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New 3D Atlas of Colorectal Cancer Promises Improved Diagnosis, Treatment

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Brightly colored light microscopy showing locations for DNA, Pan-cytokeratin, alpha-SMA, CD4, CD20, CD31, Glandular, Solid, Mucinous
Caption: Tissue from a colorectal cancer. The multi-colored scale (top right) reveals layers of hidden information, including types of tissue and protein. Credit: Sorger Lab, Harvard Medical School, Cambridge, MA

This year, too many Americans will go to the doctor for tissue biopsies to find out if they have cancer. Highly trained pathologists will examine the biopsies under a microscope for unusual cells that show the telltale physical features of a suspected cancer. As informative as the pathology will be for considering the road ahead, it would be even more helpful if pathologists had the tools to look widely inside cells for the actual molecules giving rise to the tumor.

Working this “molecular information” into the pathology report would bring greater diagnostic precision, drilling down to the actual biology driving the growth of the tumor. It also would help doctors to match the right treatments to a patient’s tumor and not waste time on drugs that will be ineffective.

That’s why researchers have been busy building the needed tools and also mapping out molecular atlases of common cancers. These atlases, really a series of 3D spatial maps detailing various biological features within the tumor, keep getting better all the time. That includes the comprehensive atlas of colorectal cancer just published in the journal Cell [1].

This colorectal atlas comes from an NIH-supported team led by Sandro Santagata, Brigham and Women’s Hospital, Boston, and Peter Sorger, Harvard Medical School, Cambridge, MA, in collaboration with investigators at Vanderbilt University, Nashville, TN. The colorectal atlas joins their previously published high-definition map of melanoma [2], and both are part of the Human Tumor Atlas Network that’s supported by NIH’s National Cancer Institute.

What’s so interesting with the colorectal atlas is the team combined traditional pathology with a sophisticated technique for imaging single cells, enabling them to capture their fine molecular details in an unprecedented way.

They did it using a cutting-edge technique known as cyclic immunofluorescence, or CyCIF. In CyCIF, researchers use many rounds of highly detailed molecular imaging on each tissue sample to generate a rich collection of molecular-level data, cell by cell. Altogether, the researchers captured this fine-scale visual information for nearly 100 million cancer cells isolated from tumor samples representing 93 individuals diagnosed with colorectal cancer.

With this single-cell information in hand, they next created detailed 2D maps covering the length and breadth of large portions of the colorectal cancers under study. Finally, with the aid of first author Jia-Ren Lin, also at Harvard Medical School, and colleagues they stitched together their 2D maps to produce detailed 3D reconstructions showing the length, breadth, and height of the tumors.

This more detailed view of colorectal cancer has allowed the team to explore differences between normal and tumor tissues, as well as variations within an individual tumor. In fact, they’ve uncovered physical features that had never been discovered.

For instance, an individual tumor has regions populated with malignant cells, while other areas look less affected by the cancer. In between are transitional areas that correspond to molecular gradients of information. With this high-resolution map as their guide, researchers can now study what this all might mean for the diagnosis, treatment, and prognosis of colorectal cancer.

The atlas also shows that the presence of immune cells varies dramatically within a single tumor. That’s an important discovery because of its potential implications for immunotherapies, in which treatments aim to unleash the immune system in the fight against cancer.

The maps also provide new insights into tumor structure. For example, scientists had previously identified what they thought were 2D pools of a mucus-like substance called mucin with clusters of cancer cells suspended inside. However, the new 3D reconstruction make clear that these aren’t simple mucin pools. Rather, they are cross sections of larger intricate caverns of mucin interconnected by channels, into which cancer cells make finger-like projections.

The good news is the researchers already are helping to bring these methods into the cancer clinic. They also hope to train other scientists to build their own cancer atlases and grow the collection even more.

In the meantime, the team will refine its 3D tumor reconstructions by integrating new imaging technologies and even more data into their maps. It also will map many more colorectal cancer samples to capture the diversity of their basic biology. Also of note, having created atlases for melanoma and colorectal cancer, the team has plans to tackle breast and brain cancers next.

Let me close by saying, if you’re between the ages of 45 and 75, don’t forget to stay up to date on your colorectal cancer screenings. These tests are very good, and they could save your life.

References:

[1] Multiplexed 3D atlas of state transitions and immune interaction in colorectal cancer. Lin JR, Wang S, Coy S, Chen YA, Yapp C, Tyler M, Nariya MK, Heiser CN, Lau KS, Santagata S, Sorger PK. Cell. 2023 Jan 19;186(2):363-381.e19.

[2] The spatial landscape of progression and immunoediting in primary melanoma at single-cell resolution. Nirmal AJ, Maliga Z, Vallius T, Quattrochi B, Chen AA, Jacobson CA, Pelletier RJ, Yapp C, Arias-Camison R, Chen YA, Lian CG, Murphy GF, Santagata S, Sorger PK. Cancer Discov. 2022 Jun 2;12(6):1518-1541.

Links:

Colorectal Cancer (National Cancer Institute/NIH)

Human Tumor Atlas Network (NCI)

CyCIF-Cyclic Immunofluorescence (Harvard Medical School, Cambridge, MA)

Sandro Santagata (Brigham and Women’s Hospital, Boston)

Peter Sorger (Harvard Medical School)

Jia-Ren Lin (Harvard Medical School)

NIH Support: National Cancer Institute; National Institute of General Medical Sciences; National Institute of Diabetes and Digestive and Kidney Diseases


Chipping Away at the Causes of Polycystic Kidney Disease

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Organoid on a chip. Glucose fills a space behind the lumen of the tubule.
Caption: Image depicts formation of cyst (surrounded by white arrows) within kidney organoid on a chip. As cyst absorbs glucose passing through the tubule, it grows larger.

It’s often said that two is better than one. That’s true whether driving across the country, renovating a kitchen, or looking for a misplaced set of car keys. But a recent study shows this old saying also applies for modeling a kidney disease with two very complementary, cutting-edge technologies: an organoid, a living miniaturized organ grown in a laboratory dish; and an “organ-on-a-chip,” silicon chips specially engineered to mimic the 3D tissue structure and basic biology of a human body organ.

Using this one-two approach at the lab bench, the researchers modeled in just a few weeks different aspects of the fluid-filled cysts that form in polycystic kidney disease (PKD), a common cause of kidney failure. This is impossible to do in real-time in humans for a variety of technical reasons.

These powerful technologies revealed that blood glucose plays a role in causing the cysts. They also showed the cysts form via a different biological mechanism than previously thought. These new leads, if confirmed, offer a whole new way of thinking about PKD cysts, and more exciting, how to prevent or slow the disease in millions of people worldwide.

These latest findings, published in the journal Nature Communications, come from Benjamin Freedman and colleagues at the University of Washington School of Medicine, Seattle [1]. While much is known about the genetic causes of PKD, Freedman and team realized there’s much still much to learn about the basics of how cysts form in the kidney’s tiny tubes, or tubules, that help to filter toxins out of the bloodstream.

Each human kidney has millions of tubules, and in people with PKD, some of them expand gradually and abnormally to form sacs of fluid that researchers liken to water balloons. These sacs, or cysts, crowd out healthy tissue, leading over time to reduced kidney function and, in some instances, complete kidney failure.

To understand cyst formation better, Freedman’s team and others have invented methods to grow human kidney organoids, complete with a system of internal tubules. Impressively, organoids made from cells carrying mutations known to cause PKD develop cysts, just as people with these same mutations do. When suspended in fluid, the organoids also develop telltale signs of PKD even more dramatically, showing they are sensitive to changes in their environments.

At any given moment, about a quarter of all the fluids in the body pass through the kidneys, and this constant flow was missing from the organoid. That’s when Freedman and colleagues turned to their other modeling tool: a kidney-on-a-chip.

These more complex 3D models, containing living kidney cells, aim to mimic more fully the kidney and its environment. They also contain a network of microfluidic channels to replicate the natural flow of fluids in a living kidney. Combining PKD organoids with kidney-on-a-chip technology provided the best of both worlds.

Their studies found that exposing PKD organoid-on-a-chip models to a solution including water, glucose, amino acids, and other nutrients caused cysts to expand more quickly than they otherwise would. However, the cysts don’t develop from fluids that the kidneys outwardly secrete, as long thought. The new findings reveal just the opposite. The PKD cysts arise and grow as the kidney tissue works to retain most of the fluids that constantly pass through them.

They also found out why: the cysts were absorbing glucose and taking in water from the fluid passing over them, causing the cysts to expand. Although scientists had known that kidneys absorb glucose, they’d never connected this process to the formation of cysts in PKD.

In further studies, the scientists gave fluorescently labeled glucose to mice with PKD and could see that kidney cysts in the animals also took up glucose. The researchers think that the tubules are taking in fluid in the mice just as they do in the organoids.

Understanding the mechanisms of PKD can point to new ways to treat it. Indeed, the research team showed adding compounds that block the transport of glucose also prevented cyst growth. Freedman notes that glucose transport inhibitors (flozins), a class of oral drugs now used to treat diabetes, are in development for other types of kidney disease. He said the new findings suggest glucose transport inhibitors might have benefits for treating PKD, too.

There’s much more work to do. But the hope is that these new insights into PKD biology will lead to promising ways to prevent or treat this genetic condition that now threatens the lives of far too many loved ones in so many families.

This two-is-better-than-one approach is just an example of the ways in which NIH-supported efforts in tissue chips are evolving to better model human disease. That includes NIH’s National Center for Advancing Translational Science’s Tissue Chip for Drug Screening program, which is enabling promising new approaches to study human diseases affecting organ systems throughout the body.

Reference:

[1] Glucose absorption drives cystogenesis in a human organoid-on-chip model of polycystic kidney disease. Li SR, Gulieva RE, Helms L, Cruz NM, Vincent T, Fu H, Himmelfarb J, Freedman BS. Nat Commun. 2022 Dec 23;13(1):7918.

Links:

Polycystic Kidney Disease (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)

Your Kidneys & How They Work (NIDDK)

Freedman Lab (University of Washington, Seattle)

Tissue Chip for Drug Screening (National Center for Advancing Translational Sciences/NIH)

NIH Support: National Center for Advancing Translational Sciences; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute


A Look Back at Science’s 2022 Breakthroughs

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RSV vaccines near the finish. Virus fingered as cause of multiple sclerosis. AI gets creative.
Credit: National Institute of Allergy and Infectious Diseases, NIH; Centers for Disease Control and Prevention; Shutterstock/tobe24, Midjourney Inc.

Happy New Year! I hope everyone finished 2022 with plenty to celebrate, whether it was completing a degree or certification, earning a promotion, attaining a physical fitness goal, or publishing a hard-fought scientific discovery.

If the latter, you are in good company. Last year produced some dazzling discoveries, and the news and editorial staff at the journal Science kept a watchful eye on the most high-impact advances of 2022. In December, the journal released its list of the top 10 advances across the sciences, from astronomy to zoology. In case you missed it, Science selected NASA’s James Webb Space Telescope (JWST) as the 2022 Breakthrough of the Year [1].

This unique space telescope took 20 years to complete, but it has turned out to be time well spent. Positioned 1.5-million-kilometers from Earth, the JWST and its unprecedented high-resolution images of space have unveiled the universe anew for astronomers and wowed millions across the globe checking in online. The telescope’s image stream, beyond its sheer beauty, will advance study of the early Universe, allowing astronomers to discover distant galaxies, explore the early formation of stars, and investigate the possibility of life on other planets.

While the biomedical sciences didn’t take home the top prize, they were well represented among Science’s runner-up breakthroughs. Some of these biomedical top contenders also have benefited, directly or indirectly, from NIH efforts and support. Let’s take a look:

RSV vaccines nearing the finish line: It’s been one of those challenging research marathons. But scientists last year started down the homestretch with the first safe-and-effective vaccine for respiratory syncytial virus (RSV), a leading cause of severe respiratory illness in the very young and the old.

In August, the company Pfizer presented evidence that its experimental RSV vaccine candidate offered protection for those age 60 and up. Later, they showed that the same vaccine, when administered to pregnant women, helped to protect their infants against RSV for six months after birth. Meanwhile, in October, the company GSK announced encouraging results from its late-stage phase III trial of an RSV vaccine in older adults.

As Science noted, the latest clinical progress also shows the power of basic science. For example, researchers have been working with chemically inactivated versions of the virus to develop the vaccine. But these versions have a key viral surface protein that changes its shape after fusing with a cell to start an infection. In this configuration, the protein elicits only weak levels of needed protective antibodies.

Back in 2013, Barney Graham, then with NIH’s National Institute of Allergy and Infectious Diseases (NIAID), and colleagues, solved the problem [2]. Graham’s NIH team discovered a way to lock the protein into its original prefusion state, which the immune system can better detect. This triggers higher levels of potent antibodies, and the discovery kept the science—and the marathon—moving forward.

These latest clinical advances come as RSV and other respiratory viruses, including SARS-CoV-2, the cause of COVID-19, are sending an alarming number of young children to the hospital. The hope is that researchers will cross the finish line this year or next, and we’ll have the first approved RSV vaccine.

Virus fingered as cause of multiple sclerosis: Researchers have long thought that multiple sclerosis, or MS, has a viral cause. Pointing to the right virus with the required high degree of certainty has been the challenge, slowing progress on the treatment front for those in need. As published in Science last January, Alberto Ascherio, Harvard T.H. Chan School of Public Health, Boston, and colleagues produced the strongest evidence yet that MS is caused by the Epstein-Barr virus (EBV), a herpesvirus also known for causing infectious mononucleosis [3].

The link between EBV and MS had long been suspected. But it was difficult to confirm because EBV infections are so widespread, and MS is so disproportionately rare. In the recent study, the NIH-supported researchers collected blood samples every other year from more than 10 million young adults in the U.S. military, including nearly 1,000 who were diagnosed with MS during their service. The evidence showed that the risk of an MS diagnosis increased 32-fold after EBV infection, but it held steady following infection with any other virus. Levels in blood serum of a biomarker for MS neurodegeneration also went up only after an EBV infection, suggesting that the viral illness is a leading cause for MS.

Further evidence came last year from a discovery published in the journal Nature by William Robinson, Stanford University School of Medicine, Stanford, CA, and colleagues. The NIH-supported team found a close resemblance between an EBV protein and one made in the healthy brain and spinal cord [4]. The findings suggest an EBV infection may produce antibodies that mistakenly attack the protective sheath surrounding our nerve cells. Indeed, the study showed that up to one in four people with MS had antibodies that bind both proteins.

This groundbreaking research suggests that an EBV vaccine and/or antiviral drugs that thwart this infection might ultimately prevent or perhaps even cure MS. Of note, NIAID launched last May an early-stage clinical trial for an experimental EBV vaccine at the NIH Clinical Center, Bethesda, MD.

AI Gets Creative: Science’s 2021 Breakthrough of the Year was AI-powered predictions of protein structure. In 2022, AI returned to take another well-deserved bow. This time, Science singled out AI’s now rapidly accelerating entry into once uniquely human attributes, such as artistic expression and scientific discovery.

On the scientific discovery side, Science singled out AI’s continued progress in getting creative with the design of novel proteins for vaccines and myriad other uses. One technique, called “hallucination,” generates new proteins from scratch. Researchers input random amino acid sequences into the computer, and it randomly and continuously mutates them into sequences that other AI tools are confident will fold into stable proteins. This greatly simplifies the process of protein design and frees researchers to focus their efforts on creating a protein with a desired function.

AI research now engages scientists around world, including hundreds of NIH grantees. Taking a broader view of AI, NIH recently launched the Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Program. It will help to create greater diversity within the field, which is a must. A lack of diversity could perpetuate harmful biases in how AI is used, how algorithms are developed and trained, and how findings are interpreted to avoid health disparities and inequities for underrepresented communities.

And there you have it, some of the 2022 breakthroughs from Science‘s news and editorial staff. Of course, the highlighted biomedical breakthroughs don’t capture the full picture of research progress. There were many other milestone papers published in 2022 that researchers worldwide will build upon in the months and years ahead to make further progress in their disciplines and, for some, draw the attention of Science’s news and editorial staff. Here’s to another productive year in biomedical research, which the blog will continue to feature and share with you as it unfolds in 2023.

References:

[1] 2022 Breakthrough of the Year. Science. Dec 15, 2022.

[2] Structure of RSV fusion glycoprotein trimer bound to a prefusion-specific neutralizing antibody. McLellan JS, Chen M, Leung S, Kwong PD, Graham BS, et al. Science. 2013 May 31;340(6136):1113-1117.

[3] Longitudinal analysis reveals high prevalence of Epstein-Barr virus associated with multiple sclerosis. Bjornevik K, Cortese M, Healy BC, Kuhle J, Mina MJ, Leng Y, Elledge SJ, Niebuhr DW, Scher AI, Munger KL, Ascherio A. Science. 2022 Jan 21;375(6578):296-301.

[4] Clonally expanded B cells in multiple sclerosis bind EBV EBNA1 and GlialCAM. Lanz TV, Brewer RC, Steinman L, Robinson WH, et al. Nature. 2022 Mar;603(7900):321-327.

Links:

Respiratory Syncytial Virus (RSV) (National Institute of Allergy and Infectious Diseases/NIH)

Multiple Sclerosis (National Institute of Neurological Disorders and Stroke/NIH)

Barney Graham (Morehouse School of Medicine, Atlanta)

Alberto Ascherio (Harvard T.H. Chan School of Public Health, Boston)

Robinson Lab (Stanford Medicine, Stanford, CA)

Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Program (NIH)

James Webb Space Telescope (Goddard Space Flight Center/NASA, Greenbelt, MD)


Experimental mRNA Vaccine May Protect Against All 20 Influenza Virus Subtypes

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mRNA-lipid Nanoparticle Vaccine. Half sphere filled with more half spheres containing RNA
Caption: Messenger RNA (mRNA)– nanoparticle vaccine encoding hemagglutinin antigens (H with number) from all 20 known influenza subtypes.

Flu season is now upon us, and protecting yourself and loved ones is still as easy as heading to the nearest pharmacy for your annual flu shot. These vaccines are formulated each year to protect against up to four circulating strains of influenza virus, and they generally do a good job of this. What they can’t do is prevent future outbreaks of more novel flu viruses that occasionally spill over from other species into humans, thereby avoiding a future influenza pandemic.

On this latter and more-challenging front, there’s some encouraging news that was published recently in the journal Science [1]. An NIH-funded team has developed a unique “universal flu vaccine” that, with one seasonal shot, that has the potential to build immune protection against any of the 20 known subtypes of influenza virus and protect against future outbreaks.

While this experimental flu vaccine hasn’t yet been tested in people, the concept has shown great promise in advanced pre-clinical studies. Human clinical trials will hopefully start in the coming year. The researchers don’t expect that this universal flu vaccine will prevent influenza infection altogether. But, like COVID-19 vaccines, the new flu vaccine should help to reduce severe influenza illnesses and deaths when a person does get sick.

So, how does one develop a 20-in-1“multivalent” flu vaccine? It turns out that the key is the same messenger RNA (mRNA) technology that’s enabled two of the safe and effective vaccines against COVID-19, which have been so instrumental in fighting the pandemic. This includes the latest boosters from both Pfizer and Moderna, which now offer updated protection against currently circulating Omicron variants.

While this isn’t the first attempt to develop a universal flu vaccine, past attempts had primarily focused on a limited number of conserved antigens. An antigen is a protein or other substance that produces an immune response. Conserved antigens are those that tend to stay the same over time.

Because conserved antigens will look similar in many different influenza viruses, the hope was that vaccines targeting a small number of them would afford some broad influenza protection. But the focus on a strategy involving few antigens was driven largely by practical limitations. Using traditional methods to produce vaccines by growing flu viruses in eggs and isolating proteins, it simply isn’t feasible to include more than about four targets.

That’s where recent advances in mRNA technology come in. What makes mRNA so nifty for vaccines is that all you need to know is the letters, or sequence, that encodes the genetic material of a virus, including the sequences that get translated into proteins.

A research team led by Scott Hensley, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, recognized that the ease of designing and manufacturing mRNA vaccines opened the door to an alternate approach to developing a universal flu vaccine. Rather than limiting themselves to a few antigens, the researchers could make an all-in-one influenza vaccine, encoding antigens from every known influenza virus subtype.

Influenza vaccines generally target portions of a plentiful protein on the viral surface known as hemagglutinin (H). In earlier work, Hensley’s team, in collaboration with Perelman’s mRNA vaccine pioneer Drew Weissman, showed they could use mRNA technology to produce vaccines with H antigens from single influenza viruses [2, 3]. To protect the fragile mRNA molecules that encode a selected H antigen, researchers deliver them to cells inside well-tolerated microscopic lipid shells, or nanoparticles. The same is true of mRNA COVID-19 vaccines. In their earlier studies, the researchers found that when an mRNA vaccine aimed at one flu virus subtype was given to mice and ferrets in the lab, their cells made the encoded H antigen, eliciting protective antibodies.

In this latest study, they threw antigens from all 20 known flu viruses into the mix. This included H antigens from 18 known types of influenza A and two lineages of influenza B. The goal was to develop a vaccine that could teach the immune system to recognize and respond to any of them.

More study is needed, of course, but early indications are encouraging. The vaccine generated strong and broad antibody responses in animals. Importantly, it worked both in animals with no previous immunity to the flu and in those previously infected with flu viruses. That came as good news because past infections and resulting antibodies sometimes can interfere with the development of new antibodies against related viral subtypes.

In more good news, the researchers found that vaccinated mice and ferrets were protected against severe illness when later challenged with flu viruses. Those viruses included some that were closely matched to antigens in the vaccine, along with some that weren’t.

The findings offer proof-of-principle that mRNA vaccines containing a wide range of antigens can offer broad protection against influenza and likely other viruses as well, including the coronavirus strains responsible for COVID-19. The researchers report that they’re moving toward clinical trials in people, with the goal of beginning an early phase 1 trial in the coming year. The hope is that these developments—driven in part by technological advances and lessons learned over the course of the COVID-19 pandemic—will help to mitigate or perhaps even prevent future pandemics.

References:

[1] A multivalent nucleoside-modified mRNA vaccine against all known influenza virus subtypes. Arevalo CP, Bolton MJ, Le Sage V, Ye N, Furey C, Muramatsu H, Alameh MG, Pardi N, Drapeau EM, Parkhouse K, Garretson T, Morris JS, Moncla LH, Tam YK, Fan SHY, Lakdawala SS, Weissman D, Hensley SE. Science. 2022 Nov 25;378(6622):899-904.

[2] Nucleoside-modified mRNA vaccination partially overcomes maternal antibody inhibition of de novo immune responses in mice. Willis E, Pardi N, Parkhouse K, Mui BL, Tam YK, Weissman D, Hensley SE. Sci Transl Med. 2020 Jan 8;12(525):eaav5701.

[3] Nucleoside-modified mRNA immunization elicits influenza virus hemagglutinin stalk-specific antibodies. Pardi N, Parkhouse K, Kirkpatrick E, McMahon M, Zost SJ, Mui BL, Tam YK, Karikó K, Barbosa CJ, Madden TD, Hope MJ, Krammer F, Hensley SE, Weissman D. Nat Commun. 2018 Aug 22;9(1):3361.

Links:

Understanding Flu Viruses (Centers for Disease Control and Prevention, Atlanta)

COVID Research (NIH)

Decades in the Making: mRNA COVID-19 Vaccines (NIH)

Video: mRNA Flu Vaccines: Preventing the Next Pandemic (Penn Medicine, Philadelphia)

Scott Hensley (Perelman School of Medicine at the University of Pennsylvania, Philadelphia)

Weissman Lab (Perelman School of Medicine)

Video: The Story Behind mRNA COVID Vaccines: Katalin Karikó and Drew Weissman (Penn Medicine, Philadelphia)

NIH Support: National Institute for Allergy and Infectious Diseases


From Brain Waves to Real-Time Text Messaging

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For people who have lost the ability to speak due to a severe disability, they want to get the words out. They just can’t physically do it. But in our digital age, there is now a fascinating way to overcome such profound physical limitations. Computers are being taught to decode brain waves as a person tries to speak and then interactively translate them onto a computer screen in real time.

The latest progress, demonstrated in the video above, establishes that it’s quite possible for computers trained with the help of current artificial intelligence (AI) methods to restore a vocabulary of more than a 1,000 words for people with the mental but not physical ability to speak. That covers more than 85 percent of most day-to-day communication in English. With further refinements, the researchers say a 9,000-word vocabulary is well within reach.

The findings published in the journal Nature Communications come from a team led by Edward Chang, University of California, San Francisco [1]. Earlier, Chang and colleagues established that this AI-enabled system could directly decode 50 full words in real time from brain waves alone in a person with paralysis trying to speak [2]. The study is known as BRAVO, short for Brain-computer interface Restoration Of Arm and Voice.

In the latest BRAVO study, the team wanted to figure out how to condense the English language into compact units for easier decoding and expand that 50-word vocabulary. They did it in the same way we all do: by focusing not on complete words, but on the 26-letter alphabet.

The study involved a 36-year-old male with severe limb and vocal paralysis. The team designed a sentence-spelling pipeline for this individual, which enabled him to silently spell out messages using code words corresponding to each of the 26 letters in his head. As he did so, a high-density array of electrodes implanted over the brain’s sensorimotor cortex, part of the cerebral cortex, recorded his brain waves.

A sophisticated system including signal processing, speech detection, word classification, and language modeling then translated those thoughts into coherent words and complete sentences on a computer screen. This so-called speech neuroprosthesis system allows those who have lost their speech to perform roughly the equivalent of text messaging.

Chang’s team put their spelling system to the test first by asking the participant to silently reproduce a sentence displayed on a screen. They then moved on to conversations, in which the participant was asked a question and could answer freely. For instance, as in the video above, when the computer asked, “How are you today?” he responded, “I am very good.” When asked about his favorite time of year, he answered, “summertime.” An attempted hand movement signaled the computer when he was done speaking.

The computer didn’t get it exactly right every time. For instance, in the initial trials with the target sentence, “good morning,” the computer got it exactly right in one case and in another came up with “good for legs.” But, overall, their tests show that their AI device could decode with a high degree of accuracy silently spoken letters to produce sentences from a 1,152-word vocabulary at a speed of about 29 characters per minute.

On average, the spelling system got it wrong 6 percent of the time. That’s really good when you consider how common it is for errors to arise with dictation software or in any text message conversation.

Of course, much more work is needed to test this approach in many more people. They don’t yet know how individual differences or specific medical conditions might affect the outcomes. They suspect that this general approach will work for anyone so long as they remain mentally capable of thinking through and attempting to speak.

They also envision future improvements as part of their BRAVO study. For instance, it may be possible to develop a system capable of more rapid decoding of many commonly used words or phrases. Such a system could then reserve the slower spelling method for other, less common words.

But, as these results clearly demonstrate, this combination of artificial intelligence and silently controlled speech neuroprostheses to restore not just speech but meaningful communication and authentic connection between individuals who’ve lost the ability to speak and their loved ones holds fantastic potential. For that, I say BRAVO.

References:

[1] Generalizable spelling using a speech neuroprosthesis in an individual with severe limb and vocal paralysis. Metzger SL, Liu JR, Moses DA, Dougherty ME, Seaton MP, Littlejohn KT, Chartier J, Anumanchipalli GK, Tu-CHan A, Gangly K, Chang, EF. Nature Communications (2022) 13: 6510.

[2] Neuroprosthesis for decoding speech in a paralyzed person with anarthria. Moses DA, Metzger SL, Liu JR, Tu-Chan A, Ganguly K, Chang EF, et al. N Engl J Med. 2021 Jul 15;385(3):217-227.

Links:

Voice, Speech, and Language (National Institute on Deafness and Other Communication Disorders/NIH)

ECoG BMI for Motor and Speech Control (BRAVO) (ClinicalTrials.gov)

Chang Lab (University of California, San Francisco)

NIH Support: National Institute on Deafness and Other Communication Disorders


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