Gel-like, radioactive tumor implant obliterates pancreatic cancer in mice

Biomedical engineers at Duke University have demonstrated the most effective treatment for pancreatic cancer ever recorded in mouse models. While most mouse trials consider simply halting growth a success, the new treatment completely eliminated tumors in 80% of mice across several model types, including those considered the most difficult to treat.

The approach combines traditional chemotherapy drugs with a new method for irradiating the tumor. Rather than delivering radiation from an external beam that travels through healthy tissue, the treatment implants radioactive iodine-131 directly into the tumor within a gel-like depot that protects healthy tissue and is absorbed by the body after the radiation fades away.

The results appear online October 19 in the journal Nature Biomedical Engineering.

"We did a deep dive through over 1100 treatments across preclinical models and never found results where the tumors shrank away and disappeared like ours did," said Jeff Schaal, who conducted the research during his PhD in the laboratory of Ashutosh Chilkoti, the Alan L. Kaganov Distinguished Professor of Biomedical Engineering at Duke. "When the rest of the literature is saying that what we're seeing doesn't happen, that's when we knew we had something extremely interesting."

Despite accounting for only 3.2% of all cancer cases, pancreatic cancer is the third leading cause of cancer-related death. It is a very difficult to treat because its tumors tend to develop aggressive genetic mutations that make it resistant to many drugs, and it is typically diagnosed very late, when it has already spread to other sites in the body.

The current leading treatment combines chemotherapy, which keeps cells in a stage of reproduction vulnerable to radiation for longer periods of time, with a beam of radiation targeted at the tumor. This approach, however, is ineffective unless a certain threshold of radiation reaches the tumor. And despite recent advances in shaping and targeting radiation beams, that threshold is very difficult to reach without risking severe side effects.

Another method researchers have tried involves implanting a radioactive sample encased in titanium directly within the tumor. But because titanium blocks all radiation other than gamma rays, which travel far outside the tumor, it can only remain within the body for a short period of time before damage to surrounding tissue begins to defeat the purpose.

"There's just no good way to treat pancreatic cancer right now," said Schaal, who is now director of research at Cereius, Inc., a Durham, North Carolina biotechnology startup working to commercialize a targeted radionuclide therapy through a different technology scheme.

To skirt these issues, Schaal decided to try a similar implantation method using a substance made of elastin-like polypeptides (ELPs), which are synthetic chains of amino acids bonded together to form a gel-like substance with tailored properties. Because ELPs are a focus of the Chilkoti lab, he was able to work with colleagues to design a delivery system well suited for the task.

The ELPs exist in a liquid state at room temperature but form a stable gel-like substance within the warmer human body. When injected into a tumor along with a radioactive element, the ELPs form a small depot encasing radioactive atoms. In this case, the researchers decided to use iodine-131, a radioactive isotope of iodine, because doctors have used it widely in medical treatments for decades and its biological effects are well understood.

The ELP depot encases the iodine-131 and prevents it from leaking out into the body. The iodine-131 emits beta radiation, which penetrates the biogel and deposits almost all its energy into the tumor without reaching the surrounding tissue. Over time, the ELP depot degrades into its constituent amino acids and is absorbed by the body -- but not before the iodine-131 has decayed into a harmless form of xenon.

"The beta radiation also improves the stability of the ELP biogel," Schaal said. "That helps the depot last longer and only break down after the radiation is spent."

In the new paper, Schaal and his collaborators in the Chilkoti laboratory tested the new treatment in concert with paclitaxel, a commonly used chemotherapy drug, to treat various mouse models of pancreatic cancer. They chose pancreatic cancer because of its infamy for being difficult to treat, hoping to show that their radioactive tumor implant creates synergistic effects with chemotherapy that relatively short-lived radiation beam therapy does not.

The researchers tested their approach on mice with cancers just under their skin created by several different mutations known to occur in pancreatic cancer. They also tested it on mice that had tumors within the pancreas, which is much more difficult to treat.

Overall, the tests saw a 100% response rate across all models, with the tumors being completely eliminated in three-quarters of the models about 80% of the time. The tests also revealed no immediately obvious side effects beyond what is caused by chemotherapy alone.

"We think the constant radiation allows the drugs to interact with its effects more strongly than external beam therapy allows," Schaal said. "That makes us think that this approach might actually work better than external beam therapy for many other cancers, too."

The approach, however, is still in its early preclinical stages and will not be available for human use anytime soon. The researchers say their next step is large animal trials, where they will need to show that the technique can be accurately done with the existing clinical tools and endoscopy techniques that doctors are already trained on. If successful, they look toward a Phase 1 clinical trial in humans.

"My lab has been working on developing new cancer treatments for close to 20 years, and this work is perhaps the most exciting we have done in terms of its potential impact, as late-stage pancreatic cancer is impossible to treat and is invariably fatal," Chilkoti said. "Pancreatic cancer patients deserve better treatment options than are currently available, and I am deeply committed to taking this all the way into the clinic."

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Scientists hit their creative peak early in their careers

A new study provides the best evidence to date that scientists overall are most innovative and creative early in their careers.

Findings showed that, on one important measure, the impact of biomedical scientists' published work drops by between one-half to two-thirds over the course of their careers.

"That's a huge decline in impact," said Bruce Weinberg, co-author of the study and professor of economics at The Ohio State University.

"We found that as they get older, the work of biomedical scientists was just not as innovative and impactful."

But the reasons behind this trend of declining innovativeness make the findings more nuanced and show why it is still important to support scientists later in their careers, Weinberg said.

The study was published online Oct. 7, 2022 in the Journal of Human Resources.

Researchers have been studying the relationship between age or experience with innovativeness for nearly 150 years, but no consensus has emerged. Findings, in fact, have been "all over the map," Weinberg said.

"For a topic that so many people with so many approaches have studied for so long, it is pretty remarkable that we still don't have a conclusive answer."

One advantage of this study is that the authors had a huge dataset to work with -- 5.6 million biomedical science articles published over a 30-year period, from 1980 to 2009, and compiled by MEDLINE. These data include detailed information on the authors.

This new study measured the innovativeness of the articles by biomedical scientists using a standard method -- the number of times other scientists mention (or "cite") a study in their own work. The more times a study is cited, the more important it is thought to be.

With detailed information on the authors of each paper, the researchers in this study were able to compare how often scientists' work was cited early in their careers compared to later in their careers.

As they analyzed the data, Weinberg and his colleagues made a discovery that was a key to understanding how innovation changes over a career.

They found that scientists who were the least innovative early in their careers tended to drop out of the field and quit publishing new research. It was the most productive, the most important young scholars who were continuing to produce research 20 or 30 years later.

"Early in their careers, scientists show a wide range of innovativeness. But over time, we see selective attrition of the people who are less innovative," Weinberg said.

"So when you look at all biomedical scientists as a group, it doesn't look like innovation is declining over time. But the fact that the least innovative researchers are dropping out when they are relatively young disguises the fact that, for any one person, innovativeness tends to decline over their career."

Results showed that for the average researcher, a scientific article they published late in their career was cited one-half to two-thirds less often than an article published early in their careers.

But it wasn't just citation counts that suggest researchers were less innovative later in their career.

"We constructed additional metrics that captured the breadth of an article's impact based on the range of fields that cite it, whether the article is employing the best and latest ideas, citing the best and latest research, and whether the article is drawing from multiple disciplines," said Huifeng Yu, a co-author, who worked on the study as a PhD student at the University at Albany, SUNY.

"These other metrics also lead to the same conclusion about declining innovativeness."

The findings showing selective attrition among less-innovative scientists can help explain why previous studies have had such conflicting results, Weinberg said.

Studies using Nobel Laureates and other eminent researchers, for whom attrition is relatively small, tend to find earlier peak ages for innovation. In contrast, studies using broader cross-sections of scientists don't normally find an early peak in creativity, because they don't account for the attrition.

Weinberg noted that attrition in the scientific community may not relate only to innovativeness. Scientists who are women or from underrepresented minorities may not have had the opportunities they needed to succeed, although this study can't quantify that effect.

"Those scientists who succeeded probably did so through a combination of talent, luck, personal background and prior training," he said.

The findings suggest that organizations that fund scientists have to maintain a delicate balance between supporting youth and experience.

"Young scientists tend to be at their peak of creativity, but there is also a big mix with some being much more innovative than others. You may not be supporting the very best researchers," said Gerald Marschke, a co-author of the study and associate professor of economics at the University at Albany,

"With older, more experienced scientists, you are getting the ones who have stood the test of time, but who on average are not at their best anymore."

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New chip-based beam steering device lays groundwork for smaller, cheaper lidar

Researchers have developed a new chip-based beam steering technology that provides a promising route to small, cost-effective and high-performance lidar (or light detection and ranging) systems. Lidar, which uses laser pulses to acquire 3D information about a scene or object, is used in a wide range of applications such as autonomous driving, free-space optical communications, 3D holography, biomedical sensing and virtual reality.

"Optical beam steering is a key technology for lidar systems, but conventional mechanical-based beam steering systems are bulky, expensive, sensitive to vibration and limited in speed," said research team leader Hao Hu from the Technical University of Denmark. "Although devices known as chip-based optical phased arrays (OPAs) can quickly and precisely steer light in a non-mechanical way, so far, these devices have had poor beam quality and a field of view typically below 100 degrees."

In Optica, Optica Publishing Group's journal for high-impact research, Hu and co-author Yong Liu describe their new chip-based OPA that solves many of the problems that have plagued OPAs. They show that the device can eliminate a key optical artifact known as aliasing, achieving beam steering over a large field of view while maintaining high beam quality, a combination that could greatly improve lidar systems.

"We believe our results are groundbreaking in the field of optical beam steering," said Hu. "This development lays the groundwork for OPA-based lidar that is low cost and compact, which would allow lidar to be widely used for a variety of applications such as high-level advanced driver-assistance systems that can assist in driving and parking and increase safety."

A new OPA design

OPAs perform beam steering by electronically controlling light's phase profile to form specific light patterns. Most OPAs use an array of waveguides to emit many beams of light and then interference is applied in far field (away from the emitter) to form the pattern. However, the fact that these waveguide emitters are typically spaced far apart from each other and generate multiple beams in the far field creates an optical artifact known as aliasing. To avoid the aliasing error and achieve a 180° field of view, the emitters need to be close together, but this causes strong crosstalk between adjacent emitters and degrades the beam quality. Thus, until now, there has been a trade-off between OPA field of view and beam quality.

To overcome this trade-off, the researchers designed a new type of OPA that replaces the multiple emitters of traditional OPAs with a slab grating to create a single emitter. This setup eliminates the aliasing error because the adjacent channels in the slab grating can be very close to each other. The coupling between the adjacent channels is not detrimental in the slab grating because it enables the interference and beam formation in the near field (close to the single emitter). The light can then be emitted to the far field with the desired angle. The researchers also applied additional optical techniques to lower the background noise and reduce other optical artifacts such as side lobes.

High quality and wide field of view

To test their new device, the researchers built a special imaging system to measure the average far-field optical power along the horizontal direction over a 180° field of view. They demonstrated aliasing-free beam steering in this direction, including steering beyond ±70°, although some beam degradation was seen.

They then characterized beam steering in the vertical direction by tuning the wavelength from 1480 nm to 1580 nm, achieving a 13.5° tuning range. Finally, they showed the versatility of the OPA by using it to form 2D images of the letters "D," "T" and "U" centered at the angles of -60°, 0° and 60° by tuning both the wavelength and the phase shifters. The experiments were performed with a beam width of 2.1°, which the researchers are now working to decrease to achieve beam steering with a higher resolution and a longer range.

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Tweaked genes borrowed from bacteria excite heart cells in live mice

Biomedical engineers at Duke University have demonstrated a gene therapy that helps heart muscle cells electrically activate in live mice. The first demonstration of its kind, the approach features engineered bacterial genes that code for sodium ion channels and could lead to therapies to treat a wide variety of electrical heart diseases and disorders.

The results appeared online February 2 in the journal Nature Communications.

"We were able to improve how well heart muscle cells can initiate and spread electrical activity, which is hard to accomplish with drugs or other tools," said Nenad Bursac, professor of biomedical engineering at Duke. "The method we used to deliver genes in heart muscle cells of mice has been previously shown to persist for a long time, which means it could effectively help hearts that struggle to beat as regularly as they should."

Sodium-ion channels are proteins in the outer membranes of electrically excitable cells, such as heart or brain cells, that transmit electrical charges into the cell. In the heart, these channels tell muscle cells when to contract and pass the instruction along so that the organ pumps blood as a cohesive unit. Damaged heart cells, however, whether from disease or trauma, often lose all or part of their ability to transmit these signals and join the effort.

One approach researchers can take to restoring this functionality is gene therapy. By delivering the genes responsible for creating sodium channel proteins, the technique can produce more ion channels in the diseased cells to help boost their activity.

In mammals, sodium channel genes are unfortunately too large to fit within the viruses currently used in modern gene therapies in humans. To skirt this issue, Bursac and his laboratory instead turned to smaller genes that code for similar sodium ion channels in bacteria. While these bacterial genes are different than their human counterparts, evolution has conserved many similarities in the channel design since multi-cellular organisms diverged from bacteria hundreds of millions of years ago.

Several years ago, Hung Nguyen, a former doctoral student in Bursac's laboratory who now works for Fujifilm Diosynth Biotechnologies, mutated these bacterial genes so that the channels they encode could become active in human cells. In the new work, current doctoral student Tianyu Wu further optimized the content of the genes and combined them with a "promoter" that exclusively restricts channel production to heart muscle cells. The researchers then tested their approach by delivering a virus loaded with the bacterial gene into veins of a mouse to spread throughout the body.

"We worked to find where the sodium ion channels were actually formed, and, as we hoped, we found that they only went into the working muscle cells of the heart within the atria and ventricles," Wu said. "We also found that they did not end up in the heart cells that originate the heartbeat, which we also wanted to avoid."

This gene therapy approach only delivers extra genes within a cell; it does not attempt to cut out, replace or rewrite the existing DNA in any way. Scientists believe these types of delivered genes make proteins while floating freely within the cell, making use of the existing biochemical machinery. Previous research with this viral gene delivery approach suggests the transplanted genes should remain active for many years.

As a proof of concept, tests on cells in a laboratory setting suggest that the treatment improves electrical excitability enough to prevent human abnormalities like arrhythmias. Within live mice, the results demonstrate that the sodium ion channels are active in the hearts, showing trends toward improved excitability. However, further tests are needed to measure how much of an improvement is made on the whole-heart level, and whether it is enough to rescue electrical function in damaged or diseased heart tissue to be used as a viable treatment.

Moving forward, the researchers have already identified different bacterial sodium channel genes that work better in preliminary benchtop studies. The team is also working with the laboratories of Craig Henriquez, professor of biomedical engineering at Duke, and Andrew Landstrom, director of the Duke Pediatric Research Scholars Program, to test the ability of these genes to restore heart functionality in mouse models that mimic human heart diseases.

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Biomedical scientists tie improved learning processes to reduced symptoms of depression

Virginia Tech scientists with the Fralin Biomedical Research Institute at VTC have identified neural learning processes to be associated with symptoms of depression and linked improvements in these processes to improved symptoms in research participants being treated for depression.

The findings, described in a study published July 28, 2021 in the Journal of the American Medical Association (JAMA) Psychiatry, suggest distinct paths to depression symptoms and new mathematically guided approaches for treating clinical depression.

Major depression is one of the most common mental disorders in the United States and can cause severe impairment, according to the National Institute of Mental Health. An estimated 7.1% of all U.S. adults have had at least one major depressive episode.

"Current medications and behavioral therapies are helpful, but for many people struggling with depression, existing treatments don't work well," said Pearl Chiu, an associate professor at the Fralin Biomedical Research Institute Computational Psychiatry Unit and the study's corresponding author. "We need to consider other possible paths to depression. These paths, or mechanisms, could point to new treatment targets to explore."

The scientists used computational models of brain functioning as a new way to consider mechanisms of depression. In a key discovery, the researchers found that the symptom improvements that followed cognitive behavioral therapy were related to improvements in reinforcement learning components that were disrupted prior to therapy.

"Depression is a very serious illness and a leading cause of disability in the world. We hope that our work can be a bridge between behavioral clinicians and computational scientists to more precisely identify what causes depression and new ways to treat the illness," said first author Vanessa Brown, a former doctoral student with Chiu in Virginia Tech's Department of Psychology and who is now an assistant professor of psychiatry at the University of Pittsburgh.

The research team began studying a baseline group of 101 adults with and without clinical depression. A subset of the participants with depression were treated with up to 12 weeks of cognitive behavioral therapy -- a treatment that involves learning how to identify and correct negative thought patterns.

Participants with depression played a learning game during functional MRI brain scanning before and after cognitive behavioral therapy, and participants without depression played the same game at time points matched to participants who took part in cognitive behavioral therapy. The scientists used computational modeling to identify different processes that contribute to learning. They found that distinct components of learning about rewards and losses -- known as reinforcement learning -- were connected to certain symptoms of depression.

"Two of the most exciting parts of the findings are that people with depression learn in different ways and that these learning processes changed when depression symptoms improved after cognitive behavioral therapy. The link between the learning components and symptoms is critical," said Brooks King-Casas, co-author of the study and an associate professor with the Fralin Biomedical Research Institute and in the Department of Psychology in Virginia Tech's College of Science.

The researchers say using computational models has potential to help other investigators and mental health professionals precisely identify new contributors to depression, which in turn could be new targets for therapies.

"An example is that for someone with depression, losing a few cents in the game could feel like losing several hundred dollars or the loss could be very hard to forget. These processes are different, but both affect how we learn and the choices we make," King-Casas said.

"We quantified some of these learning processes with computational modeling and show that they relate to depression in very different ways," said Chiu, who is also an associate professor of psychology in Virginia Tech's College of Science. "The idea is similar to how stress or too much sodium can both contribute to high blood pressure, but what contributes to a particular person's hypertension could suggest whether they focus on decreasing stress or reducing salt consumption as part of treatment. Similarly, for depression, the parts of learning that contribute to a person's depression could call for different approaches to treatment."

Chiu says forming a computational understanding of how cognitive processes align with symptoms of depression is a promising approach.

"Now that we've linked specific components of learning to depression and show that they change with specific depression symptoms, perhaps we can develop new therapies that focus on adjusting these learning components as a way to reduce depression," she said.

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