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Lawrence Tabak, D.D.S., Ph.D.

Making a Point

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I enjoyed taking part recently in a one-hour panel discussion titled Defining Moments in Health: Leading Through Turbulent Times. The event brought together five leaders from the health-care sector to discuss the question: How do you lead through moments of great uncertainty? This photo shows me addressing panelist Bruce Broussard (right), president and CEO, Humana, Louisville, KY. Looking on is panel moderator Bertha Coombs (left), a reporter with CNBC. The discussion took place on December 7 during the three-day 2022 Milken Institute Future of Health Summit at the Salamander Hotel, Washington, D.C. Credit: Milken Institute.

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


Gratitude for Biomedical Progress and All Those Who Make It Possible

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Group of people holding hands around a dinner table
Credit: Shutterstock/Rawpixel.com

It’s good for our health to eat right, exercise, and get plenty of rest. Still, many other things contribute to our sense of wellbeing, including making it a point to practice gratitude whenever we can. With this in mind, I can’t think of a better time than Thanksgiving to recognize just a few of the many reasons that I—and everyone who believes in the mission of the National Institutes of Health (NIH)—have to be grateful.

First, I’m thankful for the many enormously talented people with whom I’ve worked over the past year while performing the duties of the NIH Director. Particular thanks go to those on my immediate team within the Office of the Director. I could not have taken on this challenge without their dedicated support.

I’m also gratified by the continued enthusiasm and support for biomedical research from so many different corners of our society. This includes the many thousands of unsung, patient partners who put their time, effort, and, in some cases, even their lives on the line for the sake of medical progress and promising treatment advances. Without them, clinical research—including the most pivotal clinical trials—simply wouldn’t be possible.

I am most appreciative of the continuing efforts at NIH and across the broader biomedical community to further enable diversity, equity, inclusion, and accessibility within the biomedical research workforce and in all the work that NIH supports.

High on my Thanksgiving list is the widespread availability of COVID-19 bivalent booster shots. These boosters not only guard against older strains of the coronavirus, but also broaden immunity to the newer Omicron variant and its many subvariants. I’m also tremendously grateful for everyone who has—or soon will—get boosted to protect yourself, your loved ones, and your communities as the winter months fast approach.

Another big “thank you” goes out to all the researchers studying Long COVID, the complex and potentially debilitating constellation of symptoms that strikes some people after recovery from COVID-19. I look forward to more answers as this work continues and we certainly couldn’t do it without our patient partners.

I’d also like to express my appreciation for the NIH’s institute and center directors who’ve contributed to the NIH Director’s Blog to showcase NIH’s broad and diverse portfolio of promising research.

Finally, a special thanks to all of you who read this blog. As you gather with family and friends to celebrate this Thanksgiving holiday, I hope the time you spend here gives you a few more reasons to feel grateful and appreciate the importance of NIH in turning scientific discovery into better health for all.


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


How the Brain Differentiates the ‘Click,’ ‘Crack,’ or ‘Thud’ of Everyday Tasks

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A baseball player hits a ball. The word "crack" is highlighted. The word "thud" has a circle around and a diagonal line through it.
Credit: Donny Bliss, NIH; Shutterstock/Vasyl Shulga

If you’ve been staying up late to watch the World Series, you probably spent those nine innings hoping for superstars Bryce Harper or José Altuve to square up a fastball and send it sailing out of the yard. Long-time baseball fans like me can distinguish immediately the loud crack of a home-run swing from the dull thud of a weak grounder.

Our brains have such a fascinating ability to discern “right” sounds from “wrong” ones in just an instant. This applies not only in baseball, but in the things that we do throughout the day, whether it’s hitting the right note on a musical instrument or pushing the car door just enough to click it shut without slamming.

Now, an NIH-funded team of neuroscientists has discovered what happens in the brain when one hears an expected or “right” sound versus a “wrong” one after completing a task. It turns out that the mammalian brain is remarkably good at predicting both when a sound should happen and what it ideally ought to sound like. Any notable mismatch between that expectation and the feedback, and the hearing center of the brain reacts.

It may seem intuitive that humans and other animals have this auditory ability, but researchers didn’t know how neurons in the brain’s auditory cortex, where sound is processed, make these snap judgements to learn complex tasks. In the study published in the journal Current Biology, David Schneider, New York University, New York, set out to understand how this familiar experience really works.

To do it, Schneider and colleagues, including postdoctoral fellow Nicholas Audette, looked to mice. They are a lot easier to study in the lab than humans and, while their brains aren’t miniature versions of our own, our sensory systems share many fundamental similarities because we are both mammals.

Of course, mice don’t go around hitting home runs or opening and closing doors. So, the researchers’ first step was training the animals to complete a task akin to closing the car door. To do it, they trained the animals to push a lever with their paws in just the right way to receive a reward. They also played a distinctive tone each time the lever reached that perfect position.

After making thousands of attempts and hearing the associated sound, the mice knew just what to do—and what it should sound like when they did it right. Their studies showed that, when the researchers removed the sound, played the wrong sound, or played the correct sound at the wrong time, the mice took notice and adjusted their actions, just as you might do if you pushed a car door shut and the resulting click wasn’t right.

To find out how neurons in the auditory cortex responded to produce the observed behaviors, Schneider’s team also recorded brain activity. Intriguingly, they found that auditory neurons hardly responded when a mouse pushed the lever and heard the sound they’d learned to expect. It was only when something about the sound was “off” that their auditory neurons suddenly crackled with activity.

As the researchers explained, it seems from these studies that the mammalian auditory cortex responds not to the sounds themselves but to how those sounds match up to, or violate, expectations. When the researchers canceled the sound altogether, as might happen if you didn’t push a car door hard enough to produce the familiar click shut, activity within a select group of auditory neurons spiked right as they should have heard the sound.

Schneider’s team notes that the same brain areas and circuitry that predict and process self-generated sounds in everyday tasks also play a role in conditions such as schizophrenia, in which people may hear voices or other sounds that aren’t there. The team hopes their studies will help to explain what goes wrong—and perhaps how to help—in schizophrenia and other neural disorders. Perhaps they’ll also learn more about what goes through the healthy brain when anticipating the satisfying click of a closed door or the loud crack of a World Series home run.

Reference:

[1] Precise movement-based predictions in the mouse auditory cortex. Audette NJ, Zhou WX, Chioma A, Schneider DM. Curr Biology. 2022 Oct 24.

Links:

How Do We Hear? (National Institute on Deafness and Other Communication Disorders/NIH)

Schizophrenia (National Institute of Mental Health/NIH)

David Schneider (New York University, New York)

NIH Support: National Institute of Mental Health; National Institute on Deafness and Other Communication Disorders


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