr. and Helen C. Kleberg Foundation, the American Heart Association, National Library of Medicine, the National Science Foundation, Rice’s Ken Kennedy Institute and the Rice Institute of Synthetic Biology.

James Collins, a biomedical engineer at MIT who helped establish synthetic biology as a field, added that CLASSIC is a new, defining milestone.

“Twenty-five years ago, those early circuits showed that we could program living cells, but they were built one at a time, each requiring months of tuning,” said Collins, who was one of the inventors of the toggle switch. “Bashor and colleagues have now delivered a transformative leap: CLASSIC brings high-throughput engineering to gene circuit design, allowing exploration of combinatorial spaces that were previously out of reach. Their platform doesn’t just accelerate the design-build-test-learn cycle; it redefines its scale, marking a new era of data-driven synthetic biology.”